From c0bd0037b5164ef4f8caead72a54d2c1c5dd8147 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 21:27:08 +0100 Subject: [PATCH 01/29] feat: add model pricing --- data/.gitkeep | 2 + data/model-pricing.json | 30198 ++++++++++++++++++++++ index.ts | 77 + lib/pricing.ts | 224 + lib/report-template.ts | 223 +- lib/report.ts | 25 + package.json | 1 + results/result-2025-12-09-21-21-09.json | 1317 + scripts/update-model-pricing.ts | 76 + 9 files changed, 32141 insertions(+), 2 deletions(-) create mode 100644 data/.gitkeep create mode 100644 data/model-pricing.json create mode 100644 lib/pricing.ts create mode 100644 results/result-2025-12-09-21-21-09.json create mode 100644 scripts/update-model-pricing.ts diff --git a/data/.gitkeep b/data/.gitkeep new file mode 100644 index 0000000..4df4445 --- /dev/null +++ b/data/.gitkeep @@ -0,0 +1,2 @@ +# This directory contains versioned data files +# Run `bun run update-model-pricing` to update model-pricing.json diff --git a/data/model-pricing.json b/data/model-pricing.json new file mode 100644 index 0000000..4f516f1 --- /dev/null +++ b/data/model-pricing.json @@ -0,0 +1,30198 @@ +{ + "sample_spec": { + "code_interpreter_cost_per_session": 0, + "computer_use_input_cost_per_1k_tokens": 0, + "computer_use_output_cost_per_1k_tokens": 0, + "deprecation_date": "date when the model becomes deprecated in the format YYYY-MM-DD", + "file_search_cost_per_1k_calls": 0, + "file_search_cost_per_gb_per_day": 0, + "input_cost_per_audio_token": 0, + "input_cost_per_token": 0, + "litellm_provider": "one of https://docs.litellm.ai/docs/providers", + "max_input_tokens": "max input tokens, if the provider specifies it. if not default to max_tokens", + "max_output_tokens": "max output tokens, if the provider specifies it. if not default to max_tokens", + "max_tokens": "LEGACY parameter. set to max_output_tokens if provider specifies it. IF not set to max_input_tokens, if provider specifies it.", + "mode": "one of: chat, embedding, completion, image_generation, audio_transcription, audio_speech, image_generation, moderation, rerank, search", + "output_cost_per_reasoning_token": 0, + "output_cost_per_token": 0, + "search_context_cost_per_query": { + "search_context_size_high": 0, + "search_context_size_low": 0, + "search_context_size_medium": 0 + }, + "supported_regions": [ + "global", + "us-west-2", + "eu-west-1", + "ap-southeast-1", + "ap-northeast-1" + ], + "supports_audio_input": true, + "supports_audio_output": true, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_vision": true, + "supports_web_search": true, + "vector_store_cost_per_gb_per_day": 0 + }, + "1024-x-1024/50-steps/bedrock/amazon.nova-canvas-v1:0": { + "litellm_provider": "bedrock", + "max_input_tokens": 2600, + "mode": "image_generation", + "output_cost_per_image": 0.06 + }, + "1024-x-1024/50-steps/stability.stable-diffusion-xl-v1": { + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "image_generation", + "output_cost_per_image": 0.04 + }, + "1024-x-1024/dall-e-2": { + "input_cost_per_pixel": 1.9e-8, + "litellm_provider": "openai", + "mode": "image_generation", + "output_cost_per_pixel": 0 + }, + "1024-x-1024/max-steps/stability.stable-diffusion-xl-v1": { + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "image_generation", + "output_cost_per_image": 0.08 + }, + "256-x-256/dall-e-2": { + "input_cost_per_pixel": 2.4414e-7, + "litellm_provider": "openai", + "mode": "image_generation", + "output_cost_per_pixel": 0 + }, + "512-x-512/50-steps/stability.stable-diffusion-xl-v0": { + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "image_generation", + "output_cost_per_image": 0.018 + }, + "512-x-512/dall-e-2": { + "input_cost_per_pixel": 6.86e-8, + "litellm_provider": "openai", + "mode": "image_generation", + "output_cost_per_pixel": 0 + }, + "512-x-512/max-steps/stability.stable-diffusion-xl-v0": { + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "image_generation", + "output_cost_per_image": 0.036 + }, + "ai21.j2-mid-v1": { + "input_cost_per_token": 0.0000125, + "litellm_provider": "bedrock", + "max_input_tokens": 8191, + "max_output_tokens": 8191, + "max_tokens": 8191, + "mode": "chat", + "output_cost_per_token": 0.0000125 + }, + "ai21.j2-ultra-v1": { + "input_cost_per_token": 0.0000188, + "litellm_provider": "bedrock", + "max_input_tokens": 8191, + "max_output_tokens": 8191, + "max_tokens": 8191, + "mode": "chat", + "output_cost_per_token": 0.0000188 + }, + "ai21.jamba-1-5-large-v1:0": { + "input_cost_per_token": 0.000002, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 0.000008 + }, + "ai21.jamba-1-5-mini-v1:0": { + "input_cost_per_token": 2e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 256000, + "max_output_tokens": 256000, + "max_tokens": 256000, + "mode": "chat", + "output_cost_per_token": 4e-7 + }, + "ai21.jamba-instruct-v1:0": { + "input_cost_per_token": 5e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 70000, + "max_output_tokens": 4096, + "max_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 7e-7, + "supports_system_messages": true + }, + "aiml/dall-e-2": { + "litellm_provider": "aiml", + "metadata": { + "notes": "DALL-E 2 via AI/ML API - Reliable text-to-image generation" + }, + "mode": "image_generation", + "output_cost_per_image": 0.021, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/dall-e-3": { + "litellm_provider": "aiml", + "metadata": { + "notes": "DALL-E 3 via AI/ML API - High-quality text-to-image generation" + }, + "mode": "image_generation", + "output_cost_per_image": 0.042, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux-pro": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Dev - Development version optimized for experimentation" + }, + "mode": "image_generation", + "output_cost_per_image": 0.053, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux-pro/v1.1": { + "litellm_provider": "aiml", + "mode": "image_generation", + "output_cost_per_image": 0.042, + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux-pro/v1.1-ultra": { + "litellm_provider": "aiml", + "mode": "image_generation", + "output_cost_per_image": 0.063, + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux-realism": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Pro - Professional-grade image generation model" + }, + "mode": "image_generation", + "output_cost_per_image": 0.037, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux/dev": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Dev - Development version optimized for experimentation" + }, + "mode": "image_generation", + "output_cost_per_image": 0.026, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux/kontext-max/text-to-image": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Pro v1.1 - Enhanced version with improved capabilities and 6x faster inference speed" + }, + "mode": "image_generation", + "output_cost_per_image": 0.084, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux/kontext-pro/text-to-image": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Pro v1.1 - Enhanced version with improved capabilities and 6x faster inference speed" + }, + "mode": "image_generation", + "output_cost_per_image": 0.042, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "aiml/flux/schnell": { + "litellm_provider": "aiml", + "metadata": { + "notes": "Flux Schnell - Fast generation model optimized for speed" + }, + "mode": "image_generation", + "output_cost_per_image": 0.003, + "source": "https://docs.aimlapi.com/", + "supported_endpoints": [ + "/v1/images/generations" + ] + }, + "amazon.nova-canvas-v1:0": { + "litellm_provider": "bedrock", + "max_input_tokens": 2600, + "mode": "image_generation", + "output_cost_per_image": 0.06 + }, + "us.writer.palmyra-x4-v1:0": { + "input_cost_per_token": 0.0000025, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 128000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.00001, + "supports_function_calling": true, + "supports_pdf_input": true + }, + "us.writer.palmyra-x5-v1:0": { + "input_cost_per_token": 6e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.000006, + "supports_function_calling": true, + "supports_pdf_input": true + }, + "writer.palmyra-x4-v1:0": { + "input_cost_per_token": 0.0000025, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 128000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.00001, + "supports_function_calling": true, + "supports_pdf_input": true + }, + "writer.palmyra-x5-v1:0": { + "input_cost_per_token": 6e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.000006, + "supports_function_calling": true, + "supports_pdf_input": true + }, + "amazon.nova-lite-v1:0": { + "input_cost_per_token": 6e-8, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 2.4e-7, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon.nova-2-lite-v1:0": { + "cache_read_input_token_cost": 7.5e-8, + "input_cost_per_token": 3e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.0000025, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "apac.amazon.nova-2-lite-v1:0": { + "cache_read_input_token_cost": 8.25e-8, + "input_cost_per_token": 3.3e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.00000275, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "eu.amazon.nova-2-lite-v1:0": { + "cache_read_input_token_cost": 8.25e-8, + "input_cost_per_token": 3.3e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.00000275, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "us.amazon.nova-2-lite-v1:0": { + "cache_read_input_token_cost": 8.25e-8, + "input_cost_per_token": 3.3e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 1000000, + "max_output_tokens": 64000, + "max_tokens": 64000, + "mode": "chat", + "output_cost_per_token": 0.00000275, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_video_input": true, + "supports_vision": true + }, + "amazon.nova-micro-v1:0": { + "input_cost_per_token": 3.5e-8, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 128000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 1.4e-7, + "supports_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true + }, + "amazon.nova-pro-v1:0": { + "input_cost_per_token": 8e-7, + "litellm_provider": "bedrock_converse", + "max_input_tokens": 300000, + "max_output_tokens": 10000, + "max_tokens": 10000, + "mode": "chat", + "output_cost_per_token": 0.0000032, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_vision": true + }, + "amazon.rerank-v1:0": { + "input_cost_per_query": 0.001, + "input_cost_per_token": 0, + "litellm_provider": "bedrock", + "max_document_chunks_per_query": 100, + "max_input_tokens": 32000, + "max_output_tokens": 32000, + "max_query_tokens": 32000, + "max_tokens": 32000, + "max_tokens_per_document_chunk": 512, + "mode": "rerank", + "output_cost_per_token": 0 + }, + "amazon.titan-embed-image-v1": { + "input_cost_per_image": 0.00006, + "input_cost_per_token": 8e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 128, + "max_tokens": 128, + "metadata": { + "notes": "'supports_image_input' is a deprecated field. Use 'supports_embedding_image_input' instead." + }, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1024, + "source": "https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/providers?model=amazon.titan-image-generator-v1", + "supports_embedding_image_input": true, + "supports_image_input": true + }, + "amazon.titan-embed-text-v1": { + "input_cost_per_token": 1e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 8192, + "max_tokens": 8192, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1536 + }, + "amazon.titan-embed-text-v2:0": { + "input_cost_per_token": 2e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 8192, + "max_tokens": 8192, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1024 + }, + "amazon.titan-image-generator-v1": { + "input_cost_per_image": 0, + "output_cost_per_image": 0.008, + "output_cost_per_image_premium_image": 0.01, + "output_cost_per_image_above_512_and_512_pixels": 0.01, + "output_cost_per_image_above_512_and_512_pixels_and_premium_image": 0.012, + "litellm_provider": "bedrock", + "mode": "image_generation" + }, + "amazon.titan-image-generator-v2": { + "input_cost_per_image": 0, + "output_cost_per_image": 0.008, + "output_cost_per_image_premium_image": 0.01, + "output_cost_per_image_above_1024_and_1024_pixels": 0.01, + "output_cost_per_image_above_1024_and_1024_pixels_and_premium_image": 0.012, + "litellm_provider": "bedrock", + "mode": "image_generation" + }, + "amazon.titan-image-generator-v2:0": { + "input_cost_per_image": 0, + "output_cost_per_image": 0.008, + "output_cost_per_image_premium_image": 0.01, + "output_cost_per_image_above_1024_and_1024_pixels": 0.01, + "output_cost_per_image_above_1024_and_1024_pixels_and_premium_image": 0.012, + "litellm_provider": "bedrock", + "mode": "image_generation" + }, + "twelvelabs.marengo-embed-2-7-v1:0": { + "input_cost_per_token": 0.00007, + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1024, + "supports_embedding_image_input": true, + "supports_image_input": true + }, + "us.twelvelabs.marengo-embed-2-7-v1:0": { + "input_cost_per_token": 0.00007, + "input_cost_per_video_per_second": 0.0007, + "input_cost_per_audio_per_second": 0.00014, + "input_cost_per_image": 0.0001, + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1024, + "supports_embedding_image_input": true, + "supports_image_input": true + }, + "eu.twelvelabs.marengo-embed-2-7-v1:0": { + "input_cost_per_token": 0.00007, + "input_cost_per_video_per_second": 0.0007, + "input_cost_per_audio_per_second": 0.00014, + "input_cost_per_image": 0.0001, + "litellm_provider": "bedrock", + "max_input_tokens": 77, + "max_tokens": 77, + "mode": "embedding", + "output_cost_per_token": 0, + "output_vector_size": 1024, + "supports_embedding_image_input": true, + "supports_image_input": true + }, + "twelvelabs.pegasus-1-2-v1:0": { + "input_cost_per_video_per_second": 0.00049, + "output_cost_per_token": 0.0000075, + "litellm_provider": "bedrock", + "mode": "chat", + "supports_video_input": true + }, + "us.twelvelabs.pegasus-1-2-v1:0": { + "input_cost_per_video_per_second": 0.00049, + "output_cost_per_token": 0.0000075, + "litellm_provider": "bedrock", + "mode": "chat", + "supports_video_input": true + }, + "eu.twelvelabs.pegasus-1-2-v1:0": { + "input_cost_per_video_per_second": 0.00049, + "output_cost_per_token": 0.0000075, + "litellm_provider": "bedrock", + "mode": "chat", + "supports_video_input": true + }, + "amazon.titan-text-express-v1": { + "input_cost_per_token": 0.0000013, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 8000, + "max_tokens": 8000, + "mode": "chat", + "output_cost_per_token": 0.0000017 + }, + "amazon.titan-text-lite-v1": { + "input_cost_per_token": 3e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 4000, + "max_tokens": 4000, + "mode": "chat", + "output_cost_per_token": 4e-7 + }, + "amazon.titan-text-premier-v1:0": { + "input_cost_per_token": 5e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 42000, + "max_output_tokens": 32000, + "max_tokens": 32000, + "mode": "chat", + "output_cost_per_token": 0.0000015 + }, + "anthropic.claude-3-5-haiku-20241022-v1:0": { + "cache_creation_input_token_cost": 0.000001, + "cache_read_input_token_cost": 8e-8, + "input_cost_per_token": 8e-7, + "litellm_provider": "bedrock", + "max_input_tokens": 200000, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 0.000004, + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + 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"max_tokens": 131072, + "mode": "chat", + "output_cost_per_token": 0.0000024, + "source": "https://www.alibabacloud.com/help/en/model-studio/models", + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-bge-large-en": { + "input_cost_per_token": 1.0003e-7, + "input_dbu_cost_per_token": 0.000001429, + "litellm_provider": "databricks", + "max_input_tokens": 512, + "max_tokens": 512, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "embedding", + "output_cost_per_token": 0, + "output_dbu_cost_per_token": 0, + "output_vector_size": 1024, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-claude-3-7-sonnet": { + "input_cost_per_token": 0.0000029999900000000002, + "input_dbu_cost_per_token": 0.000042857, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 128000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000015000020000000002, + "output_dbu_cost_per_token": 0.000214286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-haiku-4-5": { + "input_cost_per_token": 0.00000100002, + "input_dbu_cost_per_token": 0.000014286, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00000500003, + "output_dbu_cost_per_token": 0.000071429, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-opus-4": { + "input_cost_per_token": 0.000015000020000000002, + "input_dbu_cost_per_token": 0.000214286, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 32000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00007500003000000001, + "output_dbu_cost_per_token": 0.001071429, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-opus-4-1": { + "input_cost_per_token": 0.000015000020000000002, + "input_dbu_cost_per_token": 0.000214286, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 32000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00007500003000000001, + "output_dbu_cost_per_token": 0.001071429, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-opus-4-5": { + "input_cost_per_token": 0.00000500003, + "input_dbu_cost_per_token": 0.000071429, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000025000010000000002, + "output_dbu_cost_per_token": 0.000357143, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-sonnet-4": { + "input_cost_per_token": 0.0000029999900000000002, + "input_dbu_cost_per_token": 0.000042857, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000015000020000000002, + "output_dbu_cost_per_token": 0.000214286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-sonnet-4-1": { + "input_cost_per_token": 0.0000029999900000000002, + "input_dbu_cost_per_token": 0.000042857, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000015000020000000002, + "output_dbu_cost_per_token": 0.000214286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-claude-sonnet-4-5": { + "input_cost_per_token": 0.0000029999900000000002, + "input_dbu_cost_per_token": 0.000042857, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 64000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000015000020000000002, + "output_dbu_cost_per_token": 0.000214286, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_assistant_prefill": true, + "supports_function_calling": true, + "supports_reasoning": true, + "supports_tool_choice": true + }, + "databricks/databricks-gemini-2-5-flash": { + "input_cost_per_token": 3.0001999999999996e-7, + "input_dbu_cost_per_token": 0.000004285999999999999, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65535, + "max_tokens": 1048576, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00000249998, + "output_dbu_cost_per_token": 0.000035714, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_function_calling": true, + "supports_tool_choice": true + }, + "databricks/databricks-gemini-2-5-pro": { + "input_cost_per_token": 0.00000124999, + "input_dbu_cost_per_token": 0.000017857, + "litellm_provider": "databricks", + "max_input_tokens": 1048576, + "max_output_tokens": 65536, + "max_tokens": 1048576, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000009999990000000002, + "output_dbu_cost_per_token": 0.000142857, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", + "supports_function_calling": true, + "supports_tool_choice": true + }, + "databricks/databricks-gemma-3-12b": { + "input_cost_per_token": 1.5000999999999998e-7, + "input_dbu_cost_per_token": 0.0000021429999999999996, + "litellm_provider": "databricks", + "max_input_tokens": 128000, + "max_output_tokens": 32000, + "max_tokens": 128000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 5.0001e-7, + "output_dbu_cost_per_token": 0.000007143, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-gpt-5": { + "input_cost_per_token": 0.00000124999, + "input_dbu_cost_per_token": 0.000017857, + "litellm_provider": "databricks", + "max_input_tokens": 400000, + "max_output_tokens": 128000, + "max_tokens": 400000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000009999990000000002, + "output_dbu_cost_per_token": 0.000142857, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-5-1": { + "input_cost_per_token": 0.00000124999, + "input_dbu_cost_per_token": 0.000017857, + "litellm_provider": "databricks", + "max_input_tokens": 400000, + "max_output_tokens": 128000, + "max_tokens": 400000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000009999990000000002, + "output_dbu_cost_per_token": 0.000142857, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-5-mini": { + "input_cost_per_token": 2.4997000000000006e-7, + "input_dbu_cost_per_token": 0.000003571, + "litellm_provider": "databricks", + "max_input_tokens": 400000, + "max_output_tokens": 128000, + "max_tokens": 400000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.0000019999700000000004, + "output_dbu_cost_per_token": 0.000028571, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-5-nano": { + "input_cost_per_token": 4.998e-8, + "input_dbu_cost_per_token": 7.14e-7, + "litellm_provider": "databricks", + "max_input_tokens": 400000, + "max_output_tokens": 128000, + "max_tokens": 400000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 3.9998000000000007e-7, + "output_dbu_cost_per_token": 0.000005714000000000001, + "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" + }, + "databricks/databricks-gpt-oss-120b": { + "input_cost_per_token": 1.5000999999999998e-7, + "input_dbu_cost_per_token": 0.0000021429999999999996, + "litellm_provider": "databricks", + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "max_tokens": 131072, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 5.9997e-7, + "output_dbu_cost_per_token": 0.000008571, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-gpt-oss-20b": { + "input_cost_per_token": 7e-8, + "input_dbu_cost_per_token": 0.000001, + "litellm_provider": "databricks", + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "max_tokens": 131072, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 3.0001999999999996e-7, + "output_dbu_cost_per_token": 0.000004285999999999999, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-gte-large-en": { + "input_cost_per_token": 1.2999000000000001e-7, + "input_dbu_cost_per_token": 0.000001857, + "litellm_provider": "databricks", + "max_input_tokens": 8192, + "max_tokens": 8192, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "embedding", + "output_cost_per_token": 0, + "output_dbu_cost_per_token": 0, + "output_vector_size": 1024, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-llama-2-70b-chat": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "max_tokens": 4096, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.0000015000300000000002, + "output_dbu_cost_per_token": 0.000021429, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-llama-4-maverick": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 128000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "metadata": { + "notes": "Databricks documentation now provides both DBU costs (_dbu_cost_per_token) and dollar costs(_cost_per_token)." + }, + "mode": "chat", + "output_cost_per_token": 0.0000015000300000000002, + "output_dbu_cost_per_token": 0.000021429, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-meta-llama-3-1-405b-instruct": { + "input_cost_per_token": 0.00000500003, + "input_dbu_cost_per_token": 0.000071429, + "litellm_provider": "databricks", + "max_input_tokens": 128000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.000015000020000000002, + "output_dbu_cost_per_token": 0.000214286, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-meta-llama-3-1-8b-instruct": { + "input_cost_per_token": 1.5000999999999998e-7, + "input_dbu_cost_per_token": 0.0000021429999999999996, + "litellm_provider": "databricks", + "max_input_tokens": 200000, + "max_output_tokens": 128000, + "max_tokens": 200000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 4.5003000000000007e-7, + "output_dbu_cost_per_token": 0.000006429000000000001, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving" + }, + "databricks/databricks-meta-llama-3-3-70b-instruct": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 128000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.0000015000300000000002, + "output_dbu_cost_per_token": 0.000021429, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-meta-llama-3-70b-instruct": { + "input_cost_per_token": 0.00000100002, + "input_dbu_cost_per_token": 0.000014286, + "litellm_provider": "databricks", + "max_input_tokens": 128000, + "max_output_tokens": 128000, + "max_tokens": 128000, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.0000029999900000000002, + "output_dbu_cost_per_token": 0.000042857, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-mixtral-8x7b-instruct": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "max_tokens": 4096, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00000100002, + "output_dbu_cost_per_token": 0.000014286, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-mpt-30b-instruct": { + "input_cost_per_token": 0.00000100002, + "input_dbu_cost_per_token": 0.000014286, + "litellm_provider": "databricks", + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "max_tokens": 8192, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0.00000100002, + "output_dbu_cost_per_token": 0.000014286, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "databricks/databricks-mpt-7b-instruct": { + "input_cost_per_token": 5.0001e-7, + "input_dbu_cost_per_token": 0.000007143, + "litellm_provider": "databricks", + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "max_tokens": 8192, + "metadata": { + "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." + }, + "mode": "chat", + "output_cost_per_token": 0, + "output_dbu_cost_per_token": 0, + "source": "https://www.databricks.com/product/pricing/foundation-model-serving", + "supports_tool_choice": true + }, + "dataforseo/search": { + "input_cost_per_query": 0.003, + "litellm_provider": "dataforseo", + "mode": "search" + }, + "davinci-002": { + "input_cost_per_token": 0.000002, + "litellm_provider": "text-completion-openai", + "max_input_tokens": 16384, + "max_output_tokens": 4096, + "max_tokens": 16384, + "mode": "completion", + "output_cost_per_token": 0.000002 + }, + "deepgram/base": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-conversationalai": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-finance": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-general": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-meeting": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-phonecall": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-video": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/base-voicemail": { + "input_cost_per_second": 0.00020833, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0125/60 seconds = $0.00020833 per second", + "original_pricing_per_minute": 0.0125 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/enhanced": { + "input_cost_per_second": 0.00024167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0145/60 seconds = $0.00024167 per second", + "original_pricing_per_minute": 0.0145 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/enhanced-finance": { + "input_cost_per_second": 0.00024167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0145/60 seconds = $0.00024167 per second", + "original_pricing_per_minute": 0.0145 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/enhanced-general": { + "input_cost_per_second": 0.00024167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0145/60 seconds = $0.00024167 per second", + "original_pricing_per_minute": 0.0145 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/enhanced-meeting": { + "input_cost_per_second": 0.00024167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0145/60 seconds = $0.00024167 per second", + "original_pricing_per_minute": 0.0145 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/enhanced-phonecall": { + "input_cost_per_second": 0.00024167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0145/60 seconds = $0.00024167 per second", + "original_pricing_per_minute": 0.0145 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-atc": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-automotive": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-conversationalai": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-drivethru": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-finance": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-general": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-meeting": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-phonecall": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-video": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-2-voicemail": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": "audio_transcription", + "output_cost_per_second": 0, + "source": "https://deepgram.com/pricing", + "supported_endpoints": [ + "/v1/audio/transcriptions" + ] + }, + "deepgram/nova-3": { + "input_cost_per_second": 0.00007167, + "litellm_provider": "deepgram", + "metadata": { + "calculation": "$0.0043/60 seconds = $0.00007167 per second", + "original_pricing_per_minute": 0.0043 + }, + "mode": 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}, + "fireworks_ai/thenlper/gte-large": { + "input_cost_per_token": 1.6e-8, + "litellm_provider": "fireworks_ai-embedding-models", + "max_input_tokens": 512, + "max_tokens": 512, + "mode": "embedding", + "output_cost_per_token": 0, + "source": "https://fireworks.ai/pricing" + }, + "friendliai/meta-llama-3.1-70b-instruct": { + "input_cost_per_token": 6e-7, + "litellm_provider": "friendliai", + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 6e-7, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "friendliai/meta-llama-3.1-8b-instruct": { + "input_cost_per_token": 1e-7, + "litellm_provider": "friendliai", + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_token": 1e-7, + "supports_function_calling": true, + 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4096, + "mode": "chat", + "output_cost_per_token": 0.000006, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "ft:gpt-4-0613": { + "input_cost_per_token": 0.00003, + "litellm_provider": "openai", + "max_input_tokens": 8192, + "max_output_tokens": 4096, + "max_tokens": 4096, + "mode": "chat", + "output_cost_per_token": 0.00006, + "source": "OpenAI needs to add pricing for this ft model, will be updated when added by OpenAI. Defaulting to base model pricing", + "supports_function_calling": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "ft:gpt-4o-2024-08-06": { + "cache_read_input_token_cost": 0.000001875, + "input_cost_per_token": 0.00000375, + "input_cost_per_token_batches": 0.000001875, + "litellm_provider": "openai", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 0.000015, + "output_cost_per_token_batches": 0.0000075, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "ft:gpt-4o-2024-11-20": { + "cache_creation_input_token_cost": 0.000001875, + "input_cost_per_token": 0.00000375, + "litellm_provider": "openai", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 0.000015, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "ft:gpt-4o-mini-2024-07-18": { + "cache_read_input_token_cost": 1.5e-7, + "input_cost_per_token": 3e-7, + "input_cost_per_token_batches": 1.5e-7, + "litellm_provider": "openai", + "max_input_tokens": 128000, + "max_output_tokens": 16384, + "max_tokens": 16384, + "mode": "chat", + "output_cost_per_token": 0.0000012, + "output_cost_per_token_batches": 6e-7, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_pdf_input": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + 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"supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "ft:gpt-4.1-nano-2025-04-14": { + "cache_read_input_token_cost": 5e-8, + "input_cost_per_token": 2e-7, + "input_cost_per_token_batches": 1e-7, + "litellm_provider": "openai", + "max_input_tokens": 1047576, + "max_output_tokens": 32768, + "max_tokens": 32768, + "mode": "chat", + "output_cost_per_token": 8e-7, + "output_cost_per_token_batches": 4e-7, + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_prompt_caching": true, + "supports_response_schema": true, + "supports_system_messages": true, + "supports_tool_choice": true + }, + "ft:o4-mini-2025-04-16": { + "cache_read_input_token_cost": 0.000001, + "input_cost_per_token": 0.000004, + "input_cost_per_token_batches": 0.000002, + "litellm_provider": "openai", + "max_input_tokens": 200000, + "max_output_tokens": 100000, + "max_tokens": 100000, + "mode": "chat", + "output_cost_per_token": 0.000016, + "output_cost_per_token_batches": 0.000008, + "supports_function_calling": true, + "supports_parallel_function_calling": false, + "supports_prompt_caching": true, + "supports_reasoning": true, + "supports_response_schema": true, + "supports_tool_choice": true + }, + "gemini-1.0-pro": { + "input_cost_per_character": 1.25e-7, + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "input_cost_per_video_per_second": 0.002, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 32760, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_character": 3.75e-7, + "output_cost_per_token": 0.0000015, + "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#google_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true + }, + "gemini-1.0-pro-001": { + "deprecation_date": "2025-04-09", + "input_cost_per_character": 1.25e-7, + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "input_cost_per_video_per_second": 0.002, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 32760, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_character": 3.75e-7, + "output_cost_per_token": 0.0000015, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true + }, + "gemini-1.0-pro-002": { + "deprecation_date": "2025-04-09", + "input_cost_per_character": 1.25e-7, + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "input_cost_per_video_per_second": 0.002, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 32760, + "max_output_tokens": 8192, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_character": 3.75e-7, + "output_cost_per_token": 0.0000015, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true + }, + "gemini-1.0-pro-vision": { + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "litellm_provider": "vertex_ai-vision-models", + "max_images_per_prompt": 16, + "max_input_tokens": 16384, + "max_output_tokens": 2048, + "max_tokens": 2048, + "max_video_length": 2, + "max_videos_per_prompt": 1, + "mode": "chat", + "output_cost_per_token": 0.0000015, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "gemini-1.0-pro-vision-001": { + "deprecation_date": "2025-04-09", + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "litellm_provider": "vertex_ai-vision-models", + "max_images_per_prompt": 16, + "max_input_tokens": 16384, + "max_output_tokens": 2048, + "max_tokens": 2048, + "max_video_length": 2, + "max_videos_per_prompt": 1, + "mode": "chat", + "output_cost_per_token": 0.0000015, + "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true, + "supports_vision": true + }, + "gemini-1.0-ultra": { + "input_cost_per_character": 1.25e-7, + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "input_cost_per_video_per_second": 0.002, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 8192, + "max_output_tokens": 2048, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_character": 3.75e-7, + "output_cost_per_token": 0.0000015, + "source": "As of Jun, 2024. There is no available doc on vertex ai pricing gemini-1.0-ultra-001. Using gemini-1.0-pro pricing. Got max_tokens info here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true + }, + "gemini-1.0-ultra-001": { + "input_cost_per_character": 1.25e-7, + "input_cost_per_image": 0.0025, + "input_cost_per_token": 5e-7, + "input_cost_per_video_per_second": 0.002, + "litellm_provider": "vertex_ai-language-models", + "max_input_tokens": 8192, + "max_output_tokens": 2048, + "max_tokens": 8192, + "mode": "chat", + "output_cost_per_character": 3.75e-7, + "output_cost_per_token": 0.0000015, + "source": "As of Jun, 2024. There is no available doc on vertex ai pricing gemini-1.0-ultra-001. Using gemini-1.0-pro pricing. Got max_tokens info here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", + "supports_function_calling": true, + "supports_parallel_function_calling": true, + "supports_tool_choice": true + }, + "gemini-1.5-flash": { + "input_cost_per_audio_per_second": 0.000002, + "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, + "input_cost_per_character": 1.875e-8, + "input_cost_per_character_above_128k_tokens": 2.5e-7, + "input_cost_per_image": 0.00002, + "input_cost_per_image_above_128k_tokens": 0.00004, + "input_cost_per_token": 7.5e-8, + "input_cost_per_token_above_128k_tokens": 0.000001, + "input_cost_per_video_per_second": 0.00002, + "input_cost_per_video_per_second_above_128k_tokens": 0.00004, + "litellm_provider": "vertex_ai-language-models", + "max_audio_length_hours": 8.4, + "max_audio_per_prompt": 1, + "max_images_per_prompt": 3000, + "max_input_tokens": 1000000, + "max_output_tokens": 8192, + "max_pdf_size_mb": 30, + "max_tokens": 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"litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/qwen3-vl-8b-instruct": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/qwq-32b": { + "max_tokens": 131072, + "max_input_tokens": 131072, + "max_output_tokens": 131072, + "input_cost_per_token": 9e-7, + "output_cost_per_token": 9e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/rolm-ocr": { + "max_tokens": 128000, + "max_input_tokens": 128000, + "max_output_tokens": 128000, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/snorkel-mistral-7b-pairrm-dpo": { + "max_tokens": 32768, + "max_input_tokens": 32768, + "max_output_tokens": 32768, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/stable-diffusion-xl-1024-v1-0": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 1.3e-10, + "output_cost_per_token": 1.3e-10, + "litellm_provider": "fireworks_ai", + "mode": "image_generation" + }, + "fireworks_ai/accounts/fireworks/models/stablecode-3b": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 1e-7, + "output_cost_per_token": 1e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/starcoder-16b": { + "max_tokens": 8192, + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/starcoder-7b": { + "max_tokens": 8192, + "max_input_tokens": 8192, + "max_output_tokens": 8192, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/starcoder2-15b": { + "max_tokens": 16384, + "max_input_tokens": 16384, + "max_output_tokens": 16384, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/starcoder2-3b": { + "max_tokens": 16384, + "max_input_tokens": 16384, + "max_output_tokens": 16384, + "input_cost_per_token": 1e-7, + "output_cost_per_token": 1e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/starcoder2-7b": { + "max_tokens": 16384, + "max_input_tokens": 16384, + "max_output_tokens": 16384, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/toppy-m-7b": { + "max_tokens": 32768, + "max_input_tokens": 32768, + "max_output_tokens": 32768, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/whisper-v3": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 0, + "output_cost_per_token": 0, + "litellm_provider": "fireworks_ai", + "mode": "audio_transcription" + }, + "fireworks_ai/accounts/fireworks/models/whisper-v3-turbo": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 0, + "output_cost_per_token": 0, + "litellm_provider": "fireworks_ai", + "mode": "audio_transcription" + }, + "fireworks_ai/accounts/fireworks/models/yi-34b": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 9e-7, + "output_cost_per_token": 9e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/yi-34b-200k-capybara": { + "max_tokens": 200000, + "max_input_tokens": 200000, + "max_output_tokens": 200000, + "input_cost_per_token": 9e-7, + "output_cost_per_token": 9e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/yi-34b-chat": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 9e-7, + "output_cost_per_token": 9e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/yi-6b": { + "max_tokens": 4096, + "max_input_tokens": 4096, + "max_output_tokens": 4096, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + }, + "fireworks_ai/accounts/fireworks/models/zephyr-7b-beta": { + "max_tokens": 32768, + "max_input_tokens": 32768, + "max_output_tokens": 32768, + "input_cost_per_token": 2e-7, + "output_cost_per_token": 2e-7, + "litellm_provider": "fireworks_ai", + "mode": "chat" + } +} \ No newline at end of file diff --git a/index.ts b/index.ts index 48a3a12..1d6c1ef 100644 --- a/index.ts +++ b/index.ts @@ -6,6 +6,8 @@ import { generateReport, type SingleTestResult, type MultiTestResultData, + type PricingInfo, + type TotalCostInfo, } from "./lib/report.ts"; import { getModelProvider, loadEnvConfig } from "./lib/providers.ts"; import { @@ -20,6 +22,12 @@ import { runTestVerification, } from "./lib/output-test-runner.ts"; import { resultWriteTool, testComponentTool } from "./lib/tools/index.ts"; +import { + getModelPricingDisplay, + calculateCost, + formatCost, + isPricingAvailable, +} from "./lib/pricing.ts"; import type { LanguageModel } from "ai"; /** @@ -84,6 +92,45 @@ function extractResultWriteContent(steps: unknown[]): string | null { return null; } +/** + * Calculate total cost from test results + */ +function calculateTotalCost( + tests: SingleTestResult[], + modelString: string, +): TotalCostInfo | null { + let totalInputTokens = 0; + let totalOutputTokens = 0; + let totalCachedInputTokens = 0; + + for (const test of tests) { + for (const step of test.steps) { + totalInputTokens += step.usage.inputTokens; + totalOutputTokens += step.usage.outputTokens; + totalCachedInputTokens += step.usage.cachedInputTokens ?? 0; + } + } + + const costResult = calculateCost( + modelString, + totalInputTokens, + totalOutputTokens, + totalCachedInputTokens, + ); + + if (!costResult) return null; + + return { + inputCost: costResult.inputCost, + outputCost: costResult.outputCost, + cacheReadCost: costResult.cacheReadCost, + totalCost: costResult.totalCost, + inputTokens: totalInputTokens, + outputTokens: totalOutputTokens, + cachedInputTokens: totalCachedInputTokens, + }; +} + /** * Run a single test with the AI agent */ @@ -251,6 +298,10 @@ async function main() { `TestComponent Tool: ${testComponentEnabled ? "Enabled" : "Disabled"}`, ); + // Check pricing availability + const hasPricing = isPricingAvailable(); + console.log(`Pricing Data: ${hasPricing ? "Available" : "Not available (run 'bun run update-model-pricing' to download)"}`); + // Discover all tests console.log("\n📁 Discovering tests..."); const tests = discoverTests(); @@ -346,6 +397,21 @@ async function main() { `Total: ${passed} passed, ${failed} failed, ${skipped} skipped (${(totalDuration / 1000).toFixed(1)}s)`, ); + // Calculate total cost + const totalCost = calculateTotalCost(testResults, envConfig.modelString); + const pricingDisplay = getModelPricingDisplay(envConfig.modelString); + + if (totalCost) { + console.log("\n💰 Cost Summary"); + console.log("─".repeat(50)); + console.log(`Input tokens: ${totalCost.inputTokens.toLocaleString()} (${formatCost(totalCost.inputCost)})`); + console.log(`Output tokens: ${totalCost.outputTokens.toLocaleString()} (${formatCost(totalCost.outputCost)})`); + if (totalCost.cachedInputTokens > 0) { + console.log(`Cached tokens: ${totalCost.cachedInputTokens.toLocaleString()} (${formatCost(totalCost.cacheReadCost)})`); + } + console.log(`Total cost: ${formatCost(totalCost.totalCost)}`); + } + // Ensure results directory exists const resultsDir = "results"; if (!existsSync(resultsDir)) { @@ -358,6 +424,15 @@ async function main() { const jsonPath = `${resultsDir}/${jsonFilename}`; const htmlPath = `${resultsDir}/${htmlFilename}`; + // Build pricing info for metadata + const pricing: PricingInfo | null = pricingDisplay + ? { + inputCostPerMTok: pricingDisplay.inputCostPerMTok, + outputCostPerMTok: pricingDisplay.outputCostPerMTok, + cacheReadCostPerMTok: pricingDisplay.cacheReadCostPerMTok, + } + : null; + // Build the result data const resultData: MultiTestResultData = { tests: testResults, @@ -367,6 +442,8 @@ async function main() { mcpTransportType: mcpEnabled ? mcpTransportType : null, timestamp: new Date().toISOString(), model: envConfig.modelString, + pricing, + totalCost, }, }; diff --git a/lib/pricing.ts b/lib/pricing.ts new file mode 100644 index 0000000..5fc1f9f --- /dev/null +++ b/lib/pricing.ts @@ -0,0 +1,224 @@ +import { readFileSync, existsSync } from "node:fs"; +import { join } from "node:path"; + +const PRICING_FILE_PATH = join(process.cwd(), "data/model-pricing.json"); + +/** + * Model pricing information + */ +export interface ModelPricing { + inputCostPerToken: number; + outputCostPerToken: number; + cacheReadInputTokenCost?: number; + cacheCreationInputTokenCost?: number; +} + +/** + * Cost calculation result + */ +export interface CostCalculation { + inputCost: number; + outputCost: number; + cacheReadCost: number; + totalCost: number; + inputTokens: number; + outputTokens: number; + cachedInputTokens: number; +} + +/** + * Model pricing data with per-million-token rates for display + */ +export interface ModelPricingDisplay { + inputCostPerMTok: number; + outputCostPerMTok: number; + cacheReadCostPerMTok?: number; +} + +// Cache the loaded pricing data +let pricingData: Record | null = null; + +/** + * Load the pricing data from the JSON file + */ +function loadPricingData(): Record { + if (pricingData) { + return pricingData; + } + + if (!existsSync(PRICING_FILE_PATH)) { + console.warn( + `⚠️ Model pricing file not found at ${PRICING_FILE_PATH}. Run 'bun run update-model-pricing' to download it.`, + ); + return {}; + } + + try { + const content = readFileSync(PRICING_FILE_PATH, "utf-8"); + pricingData = JSON.parse(content); + return pricingData ?? {}; + } catch (error) { + console.warn(`⚠️ Failed to load model pricing:`, error); + return {}; + } +} + +/** + * Normalize a model string for pricing lookup + * Handles various formats like: + * - anthropic/claude-sonnet-4 -> claude-sonnet-4 + * - openrouter/anthropic/claude-sonnet-4 -> anthropic/claude-sonnet-4 + * - openai/gpt-4o -> gpt-4o + */ +function normalizeModelForLookup(modelString: string): string[] { + const candidates: string[] = []; + + // Add the original model string (without our provider prefix) + if (modelString.startsWith("openrouter/")) { + // openrouter/anthropic/claude-sonnet-4 -> anthropic/claude-sonnet-4 + const withoutOpenRouter = modelString.replace("openrouter/", ""); + candidates.push(`openrouter/${withoutOpenRouter}`); + candidates.push(withoutOpenRouter); + + // Also try just the model name: anthropic/claude-sonnet-4 -> claude-sonnet-4 + const parts = withoutOpenRouter.split("/"); + if (parts.length > 1) { + candidates.push(parts.slice(1).join("/")); + } + } else if (modelString.startsWith("anthropic/")) { + // anthropic/claude-sonnet-4 -> claude-sonnet-4 + const modelName = modelString.replace("anthropic/", ""); + candidates.push(modelString); + candidates.push(modelName); + // Try common Anthropic naming patterns + candidates.push(`anthropic/${modelName}`); + } else if (modelString.startsWith("openai/")) { + // openai/gpt-4o -> gpt-4o + const modelName = modelString.replace("openai/", ""); + candidates.push(modelString); + candidates.push(modelName); + } else if (modelString.startsWith("lmstudio/")) { + // Local models - won't have pricing + candidates.push(modelString); + } else { + candidates.push(modelString); + } + + return candidates; +} + +/** + * Get pricing information for a model + * Returns null if pricing is not found + */ +export function getModelPricing(modelString: string): ModelPricing | null { + const data = loadPricingData(); + const candidates = normalizeModelForLookup(modelString); + + for (const candidate of candidates) { + const modelData = data[candidate] as Record | undefined; + if (modelData) { + const inputCost = modelData.input_cost_per_token; + const outputCost = modelData.output_cost_per_token; + + if (typeof inputCost === "number" || typeof outputCost === "number") { + return { + inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, + outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, + cacheReadInputTokenCost: + typeof modelData.cache_read_input_token_cost === "number" + ? modelData.cache_read_input_token_cost + : undefined, + cacheCreationInputTokenCost: + typeof modelData.cache_creation_input_token_cost === "number" + ? modelData.cache_creation_input_token_cost + : undefined, + }; + } + } + } + + return null; +} + +/** + * Get pricing display information (cost per million tokens) + */ +export function getModelPricingDisplay( + modelString: string, +): ModelPricingDisplay | null { + const pricing = getModelPricing(modelString); + if (!pricing) return null; + + return { + inputCostPerMTok: pricing.inputCostPerToken * 1_000_000, + outputCostPerMTok: pricing.outputCostPerToken * 1_000_000, + cacheReadCostPerMTok: pricing.cacheReadInputTokenCost + ? pricing.cacheReadInputTokenCost * 1_000_000 + : undefined, + }; +} + +/** + * Calculate the cost for given token usage + */ +export function calculateCost( + modelString: string, + inputTokens: number, + outputTokens: number, + cachedInputTokens: number = 0, +): CostCalculation | null { + const pricing = getModelPricing(modelString); + if (!pricing) return null; + + // For cached tokens, we subtract them from input tokens for billing purposes + // and bill them at the cache read rate (if available, otherwise free) + const uncachedInputTokens = inputTokens - cachedInputTokens; + + const inputCost = uncachedInputTokens * pricing.inputCostPerToken; + const outputCost = outputTokens * pricing.outputCostPerToken; + const cacheReadCost = + cachedInputTokens * (pricing.cacheReadInputTokenCost ?? 0); + + return { + inputCost, + outputCost, + cacheReadCost, + totalCost: inputCost + outputCost + cacheReadCost, + inputTokens, + outputTokens, + cachedInputTokens, + }; +} + +/** + * Format a cost value as USD string + */ +export function formatCost(cost: number): string { + if (cost === 0) return "$0.00"; + if (cost < 0.01) { + return `$${cost.toFixed(6)}`; + } + if (cost < 1) { + return `$${cost.toFixed(4)}`; + } + return `$${cost.toFixed(2)}`; +} + +/** + * Format per-million-token cost + */ +export function formatMTokCost(costPerMTok: number): string { + if (costPerMTok === 0) return "$0"; + if (costPerMTok < 0.01) { + return `$${costPerMTok.toFixed(4)}`; + } + return `$${costPerMTok.toFixed(2)}`; +} + +/** + * Check if pricing data is available + */ +export function isPricingAvailable(): boolean { + return existsSync(PRICING_FILE_PATH); +} diff --git a/lib/report-template.ts b/lib/report-template.ts index ab3d932..4ca2cd2 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -83,6 +83,31 @@ function getFirstLines(code: string, numLines: number): string { return lines.slice(0, numLines).join("\n"); } +/** + * Format a cost value as USD string + */ +function formatCost(cost: number): string { + if (cost === 0) return "$0.00"; + if (cost < 0.01) { + return `$${cost.toFixed(6)}`; + } + if (cost < 1) { + return `$${cost.toFixed(4)}`; + } + return `$${cost.toFixed(2)}`; +} + +/** + * Format per-million-token cost + */ +function formatMTokCost(costPerMTok: number): string { + if (costPerMTok === 0) return "$0"; + if (costPerMTok < 0.01) { + return `$${costPerMTok.toFixed(4)}`; + } + return `$${costPerMTok.toFixed(2)}`; +} + /** * Render a single content block based on its type */ @@ -267,6 +292,181 @@ function renderTestSection(test: SingleTestResult, index: number): string { `; } +/** + * Render pricing section HTML + */ +function renderPricingSection(data: MultiTestResultData): string { + const { metadata } = data; + const { pricing, totalCost } = metadata; + + if (!pricing && !totalCost) { + return ""; + } + + // Build pricing info rows + let pricingInfoHtml = ""; + if (pricing) { + pricingInfoHtml = ` +
+ Model Pricing: + ${formatMTokCost(pricing.inputCostPerMTok)}/MTok in + · + ${formatMTokCost(pricing.outputCostPerMTok)}/MTok out + ${pricing.cacheReadCostPerMTok !== undefined ? `·${formatMTokCost(pricing.cacheReadCostPerMTok)}/MTok cached` : ""} +
+ `; + } + + // Build cost breakdown + let costBreakdownHtml = ""; + if (totalCost) { + const uncachedInputTokens = totalCost.inputTokens - totalCost.cachedInputTokens; + + costBreakdownHtml = ` +
+
+ Input tokens: + ${uncachedInputTokens.toLocaleString()} + ${formatCost(totalCost.inputCost)} +
+
+ Output tokens: + ${totalCost.outputTokens.toLocaleString()} + ${formatCost(totalCost.outputCost)} +
+ ${totalCost.cachedInputTokens > 0 ? ` +
+ Cached tokens: + ${totalCost.cachedInputTokens.toLocaleString()} ⚡ + ${formatCost(totalCost.cacheReadCost)} +
+ ` : ""} +
+ Total Cost: + + ${formatCost(totalCost.totalCost)} +
+
+ `; + } + + return ` +
+
+ 💰 + Cost Summary +
+ ${pricingInfoHtml} + ${costBreakdownHtml} +
+ `; +} + +/** + * Get additional styles for pricing section + */ +function getPricingStyles(): string { + return ` + .pricing-section { + background: var(--surface); + border: 1px solid var(--border); + border-radius: 4px; + padding: 12px; + margin-bottom: 12px; + } + + .pricing-header { + display: flex; + align-items: center; + gap: 8px; + margin-bottom: 12px; + font-weight: 600; + } + + .pricing-icon { + font-size: 16px; + } + + .pricing-title { + font-size: 14px; + } + + .pricing-rates { + display: flex; + align-items: center; + gap: 8px; + font-size: 12px; + color: var(--text-muted); + margin-bottom: 12px; + padding-bottom: 12px; + border-bottom: 1px solid var(--border); + flex-wrap: wrap; + } + + .rate-label { + font-weight: 500; + } + + .rate-value { + font-family: 'JetBrains Mono', monospace; + } + + .rate-separator { + color: var(--border); + } + + .cost-breakdown { + display: flex; + flex-direction: column; + gap: 6px; + } + + .cost-row { + display: grid; + grid-template-columns: 120px 1fr auto; + gap: 8px; + align-items: center; + font-size: 13px; + } + + .cost-row.cached { + color: var(--text-muted); + } + + .cost-row.total { + margin-top: 8px; + padding-top: 8px; + border-top: 1px solid var(--border); + font-weight: 600; + } + + .cost-label { + color: var(--text-muted); + } + + .cost-row.total .cost-label { + color: var(--text); + } + + .cost-tokens { + font-family: 'JetBrains Mono', monospace; + text-align: right; + } + + .cost-value { + font-family: 'JetBrains Mono', monospace; + font-weight: 500; + text-align: right; + min-width: 80px; + } + + .cost-row.total .cost-value { + color: var(--success); + font-size: 15px; + } + `; +} + /** * Generate HTML report from multi-test result data */ @@ -299,6 +499,11 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { ` : ""; + // Cost display in header + const costDisplay = metadata.totalCost + ? `${formatCost(metadata.totalCost.totalCost)}` + : ""; + const overallStatus = failedTests === 0 && skippedTests === 0 ? "all-passed" @@ -310,7 +515,19 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { .map((test, index) => renderTestSection(test, index)) .join("\n"); - const styles = getReportStyles(); + const pricingHtml = renderPricingSection(data); + + const styles = getReportStyles() + getPricingStyles() + ` + .cost-badge { + background: var(--success); + color: white; + font-size: 11px; + padding: 2px 6px; + border-radius: 3px; + font-weight: 500; + font-family: 'JetBrains Mono', monospace; + } + `; return ` @@ -324,7 +541,7 @@ export function generateMultiTestHtml(data: MultiTestResultData): string {
-

SvelteBench 2.0 ${mcpBadge}

+

SvelteBench 2.0 ${mcpBadge} ${costDisplay}

${escapeHtml(metadata.model)} · ${totalTests} tests · ${totalTokens.toLocaleString()} tokens · ${formatTimestamp(metadata.timestamp)}
@@ -338,6 +555,8 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { ${mcpNotice} + ${pricingHtml} + ${testsHtml} \n\n
    \n {#each books as book}\n
  • \n {@render title(book)}\n
    • \n {/each}\n
\n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "toolName": "TestComponent", + "input": { + "content": "\n\n
    \n {#each books as book}\n
  • \n {@render title(book)}\n
    • \n {/each}\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ], + "stop_reason": "tool_use", + "stop_sequence": null, + "usage": { + "input_tokens": 1637, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "output_tokens": 190, + "service_tier": "standard" + } + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 883, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 609, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me try a different approach - snippet declarations in Svelte 5 should be in the template area:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 549 + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1637, + "output_tokens": 190, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Perfect! All tests passed. Now let me submit the final component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": true + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1869, + "outputTokens": 181, + "totalTokens": 2050, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "claude-haiku-4-5", + "max_tokens": 64000, + "messages": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." + }, + { + "type": "tool_use", + "id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":883,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" + }, + { + "type": "tool_use", + "id": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":609,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me try a different approach - snippet declarations in Svelte 5 should be in the template area:" + }, + { + "type": "tool_use", + "id": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "name": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":549}" + } + ] + } + ], + "tools": [ + { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "tool_choice": { + "type": "auto" + } + } + }, + "response": { + "id": "msg_01XLwdY3Phr2FzR5wBEtFzhL", + "timestamp": "2025-12-09T20:21:09.449Z", + "modelId": "claude-haiku-4-5-20251001", + "headers": { + "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", + "anthropic-ratelimit-input-tokens-limit": "450000", + "anthropic-ratelimit-input-tokens-remaining": "449000", + "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:21:08Z", + "anthropic-ratelimit-output-tokens-limit": "90000", + "anthropic-ratelimit-output-tokens-remaining": "90000", + "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:21:09Z", + "anthropic-ratelimit-requests-limit": "1000", + "anthropic-ratelimit-requests-remaining": "999", + "anthropic-ratelimit-requests-reset": "2025-12-09T20:21:08Z", + "anthropic-ratelimit-tokens-limit": "540000", + "anthropic-ratelimit-tokens-remaining": "539000", + "anthropic-ratelimit-tokens-reset": "2025-12-09T20:21:08Z", + "cf-cache-status": "DYNAMIC", + "cf-ray": "9ab73506494b5571-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:21:09 GMT", + "request-id": "req_011CVwja1GKBgXYfdmgBpmto", + "server": "cloudflare", + "strict-transport-security": "max-age=31536000; includeSubDomains; preload", + "transfer-encoding": "chunked", + "x-envoy-upstream-service-time": "1277", + "x-robots-tag": "none" + }, + "body": { + "model": "claude-haiku-4-5-20251001", + "id": "msg_01XLwdY3Phr2FzR5wBEtFzhL", + "type": "message", + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Perfect! All tests passed. Now let me submit the final component:" + }, + { + "type": "tool_use", + "id": "toolu_018hisFMvwP6DvXdmuFZ6w19", + "name": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ], + "stop_reason": "tool_use", + "stop_sequence": null, + "usage": { + "input_tokens": 1869, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "output_tokens": 181, + "service_tier": "standard" + } + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 883, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 609, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me try a different approach - snippet declarations in Svelte 5 should be in the template area:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 549 + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Perfect! All tests passed. Now let me submit the final component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", + "toolName": "ResultWrite", + "output": { + "type": "json", + "value": { + "success": true + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1869, + "output_tokens": 181, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + } + } + } + ], + "resultWriteContent": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n", + "verification": { + "testName": "snippets", + "passed": true, + "numTests": 3, + "numPassed": 3, + "numFailed": 0, + "duration": 488 + } + } + ], + "metadata": { + "mcpEnabled": false, + "mcpServerUrl": null, + "mcpTransportType": null, + "timestamp": "2025-12-09T20:21:09.952Z", + "model": "anthropic/claude-haiku-4-5", + "pricing": { + "inputCostPerMTok": 1, + "outputCostPerMTok": 5, + "cacheReadCostPerMTok": 0.09999999999999999 + }, + "totalCost": { + "inputCost": 0.0059039999999999995, + "outputCost": 0.0038250000000000003, + "cacheReadCost": 0, + "totalCost": 0.009729, + "inputTokens": 5904, + "outputTokens": 765, + "cachedInputTokens": 0 + } + } +} \ No newline at end of file diff --git a/scripts/update-model-pricing.ts b/scripts/update-model-pricing.ts new file mode 100644 index 0000000..20d8109 --- /dev/null +++ b/scripts/update-model-pricing.ts @@ -0,0 +1,76 @@ +#!/usr/bin/env bun +/** + * Script to download the latest model pricing data from LiteLLM + * Run with: bun run update-model-pricing + */ + +import { writeFileSync, mkdirSync, existsSync } from "node:fs"; +import { dirname } from "node:path"; + +const PRICING_URL = + "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"; +const OUTPUT_PATH = "data/model-pricing.json"; + +async function downloadPricing(): Promise { + console.log("📥 Downloading model pricing data from LiteLLM..."); + console.log(` URL: ${PRICING_URL}`); + + try { + const response = await fetch(PRICING_URL); + + if (!response.ok) { + throw new Error(`HTTP ${response.status}: ${response.statusText}`); + } + + const data = await response.json(); + + // Validate the data has expected structure + if (typeof data !== "object" || data === null) { + throw new Error("Invalid JSON: expected an object"); + } + + const modelCount = Object.keys(data).length; + console.log(`✓ Downloaded pricing for ${modelCount} models`); + + // Ensure the output directory exists + const dir = dirname(OUTPUT_PATH); + if (!existsSync(dir)) { + mkdirSync(dir, { recursive: true }); + } + + // Write the file with pretty formatting + writeFileSync(OUTPUT_PATH, JSON.stringify(data, null, 2)); + console.log(`✓ Saved to ${OUTPUT_PATH}`); + + // Show some stats + let chatModels = 0; + let modelsWithPricing = 0; + + for (const [key, value] of Object.entries(data)) { + if (key === "sample_spec") continue; + + const model = value as Record; + if (model.mode === "chat") { + chatModels++; + } + if ( + typeof model.input_cost_per_token === "number" || + typeof model.output_cost_per_token === "number" + ) { + modelsWithPricing++; + } + } + + console.log(`\n📊 Stats:`); + console.log(` Chat models: ${chatModels}`); + console.log(` Models with token pricing: ${modelsWithPricing}`); + } catch (error) { + console.error( + "✗ Failed to download pricing:", + error instanceof Error ? error.message : error, + ); + process.exit(1); + } +} + +downloadPricing(); From a872789ca9adcf74ccd9330b93674b69ca3f15ce Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 21:47:13 +0100 Subject: [PATCH 02/29] add pricing mapping --- index.ts | 138 ++++++++++++++++++++++++++++++++--------- lib/pricing.ts | 102 +++++++++++++++++++++++------- lib/report-template.ts | 17 ++++- lib/report.ts | 2 +- 4 files changed, 206 insertions(+), 53 deletions(-) diff --git a/index.ts b/index.ts index 1d6c1ef..a2c7544 100644 --- a/index.ts +++ b/index.ts @@ -23,10 +23,14 @@ import { } from "./lib/output-test-runner.ts"; import { resultWriteTool, testComponentTool } from "./lib/tools/index.ts"; import { + lookupModelPricing, + lookupModelPricingByKey, getModelPricingDisplay, calculateCost, formatCost, isPricingAvailable, + type ModelPricing, + type ModelPricingLookup, } from "./lib/pricing.ts"; import type { LanguageModel } from "ai"; @@ -97,8 +101,8 @@ function extractResultWriteContent(steps: unknown[]): string | null { */ function calculateTotalCost( tests: SingleTestResult[], - modelString: string, -): TotalCostInfo | null { + pricing: ModelPricing, +): TotalCostInfo { let totalInputTokens = 0; let totalOutputTokens = 0; let totalCachedInputTokens = 0; @@ -112,14 +116,12 @@ function calculateTotalCost( } const costResult = calculateCost( - modelString, + pricing, totalInputTokens, totalOutputTokens, totalCachedInputTokens, ); - if (!costResult) return null; - return { inputCost: costResult.inputCost, outputCost: costResult.outputCost, @@ -131,6 +133,69 @@ function calculateTotalCost( }; } +/** + * Resolve pricing lookup based on environment variables + * Returns the pricing lookup result or null if disabled + * Throws an error if pricing cannot be found and is not disabled + */ +function resolvePricingLookup(modelString: string): ModelPricingLookup | null { + const costDisabled = process.env.MODEL_COST_DISABLED === "true"; + const explicitCostName = process.env.MODEL_COST_NAME; + + // If cost calculation is explicitly disabled, return null + if (costDisabled) { + return null; + } + + // Check if pricing data file exists + if (!isPricingAvailable()) { + console.error( + `\n✗ Model pricing file not found. Run 'bun run update-model-pricing' to download it.`, + ); + console.error( + ` Or set MODEL_COST_DISABLED=true to skip cost calculation.\n`, + ); + process.exit(1); + } + + // If explicit cost name is provided, use that + if (explicitCostName) { + const lookup = lookupModelPricingByKey(explicitCostName); + if (!lookup) { + console.error( + `\n✗ Could not find pricing for MODEL_COST_NAME="${explicitCostName}" in model-pricing.json`, + ); + console.error( + ` Check that the key exists in data/model-pricing.json.\n`, + ); + process.exit(1); + } + return lookup; + } + + // Try automatic lookup + const lookup = lookupModelPricing(modelString); + if (!lookup) { + console.error( + `\n✗ Could not find pricing for model "${modelString}" in model-pricing.json`, + ); + console.error(`\n Options:`); + console.error( + ` 1. Set MODEL_COST_NAME= to explicitly specify the pricing key`, + ); + console.error(` Example: MODEL_COST_NAME=claude-sonnet-4-20250514`); + console.error( + ` 2. Set MODEL_COST_DISABLED=true to skip cost calculation`, + ); + console.error( + `\n Browse data/model-pricing.json to find the correct key for your model.\n`, + ); + process.exit(1); + } + + return lookup; +} + /** * Run a single test with the AI agent */ @@ -281,10 +346,24 @@ async function main() { const isHttpTransport = mcpEnabled && isHttpUrl(mcpServerUrl); const mcpTransportType = isHttpTransport ? "HTTP" : "StdIO"; + // Load environment configuration + const envConfig = loadEnvConfig(); + console.log("╔════════════════════════════════════════════════════╗"); console.log("║ SvelteBench 2.0 - Multi-Test ║"); console.log("╚════════════════════════════════════════════════════╝"); - console.log(`Model: ${process.env.MODEL}`); + console.log(`Model: ${envConfig.modelString}`); + + // Resolve pricing lookup + const costDisabled = process.env.MODEL_COST_DISABLED === "true"; + const pricingLookup = resolvePricingLookup(envConfig.modelString); + + if (pricingLookup) { + console.log(`Pricing model mapped: ${pricingLookup.matchedKey}`); + } else if (costDisabled) { + console.log(`Pricing: Disabled (MODEL_COST_DISABLED=true)`); + } + console.log(`MCP Integration: ${mcpEnabled ? "Enabled" : "Disabled"}`); if (mcpEnabled) { console.log(`MCP Transport: ${mcpTransportType}`); @@ -298,10 +377,6 @@ async function main() { `TestComponent Tool: ${testComponentEnabled ? "Enabled" : "Disabled"}`, ); - // Check pricing availability - const hasPricing = isPricingAvailable(); - console.log(`Pricing Data: ${hasPricing ? "Available" : "Not available (run 'bun run update-model-pricing' to download)"}`); - // Discover all tests console.log("\n📁 Discovering tests..."); const tests = discoverTests(); @@ -340,8 +415,7 @@ async function main() { } } - // Load environment configuration and get model provider - const envConfig = loadEnvConfig(); + // Get model provider const model = getModelProvider(envConfig); // Run all tests @@ -397,17 +471,31 @@ async function main() { `Total: ${passed} passed, ${failed} failed, ${skipped} skipped (${(totalDuration / 1000).toFixed(1)}s)`, ); - // Calculate total cost - const totalCost = calculateTotalCost(testResults, envConfig.modelString); - const pricingDisplay = getModelPricingDisplay(envConfig.modelString); + // Calculate total cost if pricing is available + let totalCost: TotalCostInfo | null = null; + let pricingInfo: PricingInfo | null = null; + + if (pricingLookup) { + totalCost = calculateTotalCost(testResults, pricingLookup.pricing); + const pricingDisplay = getModelPricingDisplay(pricingLookup.pricing); + pricingInfo = { + inputCostPerMTok: pricingDisplay.inputCostPerMTok, + outputCostPerMTok: pricingDisplay.outputCostPerMTok, + cacheReadCostPerMTok: pricingDisplay.cacheReadCostPerMTok, + }; - if (totalCost) { console.log("\n💰 Cost Summary"); console.log("─".repeat(50)); - console.log(`Input tokens: ${totalCost.inputTokens.toLocaleString()} (${formatCost(totalCost.inputCost)})`); - console.log(`Output tokens: ${totalCost.outputTokens.toLocaleString()} (${formatCost(totalCost.outputCost)})`); + console.log( + `Input tokens: ${totalCost.inputTokens.toLocaleString()} (${formatCost(totalCost.inputCost)})`, + ); + console.log( + `Output tokens: ${totalCost.outputTokens.toLocaleString()} (${formatCost(totalCost.outputCost)})`, + ); if (totalCost.cachedInputTokens > 0) { - console.log(`Cached tokens: ${totalCost.cachedInputTokens.toLocaleString()} (${formatCost(totalCost.cacheReadCost)})`); + console.log( + `Cached tokens: ${totalCost.cachedInputTokens.toLocaleString()} (${formatCost(totalCost.cacheReadCost)})`, + ); } console.log(`Total cost: ${formatCost(totalCost.totalCost)}`); } @@ -424,15 +512,6 @@ async function main() { const jsonPath = `${resultsDir}/${jsonFilename}`; const htmlPath = `${resultsDir}/${htmlFilename}`; - // Build pricing info for metadata - const pricing: PricingInfo | null = pricingDisplay - ? { - inputCostPerMTok: pricingDisplay.inputCostPerMTok, - outputCostPerMTok: pricingDisplay.outputCostPerMTok, - cacheReadCostPerMTok: pricingDisplay.cacheReadCostPerMTok, - } - : null; - // Build the result data const resultData: MultiTestResultData = { tests: testResults, @@ -442,7 +521,8 @@ async function main() { mcpTransportType: mcpEnabled ? mcpTransportType : null, timestamp: new Date().toISOString(), model: envConfig.modelString, - pricing, + pricingKey: pricingLookup?.matchedKey ?? null, + pricing: pricingInfo, totalCost, }, }; diff --git a/lib/pricing.ts b/lib/pricing.ts index 5fc1f9f..d064e47 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -35,6 +35,14 @@ export interface ModelPricingDisplay { cacheReadCostPerMTok?: number; } +/** + * Result of looking up a model's pricing + */ +export interface ModelPricingLookup { + pricing: ModelPricing; + matchedKey: string; +} + // Cache the loaded pricing data let pricingData: Record | null = null; @@ -108,10 +116,10 @@ function normalizeModelForLookup(modelString: string): string[] { } /** - * Get pricing information for a model + * Look up pricing information for a model, returning both the pricing and the matched key * Returns null if pricing is not found */ -export function getModelPricing(modelString: string): ModelPricing | null { +export function lookupModelPricing(modelString: string): ModelPricingLookup | null { const data = loadPricingData(); const candidates = normalizeModelForLookup(modelString); @@ -123,16 +131,19 @@ export function getModelPricing(modelString: string): ModelPricing | null { if (typeof inputCost === "number" || typeof outputCost === "number") { return { - inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, - outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, - cacheReadInputTokenCost: - typeof modelData.cache_read_input_token_cost === "number" - ? modelData.cache_read_input_token_cost - : undefined, - cacheCreationInputTokenCost: - typeof modelData.cache_creation_input_token_cost === "number" - ? modelData.cache_creation_input_token_cost - : undefined, + pricing: { + inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, + outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, + cacheReadInputTokenCost: + typeof modelData.cache_read_input_token_cost === "number" + ? modelData.cache_read_input_token_cost + : undefined, + cacheCreationInputTokenCost: + typeof modelData.cache_creation_input_token_cost === "number" + ? modelData.cache_creation_input_token_cost + : undefined, + }, + matchedKey: candidate, }; } } @@ -141,15 +152,57 @@ export function getModelPricing(modelString: string): ModelPricing | null { return null; } +/** + * Get pricing information for a model using an explicit key + * Returns null if pricing is not found + */ +export function lookupModelPricingByKey(pricingKey: string): ModelPricingLookup | null { + const data = loadPricingData(); + const modelData = data[pricingKey] as Record | undefined; + + if (!modelData) { + return null; + } + + const inputCost = modelData.input_cost_per_token; + const outputCost = modelData.output_cost_per_token; + + if (typeof inputCost === "number" || typeof outputCost === "number") { + return { + pricing: { + inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, + outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, + cacheReadInputTokenCost: + typeof modelData.cache_read_input_token_cost === "number" + ? modelData.cache_read_input_token_cost + : undefined, + cacheCreationInputTokenCost: + typeof modelData.cache_creation_input_token_cost === "number" + ? modelData.cache_creation_input_token_cost + : undefined, + }, + matchedKey: pricingKey, + }; + } + + return null; +} + +/** + * Get pricing information for a model (legacy function for compatibility) + * Returns null if pricing is not found + */ +export function getModelPricing(modelString: string): ModelPricing | null { + const lookup = lookupModelPricing(modelString); + return lookup?.pricing ?? null; +} + /** * Get pricing display information (cost per million tokens) */ export function getModelPricingDisplay( - modelString: string, -): ModelPricingDisplay | null { - const pricing = getModelPricing(modelString); - if (!pricing) return null; - + pricing: ModelPricing, +): ModelPricingDisplay { return { inputCostPerMTok: pricing.inputCostPerToken * 1_000_000, outputCostPerMTok: pricing.outputCostPerToken * 1_000_000, @@ -163,14 +216,11 @@ export function getModelPricingDisplay( * Calculate the cost for given token usage */ export function calculateCost( - modelString: string, + pricing: ModelPricing, inputTokens: number, outputTokens: number, cachedInputTokens: number = 0, -): CostCalculation | null { - const pricing = getModelPricing(modelString); - if (!pricing) return null; - +): CostCalculation { // For cached tokens, we subtract them from input tokens for billing purposes // and bill them at the cache read rate (if available, otherwise free) const uncachedInputTokens = inputTokens - cachedInputTokens; @@ -222,3 +272,11 @@ export function formatMTokCost(costPerMTok: number): string { export function isPricingAvailable(): boolean { return existsSync(PRICING_FILE_PATH); } + +/** + * Get all available model keys (for debugging/listing) + */ +export function getAllModelKeys(): string[] { + const data = loadPricingData(); + return Object.keys(data).filter((key) => key !== "sample_spec"); +} diff --git a/lib/report-template.ts b/lib/report-template.ts index 4ca2cd2..57429cc 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -297,7 +297,7 @@ function renderTestSection(test: SingleTestResult, index: number): string { */ function renderPricingSection(data: MultiTestResultData): string { const { metadata } = data; - const { pricing, totalCost } = metadata; + const { pricing, totalCost, pricingKey } = metadata; if (!pricing && !totalCost) { return ""; @@ -306,9 +306,14 @@ function renderPricingSection(data: MultiTestResultData): string { // Build pricing info rows let pricingInfoHtml = ""; if (pricing) { + const pricingKeyDisplay = pricingKey + ? `${escapeHtml(pricingKey)}` + : ""; + pricingInfoHtml = `
    Model Pricing: + ${pricingKeyDisplay} ${formatMTokCost(pricing.inputCostPerMTok)}/MTok in · ${formatMTokCost(pricing.outputCostPerMTok)}/MTok out @@ -407,6 +412,16 @@ function getPricingStyles(): string { font-weight: 500; } + .pricing-key { + font-family: 'JetBrains Mono', monospace; + background: var(--bg); + padding: 2px 6px; + border-radius: 3px; + border: 1px solid var(--border); + color: var(--text); + font-size: 11px; + } + .rate-value { font-family: 'JetBrains Mono', monospace; } diff --git a/lib/report.ts b/lib/report.ts index b5aa34b..e1a4227 100644 --- a/lib/report.ts +++ b/lib/report.ts @@ -1,7 +1,6 @@ import { readFile, writeFile } from "node:fs/promises"; import type { TestVerificationResult } from "./output-test-runner.ts"; import { generateMultiTestHtml } from "./report-template.ts"; -import type { CostCalculation, ModelPricingDisplay } from "./pricing.ts"; // Type definitions for result.json structure interface TextBlock { @@ -95,6 +94,7 @@ interface Metadata { mcpTransportType?: string | null; timestamp: string; model: string; + pricingKey?: string | null; pricing?: PricingInfo | null; totalCost?: TotalCostInfo | null; } From cf36c36e8dd7f0d117e0d3f7b62d24b33f4b2b12 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 21:48:35 +0100 Subject: [PATCH 03/29] examples with pricing --- results/result-2025-12-09-21-45-46.json | 41 + results/result-2025-12-09-21-46-37.json | 1314 +++++++++++++++++++++++ results/result-2025-12-09-21-48-12.json | 1152 ++++++++++++++++++++ 3 files changed, 2507 insertions(+) create mode 100644 results/result-2025-12-09-21-45-46.json create mode 100644 results/result-2025-12-09-21-46-37.json create mode 100644 results/result-2025-12-09-21-48-12.json diff --git a/results/result-2025-12-09-21-45-46.json b/results/result-2025-12-09-21-45-46.json new file mode 100644 index 0000000..a70462f --- /dev/null +++ b/results/result-2025-12-09-21-45-46.json @@ -0,0 +1,41 @@ +{ + "tests": [ + { + "testName": "snippets", + "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", + "steps": [], + "resultWriteContent": null, + "verification": { + "testName": "snippets", + "passed": false, + "numTests": 0, + "numPassed": 0, + "numFailed": 0, + "duration": 0, + "error": "anthropic/claude-haiku-4-5 is not a valid model ID" + } + } + ], + "metadata": { + "mcpEnabled": false, + "mcpServerUrl": null, + "mcpTransportType": null, + "timestamp": "2025-12-09T20:45:46.019Z", + "model": "openrouter/anthropic/claude-haiku-4-5", + "pricingKey": "claude-haiku-4-5", + "pricing": { + "inputCostPerMTok": 1, + "outputCostPerMTok": 5, + "cacheReadCostPerMTok": 0.09999999999999999 + }, + "totalCost": { + "inputCost": 0, + "outputCost": 0, + "cacheReadCost": 0, + "totalCost": 0, + "inputTokens": 0, + "outputTokens": 0, + "cachedInputTokens": 0 + } + } +} \ No newline at end of file diff --git a/results/result-2025-12-09-21-46-37.json b/results/result-2025-12-09-21-46-37.json new file mode 100644 index 0000000..3112711 --- /dev/null +++ b/results/result-2025-12-09-21-46-37.json @@ -0,0 +1,1314 @@ +{ + "tests": [ + { + "testName": "snippets", + "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", + "steps": [ + { + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 841, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1051, + "outputTokens": 198, + "totalTokens": 1249, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "claude-haiku-4-5", + "max_tokens": 64000, + "messages": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + } + ], + "tools": [ + { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "tool_choice": { + "type": "auto" + } + } + }, + "response": { + "id": "msg_01DS8ULCCUfKKRtFwjfhNV5d", + "timestamp": "2025-12-09T20:46:29.821Z", + "modelId": "claude-haiku-4-5-20251001", + "headers": { + "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", + "anthropic-ratelimit-input-tokens-limit": "450000", + "anthropic-ratelimit-input-tokens-remaining": "450000", + "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:28Z", + "anthropic-ratelimit-output-tokens-limit": "90000", + "anthropic-ratelimit-output-tokens-remaining": "90000", + "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:29Z", + "anthropic-ratelimit-requests-limit": "1000", + "anthropic-ratelimit-requests-remaining": "999", + "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:28Z", + "anthropic-ratelimit-tokens-limit": "540000", + "anthropic-ratelimit-tokens-remaining": "540000", + "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:28Z", + "cf-cache-status": "DYNAMIC", + "cf-ray": "9ab75a22b9b27bf6-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:46:29 GMT", + "request-id": "req_011CVwmW4EXTmTBuUVPpZP98", + "server": "cloudflare", + "strict-transport-security": "max-age=31536000; includeSubDomains; preload", + "transfer-encoding": "chunked", + "x-envoy-upstream-service-time": "1497", + "x-robots-tag": "none" + }, + "body": { + "model": "claude-haiku-4-5-20251001", + "id": "msg_01DS8ULCCUfKKRtFwjfhNV5d", + "type": "message", + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool_use", + "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ], + "stop_reason": "tool_use", + "stop_sequence": null, + "usage": { + "input_tokens": 1051, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "output_tokens": 198, + "service_tier": "standard" + } + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 841, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1051, + "output_tokens": 198, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 532 + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1345, + "outputTokens": 209, + "totalTokens": 1554, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "claude-haiku-4-5", + "max_tokens": 64000, + "messages": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool_use", + "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ] + } + ], + "tools": [ + { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "input_schema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "tool_choice": { + "type": "auto" + } + } + }, + "response": { + "id": "msg_019g2cMRiK4VhszbmqGcsy4Y", + "timestamp": "2025-12-09T20:46:32.255Z", + "modelId": "claude-haiku-4-5-20251001", + "headers": { + "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", + "anthropic-ratelimit-input-tokens-limit": "450000", + "anthropic-ratelimit-input-tokens-remaining": "449000", + "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:31Z", + "anthropic-ratelimit-output-tokens-limit": "90000", + "anthropic-ratelimit-output-tokens-remaining": "90000", + "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:32Z", + "anthropic-ratelimit-requests-limit": "1000", + "anthropic-ratelimit-requests-remaining": "999", + "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:31Z", + "anthropic-ratelimit-tokens-limit": "540000", + "anthropic-ratelimit-tokens-remaining": "539000", + "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:31Z", + "cf-cache-status": "DYNAMIC", + "cf-ray": "9ab75a339bff7bf6-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:46:32 GMT", + "request-id": "req_011CVwmWFnJfuTLjFR9c1b5C", + "server": "cloudflare", + "strict-transport-security": "max-age=31536000; includeSubDomains; preload", + "transfer-encoding": "chunked", + "x-envoy-upstream-service-time": "1342", + "x-robots-tag": "none" + }, + "body": { + "model": "claude-haiku-4-5-20251001", + "id": "msg_019g2cMRiK4VhszbmqGcsy4Y", + "type": "message", + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool_use", + "id": "toolu_019MyaVX5GgJzVQUum78NnHt", + "name": "TestComponent", + "input": { + "content": "\n\n
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    • \n {book}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 841, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 532 + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1345, + "output_tokens": 209, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 507 + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1596, + "outputTokens": 198, + "totalTokens": 1794, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "claude-haiku-4-5", + "max_tokens": 64000, + "messages": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool_use", + "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool_use", + "id": "toolu_019MyaVX5GgJzVQUum78NnHt", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ], + "stop_reason": "tool_use", + "stop_sequence": null, + "usage": { + "input_tokens": 1596, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "output_tokens": 198, + "service_tier": "standard" + } + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 507 + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1596, + "output_tokens": 198, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Perfect! The Svelte 5 snippet syntax is working correctly. Now let me submit the final component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." + }, + { + "type": "tool_use", + "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool_use", + "id": "toolu_019MyaVX5GgJzVQUum78NnHt", + "name": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "user", + "content": [ + { + "type": "tool_result", + "tool_use_id": "toolu_019MyaVX5GgJzVQUum78NnHt", + "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":532}" + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" + }, + { + "type": "tool_use", + "id": "toolu_012kiBuyMBsADkHJ43yvMzzV", + "name": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 841, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", + "toolName": "TestComponent", + "input": { + "content": "\n\n
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      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", + "steps": [ + { + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ], + "tools": [ + { + "type": "function", + "function": { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + }, + { + "type": "function", + "function": { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + } + ], + "tool_choice": "auto" + } + }, + "response": { + "id": "gen-1765313278-2tTFQlOjDEkBYaENUhMY", + "timestamp": "2025-12-09T20:48:01.151Z", + "modelId": "anthropic/claude-haiku-4.5", + "headers": { + "access-control-allow-origin": "*", + "cf-ray": "9ab75c574e969920-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:47:59 GMT", + "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", + "referrer-policy": "no-referrer, strict-origin-when-cross-origin", + "server": "cloudflare", + "transfer-encoding": "chunked", + "vary": "Accept-Encoding", + "x-content-type-options": "nosniff" + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "input": { + "content": "\n\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + }, + { + "role": "assistant", + "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", + "tool_calls": [ + { + "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
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      • \\n {/each}\\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 508, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + } + ] + }, + "providerMetadata": { + "openrouter": { + "provider": "Amazon Bedrock", + "reasoning_details": [], + "usage": { + "promptTokens": 1348, + "promptTokensDetails": { + "cachedTokens": 0 + }, + "completionTokens": 185, + "completionTokensDetails": { + "reasoningTokens": 0 + }, + "totalTokens": 1533, + "cost": 0.00225027 + } + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerMetadata": { + "openrouter": { + "reasoning_details": [] + } + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 521 + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1629, + "outputTokens": 186, + "totalTokens": 1815, + "reasoningTokens": 0, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "anthropic/claude-haiku-4.5", + "messages": [ + { + "role": "user", + "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + }, + { + "role": "assistant", + "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", + "tool_calls": [ + { + "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":827,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + }, + { + "role": "assistant", + "content": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:", + "tool_calls": [ + { + "id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":508,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + } + ], + "tools": [ + { + "type": "function", + "function": { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + }, + { + "type": "function", + "function": { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + } + ], + "tool_choice": "auto" + } + }, + "response": { + "id": "gen-1765313285-cXUgg1XpbsQi9AUgVJx2", + "timestamp": "2025-12-09T20:48:08.501Z", + "modelId": "anthropic/claude-haiku-4.5", + "headers": { + "access-control-allow-origin": "*", + "cf-ray": "9ab75c82fedc9920-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:48:07 GMT", + "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", + "referrer-policy": "no-referrer, strict-origin-when-cross-origin", + "server": "cloudflare", + "transfer-encoding": "chunked", + "vary": "Accept-Encoding", + "x-content-type-options": "nosniff" + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 827, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 508, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 521 + } + } + } + ] + } + ] + }, + "providerMetadata": { + "openrouter": { + "provider": "Amazon Bedrock", + "reasoning_details": [], + "usage": { + "promptTokens": 1629, + "promptTokensDetails": { + "cachedTokens": 0 + }, + "completionTokens": 186, + "completionTokensDetails": { + "reasoningTokens": 0 + }, + "totalTokens": 1815, + "cost": 0.00253341 + } + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Perfect! The component passes all tests. Now let me submit the final implementation:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerMetadata": { + "openrouter": { + "reasoning_details": [] + } + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "output": { + "success": true + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1857, + "outputTokens": 183, + "totalTokens": 2040, + "reasoningTokens": 0, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "model": "anthropic/claude-haiku-4.5", + "messages": [ + { + "role": "user", + "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + }, + { + "role": "assistant", + "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", + "tool_calls": [ + { + "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":827,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + }, + { + "role": "assistant", + "content": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:", + "tool_calls": [ + { + "id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":508,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" + }, + { + "role": "assistant", + "content": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:", + "tool_calls": [ + { + "id": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "type": "function", + "function": { + "name": "TestComponent", + "arguments": "{\"content\":\"\\n\\n{#snippet title(bookTitle)}\\n {bookTitle}\\n{/snippet}\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":521}" + } + ], + "tools": [ + { + "type": "function", + "function": { + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + }, + { + "type": "function", + "function": { + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "parameters": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + } + ], + "tool_choice": "auto" + } + }, + "response": { + "id": "gen-1765313289-24sHvpTHhwj6FV298zOu", + "timestamp": "2025-12-09T20:48:11.690Z", + "modelId": "anthropic/claude-haiku-4.5", + "headers": { + "access-control-allow-origin": "*", + "cf-ray": "9ab75c9a4c369920-ARN", + "connection": "keep-alive", + "content-encoding": "gzip", + "content-type": "application/json", + "date": "Tue, 09 Dec 2025 20:48:10 GMT", + "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", + "referrer-policy": "no-referrer, strict-origin-when-cross-origin", + "server": "cloudflare", + "transfer-encoding": "chunked", + "vary": "Accept-Encoding", + "x-content-type-options": "nosniff" + }, + "messages": [ + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 827, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 508, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 521 + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Perfect! The component passes all tests. Now let me submit the final implementation:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" + }, + "providerOptions": { + "openrouter": { + "reasoning_details": [] + } + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", + "toolName": "ResultWrite", + "output": { + "type": "json", + "value": { + "success": true + } + } + } + ] + } + ] + }, + "providerMetadata": { + "openrouter": { + "provider": "Amazon Bedrock", + "reasoning_details": [], + "usage": { + "promptTokens": 1857, + "promptTokensDetails": { + "cachedTokens": 0 + }, + "completionTokens": 183, + "completionTokensDetails": { + "reasoningTokens": 0 + }, + "totalTokens": 2040, + "cost": 0.00274428 + } + } + } + } + ], + "resultWriteContent": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n", + "verification": { + "testName": "snippets", + "passed": true, + "numTests": 3, + "numPassed": 3, + "numFailed": 0, + "duration": 532 + } + } + ], + "metadata": { + "mcpEnabled": false, + "mcpServerUrl": null, + "mcpTransportType": null, + "timestamp": "2025-12-09T20:48:12.235Z", + "model": "openrouter/anthropic/claude-haiku-4.5", + "pricingKey": "openrouter/anthropic/claude-haiku-4.5", + "pricing": { + "inputCostPerMTok": 1, + "outputCostPerMTok": 5, + "cacheReadCostPerMTok": 0.09999999999999999 + }, + "totalCost": { + "inputCost": 0.005885, + "outputCost": 0.003775, + "cacheReadCost": 0, + "totalCost": 0.00966, + "inputTokens": 5885, + "outputTokens": 755, + "cachedInputTokens": 0 + } + } +} \ No newline at end of file From eb74cf02e1465733dd5cd27fbf4bf49332f0917b Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 21:50:08 +0100 Subject: [PATCH 04/29] Update .gitkeep --- data/.gitkeep | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/data/.gitkeep b/data/.gitkeep index 4df4445..488db3c 100644 --- a/data/.gitkeep +++ b/data/.gitkeep @@ -1,2 +1,2 @@ -# This directory contains versioned data files +# This directory contains downloaded data files # Run `bun run update-model-pricing` to update model-pricing.json From d2d580868987fcb580648f420136c24315f5cdeb Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 21:59:50 +0100 Subject: [PATCH 05/29] wip --- lib/pricing.test.ts | 260 +++++++++++++++++++++++++++++++++++++++++ lib/pricing.ts | 194 +++++++++++++++++------------- lib/report-template.ts | 26 +---- package.json | 3 +- 4 files changed, 375 insertions(+), 108 deletions(-) create mode 100644 lib/pricing.test.ts diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts new file mode 100644 index 0000000..9ecf453 --- /dev/null +++ b/lib/pricing.test.ts @@ -0,0 +1,260 @@ +import { describe, it, expect } from "vitest"; +import { + _generateLookupCandidates as generateLookupCandidates, + calculateCost, + formatCost, + formatMTokCost, + getModelPricingDisplay, + type ModelPricing, +} from "./pricing.ts"; + +describe("generateLookupCandidates", () => { + describe("openrouter provider", () => { + it("should generate candidates for openrouter/anthropic/model", () => { + const candidates = generateLookupCandidates( + "openrouter/anthropic/claude-sonnet-4", + ); + expect(candidates).toEqual([ + "openrouter/anthropic/claude-sonnet-4", + "anthropic/claude-sonnet-4", + "claude-sonnet-4", + ]); + }); + + it("should generate candidates for openrouter/openai/model", () => { + const candidates = generateLookupCandidates("openrouter/openai/gpt-4o"); + expect(candidates).toEqual([ + "openrouter/openai/gpt-4o", + "openai/gpt-4o", + "gpt-4o", + ]); + }); + + it("should handle openrouter with simple model name", () => { + const candidates = generateLookupCandidates("openrouter/some-model"); + expect(candidates).toEqual(["openrouter/some-model", "some-model"]); + }); + }); + + describe("anthropic provider", () => { + it("should generate candidates for anthropic/model", () => { + const candidates = generateLookupCandidates("anthropic/claude-haiku-4-5"); + expect(candidates).toEqual([ + "anthropic/claude-haiku-4-5", + "claude-haiku-4-5", + ]); + }); + }); + + describe("openai provider", () => { + it("should generate candidates for openai/model", () => { + const candidates = generateLookupCandidates("openai/gpt-4o"); + expect(candidates).toEqual(["openai/gpt-4o", "gpt-4o"]); + }); + + it("should handle openai/gpt-4o-mini", () => { + const candidates = generateLookupCandidates("openai/gpt-4o-mini"); + expect(candidates).toEqual(["openai/gpt-4o-mini", "gpt-4o-mini"]); + }); + }); + + describe("lmstudio provider", () => { + it("should generate candidates for lmstudio/model", () => { + const candidates = generateLookupCandidates("lmstudio/llama-3-8b"); + expect(candidates).toEqual(["lmstudio/llama-3-8b", "llama-3-8b"]); + }); + }); + + describe("unknown provider", () => { + it("should return only the original string for unknown provider", () => { + const candidates = generateLookupCandidates("unknown/some-model"); + expect(candidates).toEqual(["unknown/some-model"]); + }); + }); + + describe("no provider prefix", () => { + it("should return only the original string when no slash", () => { + const candidates = generateLookupCandidates("claude-sonnet-4"); + expect(candidates).toEqual(["claude-sonnet-4"]); + }); + }); +}); + +describe("calculateCost", () => { + const basePricing: ModelPricing = { + inputCostPerToken: 0.000003, // $3 per MTok + outputCostPerToken: 0.000015, // $15 per MTok + }; + + const pricingWithCache: ModelPricing = { + ...basePricing, + cacheReadInputTokenCost: 0.0000003, // $0.30 per MTok (10% of input) + }; + + describe("basic cost calculation", () => { + it("should calculate cost with no cached tokens", () => { + const result = calculateCost(basePricing, 1000, 500, 0); + + expect(result.inputTokens).toBe(1000); + expect(result.outputTokens).toBe(500); + expect(result.cachedInputTokens).toBe(0); + expect(result.inputCost).toBeCloseTo(0.003); // 1000 * $3/MTok + expect(result.outputCost).toBeCloseTo(0.0075); // 500 * $15/MTok + expect(result.cacheReadCost).toBe(0); + expect(result.totalCost).toBeCloseTo(0.0105); + }); + + it("should default cachedInputTokens to 0", () => { + const result = calculateCost(basePricing, 1000, 500); + + expect(result.cachedInputTokens).toBe(0); + expect(result.inputCost).toBeCloseTo(0.003); + }); + }); + + describe("cached token billing", () => { + it("should bill cached tokens at reduced rate", () => { + // 1000 input tokens, 800 are cached + const result = calculateCost(pricingWithCache, 1000, 500, 800); + + expect(result.inputTokens).toBe(1000); + expect(result.cachedInputTokens).toBe(800); + // Uncached: 200 tokens * $3/MTok = $0.0006 + expect(result.inputCost).toBeCloseTo(0.0006); + // Cached: 800 tokens * $0.30/MTok = $0.00024 + expect(result.cacheReadCost).toBeCloseTo(0.00024); + // Output: 500 * $15/MTok = $0.0075 + expect(result.outputCost).toBeCloseTo(0.0075); + expect(result.totalCost).toBeCloseTo(0.00834); + }); + + it("should treat cached tokens as free when no cache rate specified", () => { + // Using basePricing which has no cacheReadInputTokenCost + const result = calculateCost(basePricing, 1000, 500, 800); + + // Only 200 uncached tokens should be billed + expect(result.inputCost).toBeCloseTo(0.0006); + expect(result.cacheReadCost).toBe(0); + }); + + it("should handle all tokens being cached", () => { + const result = calculateCost(pricingWithCache, 1000, 500, 1000); + + expect(result.inputCost).toBe(0); + expect(result.cacheReadCost).toBeCloseTo(0.0003); // 1000 * $0.30/MTok + }); + }); + + describe("edge cases", () => { + it("should handle zero tokens", () => { + const result = calculateCost(basePricing, 0, 0, 0); + + expect(result.inputCost).toBe(0); + expect(result.outputCost).toBe(0); + expect(result.cacheReadCost).toBe(0); + expect(result.totalCost).toBe(0); + }); + + it("should handle large token counts", () => { + const result = calculateCost(basePricing, 1_000_000, 500_000, 0); + + expect(result.inputCost).toBeCloseTo(3); // 1M * $3/MTok + expect(result.outputCost).toBeCloseTo(7.5); // 500K * $15/MTok + expect(result.totalCost).toBeCloseTo(10.5); + }); + + it("should handle pricing with zero costs", () => { + const freePricing: ModelPricing = { + inputCostPerToken: 0, + outputCostPerToken: 0, + }; + const result = calculateCost(freePricing, 1000, 500, 0); + + expect(result.totalCost).toBe(0); + }); + }); +}); + +describe("formatCost", () => { + it('should format zero as "$0.00"', () => { + expect(formatCost(0)).toBe("$0.00"); + }); + + it("should format very small costs with 6 decimal places", () => { + expect(formatCost(0.000123)).toBe("$0.000123"); + expect(formatCost(0.001)).toBe("$0.001000"); + expect(formatCost(0.0099)).toBe("$0.009900"); + }); + + it("should format small costs with 4 decimal places", () => { + expect(formatCost(0.01)).toBe("$0.0100"); + expect(formatCost(0.1234)).toBe("$0.1234"); + expect(formatCost(0.99)).toBe("$0.9900"); + }); + + it("should format costs >= $1 with 2 decimal places", () => { + expect(formatCost(1)).toBe("$1.00"); + expect(formatCost(1.234)).toBe("$1.23"); + expect(formatCost(10.5)).toBe("$10.50"); + expect(formatCost(100)).toBe("$100.00"); + }); +}); + +describe("formatMTokCost", () => { + it('should format zero as "$0"', () => { + expect(formatMTokCost(0)).toBe("$0"); + }); + + it("should format very small per-MTok costs with 4 decimal places", () => { + expect(formatMTokCost(0.001)).toBe("$0.0010"); + expect(formatMTokCost(0.0099)).toBe("$0.0099"); + }); + + it("should format per-MTok costs >= $0.01 with 2 decimal places", () => { + expect(formatMTokCost(0.01)).toBe("$0.01"); + expect(formatMTokCost(0.30)).toBe("$0.30"); + expect(formatMTokCost(3)).toBe("$3.00"); + expect(formatMTokCost(15)).toBe("$15.00"); + }); +}); + +describe("getModelPricingDisplay", () => { + it("should convert per-token costs to per-MTok", () => { + const pricing: ModelPricing = { + inputCostPerToken: 0.000003, // $3 per MTok + outputCostPerToken: 0.000015, // $15 per MTok + }; + + const display = getModelPricingDisplay(pricing); + + expect(display.inputCostPerMTok).toBe(3); + expect(display.outputCostPerMTok).toBe(15); + expect(display.cacheReadCostPerMTok).toBeUndefined(); + }); + + it("should include cache read cost when available", () => { + const pricing: ModelPricing = { + inputCostPerToken: 0.000003, + outputCostPerToken: 0.000015, + cacheReadInputTokenCost: 0.0000003, // $0.30 per MTok + }; + + const display = getModelPricingDisplay(pricing); + + expect(display.inputCostPerMTok).toBe(3); + expect(display.outputCostPerMTok).toBe(15); + expect(display.cacheReadCostPerMTok).toBeCloseTo(0.3); + }); + + it("should handle zero costs", () => { + const pricing: ModelPricing = { + inputCostPerToken: 0, + outputCostPerToken: 0, + }; + + const display = getModelPricingDisplay(pricing); + + expect(display.inputCostPerMTok).toBe(0); + expect(display.outputCostPerMTok).toBe(0); + }); +}); diff --git a/lib/pricing.ts b/lib/pricing.ts index d064e47..00a9efa 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -1,7 +1,10 @@ import { readFileSync, existsSync } from "node:fs"; -import { join } from "node:path"; +import { join, dirname } from "node:path"; +import { fileURLToPath } from "node:url"; -const PRICING_FILE_PATH = join(process.cwd(), "data/model-pricing.json"); +// Use import.meta for robust path resolution regardless of working directory +const __dirname = dirname(fileURLToPath(import.meta.url)); +const PRICING_FILE_PATH = join(__dirname, "../data/model-pricing.json"); /** * Model pricing information @@ -43,6 +46,23 @@ export interface ModelPricingLookup { matchedKey: string; } +/** + * Provider normalization configuration + * - strip: Remove the provider prefix when generating candidates + * - keepNested: For nested paths like "openrouter/anthropic/model", also try "anthropic/model" + */ +interface ProviderConfig { + strip: boolean; + keepNested: boolean; +} + +const PROVIDER_CONFIGS: Record = { + openrouter: { strip: true, keepNested: true }, + anthropic: { strip: true, keepNested: false }, + openai: { strip: true, keepNested: false }, + lmstudio: { strip: true, keepNested: false }, +}; + // Cache the loaded pricing data let pricingData: Record | null = null; @@ -72,79 +92,91 @@ function loadPricingData(): Record { } /** - * Normalize a model string for pricing lookup - * Handles various formats like: - * - anthropic/claude-sonnet-4 -> claude-sonnet-4 - * - openrouter/anthropic/claude-sonnet-4 -> anthropic/claude-sonnet-4 - * - openai/gpt-4o -> gpt-4o + * Generate lookup candidates for a model string using provider configuration + * Returns candidates in priority order (most specific first) */ -function normalizeModelForLookup(modelString: string): string[] { +function generateLookupCandidates(modelString: string): string[] { const candidates: string[] = []; - // Add the original model string (without our provider prefix) - if (modelString.startsWith("openrouter/")) { - // openrouter/anthropic/claude-sonnet-4 -> anthropic/claude-sonnet-4 - const withoutOpenRouter = modelString.replace("openrouter/", ""); - candidates.push(`openrouter/${withoutOpenRouter}`); - candidates.push(withoutOpenRouter); - - // Also try just the model name: anthropic/claude-sonnet-4 -> claude-sonnet-4 - const parts = withoutOpenRouter.split("/"); - if (parts.length > 1) { - candidates.push(parts.slice(1).join("/")); + // Find matching provider config + const slashIndex = modelString.indexOf("/"); + if (slashIndex === -1) { + // No provider prefix, just use as-is + return [modelString]; + } + + const provider = modelString.slice(0, slashIndex); + const config = PROVIDER_CONFIGS[provider]; + + if (!config) { + // Unknown provider, try original string only + return [modelString]; + } + + const remainder = modelString.slice(slashIndex + 1); + + // Always try the full string first (with provider prefix for the pricing file format) + candidates.push(modelString); + + if (config.strip) { + // Try without our provider prefix + candidates.push(remainder); + } + + if (config.keepNested) { + // For nested paths like "anthropic/claude-model", also try just "claude-model" + const nestedSlashIndex = remainder.indexOf("/"); + if (nestedSlashIndex !== -1) { + candidates.push(remainder.slice(nestedSlashIndex + 1)); } - } else if (modelString.startsWith("anthropic/")) { - // anthropic/claude-sonnet-4 -> claude-sonnet-4 - const modelName = modelString.replace("anthropic/", ""); - candidates.push(modelString); - candidates.push(modelName); - // Try common Anthropic naming patterns - candidates.push(`anthropic/${modelName}`); - } else if (modelString.startsWith("openai/")) { - // openai/gpt-4o -> gpt-4o - const modelName = modelString.replace("openai/", ""); - candidates.push(modelString); - candidates.push(modelName); - } else if (modelString.startsWith("lmstudio/")) { - // Local models - won't have pricing - candidates.push(modelString); - } else { - candidates.push(modelString); } return candidates; } +/** + * Extract pricing from model data if available + */ +function extractPricing( + modelData: Record, +): ModelPricing | null { + const inputCost = modelData.input_cost_per_token; + const outputCost = modelData.output_cost_per_token; + + if (typeof inputCost !== "number" && typeof outputCost !== "number") { + return null; + } + + return { + inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, + outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, + cacheReadInputTokenCost: + typeof modelData.cache_read_input_token_cost === "number" + ? modelData.cache_read_input_token_cost + : undefined, + cacheCreationInputTokenCost: + typeof modelData.cache_creation_input_token_cost === "number" + ? modelData.cache_creation_input_token_cost + : undefined, + }; +} + /** * Look up pricing information for a model, returning both the pricing and the matched key * Returns null if pricing is not found */ -export function lookupModelPricing(modelString: string): ModelPricingLookup | null { +export function lookupModelPricing( + modelString: string, +): ModelPricingLookup | null { const data = loadPricingData(); - const candidates = normalizeModelForLookup(modelString); + const candidates = generateLookupCandidates(modelString); for (const candidate of candidates) { const modelData = data[candidate] as Record | undefined; if (modelData) { - const inputCost = modelData.input_cost_per_token; - const outputCost = modelData.output_cost_per_token; - - if (typeof inputCost === "number" || typeof outputCost === "number") { - return { - pricing: { - inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, - outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, - cacheReadInputTokenCost: - typeof modelData.cache_read_input_token_cost === "number" - ? modelData.cache_read_input_token_cost - : undefined, - cacheCreationInputTokenCost: - typeof modelData.cache_creation_input_token_cost === "number" - ? modelData.cache_creation_input_token_cost - : undefined, - }, - matchedKey: candidate, - }; + const pricing = extractPricing(modelData); + if (pricing) { + return { pricing, matchedKey: candidate }; } } } @@ -153,10 +185,12 @@ export function lookupModelPricing(modelString: string): ModelPricingLookup | nu } /** - * Get pricing information for a model using an explicit key + * Look up pricing information for a model using an explicit key * Returns null if pricing is not found */ -export function lookupModelPricingByKey(pricingKey: string): ModelPricingLookup | null { +export function lookupModelPricingByKey( + pricingKey: string, +): ModelPricingLookup | null { const data = loadPricingData(); const modelData = data[pricingKey] as Record | undefined; @@ -164,28 +198,12 @@ export function lookupModelPricingByKey(pricingKey: string): ModelPricingLookup return null; } - const inputCost = modelData.input_cost_per_token; - const outputCost = modelData.output_cost_per_token; - - if (typeof inputCost === "number" || typeof outputCost === "number") { - return { - pricing: { - inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, - outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, - cacheReadInputTokenCost: - typeof modelData.cache_read_input_token_cost === "number" - ? modelData.cache_read_input_token_cost - : undefined, - cacheCreationInputTokenCost: - typeof modelData.cache_creation_input_token_cost === "number" - ? modelData.cache_creation_input_token_cost - : undefined, - }, - matchedKey: pricingKey, - }; + const pricing = extractPricing(modelData); + if (!pricing) { + return null; } - return null; + return { pricing, matchedKey: pricingKey }; } /** @@ -214,6 +232,13 @@ export function getModelPricingDisplay( /** * Calculate the cost for given token usage + * + * Billing model explanation: + * - inputTokens: Total input tokens reported by the API (includes cached) + * - cachedInputTokens: Subset of input tokens that were cache hits + * - Cached tokens are billed at a reduced rate (cacheReadInputTokenCost) + * - Uncached input tokens (inputTokens - cachedInputTokens) are billed at full rate + * - Output tokens are always billed at the output rate */ export function calculateCost( pricing: ModelPricing, @@ -221,12 +246,14 @@ export function calculateCost( outputTokens: number, cachedInputTokens: number = 0, ): CostCalculation { - // For cached tokens, we subtract them from input tokens for billing purposes - // and bill them at the cache read rate (if available, otherwise free) + // Uncached input tokens are billed at full input rate const uncachedInputTokens = inputTokens - cachedInputTokens; - const inputCost = uncachedInputTokens * pricing.inputCostPerToken; + + // Output tokens billed at output rate const outputCost = outputTokens * pricing.outputCostPerToken; + + // Cached tokens billed at reduced cache read rate (or free if not specified) const cacheReadCost = cachedInputTokens * (pricing.cacheReadInputTokenCost ?? 0); @@ -280,3 +307,6 @@ export function getAllModelKeys(): string[] { const data = loadPricingData(); return Object.keys(data).filter((key) => key !== "sample_spec"); } + +// Export for testing +export { generateLookupCandidates as _generateLookupCandidates }; diff --git a/lib/report-template.ts b/lib/report-template.ts index 57429cc..be37605 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -1,6 +1,7 @@ import type { TestVerificationResult } from "./output-test-runner.ts"; import type { MultiTestResultData, SingleTestResult } from "./report.ts"; import { getReportStyles } from "./report-styles.ts"; +import { formatCost, formatMTokCost } from "./pricing.ts"; // Type definitions for content blocks interface TextBlock { @@ -83,31 +84,6 @@ function getFirstLines(code: string, numLines: number): string { return lines.slice(0, numLines).join("\n"); } -/** - * Format a cost value as USD string - */ -function formatCost(cost: number): string { - if (cost === 0) return "$0.00"; - if (cost < 0.01) { - return `$${cost.toFixed(6)}`; - } - if (cost < 1) { - return `$${cost.toFixed(4)}`; - } - return `$${cost.toFixed(2)}`; -} - -/** - * Format per-million-token cost - */ -function formatMTokCost(costPerMTok: number): string { - if (costPerMTok === 0) return "$0"; - if (costPerMTok < 0.01) { - return `$${costPerMTok.toFixed(4)}`; - } - return `$${costPerMTok.toFixed(2)}`; -} - /** * Render a single content block based on its type */ diff --git a/package.json b/package.json index 4dc14f4..c87387f 100644 --- a/package.json +++ b/package.json @@ -9,7 +9,8 @@ "update-model-pricing": "bun run scripts/update-model-pricing.ts", "verify-tests": "bun run verify-references.ts", "prettier": "prettier --write .", - "tsc": "tsc --noEmit" + "tsc": "tsc --noEmit", + "test:self": "bun vitest run lib/*.test.ts" }, "devDependencies": { "@sveltejs/vite-plugin-svelte": "^5.0.3", From 71239e9e00da5a749d7756fddbea3f2efbe2649b Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Tue, 9 Dec 2025 22:03:56 +0100 Subject: [PATCH 06/29] Create GEMINI.md --- GEMINI.md | 1 + 1 file changed, 1 insertion(+) create mode 100644 GEMINI.md diff --git a/GEMINI.md b/GEMINI.md new file mode 100644 index 0000000..43c994c --- /dev/null +++ b/GEMINI.md @@ -0,0 +1 @@ +@AGENTS.md From ad14d0dd58994e811c2916173636e43ead9a0db0 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Wed, 10 Dec 2025 23:14:26 +0100 Subject: [PATCH 07/29] Update .cocominify --- .cocominify | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/.cocominify b/.cocominify index 3d0dbe4..0685a19 100644 --- a/.cocominify +++ b/.cocominify @@ -1 +1,2 @@ -tests/ \ No newline at end of file +tests/ +data/ \ No newline at end of file From 0845eade965b5a16391965771d7e70d0012f35f6 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Wed, 10 Dec 2025 23:24:48 +0100 Subject: [PATCH 08/29] update --- lib/pricing.test.ts | 78 ++++++++++++++++++++++++++++++++------------- lib/pricing.ts | 60 +++++++++++++++++++++++++++------- 2 files changed, 104 insertions(+), 34 deletions(-) diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index 9ecf453..3dfd6db 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -9,59 +9,87 @@ import { } from "./pricing.ts"; describe("generateLookupCandidates", () => { - describe("openrouter provider", () => { + describe("openrouter provider (slash format)", () => { it("should generate candidates for openrouter/anthropic/model", () => { const candidates = generateLookupCandidates( "openrouter/anthropic/claude-sonnet-4", ); - expect(candidates).toEqual([ - "openrouter/anthropic/claude-sonnet-4", - "anthropic/claude-sonnet-4", - "claude-sonnet-4", - ]); + expect(candidates).toContain("openrouter/anthropic/claude-sonnet-4"); + expect(candidates).toContain("anthropic/claude-sonnet-4"); + expect(candidates).toContain("claude-sonnet-4"); }); it("should generate candidates for openrouter/openai/model", () => { const candidates = generateLookupCandidates("openrouter/openai/gpt-4o"); - expect(candidates).toEqual([ - "openrouter/openai/gpt-4o", - "openai/gpt-4o", - "gpt-4o", - ]); + expect(candidates).toContain("openrouter/openai/gpt-4o"); + expect(candidates).toContain("openai/gpt-4o"); + expect(candidates).toContain("gpt-4o"); }); it("should handle openrouter with simple model name", () => { const candidates = generateLookupCandidates("openrouter/some-model"); - expect(candidates).toEqual(["openrouter/some-model", "some-model"]); + expect(candidates).toContain("openrouter/some-model"); + expect(candidates).toContain("some-model"); }); }); - describe("anthropic provider", () => { + describe("anthropic provider (slash format)", () => { it("should generate candidates for anthropic/model", () => { const candidates = generateLookupCandidates("anthropic/claude-haiku-4-5"); - expect(candidates).toEqual([ - "anthropic/claude-haiku-4-5", - "claude-haiku-4-5", - ]); + expect(candidates).toContain("anthropic/claude-haiku-4-5"); + expect(candidates).toContain("claude-haiku-4-5"); + }); + }); + + describe("Vercel AI Gateway format (colon separator)", () => { + it("should generate candidates for anthropic:model", () => { + const candidates = generateLookupCandidates("anthropic:claude-sonnet-4"); + expect(candidates).toContain("anthropic:claude-sonnet-4"); + expect(candidates).toContain("anthropic/claude-sonnet-4"); + expect(candidates).toContain("claude-sonnet-4"); + }); + + it("should generate candidates for openai:model", () => { + const candidates = generateLookupCandidates("openai:gpt-4o"); + expect(candidates).toContain("openai:gpt-4o"); + expect(candidates).toContain("openai/gpt-4o"); + expect(candidates).toContain("gpt-4o"); + }); + + it("should generate candidates for google:model", () => { + const candidates = generateLookupCandidates("google:gemini-2.0-flash"); + expect(candidates).toContain("google:gemini-2.0-flash"); + expect(candidates).toContain("google/gemini-2.0-flash"); + expect(candidates).toContain("gemini-2.0-flash"); + }); + + it("should generate candidates for x-ai:model", () => { + const candidates = generateLookupCandidates("x-ai:grok-2"); + expect(candidates).toContain("x-ai:grok-2"); + expect(candidates).toContain("x-ai/grok-2"); + expect(candidates).toContain("grok-2"); }); }); - describe("openai provider", () => { + describe("openai provider (slash format)", () => { it("should generate candidates for openai/model", () => { const candidates = generateLookupCandidates("openai/gpt-4o"); - expect(candidates).toEqual(["openai/gpt-4o", "gpt-4o"]); + expect(candidates).toContain("openai/gpt-4o"); + expect(candidates).toContain("gpt-4o"); }); it("should handle openai/gpt-4o-mini", () => { const candidates = generateLookupCandidates("openai/gpt-4o-mini"); - expect(candidates).toEqual(["openai/gpt-4o-mini", "gpt-4o-mini"]); + expect(candidates).toContain("openai/gpt-4o-mini"); + expect(candidates).toContain("gpt-4o-mini"); }); }); describe("lmstudio provider", () => { it("should generate candidates for lmstudio/model", () => { const candidates = generateLookupCandidates("lmstudio/llama-3-8b"); - expect(candidates).toEqual(["lmstudio/llama-3-8b", "llama-3-8b"]); + expect(candidates).toContain("lmstudio/llama-3-8b"); + expect(candidates).toContain("llama-3-8b"); }); }); @@ -70,10 +98,16 @@ describe("generateLookupCandidates", () => { const candidates = generateLookupCandidates("unknown/some-model"); expect(candidates).toEqual(["unknown/some-model"]); }); + + it("should handle unknown provider with colon format", () => { + const candidates = generateLookupCandidates("unknown:some-model"); + expect(candidates).toContain("unknown:some-model"); + expect(candidates).toContain("unknown/some-model"); + }); }); describe("no provider prefix", () => { - it("should return only the original string when no slash", () => { + it("should return only the original string when no separator", () => { const candidates = generateLookupCandidates("claude-sonnet-4"); expect(candidates).toEqual(["claude-sonnet-4"]); }); diff --git a/lib/pricing.ts b/lib/pricing.ts index 00a9efa..a791684 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -61,6 +61,12 @@ const PROVIDER_CONFIGS: Record = { anthropic: { strip: true, keepNested: false }, openai: { strip: true, keepNested: false }, lmstudio: { strip: true, keepNested: false }, + google: { strip: true, keepNested: false }, + meta: { strip: true, keepNested: false }, + mistral: { strip: true, keepNested: false }, + cohere: { strip: true, keepNested: false }, + "x-ai": { strip: true, keepNested: false }, + deepseek: { strip: true, keepNested: false }, }; // Cache the loaded pricing data @@ -91,35 +97,58 @@ function loadPricingData(): Record { } } +/** + * Normalize a model string by converting different separator formats + * Vercel AI Gateway uses "provider:model" format + * Old multi-provider setup used "provider/model" format + * LiteLLM pricing data uses various formats + */ +function normalizeModelString(modelString: string): string { + // Convert colon separator to slash for unified processing + // e.g., "anthropic:claude-sonnet-4" -> "anthropic/claude-sonnet-4" + return modelString.replace(":", "/"); +} + /** * Generate lookup candidates for a model string using provider configuration * Returns candidates in priority order (most specific first) + * + * Supports both formats: + * - Vercel AI Gateway: "anthropic:claude-sonnet-4" + * - Multi-provider: "anthropic/claude-sonnet-4" */ function generateLookupCandidates(modelString: string): string[] { const candidates: string[] = []; + + // Normalize the model string (convert : to /) + const normalizedString = normalizeModelString(modelString); // Find matching provider config - const slashIndex = modelString.indexOf("/"); + const slashIndex = normalizedString.indexOf("/"); if (slashIndex === -1) { // No provider prefix, just use as-is - return [modelString]; + return [modelString, normalizedString].filter((v, i, a) => a.indexOf(v) === i); } - const provider = modelString.slice(0, slashIndex); + const provider = normalizedString.slice(0, slashIndex); const config = PROVIDER_CONFIGS[provider]; + const remainder = normalizedString.slice(slashIndex + 1); - if (!config) { - // Unknown provider, try original string only - return [modelString]; + // Always try the original string first + candidates.push(modelString); + + // Also try the normalized version (with / instead of :) + if (normalizedString !== modelString) { + candidates.push(normalizedString); } - const remainder = modelString.slice(slashIndex + 1); - - // Always try the full string first (with provider prefix for the pricing file format) - candidates.push(modelString); + if (!config) { + // Unknown provider, try original strings only + return candidates.filter((v, i, a) => a.indexOf(v) === i); + } if (config.strip) { - // Try without our provider prefix + // Try without our provider prefix (just the model name) candidates.push(remainder); } @@ -131,7 +160,14 @@ function generateLookupCandidates(modelString: string): string[] { } } - return candidates; + // Also try with common LiteLLM prefixes + // LiteLLM often uses "provider/model" format + if (!normalizedString.startsWith(provider + "/")) { + candidates.push(`${provider}/${remainder}`); + } + + // Remove duplicates while preserving order + return candidates.filter((v, i, a) => a.indexOf(v) === i); } /** From 093996143dc22e61b6ea997cc37c920b49704a0e Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Wed, 10 Dec 2025 23:58:07 +0100 Subject: [PATCH 09/29] wip --- index.ts | 58 +++++++++++++++---- lib/pricing.test.ts | 135 +++++++++++++++++--------------------------- lib/pricing.ts | 99 +++++++------------------------- 3 files changed, 117 insertions(+), 175 deletions(-) diff --git a/index.ts b/index.ts index 5dbf5c9..eb11ea5 100644 --- a/index.ts +++ b/index.ts @@ -242,7 +242,8 @@ function calculateTotalCost( /** * Resolve pricing lookup for a model - * Returns the pricing lookup result or null if not found or disabled + * Returns the pricing lookup result or null if disabled + * Throws an error (exits process) if pricing cannot be found and is not disabled */ function resolvePricingLookup(modelString: string): ModelPricingLookup | null { const costDisabled = process.env.MODEL_COST_DISABLED === "true"; @@ -255,21 +256,26 @@ function resolvePricingLookup(modelString: string): ModelPricingLookup | null { // Check if pricing data file exists if (!isPricingAvailable()) { - console.warn( - `⚠️ Model pricing file not found. Run 'bun run update-model-pricing' to download it.`, + console.error( + `\n✗ Model pricing file not found. Run 'bun run update-model-pricing' to download it.`, ); - console.warn(` Cost calculation will be skipped.`); - return null; + console.error( + ` Or set MODEL_COST_DISABLED=true to skip cost calculation.\n`, + ); + process.exit(1); } // If explicit cost name is provided, use that if (explicitCostName) { const lookup = lookupModelPricingByKey(explicitCostName); if (!lookup) { - console.warn( - `⚠️ Could not find pricing for MODEL_COST_NAME="${explicitCostName}"`, + console.error( + `\n✗ Could not find pricing for MODEL_COST_NAME="${explicitCostName}" in model-pricing.json`, ); - return null; + console.error( + ` Check that the key exists in data/model-pricing.json.\n`, + ); + process.exit(1); } return lookup; } @@ -277,8 +283,23 @@ function resolvePricingLookup(modelString: string): ModelPricingLookup | null { // Try automatic lookup const lookup = lookupModelPricing(modelString); if (!lookup) { - console.warn(`⚠️ Could not find pricing for model "${modelString}"`); - return null; + console.error( + `\n✗ Could not find pricing for model "${modelString}" in model-pricing.json`, + ); + console.error(`\n Options:`); + console.error( + ` 1. Set MODEL_COST_NAME= to explicitly specify the pricing key`, + ); + console.error( + ` Example: MODEL_COST_NAME=vercel_ai_gateway/anthropic/claude-sonnet-4`, + ); + console.error( + ` 2. Set MODEL_COST_DISABLED=true to skip cost calculation`, + ); + console.error( + `\n Browse data/model-pricing.json to find the correct key for your model.\n`, + ); + process.exit(1); } return lookup; @@ -435,10 +456,15 @@ async function main() { const isHttpTransport = mcpServerUrl && isHttpUrl(mcpServerUrl); const mcpTransportType = isHttpTransport ? "HTTP" : "StdIO"; + const costDisabled = process.env.MODEL_COST_DISABLED === "true"; + console.log("╔════════════════════════════════════════════════════╗"); console.log("║ SvelteBench 2.0 - Multi-Test ║"); console.log("╚════════════════════════════════════════════════════╝"); console.log(`Model(s): ${models.join(", ")}`); + if (costDisabled) { + console.log(`Pricing: Disabled (MODEL_COST_DISABLED=true)`); + } console.log(`MCP Integration: ${mcpEnabled ? "Enabled" : "Disabled"}`); if (mcpEnabled) { console.log(`MCP Transport: ${mcpTransportType}`); @@ -464,6 +490,14 @@ async function main() { process.exit(1); } + // Pre-validate pricing for all models before starting any benchmarks + // This ensures we fail fast if any model's pricing is missing + const pricingLookups = new Map(); + for (const modelId of models) { + const pricingLookup = resolvePricingLookup(modelId); + pricingLookups.set(modelId, pricingLookup); + } + // Set up outputs directory setupOutputsDirectory(); @@ -497,8 +531,8 @@ async function main() { console.log(`🤖 Running benchmark for model: ${modelId}`); console.log("═".repeat(50)); - // Resolve pricing for this model - const pricingLookup = resolvePricingLookup(modelId); + // Get pre-validated pricing for this model + const pricingLookup = pricingLookups.get(modelId) ?? null; if (pricingLookup) { console.log(`💰 Pricing mapped: ${pricingLookup.matchedKey}`); } diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index 3dfd6db..dcb39e4 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -9,107 +9,74 @@ import { } from "./pricing.ts"; describe("generateLookupCandidates", () => { - describe("openrouter provider (slash format)", () => { - it("should generate candidates for openrouter/anthropic/model", () => { - const candidates = generateLookupCandidates( - "openrouter/anthropic/claude-sonnet-4", - ); - expect(candidates).toContain("openrouter/anthropic/claude-sonnet-4"); - expect(candidates).toContain("anthropic/claude-sonnet-4"); - expect(candidates).toContain("claude-sonnet-4"); - }); - - it("should generate candidates for openrouter/openai/model", () => { - const candidates = generateLookupCandidates("openrouter/openai/gpt-4o"); - expect(candidates).toContain("openrouter/openai/gpt-4o"); - expect(candidates).toContain("openai/gpt-4o"); - expect(candidates).toContain("gpt-4o"); - }); - - it("should handle openrouter with simple model name", () => { - const candidates = generateLookupCandidates("openrouter/some-model"); - expect(candidates).toContain("openrouter/some-model"); - expect(candidates).toContain("some-model"); - }); - }); - - describe("anthropic provider (slash format)", () => { - it("should generate candidates for anthropic/model", () => { - const candidates = generateLookupCandidates("anthropic/claude-haiku-4-5"); - expect(candidates).toContain("anthropic/claude-haiku-4-5"); - expect(candidates).toContain("claude-haiku-4-5"); - }); - }); - - describe("Vercel AI Gateway format (colon separator)", () => { - it("should generate candidates for anthropic:model", () => { - const candidates = generateLookupCandidates("anthropic:claude-sonnet-4"); - expect(candidates).toContain("anthropic:claude-sonnet-4"); - expect(candidates).toContain("anthropic/claude-sonnet-4"); - expect(candidates).toContain("claude-sonnet-4"); + describe("Vercel AI Gateway format (provider/model)", () => { + it("should generate candidates for alibaba/qwen-3-14b", () => { + const candidates = generateLookupCandidates("alibaba/qwen-3-14b"); + expect(candidates).toEqual([ + "vercel_ai_gateway/alibaba/qwen-3-14b", + "alibaba/qwen-3-14b", + "qwen-3-14b", + ]); }); - it("should generate candidates for openai:model", () => { - const candidates = generateLookupCandidates("openai:gpt-4o"); - expect(candidates).toContain("openai:gpt-4o"); - expect(candidates).toContain("openai/gpt-4o"); - expect(candidates).toContain("gpt-4o"); + it("should generate candidates for anthropic/claude-sonnet-4", () => { + const candidates = generateLookupCandidates("anthropic/claude-sonnet-4"); + expect(candidates).toEqual([ + "vercel_ai_gateway/anthropic/claude-sonnet-4", + "anthropic/claude-sonnet-4", + "claude-sonnet-4", + ]); }); - it("should generate candidates for google:model", () => { - const candidates = generateLookupCandidates("google:gemini-2.0-flash"); - expect(candidates).toContain("google:gemini-2.0-flash"); - expect(candidates).toContain("google/gemini-2.0-flash"); - expect(candidates).toContain("gemini-2.0-flash"); - }); - - it("should generate candidates for x-ai:model", () => { - const candidates = generateLookupCandidates("x-ai:grok-2"); - expect(candidates).toContain("x-ai:grok-2"); - expect(candidates).toContain("x-ai/grok-2"); - expect(candidates).toContain("grok-2"); - }); - }); - - describe("openai provider (slash format)", () => { - it("should generate candidates for openai/model", () => { + it("should generate candidates for openai/gpt-4o", () => { const candidates = generateLookupCandidates("openai/gpt-4o"); - expect(candidates).toContain("openai/gpt-4o"); - expect(candidates).toContain("gpt-4o"); + expect(candidates).toEqual([ + "vercel_ai_gateway/openai/gpt-4o", + "openai/gpt-4o", + "gpt-4o", + ]); }); - it("should handle openai/gpt-4o-mini", () => { - const candidates = generateLookupCandidates("openai/gpt-4o-mini"); - expect(candidates).toContain("openai/gpt-4o-mini"); - expect(candidates).toContain("gpt-4o-mini"); + it("should generate candidates for google/gemini-2.0-flash", () => { + const candidates = generateLookupCandidates("google/gemini-2.0-flash"); + expect(candidates).toEqual([ + "vercel_ai_gateway/google/gemini-2.0-flash", + "google/gemini-2.0-flash", + "gemini-2.0-flash", + ]); }); - }); - describe("lmstudio provider", () => { - it("should generate candidates for lmstudio/model", () => { - const candidates = generateLookupCandidates("lmstudio/llama-3-8b"); - expect(candidates).toContain("lmstudio/llama-3-8b"); - expect(candidates).toContain("llama-3-8b"); + it("should generate candidates for x-ai/grok-2", () => { + const candidates = generateLookupCandidates("x-ai/grok-2"); + expect(candidates).toEqual([ + "vercel_ai_gateway/x-ai/grok-2", + "x-ai/grok-2", + "grok-2", + ]); }); }); - describe("unknown provider", () => { - it("should return only the original string for unknown provider", () => { - const candidates = generateLookupCandidates("unknown/some-model"); - expect(candidates).toEqual(["unknown/some-model"]); - }); - - it("should handle unknown provider with colon format", () => { - const candidates = generateLookupCandidates("unknown:some-model"); - expect(candidates).toContain("unknown:some-model"); - expect(candidates).toContain("unknown/some-model"); + describe("nested paths (openrouter style)", () => { + it("should handle openrouter/anthropic/claude-sonnet-4", () => { + const candidates = generateLookupCandidates( + "openrouter/anthropic/claude-sonnet-4", + ); + expect(candidates).toEqual([ + "vercel_ai_gateway/openrouter/anthropic/claude-sonnet-4", + "openrouter/anthropic/claude-sonnet-4", + "anthropic/claude-sonnet-4", + "claude-sonnet-4", + ]); }); }); describe("no provider prefix", () => { - it("should return only the original string when no separator", () => { + it("should return only the original string with gateway prefix when no separator", () => { const candidates = generateLookupCandidates("claude-sonnet-4"); - expect(candidates).toEqual(["claude-sonnet-4"]); + expect(candidates).toEqual([ + "vercel_ai_gateway/claude-sonnet-4", + "claude-sonnet-4", + ]); }); }); }); diff --git a/lib/pricing.ts b/lib/pricing.ts index a791684..5f93230 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -46,29 +46,6 @@ export interface ModelPricingLookup { matchedKey: string; } -/** - * Provider normalization configuration - * - strip: Remove the provider prefix when generating candidates - * - keepNested: For nested paths like "openrouter/anthropic/model", also try "anthropic/model" - */ -interface ProviderConfig { - strip: boolean; - keepNested: boolean; -} - -const PROVIDER_CONFIGS: Record = { - openrouter: { strip: true, keepNested: true }, - anthropic: { strip: true, keepNested: false }, - openai: { strip: true, keepNested: false }, - lmstudio: { strip: true, keepNested: false }, - google: { strip: true, keepNested: false }, - meta: { strip: true, keepNested: false }, - mistral: { strip: true, keepNested: false }, - cohere: { strip: true, keepNested: false }, - "x-ai": { strip: true, keepNested: false }, - deepseek: { strip: true, keepNested: false }, -}; - // Cache the loaded pricing data let pricingData: Record | null = null; @@ -98,74 +75,38 @@ function loadPricingData(): Record { } /** - * Normalize a model string by converting different separator formats - * Vercel AI Gateway uses "provider:model" format - * Old multi-provider setup used "provider/model" format - * LiteLLM pricing data uses various formats - */ -function normalizeModelString(modelString: string): string { - // Convert colon separator to slash for unified processing - // e.g., "anthropic:claude-sonnet-4" -> "anthropic/claude-sonnet-4" - return modelString.replace(":", "/"); -} - -/** - * Generate lookup candidates for a model string using provider configuration + * Generate lookup candidates for a model string * Returns candidates in priority order (most specific first) * - * Supports both formats: - * - Vercel AI Gateway: "anthropic:claude-sonnet-4" - * - Multi-provider: "anthropic/claude-sonnet-4" + * Vercel AI Gateway model IDs are in the format "provider/model-name" + * LiteLLM pricing data stores them as "vercel_ai_gateway/provider/model-name" + * + * Examples: + * - "alibaba/qwen-3-14b" -> tries "vercel_ai_gateway/alibaba/qwen-3-14b", "alibaba/qwen-3-14b", "qwen-3-14b" + * - "anthropic/claude-sonnet-4" -> tries "vercel_ai_gateway/anthropic/claude-sonnet-4", "anthropic/claude-sonnet-4", "claude-sonnet-4" */ function generateLookupCandidates(modelString: string): string[] { const candidates: string[] = []; - // Normalize the model string (convert : to /) - const normalizedString = normalizeModelString(modelString); - - // Find matching provider config - const slashIndex = normalizedString.indexOf("/"); - if (slashIndex === -1) { - // No provider prefix, just use as-is - return [modelString, normalizedString].filter((v, i, a) => a.indexOf(v) === i); - } - - const provider = normalizedString.slice(0, slashIndex); - const config = PROVIDER_CONFIGS[provider]; - const remainder = normalizedString.slice(slashIndex + 1); - - // Always try the original string first + // Primary: Try with vercel_ai_gateway prefix (how LiteLLM stores gateway models) + candidates.push(`vercel_ai_gateway/${modelString}`); + + // Secondary: Try the model string as-is candidates.push(modelString); - // Also try the normalized version (with / instead of :) - if (normalizedString !== modelString) { - candidates.push(normalizedString); - } - - if (!config) { - // Unknown provider, try original strings only - return candidates.filter((v, i, a) => a.indexOf(v) === i); - } - - if (config.strip) { - // Try without our provider prefix (just the model name) - candidates.push(remainder); - } - - if (config.keepNested) { - // For nested paths like "anthropic/claude-model", also try just "claude-model" - const nestedSlashIndex = remainder.indexOf("/"); + // Tertiary: If there's a provider prefix, try just the model name + const slashIndex = modelString.indexOf("/"); + if (slashIndex !== -1) { + const modelName = modelString.slice(slashIndex + 1); + candidates.push(modelName); + + // Also try nested paths (e.g., "openrouter/anthropic/claude" -> "anthropic/claude", "claude") + const nestedSlashIndex = modelName.indexOf("/"); if (nestedSlashIndex !== -1) { - candidates.push(remainder.slice(nestedSlashIndex + 1)); + candidates.push(modelName.slice(nestedSlashIndex + 1)); } } - // Also try with common LiteLLM prefixes - // LiteLLM often uses "provider/model" format - if (!normalizedString.startsWith(provider + "/")) { - candidates.push(`${provider}/${remainder}`); - } - // Remove duplicates while preserving order return candidates.filter((v, i, a) => a.indexOf(v) === i); } From 1fdedf4e0741be190d667f03fbab8690a05d2bb5 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Thu, 11 Dec 2025 00:01:42 +0100 Subject: [PATCH 10/29] enable pricing --- index.ts | 255 +++++++++++++++++++++++++++++++------------------ lib/pricing.ts | 34 ++----- 2 files changed, 169 insertions(+), 120 deletions(-) diff --git a/index.ts b/index.ts index eb11ea5..8e32d8f 100644 --- a/index.ts +++ b/index.ts @@ -23,10 +23,10 @@ import { import { resultWriteTool, testComponentTool } from "./lib/tools/index.ts"; import { lookupModelPricing, - lookupModelPricingByKey, getModelPricingDisplay, calculateCost, formatCost, + formatMTokCost, isPricingAvailable, type ModelPricing, type ModelPricingLookup, @@ -40,16 +40,131 @@ import { text, select, confirm, + note, } from "@clack/prompts"; import { gateway } from "ai"; -async function selectOptions() { +interface PricingValidationResult { + enabled: boolean; + lookups: Map; +} + +interface SelectOptionsResult { + models: string[]; + mcp: string | undefined; + testingTool: boolean; + pricing: PricingValidationResult; +} + +/** + * Validate pricing for selected models and get user confirmation + */ +async function validateAndConfirmPricing( + models: string[], +): Promise { + const lookups = new Map(); + + // Check if pricing file exists + if (!isPricingAvailable()) { + note( + "Model pricing file not found.\nRun 'bun run update-model-pricing' to download it.", + "⚠️ Pricing Unavailable", + ); + + const proceed = await confirm({ + message: "Continue without pricing?", + initialValue: true, + }); + + if (isCancel(proceed) || !proceed) { + cancel("Operation cancelled."); + process.exit(0); + } + + // Initialize all models with null pricing + for (const modelId of models) { + lookups.set(modelId, null); + } + + return { enabled: false, lookups }; + } + + // Look up pricing for each model + for (const modelId of models) { + const lookup = lookupModelPricing(modelId); + lookups.set(modelId, lookup); + } + + const modelsWithPricing = models.filter((m) => lookups.get(m) !== null); + const modelsWithoutPricing = models.filter((m) => lookups.get(m) === null); + + if (modelsWithoutPricing.length === 0) { + // All models have pricing - show details and let user choose + const pricingLines = models.map((modelId) => { + const lookup = lookups.get(modelId)!; + const display = getModelPricingDisplay(lookup.pricing); + return `${modelId}\n → ${lookup.matchedKey}\n → ${formatMTokCost(display.inputCostPerMTok)}/MTok in, ${formatMTokCost(display.outputCostPerMTok)}/MTok out`; + }); + + note(pricingLines.join("\n\n"), "💰 Pricing Found"); + + const usePricing = await confirm({ + message: "Enable cost calculation?", + initialValue: true, + }); + + if (isCancel(usePricing)) { + cancel("Operation cancelled."); + process.exit(0); + } + + return { enabled: usePricing, lookups }; + } else { + // Some or all models don't have pricing + const lines: string[] = []; + + if (modelsWithoutPricing.length > 0) { + lines.push("No pricing found for:"); + for (const modelId of modelsWithoutPricing) { + lines.push(` ✗ ${modelId}`); + } + } + + if (modelsWithPricing.length > 0) { + lines.push(""); + lines.push("Pricing available for:"); + for (const modelId of modelsWithPricing) { + const lookup = lookups.get(modelId)!; + lines.push(` ✓ ${modelId} → ${lookup.matchedKey}`); + } + } + + lines.push(""); + lines.push("Cost calculation will be disabled."); + + note(lines.join("\n"), "⚠️ Pricing Incomplete"); + + const proceed = await confirm({ + message: "Continue without pricing?", + initialValue: true, + }); + + if (isCancel(proceed) || !proceed) { + cancel("Operation cancelled."); + process.exit(0); + } + + return { enabled: false, lookups }; + } +} + +async function selectOptions(): Promise { intro("🚀 Svelte AI Bench"); const available_models = await gateway.getAvailableModels(); const models = await multiselect({ - message: "Select a model to benchmark", + message: "Select model(s) to benchmark", options: [{ value: "custom", label: "Custom" }].concat( available_models.models.reduce>( (arr, model) => { @@ -79,6 +194,11 @@ async function selectOptions() { models.push(custom_model); } + const selectedModels = models.filter((model) => model !== "custom"); + + // Validate pricing for selected models + const pricing = await validateAndConfirmPricing(selectedModels); + const mcp_integration = await select({ message: "Which MCP integration to use?", options: [ @@ -135,9 +255,10 @@ async function selectOptions() { } return { - models: models.filter((model) => model !== "custom"), + models: selectedModels, mcp, testingTool, + pricing, }; } @@ -240,71 +361,6 @@ function calculateTotalCost( }; } -/** - * Resolve pricing lookup for a model - * Returns the pricing lookup result or null if disabled - * Throws an error (exits process) if pricing cannot be found and is not disabled - */ -function resolvePricingLookup(modelString: string): ModelPricingLookup | null { - const costDisabled = process.env.MODEL_COST_DISABLED === "true"; - const explicitCostName = process.env.MODEL_COST_NAME; - - // If cost calculation is explicitly disabled, return null - if (costDisabled) { - return null; - } - - // Check if pricing data file exists - if (!isPricingAvailable()) { - console.error( - `\n✗ Model pricing file not found. Run 'bun run update-model-pricing' to download it.`, - ); - console.error( - ` Or set MODEL_COST_DISABLED=true to skip cost calculation.\n`, - ); - process.exit(1); - } - - // If explicit cost name is provided, use that - if (explicitCostName) { - const lookup = lookupModelPricingByKey(explicitCostName); - if (!lookup) { - console.error( - `\n✗ Could not find pricing for MODEL_COST_NAME="${explicitCostName}" in model-pricing.json`, - ); - console.error( - ` Check that the key exists in data/model-pricing.json.\n`, - ); - process.exit(1); - } - return lookup; - } - - // Try automatic lookup - const lookup = lookupModelPricing(modelString); - if (!lookup) { - console.error( - `\n✗ Could not find pricing for model "${modelString}" in model-pricing.json`, - ); - console.error(`\n Options:`); - console.error( - ` 1. Set MODEL_COST_NAME= to explicitly specify the pricing key`, - ); - console.error( - ` Example: MODEL_COST_NAME=vercel_ai_gateway/anthropic/claude-sonnet-4`, - ); - console.error( - ` 2. Set MODEL_COST_DISABLED=true to skip cost calculation`, - ); - console.error( - `\n Browse data/model-pricing.json to find the correct key for your model.\n`, - ); - process.exit(1); - } - - return lookup; -} - /** * Run a single test with the AI agent */ @@ -444,7 +500,8 @@ async function runSingleTest( // Main execution async function main() { - const { models, mcp, testingTool } = await selectOptions(); + const { models, mcp, testingTool, pricing } = await selectOptions(); + // Get MCP server URL/command from environment (optional) const mcpServerUrl = mcp; const mcpEnabled = !!mcp; @@ -456,33 +513,50 @@ async function main() { const isHttpTransport = mcpServerUrl && isHttpUrl(mcpServerUrl); const mcpTransportType = isHttpTransport ? "HTTP" : "StdIO"; - const costDisabled = process.env.MODEL_COST_DISABLED === "true"; - - console.log("╔════════════════════════════════════════════════════╗"); + // Print configuration header + console.log("\n╔════════════════════════════════════════════════════╗"); console.log("║ SvelteBench 2.0 - Multi-Test ║"); console.log("╚════════════════════════════════════════════════════╝"); - console.log(`Model(s): ${models.join(", ")}`); - if (costDisabled) { - console.log(`Pricing: Disabled (MODEL_COST_DISABLED=true)`); + + // Print models with pricing info + console.log("\n📋 Models:"); + for (const modelId of models) { + const lookup = pricing.lookups.get(modelId); + if (pricing.enabled && lookup) { + const display = getModelPricingDisplay(lookup.pricing); + console.log(` ${modelId}`); + console.log( + ` 💰 ${formatMTokCost(display.inputCostPerMTok)}/MTok in, ${formatMTokCost(display.outputCostPerMTok)}/MTok out`, + ); + } else { + console.log(` ${modelId}`); + } } - console.log(`MCP Integration: ${mcpEnabled ? "Enabled" : "Disabled"}`); + + // Print pricing status + console.log(`\n💰 Pricing: ${pricing.enabled ? "Enabled" : "Disabled"}`); + + // Print MCP config + console.log(`🔌 MCP Integration: ${mcpEnabled ? "Enabled" : "Disabled"}`); if (mcpEnabled) { - console.log(`MCP Transport: ${mcpTransportType}`); + console.log(` Transport: ${mcpTransportType}`); if (isHttpTransport) { - console.log(`MCP Server URL: ${mcpServerUrl}`); + console.log(` URL: ${mcpServerUrl}`); } else { - console.log(`MCP StdIO Command: ${mcpServerUrl}`); + console.log(` Command: ${mcpServerUrl}`); } } + + // Print tool config console.log( - `TestComponent Tool: ${testComponentEnabled ? "Enabled" : "Disabled"}`, + `🧪 TestComponent Tool: ${testComponentEnabled ? "Enabled" : "Disabled"}`, ); // Discover all tests console.log("\n📁 Discovering tests..."); const tests = discoverTests(); console.log( - `Found ${tests.length} test(s): ${tests.map((t) => t.name).join(", ")}`, + ` Found ${tests.length} test(s): ${tests.map((t) => t.name).join(", ")}`, ); if (tests.length === 0) { @@ -490,14 +564,6 @@ async function main() { process.exit(1); } - // Pre-validate pricing for all models before starting any benchmarks - // This ensures we fail fast if any model's pricing is missing - const pricingLookups = new Map(); - for (const modelId of models) { - const pricingLookup = resolvePricingLookup(modelId); - pricingLookups.set(modelId, pricingLookup); - } - // Set up outputs directory setupOutputsDirectory(); @@ -532,9 +598,14 @@ async function main() { console.log("═".repeat(50)); // Get pre-validated pricing for this model - const pricingLookup = pricingLookups.get(modelId) ?? null; + const pricingLookup = + pricing.enabled ? (pricing.lookups.get(modelId) ?? null) : null; + if (pricingLookup) { - console.log(`💰 Pricing mapped: ${pricingLookup.matchedKey}`); + const display = getModelPricingDisplay(pricingLookup.pricing); + console.log( + `💰 Pricing: ${formatMTokCost(display.inputCostPerMTok)}/MTok in, ${formatMTokCost(display.outputCostPerMTok)}/MTok out`, + ); } // Get the model from gateway diff --git a/lib/pricing.ts b/lib/pricing.ts index 5f93230..d3689ed 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -77,29 +77,29 @@ function loadPricingData(): Record { /** * Generate lookup candidates for a model string * Returns candidates in priority order (most specific first) - * + * * Vercel AI Gateway model IDs are in the format "provider/model-name" * LiteLLM pricing data stores them as "vercel_ai_gateway/provider/model-name" - * + * * Examples: * - "alibaba/qwen-3-14b" -> tries "vercel_ai_gateway/alibaba/qwen-3-14b", "alibaba/qwen-3-14b", "qwen-3-14b" * - "anthropic/claude-sonnet-4" -> tries "vercel_ai_gateway/anthropic/claude-sonnet-4", "anthropic/claude-sonnet-4", "claude-sonnet-4" */ function generateLookupCandidates(modelString: string): string[] { const candidates: string[] = []; - + // Primary: Try with vercel_ai_gateway prefix (how LiteLLM stores gateway models) candidates.push(`vercel_ai_gateway/${modelString}`); - + // Secondary: Try the model string as-is candidates.push(modelString); - + // Tertiary: If there's a provider prefix, try just the model name const slashIndex = modelString.indexOf("/"); if (slashIndex !== -1) { const modelName = modelString.slice(slashIndex + 1); candidates.push(modelName); - + // Also try nested paths (e.g., "openrouter/anthropic/claude" -> "anthropic/claude", "claude") const nestedSlashIndex = modelName.indexOf("/"); if (nestedSlashIndex !== -1) { @@ -161,28 +161,6 @@ export function lookupModelPricing( return null; } -/** - * Look up pricing information for a model using an explicit key - * Returns null if pricing is not found - */ -export function lookupModelPricingByKey( - pricingKey: string, -): ModelPricingLookup | null { - const data = loadPricingData(); - const modelData = data[pricingKey] as Record | undefined; - - if (!modelData) { - return null; - } - - const pricing = extractPricing(modelData); - if (!pricing) { - return null; - } - - return { pricing, matchedKey: pricingKey }; -} - /** * Get pricing information for a model (legacy function for compatibility) * Returns null if pricing is not found From 0c99ad755c61db09cbc90016d918e5abae5f2c07 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 11:45:00 +0100 Subject: [PATCH 11/29] test fix --- lib/pricing.test.ts | 14 ++++++++++++++ lib/pricing.ts | 7 ++++--- 2 files changed, 18 insertions(+), 3 deletions(-) diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index dcb39e4..ce7cfa9 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -258,4 +258,18 @@ describe("getModelPricingDisplay", () => { expect(display.inputCostPerMTok).toBe(0); expect(display.outputCostPerMTok).toBe(0); }); + + it("should preserve explicit zero cost for cache read", () => { + const pricing: ModelPricing = { + inputCostPerToken: 0.000003, + outputCostPerToken: 0.000015, + cacheReadInputTokenCost: 0, + }; + + const display = getModelPricingDisplay(pricing); + + expect(display.inputCostPerMTok).toBe(3); + expect(display.outputCostPerMTok).toBe(15); + expect(display.cacheReadCostPerMTok).toBe(0); + }); }); diff --git a/lib/pricing.ts b/lib/pricing.ts index d3689ed..78f1be0 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -179,9 +179,10 @@ export function getModelPricingDisplay( return { inputCostPerMTok: pricing.inputCostPerToken * 1_000_000, outputCostPerMTok: pricing.outputCostPerToken * 1_000_000, - cacheReadCostPerMTok: pricing.cacheReadInputTokenCost - ? pricing.cacheReadInputTokenCost * 1_000_000 - : undefined, + cacheReadCostPerMTok: + pricing.cacheReadInputTokenCost !== undefined + ? pricing.cacheReadInputTokenCost * 1_000_000 + : undefined, }; } From 1bd240d540f661e01327a6114c502abdef5dc853 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 11:53:29 +0100 Subject: [PATCH 12/29] install correct bun version --- .bunversion | 1 + README.md | 1 + scripts/install.sh | 11 +++++++++++ 3 files changed, 13 insertions(+) create mode 100644 .bunversion create mode 100755 scripts/install.sh diff --git a/.bunversion b/.bunversion new file mode 100644 index 0000000..5cf6288 --- /dev/null +++ b/.bunversion @@ -0,0 +1 @@ +bun-v1.3.4 \ No newline at end of file diff --git a/README.md b/README.md index 2dbb337..91a33a7 100644 --- a/README.md +++ b/README.md @@ -7,6 +7,7 @@ AI SDK benchmarking tool that tests AI agents with MCP (Model Context Protocol) To install dependencies: ```bash +./scripts/install.sh # installs the correct bun version bun install ``` diff --git a/scripts/install.sh b/scripts/install.sh new file mode 100755 index 0000000..09a63c0 --- /dev/null +++ b/scripts/install.sh @@ -0,0 +1,11 @@ +#!/usr/bin/env bash + +# Read the Bun version from .bunversion file +if [ -f ".bunversion" ]; then + BUN_VERSION=$(cat .bunversion | tr -d '[:space:]') + echo "Installing Bun version: $BUN_VERSION" + curl -fsSL https://bun.com/install | bash -s "$BUN_VERSION" +else + echo "Error: .bunversion file not found" + exit 1 +fi From 1c61ed9614276bcf4424df99b936e2af1d0c9152 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 11:59:14 +0100 Subject: [PATCH 13/29] Create test.yml --- .github/workflows/test.yml | 28 ++++++++++++++++++++++++++++ 1 file changed, 28 insertions(+) create mode 100644 .github/workflows/test.yml diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml new file mode 100644 index 0000000..5333154 --- /dev/null +++ b/.github/workflows/test.yml @@ -0,0 +1,28 @@ +name: Test + +on: + pull_request: + push: + branches: + - main + +jobs: + test: + name: Run Tests + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Get Bun version + id: bun-version + run: echo "version=$(cat .bunversion | sed 's/bun-v//')" >> $GITHUB_OUTPUT + + - uses: oven-sh/setup-bun@v2 + with: + bun-version: ${{ steps.bun-version.outputs.version }} + + - name: Install dependencies + run: bun install + + - name: Run tests + run: bun test From 973b344c44aaf761d7a888e6f97fde0130f29117 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:20:31 +0100 Subject: [PATCH 14/29] use vercel ai data --- data/model-pricing.json | 30198 ------------------------------ index.ts | 48 +- lib/pricing.test.ts | 197 +- lib/pricing.ts | 196 +- scripts/update-model-pricing.ts | 76 - 5 files changed, 224 insertions(+), 30491 deletions(-) delete mode 100644 data/model-pricing.json delete mode 100644 scripts/update-model-pricing.ts diff --git a/data/model-pricing.json b/data/model-pricing.json deleted file mode 100644 index 4f516f1..0000000 --- a/data/model-pricing.json +++ /dev/null @@ -1,30198 +0,0 @@ -{ - "sample_spec": { - "code_interpreter_cost_per_session": 0, - "computer_use_input_cost_per_1k_tokens": 0, - "computer_use_output_cost_per_1k_tokens": 0, - "deprecation_date": "date when the model becomes deprecated in the format YYYY-MM-DD", - "file_search_cost_per_1k_calls": 0, - "file_search_cost_per_gb_per_day": 0, - "input_cost_per_audio_token": 0, - "input_cost_per_token": 0, - "litellm_provider": "one of https://docs.litellm.ai/docs/providers", - "max_input_tokens": "max input tokens, if the provider specifies it. if not default to max_tokens", - "max_output_tokens": "max output tokens, if the provider specifies it. if not default to max_tokens", - "max_tokens": "LEGACY parameter. set to max_output_tokens if provider specifies it. IF not set to max_input_tokens, if provider specifies it.", - "mode": "one of: chat, embedding, completion, image_generation, audio_transcription, audio_speech, image_generation, moderation, rerank, search", - "output_cost_per_reasoning_token": 0, - "output_cost_per_token": 0, - "search_context_cost_per_query": { - "search_context_size_high": 0, - "search_context_size_low": 0, - "search_context_size_medium": 0 - }, - "supported_regions": [ - "global", - "us-west-2", - "eu-west-1", - "ap-southeast-1", - "ap-northeast-1" - ], - "supports_audio_input": true, - "supports_audio_output": true, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_vision": true, - "supports_web_search": true, - "vector_store_cost_per_gb_per_day": 0 - }, - "1024-x-1024/50-steps/bedrock/amazon.nova-canvas-v1:0": { - "litellm_provider": "bedrock", - "max_input_tokens": 2600, - "mode": "image_generation", - "output_cost_per_image": 0.06 - }, - "1024-x-1024/50-steps/stability.stable-diffusion-xl-v1": { - "litellm_provider": "bedrock", - "max_input_tokens": 77, - "max_tokens": 77, - "mode": "image_generation", - "output_cost_per_image": 0.04 - }, - "1024-x-1024/dall-e-2": { - "input_cost_per_pixel": 1.9e-8, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0 - }, - "1024-x-1024/max-steps/stability.stable-diffusion-xl-v1": { - "litellm_provider": "bedrock", - "max_input_tokens": 77, - "max_tokens": 77, - "mode": "image_generation", - "output_cost_per_image": 0.08 - }, - "256-x-256/dall-e-2": { - "input_cost_per_pixel": 2.4414e-7, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0 - }, - "512-x-512/50-steps/stability.stable-diffusion-xl-v0": { - "litellm_provider": "bedrock", - "max_input_tokens": 77, - "max_tokens": 77, - "mode": "image_generation", - "output_cost_per_image": 0.018 - }, - "512-x-512/dall-e-2": { - "input_cost_per_pixel": 6.86e-8, - "litellm_provider": "openai", - "mode": "image_generation", - "output_cost_per_pixel": 0 - }, - "512-x-512/max-steps/stability.stable-diffusion-xl-v0": { - "litellm_provider": "bedrock", - "max_input_tokens": 77, - "max_tokens": 77, - "mode": "image_generation", - "output_cost_per_image": 0.036 - }, - "ai21.j2-mid-v1": { - "input_cost_per_token": 0.0000125, - "litellm_provider": "bedrock", - "max_input_tokens": 8191, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 0.0000125 - }, - "ai21.j2-ultra-v1": { - "input_cost_per_token": 0.0000188, - "litellm_provider": "bedrock", - "max_input_tokens": 8191, - "max_output_tokens": 8191, - "max_tokens": 8191, - "mode": "chat", - "output_cost_per_token": 0.0000188 - }, - "ai21.jamba-1-5-large-v1:0": { - "input_cost_per_token": 0.000002, - "litellm_provider": "bedrock", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 0.000008 - }, - "ai21.jamba-1-5-mini-v1:0": { - "input_cost_per_token": 2e-7, - "litellm_provider": "bedrock", - "max_input_tokens": 256000, - "max_output_tokens": 256000, - "max_tokens": 256000, - "mode": "chat", - "output_cost_per_token": 4e-7 - }, - "ai21.jamba-instruct-v1:0": { - "input_cost_per_token": 5e-7, - "litellm_provider": "bedrock", - "max_input_tokens": 70000, - "max_output_tokens": 4096, - "max_tokens": 4096, - "mode": "chat", - "output_cost_per_token": 7e-7, - "supports_system_messages": true - }, - "aiml/dall-e-2": { - "litellm_provider": "aiml", - "metadata": { - "notes": "DALL-E 2 via AI/ML API - Reliable text-to-image generation" - }, - "mode": "image_generation", - "output_cost_per_image": 0.021, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/dall-e-3": { - "litellm_provider": "aiml", - "metadata": { - "notes": "DALL-E 3 via AI/ML API - High-quality text-to-image generation" - }, - "mode": "image_generation", - "output_cost_per_image": 0.042, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux-pro": { - "litellm_provider": "aiml", - "metadata": { - "notes": "Flux Dev - Development version optimized for experimentation" - }, - "mode": "image_generation", - "output_cost_per_image": 0.053, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux-pro/v1.1": { - "litellm_provider": "aiml", - "mode": "image_generation", - "output_cost_per_image": 0.042, - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux-pro/v1.1-ultra": { - "litellm_provider": "aiml", - "mode": "image_generation", - "output_cost_per_image": 0.063, - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux-realism": { - "litellm_provider": "aiml", - "metadata": { - "notes": "Flux Pro - Professional-grade image generation model" - }, - "mode": "image_generation", - "output_cost_per_image": 0.037, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux/dev": { - "litellm_provider": "aiml", - "metadata": { - "notes": "Flux Dev - Development version optimized for experimentation" - }, - "mode": "image_generation", - "output_cost_per_image": 0.026, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux/kontext-max/text-to-image": { - "litellm_provider": "aiml", - "metadata": { - "notes": "Flux Pro v1.1 - Enhanced version with improved capabilities and 6x faster inference speed" - }, - "mode": "image_generation", - "output_cost_per_image": 0.084, - "source": "https://docs.aimlapi.com/", - "supported_endpoints": [ - "/v1/images/generations" - ] - }, - "aiml/flux/kontext-pro/text-to-image": { - "litellm_provider": "aiml", - "metadata": { - "notes": "Flux Pro v1.1 - Enhanced version with improved capabilities and 6x faster inference speed" - 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"output_cost_per_token": 0.000006, - "range": [ - 0, - 32000 - ] - }, - { - "input_cost_per_token": 0.0000024, - "output_cost_per_token": 0.000012, - "range": [ - 32000, - 128000 - ] - }, - { - "input_cost_per_token": 0.000003, - "output_cost_per_token": 0.000015, - "range": [ - 128000, - 252000 - ] - } - ] - }, - "dashscope/qwq-plus": { - "input_cost_per_token": 8e-7, - "litellm_provider": "dashscope", - "max_input_tokens": 98304, - "max_output_tokens": 8192, - "max_tokens": 131072, - "mode": "chat", - "output_cost_per_token": 0.0000024, - "source": "https://www.alibabacloud.com/help/en/model-studio/models", - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-bge-large-en": { - "input_cost_per_token": 1.0003e-7, - "input_dbu_cost_per_token": 0.000001429, - "litellm_provider": "databricks", - "max_input_tokens": 512, - "max_tokens": 512, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "embedding", - "output_cost_per_token": 0, - "output_dbu_cost_per_token": 0, - "output_vector_size": 1024, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-claude-3-7-sonnet": { - "input_cost_per_token": 0.0000029999900000000002, - "input_dbu_cost_per_token": 0.000042857, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 128000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000015000020000000002, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-haiku-4-5": { - "input_cost_per_token": 0.00000100002, - "input_dbu_cost_per_token": 0.000014286, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00000500003, - "output_dbu_cost_per_token": 0.000071429, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-opus-4": { - "input_cost_per_token": 0.000015000020000000002, - "input_dbu_cost_per_token": 0.000214286, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00007500003000000001, - "output_dbu_cost_per_token": 0.001071429, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-opus-4-1": { - "input_cost_per_token": 0.000015000020000000002, - "input_dbu_cost_per_token": 0.000214286, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 32000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00007500003000000001, - "output_dbu_cost_per_token": 0.001071429, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-opus-4-5": { - "input_cost_per_token": 0.00000500003, - "input_dbu_cost_per_token": 0.000071429, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000025000010000000002, - "output_dbu_cost_per_token": 0.000357143, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-sonnet-4": { - "input_cost_per_token": 0.0000029999900000000002, - "input_dbu_cost_per_token": 0.000042857, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000015000020000000002, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-sonnet-4-1": { - "input_cost_per_token": 0.0000029999900000000002, - "input_dbu_cost_per_token": 0.000042857, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000015000020000000002, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-claude-sonnet-4-5": { - "input_cost_per_token": 0.0000029999900000000002, - "input_dbu_cost_per_token": 0.000042857, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 64000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000015000020000000002, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_assistant_prefill": true, - "supports_function_calling": true, - "supports_reasoning": true, - "supports_tool_choice": true - }, - "databricks/databricks-gemini-2-5-flash": { - "input_cost_per_token": 3.0001999999999996e-7, - "input_dbu_cost_per_token": 0.000004285999999999999, - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65535, - "max_tokens": 1048576, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00000249998, - "output_dbu_cost_per_token": 0.000035714, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_function_calling": true, - "supports_tool_choice": true - }, - "databricks/databricks-gemini-2-5-pro": { - "input_cost_per_token": 0.00000124999, - "input_dbu_cost_per_token": 0.000017857, - "litellm_provider": "databricks", - "max_input_tokens": 1048576, - "max_output_tokens": 65536, - "max_tokens": 1048576, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000009999990000000002, - "output_dbu_cost_per_token": 0.000142857, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving", - "supports_function_calling": true, - "supports_tool_choice": true - }, - "databricks/databricks-gemma-3-12b": { - "input_cost_per_token": 1.5000999999999998e-7, - "input_dbu_cost_per_token": 0.0000021429999999999996, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 32000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 5.0001e-7, - "output_dbu_cost_per_token": 0.000007143, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-gpt-5": { - "input_cost_per_token": 0.00000124999, - "input_dbu_cost_per_token": 0.000017857, - "litellm_provider": "databricks", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 400000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000009999990000000002, - "output_dbu_cost_per_token": 0.000142857, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" - }, - "databricks/databricks-gpt-5-1": { - "input_cost_per_token": 0.00000124999, - "input_dbu_cost_per_token": 0.000017857, - "litellm_provider": "databricks", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 400000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000009999990000000002, - "output_dbu_cost_per_token": 0.000142857, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" - }, - "databricks/databricks-gpt-5-mini": { - "input_cost_per_token": 2.4997000000000006e-7, - "input_dbu_cost_per_token": 0.000003571, - "litellm_provider": "databricks", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 400000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0000019999700000000004, - "output_dbu_cost_per_token": 0.000028571, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" - }, - "databricks/databricks-gpt-5-nano": { - "input_cost_per_token": 4.998e-8, - "input_dbu_cost_per_token": 7.14e-7, - "litellm_provider": "databricks", - "max_input_tokens": 400000, - "max_output_tokens": 128000, - "max_tokens": 400000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 3.9998000000000007e-7, - "output_dbu_cost_per_token": 0.000005714000000000001, - "source": "https://www.databricks.com/product/pricing/proprietary-foundation-model-serving" - }, - "databricks/databricks-gpt-oss-120b": { - "input_cost_per_token": 1.5000999999999998e-7, - "input_dbu_cost_per_token": 0.0000021429999999999996, - "litellm_provider": "databricks", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 5.9997e-7, - "output_dbu_cost_per_token": 0.000008571, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-gpt-oss-20b": { - "input_cost_per_token": 7e-8, - "input_dbu_cost_per_token": 0.000001, - "litellm_provider": "databricks", - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "max_tokens": 131072, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 3.0001999999999996e-7, - "output_dbu_cost_per_token": 0.000004285999999999999, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-gte-large-en": { - "input_cost_per_token": 1.2999000000000001e-7, - "input_dbu_cost_per_token": 0.000001857, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "embedding", - "output_cost_per_token": 0, - "output_dbu_cost_per_token": 0, - "output_vector_size": 1024, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-llama-2-70b-chat": { - "input_cost_per_token": 5.0001e-7, - "input_dbu_cost_per_token": 0.000007143, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0000015000300000000002, - "output_dbu_cost_per_token": 0.000021429, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-llama-4-maverick": { - "input_cost_per_token": 5.0001e-7, - "input_dbu_cost_per_token": 0.000007143, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Databricks documentation now provides both DBU costs (_dbu_cost_per_token) and dollar costs(_cost_per_token)." - }, - "mode": "chat", - "output_cost_per_token": 0.0000015000300000000002, - "output_dbu_cost_per_token": 0.000021429, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-meta-llama-3-1-405b-instruct": { - "input_cost_per_token": 0.00000500003, - "input_dbu_cost_per_token": 0.000071429, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.000015000020000000002, - "output_dbu_cost_per_token": 0.000214286, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-meta-llama-3-1-8b-instruct": { - "input_cost_per_token": 1.5000999999999998e-7, - "input_dbu_cost_per_token": 0.0000021429999999999996, - "litellm_provider": "databricks", - "max_input_tokens": 200000, - "max_output_tokens": 128000, - "max_tokens": 200000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 4.5003000000000007e-7, - "output_dbu_cost_per_token": 0.000006429000000000001, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving" - }, - "databricks/databricks-meta-llama-3-3-70b-instruct": { - "input_cost_per_token": 5.0001e-7, - "input_dbu_cost_per_token": 0.000007143, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0000015000300000000002, - "output_dbu_cost_per_token": 0.000021429, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-meta-llama-3-70b-instruct": { - "input_cost_per_token": 0.00000100002, - "input_dbu_cost_per_token": 0.000014286, - "litellm_provider": "databricks", - "max_input_tokens": 128000, - "max_output_tokens": 128000, - "max_tokens": 128000, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.0000029999900000000002, - "output_dbu_cost_per_token": 0.000042857, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mixtral-8x7b-instruct": { - "input_cost_per_token": 5.0001e-7, - "input_dbu_cost_per_token": 0.000007143, - "litellm_provider": "databricks", - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "max_tokens": 4096, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00000100002, - "output_dbu_cost_per_token": 0.000014286, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-30b-instruct": { - "input_cost_per_token": 0.00000100002, - "input_dbu_cost_per_token": 0.000014286, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0.00000100002, - "output_dbu_cost_per_token": 0.000014286, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "databricks/databricks-mpt-7b-instruct": { - "input_cost_per_token": 5.0001e-7, - "input_dbu_cost_per_token": 0.000007143, - "litellm_provider": "databricks", - "max_input_tokens": 8192, - "max_output_tokens": 8192, - "max_tokens": 8192, - "metadata": { - "notes": "Input/output cost per token is dbu cost * $0.070, based on databricks Llama 3.1 70B conversion. Number provided for reference, '*_dbu_cost_per_token' used in actual calculation." - }, - "mode": "chat", - "output_cost_per_token": 0, - "output_dbu_cost_per_token": 0, - "source": "https://www.databricks.com/product/pricing/foundation-model-serving", - "supports_tool_choice": true - }, - "dataforseo/search": { - "input_cost_per_query": 0.003, - "litellm_provider": "dataforseo", - "mode": "search" - }, - "davinci-002": { - "input_cost_per_token": 0.000002, - "litellm_provider": "text-completion-openai", - "max_input_tokens": 16384, - "max_output_tokens": 4096, - "max_tokens": 16384, - "mode": "completion", - "output_cost_per_token": 0.000002 - }, - "deepgram/base": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-conversationalai": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-finance": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-general": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-meeting": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-phonecall": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-video": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/base-voicemail": { - "input_cost_per_second": 0.00020833, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0125/60 seconds = $0.00020833 per second", - "original_pricing_per_minute": 0.0125 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/enhanced": { - "input_cost_per_second": 0.00024167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0145/60 seconds = $0.00024167 per second", - "original_pricing_per_minute": 0.0145 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/enhanced-finance": { - "input_cost_per_second": 0.00024167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0145/60 seconds = $0.00024167 per second", - "original_pricing_per_minute": 0.0145 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/enhanced-general": { - "input_cost_per_second": 0.00024167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0145/60 seconds = $0.00024167 per second", - "original_pricing_per_minute": 0.0145 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/enhanced-meeting": { - "input_cost_per_second": 0.00024167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0145/60 seconds = $0.00024167 per second", - "original_pricing_per_minute": 0.0145 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/enhanced-phonecall": { - "input_cost_per_second": 0.00024167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0145/60 seconds = $0.00024167 per second", - "original_pricing_per_minute": 0.0145 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-atc": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-automotive": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-conversationalai": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-drivethru": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-finance": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-general": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-meeting": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-phonecall": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-video": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-2-voicemail": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-3": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-3-general": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-3-medical": { - "input_cost_per_second": 0.00008667, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0052/60 seconds = $0.00008667 per second (multilingual)", - "original_pricing_per_minute": 0.0052 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-general": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/nova-phonecall": { - "input_cost_per_second": 0.00007167, - "litellm_provider": "deepgram", - "metadata": { - "calculation": "$0.0043/60 seconds = $0.00007167 per second", - "original_pricing_per_minute": 0.0043 - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper-base": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper-large": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper-medium": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper-small": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepgram/whisper-tiny": { - "input_cost_per_second": 0.0001, - "litellm_provider": "deepgram", - "metadata": { - "notes": "Deepgram's hosted OpenAI Whisper models - pricing may differ from native Deepgram models" - }, - "mode": "audio_transcription", - "output_cost_per_second": 0, - "source": "https://deepgram.com/pricing", - "supported_endpoints": [ - "/v1/audio/transcriptions" - ] - }, - "deepinfra/Gryphe/MythoMax-L2-13b": { - "max_tokens": 4096, - "max_input_tokens": 4096, - "max_output_tokens": 4096, - "input_cost_per_token": 8e-8, - "output_cost_per_token": 9e-8, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/NousResearch/Hermes-3-Llama-3.1-405B": { - "max_tokens": 131072, - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "input_cost_per_token": 0.000001, - "output_cost_per_token": 0.000001, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/NousResearch/Hermes-3-Llama-3.1-70B": { - "max_tokens": 131072, - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "input_cost_per_token": 3e-7, - "output_cost_per_token": 3e-7, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": false - }, - "deepinfra/Qwen/QwQ-32B": { - "max_tokens": 131072, - "max_input_tokens": 131072, - "max_output_tokens": 131072, - "input_cost_per_token": 1.5e-7, - "output_cost_per_token": 4e-7, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/Qwen/Qwen2.5-72B-Instruct": { - 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"litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/Qwen/Qwen3-235B-A22B": { - "max_tokens": 40960, - "max_input_tokens": 40960, - "max_output_tokens": 40960, - "input_cost_per_token": 1.8e-7, - "output_cost_per_token": 5.4e-7, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/Qwen/Qwen3-235B-A22B-Instruct-2507": { - "max_tokens": 262144, - "max_input_tokens": 262144, - "max_output_tokens": 262144, - "input_cost_per_token": 9e-8, - "output_cost_per_token": 6e-7, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/Qwen/Qwen3-235B-A22B-Thinking-2507": { - "max_tokens": 262144, - "max_input_tokens": 262144, - "max_output_tokens": 262144, - "input_cost_per_token": 3e-7, - "output_cost_per_token": 0.0000029, - "litellm_provider": "deepinfra", - "mode": "chat", - "supports_tool_choice": true - }, - "deepinfra/Qwen/Qwen3-30B-A3B": { - "max_tokens": 40960, - 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Defaulting to base model pricing", - "supports_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:gpt-4o-2024-08-06": { - "cache_read_input_token_cost": 0.000001875, - "input_cost_per_token": 0.00000375, - "input_cost_per_token_batches": 0.000001875, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 0.000015, - "output_cost_per_token_batches": 0.0000075, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "ft:gpt-4o-2024-11-20": { - "cache_creation_input_token_cost": 0.000001875, - "input_cost_per_token": 0.00000375, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 0.000015, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:gpt-4o-mini-2024-07-18": { - "cache_read_input_token_cost": 1.5e-7, - "input_cost_per_token": 3e-7, - "input_cost_per_token_batches": 1.5e-7, - "litellm_provider": "openai", - "max_input_tokens": 128000, - "max_output_tokens": 16384, - "max_tokens": 16384, - "mode": "chat", - "output_cost_per_token": 0.0000012, - "output_cost_per_token_batches": 6e-7, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:gpt-4.1-2025-04-14": { - "cache_read_input_token_cost": 7.5e-7, - "input_cost_per_token": 0.000003, - "input_cost_per_token_batches": 0.0000015, - "litellm_provider": "openai", - "max_input_tokens": 1047576, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 0.000012, - "output_cost_per_token_batches": 0.000006, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:gpt-4.1-mini-2025-04-14": { - "cache_read_input_token_cost": 2e-7, - "input_cost_per_token": 8e-7, - "input_cost_per_token_batches": 4e-7, - "litellm_provider": "openai", - "max_input_tokens": 1047576, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 0.0000032, - "output_cost_per_token_batches": 0.0000016, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:gpt-4.1-nano-2025-04-14": { - "cache_read_input_token_cost": 5e-8, - "input_cost_per_token": 2e-7, - "input_cost_per_token_batches": 1e-7, - "litellm_provider": "openai", - "max_input_tokens": 1047576, - "max_output_tokens": 32768, - "max_tokens": 32768, - "mode": "chat", - "output_cost_per_token": 8e-7, - "output_cost_per_token_batches": 4e-7, - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_prompt_caching": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true - }, - "ft:o4-mini-2025-04-16": { - "cache_read_input_token_cost": 0.000001, - "input_cost_per_token": 0.000004, - "input_cost_per_token_batches": 0.000002, - "litellm_provider": "openai", - "max_input_tokens": 200000, - "max_output_tokens": 100000, - "max_tokens": 100000, - "mode": "chat", - "output_cost_per_token": 0.000016, - "output_cost_per_token_batches": 0.000008, - "supports_function_calling": true, - "supports_parallel_function_calling": false, - "supports_prompt_caching": true, - "supports_reasoning": true, - "supports_response_schema": true, - "supports_tool_choice": true - }, - "gemini-1.0-pro": { - "input_cost_per_character": 1.25e-7, - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "input_cost_per_video_per_second": 0.002, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 32760, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 3.75e-7, - "output_cost_per_token": 0.0000015, - "source": "https://cloud.google.com/vertex-ai/generative-ai/pricing#google_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "gemini-1.0-pro-001": { - "deprecation_date": "2025-04-09", - "input_cost_per_character": 1.25e-7, - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "input_cost_per_video_per_second": 0.002, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 32760, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 3.75e-7, - "output_cost_per_token": 0.0000015, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "gemini-1.0-pro-002": { - "deprecation_date": "2025-04-09", - "input_cost_per_character": 1.25e-7, - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "input_cost_per_video_per_second": 0.002, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 32760, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 3.75e-7, - "output_cost_per_token": 0.0000015, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "gemini-1.0-pro-vision": { - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "litellm_provider": "vertex_ai-vision-models", - "max_images_per_prompt": 16, - "max_input_tokens": 16384, - "max_output_tokens": 2048, - "max_tokens": 2048, - "max_video_length": 2, - "max_videos_per_prompt": 1, - "mode": "chat", - "output_cost_per_token": 0.0000015, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.0-pro-vision-001": { - "deprecation_date": "2025-04-09", - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "litellm_provider": "vertex_ai-vision-models", - "max_images_per_prompt": 16, - "max_input_tokens": 16384, - "max_output_tokens": 2048, - "max_tokens": 2048, - "max_video_length": 2, - "max_videos_per_prompt": 1, - "mode": "chat", - "output_cost_per_token": 0.0000015, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.0-ultra": { - "input_cost_per_character": 1.25e-7, - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "input_cost_per_video_per_second": 0.002, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 8192, - "max_output_tokens": 2048, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 3.75e-7, - "output_cost_per_token": 0.0000015, - "source": "As of Jun, 2024. There is no available doc on vertex ai pricing gemini-1.0-ultra-001. Using gemini-1.0-pro pricing. Got max_tokens info here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "gemini-1.0-ultra-001": { - "input_cost_per_character": 1.25e-7, - "input_cost_per_image": 0.0025, - "input_cost_per_token": 5e-7, - "input_cost_per_video_per_second": 0.002, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 8192, - "max_output_tokens": 2048, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 3.75e-7, - "output_cost_per_token": 0.0000015, - "source": "As of Jun, 2024. There is no available doc on vertex ai pricing gemini-1.0-ultra-001. Using gemini-1.0-pro pricing. Got max_tokens info here: https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_tool_choice": true - }, - "gemini-1.5-flash": { - "input_cost_per_audio_per_second": 0.000002, - "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, - "input_cost_per_character": 1.875e-8, - "input_cost_per_character_above_128k_tokens": 2.5e-7, - "input_cost_per_image": 0.00002, - "input_cost_per_image_above_128k_tokens": 0.00004, - "input_cost_per_token": 7.5e-8, - "input_cost_per_token_above_128k_tokens": 0.000001, - "input_cost_per_video_per_second": 0.00002, - "input_cost_per_video_per_second_above_128k_tokens": 0.00004, - "litellm_provider": "vertex_ai-language-models", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_pdf_size_mb": 30, - "max_tokens": 8192, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_character": 7.5e-8, - "output_cost_per_character_above_128k_tokens": 1.5e-7, - "output_cost_per_token": 3e-7, - "output_cost_per_token_above_128k_tokens": 6e-7, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.5-flash-001": { - "deprecation_date": "2025-05-24", - "input_cost_per_audio_per_second": 0.000002, - "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, - "input_cost_per_character": 1.875e-8, - "input_cost_per_character_above_128k_tokens": 2.5e-7, - "input_cost_per_image": 0.00002, - "input_cost_per_image_above_128k_tokens": 0.00004, - "input_cost_per_token": 7.5e-8, - "input_cost_per_token_above_128k_tokens": 0.000001, - "input_cost_per_video_per_second": 0.00002, - "input_cost_per_video_per_second_above_128k_tokens": 0.00004, - "litellm_provider": "vertex_ai-language-models", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_pdf_size_mb": 30, - "max_tokens": 8192, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_character": 7.5e-8, - "output_cost_per_character_above_128k_tokens": 1.5e-7, - "output_cost_per_token": 3e-7, - "output_cost_per_token_above_128k_tokens": 6e-7, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.5-flash-002": { - "deprecation_date": "2025-09-24", - "input_cost_per_audio_per_second": 0.000002, - "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, - "input_cost_per_character": 1.875e-8, - "input_cost_per_character_above_128k_tokens": 2.5e-7, - "input_cost_per_image": 0.00002, - "input_cost_per_image_above_128k_tokens": 0.00004, - "input_cost_per_token": 7.5e-8, - "input_cost_per_token_above_128k_tokens": 0.000001, - "input_cost_per_video_per_second": 0.00002, - "input_cost_per_video_per_second_above_128k_tokens": 0.00004, - "litellm_provider": "vertex_ai-language-models", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1048576, - "max_output_tokens": 8192, - "max_pdf_size_mb": 30, - "max_tokens": 8192, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_character": 7.5e-8, - "output_cost_per_character_above_128k_tokens": 1.5e-7, - "output_cost_per_token": 3e-7, - "output_cost_per_token_above_128k_tokens": 6e-7, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-1.5-flash", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.5-flash-exp-0827": { - "input_cost_per_audio_per_second": 0.000002, - "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, - "input_cost_per_character": 1.875e-8, - "input_cost_per_character_above_128k_tokens": 2.5e-7, - "input_cost_per_image": 0.00002, - "input_cost_per_image_above_128k_tokens": 0.00004, - "input_cost_per_token": 4.688e-9, - "input_cost_per_token_above_128k_tokens": 0.000001, - "input_cost_per_video_per_second": 0.00002, - "input_cost_per_video_per_second_above_128k_tokens": 0.00004, - "litellm_provider": "vertex_ai-language-models", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_pdf_size_mb": 30, - "max_tokens": 8192, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_character": 1.875e-8, - "output_cost_per_character_above_128k_tokens": 3.75e-8, - "output_cost_per_token": 4.6875e-9, - "output_cost_per_token_above_128k_tokens": 9.375e-9, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_response_schema": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.5-flash-preview-0514": { - "input_cost_per_audio_per_second": 0.000002, - "input_cost_per_audio_per_second_above_128k_tokens": 0.000004, - "input_cost_per_character": 1.875e-8, - "input_cost_per_character_above_128k_tokens": 2.5e-7, - "input_cost_per_image": 0.00002, - "input_cost_per_image_above_128k_tokens": 0.00004, - "input_cost_per_token": 7.5e-8, - "input_cost_per_token_above_128k_tokens": 0.000001, - "input_cost_per_video_per_second": 0.00002, - "input_cost_per_video_per_second_above_128k_tokens": 0.00004, - "litellm_provider": "vertex_ai-language-models", - "max_audio_length_hours": 8.4, - "max_audio_per_prompt": 1, - "max_images_per_prompt": 3000, - "max_input_tokens": 1000000, - "max_output_tokens": 8192, - "max_pdf_size_mb": 30, - "max_tokens": 8192, - "max_video_length": 1, - "max_videos_per_prompt": 10, - "mode": "chat", - "output_cost_per_character": 1.875e-8, - "output_cost_per_character_above_128k_tokens": 3.75e-8, - "output_cost_per_token": 4.6875e-9, - "output_cost_per_token_above_128k_tokens": 9.375e-9, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_system_messages": true, - "supports_tool_choice": true, - "supports_vision": true - }, - "gemini-1.5-pro": { - "input_cost_per_audio_per_second": 0.00003125, - "input_cost_per_audio_per_second_above_128k_tokens": 0.0000625, - "input_cost_per_character": 3.125e-7, - "input_cost_per_character_above_128k_tokens": 6.25e-7, - "input_cost_per_image": 0.00032875, - "input_cost_per_image_above_128k_tokens": 0.0006575, - "input_cost_per_token": 0.00000125, - "input_cost_per_token_above_128k_tokens": 0.0000025, - "input_cost_per_video_per_second": 0.00032875, - "input_cost_per_video_per_second_above_128k_tokens": 0.0006575, - "litellm_provider": "vertex_ai-language-models", - "max_input_tokens": 2097152, - "max_output_tokens": 8192, - "max_tokens": 8192, - "mode": "chat", - "output_cost_per_character": 0.00000125, - "output_cost_per_character_above_128k_tokens": 0.0000025, - "output_cost_per_token": 0.000005, - "output_cost_per_token_above_128k_tokens": 0.00001, - "source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#foundation_models", - "supports_function_calling": true, - "supports_parallel_function_calling": true, - "supports_pdf_input": true, - "supports_response_schema": true, - "supports_system_messages": true, - 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// Check if pricing file exists - if (!isPricingAvailable()) { - note( - "Model pricing file not found.\nRun 'bun run update-model-pricing' to download it.", - "⚠️ Pricing Unavailable", - ); - - const proceed = await confirm({ - message: "Continue without pricing?", - initialValue: true, - }); - - if (isCancel(proceed) || !proceed) { - cancel("Operation cancelled."); - process.exit(0); - } - - // Initialize all models with null pricing - for (const modelId of models) { - lookups.set(modelId, null); - } - - return { enabled: false, lookups }; - } - - // Look up pricing for each model + // Look up pricing for each model from the pre-built map for (const modelId of models) { - const lookup = lookupModelPricing(modelId); + const lookup = lookupPricingFromMap(modelId, pricingMap); lookups.set(modelId, lookup); } @@ -103,7 +80,7 @@ async function validateAndConfirmPricing( const pricingLines = models.map((modelId) => { const lookup = lookups.get(modelId)!; const display = getModelPricingDisplay(lookup.pricing); - return `${modelId}\n → ${lookup.matchedKey}\n → ${formatMTokCost(display.inputCostPerMTok)}/MTok in, ${formatMTokCost(display.outputCostPerMTok)}/MTok out`; + return `${modelId}\n → ${formatMTokCost(display.inputCostPerMTok)}/MTok in, ${formatMTokCost(display.outputCostPerMTok)}/MTok out`; }); note(pricingLines.join("\n\n"), "💰 Pricing Found"); @@ -135,7 +112,8 @@ async function validateAndConfirmPricing( lines.push("Pricing available for:"); for (const modelId of modelsWithPricing) { const lookup = lookups.get(modelId)!; - lines.push(` ✓ ${modelId} → ${lookup.matchedKey}`); + const display = getModelPricingDisplay(lookup.pricing); + lines.push(` ✓ ${modelId} (${formatMTokCost(display.inputCostPerMTok)}/MTok in)`); } } @@ -163,6 +141,10 @@ async function selectOptions(): Promise { const available_models = await gateway.getAvailableModels(); + // Build pricing map from gateway models + const gatewayModels = available_models.models as GatewayModel[]; + const pricingMap = buildPricingMap(gatewayModels); + const models = await multiselect({ message: "Select model(s) to benchmark", options: [{ value: "custom", label: "Custom" }].concat( @@ -196,8 +178,8 @@ async function selectOptions(): Promise { const selectedModels = models.filter((model) => model !== "custom"); - // Validate pricing for selected models - const pricing = await validateAndConfirmPricing(selectedModels); + // Validate pricing for selected models using the pre-built map + const pricing = await validateAndConfirmPricing(selectedModels, pricingMap); const mcp_integration = await select({ message: "Which MCP integration to use?", diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index ce7cfa9..661080b 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -1,83 +1,154 @@ import { describe, it, expect } from "vitest"; import { - _generateLookupCandidates as generateLookupCandidates, + extractPricingFromGatewayModel, + buildPricingMap, + lookupPricingFromMap, calculateCost, formatCost, formatMTokCost, getModelPricingDisplay, type ModelPricing, + type GatewayModel, } from "./pricing.ts"; -describe("generateLookupCandidates", () => { - describe("Vercel AI Gateway format (provider/model)", () => { - it("should generate candidates for alibaba/qwen-3-14b", () => { - const candidates = generateLookupCandidates("alibaba/qwen-3-14b"); - expect(candidates).toEqual([ - "vercel_ai_gateway/alibaba/qwen-3-14b", - "alibaba/qwen-3-14b", - "qwen-3-14b", - ]); - }); +describe("extractPricingFromGatewayModel", () => { + it("should extract pricing from a gateway model with all fields", () => { + const model: GatewayModel = { + id: "anthropic/claude-opus-4.5", + name: "Claude Opus 4.5", + pricing: { + input: "0.000005", + output: "0.000025", + cachedInputTokens: "0.0000005", + cacheCreationInputTokens: "0.00000625", + }, + modelType: "language", + }; - it("should generate candidates for anthropic/claude-sonnet-4", () => { - const candidates = generateLookupCandidates("anthropic/claude-sonnet-4"); - expect(candidates).toEqual([ - "vercel_ai_gateway/anthropic/claude-sonnet-4", - "anthropic/claude-sonnet-4", - "claude-sonnet-4", - ]); - }); + const pricing = extractPricingFromGatewayModel(model); - it("should generate candidates for openai/gpt-4o", () => { - const candidates = generateLookupCandidates("openai/gpt-4o"); - expect(candidates).toEqual([ - "vercel_ai_gateway/openai/gpt-4o", - "openai/gpt-4o", - "gpt-4o", - ]); - }); + expect(pricing).not.toBeNull(); + expect(pricing!.inputCostPerToken).toBe(0.000005); + expect(pricing!.outputCostPerToken).toBe(0.000025); + expect(pricing!.cacheReadInputTokenCost).toBe(0.0000005); + expect(pricing!.cacheCreationInputTokenCost).toBe(0.00000625); + }); - it("should generate candidates for google/gemini-2.0-flash", () => { - const candidates = generateLookupCandidates("google/gemini-2.0-flash"); - expect(candidates).toEqual([ - "vercel_ai_gateway/google/gemini-2.0-flash", - "google/gemini-2.0-flash", - "gemini-2.0-flash", - ]); - }); + it("should extract pricing with only input and output", () => { + const model: GatewayModel = { + id: "openai/gpt-4o", + name: "GPT-4o", + pricing: { + input: "0.000003", + output: "0.000015", + }, + modelType: "language", + }; - it("should generate candidates for x-ai/grok-2", () => { - const candidates = generateLookupCandidates("x-ai/grok-2"); - expect(candidates).toEqual([ - "vercel_ai_gateway/x-ai/grok-2", - "x-ai/grok-2", - "grok-2", - ]); - }); + const pricing = extractPricingFromGatewayModel(model); + + expect(pricing).not.toBeNull(); + expect(pricing!.inputCostPerToken).toBe(0.000003); + expect(pricing!.outputCostPerToken).toBe(0.000015); + expect(pricing!.cacheReadInputTokenCost).toBeUndefined(); }); - describe("nested paths (openrouter style)", () => { - it("should handle openrouter/anthropic/claude-sonnet-4", () => { - const candidates = generateLookupCandidates( - "openrouter/anthropic/claude-sonnet-4", - ); - expect(candidates).toEqual([ - "vercel_ai_gateway/openrouter/anthropic/claude-sonnet-4", - "openrouter/anthropic/claude-sonnet-4", - "anthropic/claude-sonnet-4", - "claude-sonnet-4", - ]); - }); + it("should return null for model without pricing", () => { + const model: GatewayModel = { + id: "local/model", + name: "Local Model", + modelType: "language", + }; + + const pricing = extractPricingFromGatewayModel(model); + expect(pricing).toBeNull(); }); - describe("no provider prefix", () => { - it("should return only the original string with gateway prefix when no separator", () => { - const candidates = generateLookupCandidates("claude-sonnet-4"); - expect(candidates).toEqual([ - "vercel_ai_gateway/claude-sonnet-4", - "claude-sonnet-4", - ]); - }); + it("should return null for model with empty pricing object", () => { + const model: GatewayModel = { + id: "local/model", + name: "Local Model", + pricing: {}, + modelType: "language", + }; + + const pricing = extractPricingFromGatewayModel(model); + expect(pricing).toBeNull(); + }); + + it("should handle invalid pricing values gracefully", () => { + const model: GatewayModel = { + id: "test/model", + name: "Test Model", + pricing: { + input: "invalid", + output: "0.000015", + }, + modelType: "language", + }; + + const pricing = extractPricingFromGatewayModel(model); + + expect(pricing).not.toBeNull(); + expect(pricing!.inputCostPerToken).toBe(0); + expect(pricing!.outputCostPerToken).toBe(0.000015); + }); +}); + +describe("buildPricingMap", () => { + it("should build a map from gateway models", () => { + const models: GatewayModel[] = [ + { + id: "anthropic/claude-sonnet-4", + name: "Claude Sonnet 4", + pricing: { input: "0.000003", output: "0.000015" }, + modelType: "language", + }, + { + id: "openai/gpt-4o", + name: "GPT-4o", + pricing: { input: "0.000005", output: "0.000015" }, + modelType: "language", + }, + { + id: "local/model", + name: "Local Model", + modelType: "language", + }, + ]; + + const map = buildPricingMap(models); + + expect(map.size).toBe(3); + expect(map.get("anthropic/claude-sonnet-4")).not.toBeNull(); + expect(map.get("openai/gpt-4o")).not.toBeNull(); + expect(map.get("local/model")).toBeNull(); + }); +}); + +describe("lookupPricingFromMap", () => { + it("should return pricing lookup for existing model", () => { + const models: GatewayModel[] = [ + { + id: "anthropic/claude-sonnet-4", + name: "Claude Sonnet 4", + pricing: { input: "0.000003", output: "0.000015" }, + modelType: "language", + }, + ]; + + const map = buildPricingMap(models); + const lookup = lookupPricingFromMap("anthropic/claude-sonnet-4", map); + + expect(lookup).not.toBeNull(); + expect(lookup!.matchedKey).toBe("anthropic/claude-sonnet-4"); + expect(lookup!.pricing.inputCostPerToken).toBe(0.000003); + }); + + it("should return null for non-existent model", () => { + const map = buildPricingMap([]); + const lookup = lookupPricingFromMap("non/existent", map); + expect(lookup).toBeNull(); }); }); diff --git a/lib/pricing.ts b/lib/pricing.ts index 78f1be0..b3bfb75 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -1,11 +1,3 @@ -import { readFileSync, existsSync } from "node:fs"; -import { join, dirname } from "node:path"; -import { fileURLToPath } from "node:url"; - -// Use import.meta for robust path resolution regardless of working directory -const __dirname = dirname(fileURLToPath(import.meta.url)); -const PRICING_FILE_PATH = join(__dirname, "../data/model-pricing.json"); - /** * Model pricing information */ @@ -46,128 +38,108 @@ export interface ModelPricingLookup { matchedKey: string; } -// Cache the loaded pricing data -let pricingData: Record | null = null; - /** - * Load the pricing data from the JSON file + * Vercel AI Gateway pricing format from getAvailableModels() */ -function loadPricingData(): Record { - if (pricingData) { - return pricingData; - } - - if (!existsSync(PRICING_FILE_PATH)) { - console.warn( - `⚠️ Model pricing file not found at ${PRICING_FILE_PATH}. Run 'bun run update-model-pricing' to download it.`, - ); - return {}; - } - - try { - const content = readFileSync(PRICING_FILE_PATH, "utf-8"); - pricingData = JSON.parse(content); - return pricingData ?? {}; - } catch (error) { - console.warn(`⚠️ Failed to load model pricing:`, error); - return {}; - } +export interface GatewayPricing { + input?: string; + output?: string; + cachedInputTokens?: string; + cacheCreationInputTokens?: string; } /** - * Generate lookup candidates for a model string - * Returns candidates in priority order (most specific first) - * - * Vercel AI Gateway model IDs are in the format "provider/model-name" - * LiteLLM pricing data stores them as "vercel_ai_gateway/provider/model-name" - * - * Examples: - * - "alibaba/qwen-3-14b" -> tries "vercel_ai_gateway/alibaba/qwen-3-14b", "alibaba/qwen-3-14b", "qwen-3-14b" - * - "anthropic/claude-sonnet-4" -> tries "vercel_ai_gateway/anthropic/claude-sonnet-4", "anthropic/claude-sonnet-4", "claude-sonnet-4" + * Vercel AI Gateway model format from getAvailableModels() */ -function generateLookupCandidates(modelString: string): string[] { - const candidates: string[] = []; - - // Primary: Try with vercel_ai_gateway prefix (how LiteLLM stores gateway models) - candidates.push(`vercel_ai_gateway/${modelString}`); - - // Secondary: Try the model string as-is - candidates.push(modelString); - - // Tertiary: If there's a provider prefix, try just the model name - const slashIndex = modelString.indexOf("/"); - if (slashIndex !== -1) { - const modelName = modelString.slice(slashIndex + 1); - candidates.push(modelName); - - // Also try nested paths (e.g., "openrouter/anthropic/claude" -> "anthropic/claude", "claude") - const nestedSlashIndex = modelName.indexOf("/"); - if (nestedSlashIndex !== -1) { - candidates.push(modelName.slice(nestedSlashIndex + 1)); - } - } - - // Remove duplicates while preserving order - return candidates.filter((v, i, a) => a.indexOf(v) === i); +export interface GatewayModel { + id: string; + name: string; + description?: string; + pricing?: GatewayPricing; + specification?: { + specificationVersion: string; + provider: string; + modelId: string; + }; + modelType: string; } /** - * Extract pricing from model data if available + * Extract ModelPricing from a Vercel AI Gateway model + * Returns null if no pricing information is available */ -function extractPricing( - modelData: Record, +export function extractPricingFromGatewayModel( + model: GatewayModel, ): ModelPricing | null { - const inputCost = modelData.input_cost_per_token; - const outputCost = modelData.output_cost_per_token; + if (!model.pricing) { + return null; + } + + const { pricing } = model; + + // Parse string values to numbers + const inputCost = pricing.input ? parseFloat(pricing.input) : 0; + const outputCost = pricing.output ? parseFloat(pricing.output) : 0; - if (typeof inputCost !== "number" && typeof outputCost !== "number") { + // If both are zero or NaN, no valid pricing + if ((inputCost === 0 || isNaN(inputCost)) && (outputCost === 0 || isNaN(outputCost))) { return null; } - return { - inputCostPerToken: typeof inputCost === "number" ? inputCost : 0, - outputCostPerToken: typeof outputCost === "number" ? outputCost : 0, - cacheReadInputTokenCost: - typeof modelData.cache_read_input_token_cost === "number" - ? modelData.cache_read_input_token_cost - : undefined, - cacheCreationInputTokenCost: - typeof modelData.cache_creation_input_token_cost === "number" - ? modelData.cache_creation_input_token_cost - : undefined, + const result: ModelPricing = { + inputCostPerToken: isNaN(inputCost) ? 0 : inputCost, + outputCostPerToken: isNaN(outputCost) ? 0 : outputCost, }; + + if (pricing.cachedInputTokens) { + const cached = parseFloat(pricing.cachedInputTokens); + if (!isNaN(cached)) { + result.cacheReadInputTokenCost = cached; + } + } + + if (pricing.cacheCreationInputTokens) { + const creation = parseFloat(pricing.cacheCreationInputTokens); + if (!isNaN(creation)) { + result.cacheCreationInputTokenCost = creation; + } + } + + return result; } /** - * Look up pricing information for a model, returning both the pricing and the matched key - * Returns null if pricing is not found + * Build a pricing lookup map from gateway models + * Returns a map of model ID to pricing lookup result */ -export function lookupModelPricing( - modelString: string, -): ModelPricingLookup | null { - const data = loadPricingData(); - const candidates = generateLookupCandidates(modelString); - - for (const candidate of candidates) { - const modelData = data[candidate] as Record | undefined; - if (modelData) { - const pricing = extractPricing(modelData); - if (pricing) { - return { pricing, matchedKey: candidate }; - } +export function buildPricingMap( + models: GatewayModel[], +): Map { + const map = new Map(); + + for (const model of models) { + const pricing = extractPricingFromGatewayModel(model); + if (pricing) { + map.set(model.id, { + pricing, + matchedKey: model.id, + }); + } else { + map.set(model.id, null); } } - return null; + return map; } /** - * Get pricing information for a model (legacy function for compatibility) - * Returns null if pricing is not found + * Look up pricing for a specific model ID from pre-built pricing map */ -export function getModelPricing(modelString: string): ModelPricing | null { - const lookup = lookupModelPricing(modelString); - return lookup?.pricing ?? null; +export function lookupPricingFromMap( + modelId: string, + pricingMap: Map, +): ModelPricingLookup | null { + return pricingMap.get(modelId) ?? null; } /** @@ -248,21 +220,3 @@ export function formatMTokCost(costPerMTok: number): string { } return `$${costPerMTok.toFixed(2)}`; } - -/** - * Check if pricing data is available - */ -export function isPricingAvailable(): boolean { - return existsSync(PRICING_FILE_PATH); -} - -/** - * Get all available model keys (for debugging/listing) - */ -export function getAllModelKeys(): string[] { - const data = loadPricingData(); - return Object.keys(data).filter((key) => key !== "sample_spec"); -} - -// Export for testing -export { generateLookupCandidates as _generateLookupCandidates }; diff --git a/scripts/update-model-pricing.ts b/scripts/update-model-pricing.ts deleted file mode 100644 index 20d8109..0000000 --- a/scripts/update-model-pricing.ts +++ /dev/null @@ -1,76 +0,0 @@ -#!/usr/bin/env bun -/** - * Script to download the latest model pricing data from LiteLLM - * Run with: bun run update-model-pricing - */ - -import { writeFileSync, mkdirSync, existsSync } from "node:fs"; -import { dirname } from "node:path"; - -const PRICING_URL = - "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"; -const OUTPUT_PATH = "data/model-pricing.json"; - -async function downloadPricing(): Promise { - console.log("📥 Downloading model pricing data from LiteLLM..."); - console.log(` URL: ${PRICING_URL}`); - - try { - const response = await fetch(PRICING_URL); - - if (!response.ok) { - throw new Error(`HTTP ${response.status}: ${response.statusText}`); - } - - const data = await response.json(); - - // Validate the data has expected structure - if (typeof data !== "object" || data === null) { - throw new Error("Invalid JSON: expected an object"); - } - - const modelCount = Object.keys(data).length; - console.log(`✓ Downloaded pricing for ${modelCount} models`); - - // Ensure the output directory exists - const dir = dirname(OUTPUT_PATH); - if (!existsSync(dir)) { - mkdirSync(dir, { recursive: true }); - } - - // Write the file with pretty formatting - writeFileSync(OUTPUT_PATH, JSON.stringify(data, null, 2)); - console.log(`✓ Saved to ${OUTPUT_PATH}`); - - // Show some stats - let chatModels = 0; - let modelsWithPricing = 0; - - for (const [key, value] of Object.entries(data)) { - if (key === "sample_spec") continue; - - const model = value as Record; - if (model.mode === "chat") { - chatModels++; - } - if ( - typeof model.input_cost_per_token === "number" || - typeof model.output_cost_per_token === "number" - ) { - modelsWithPricing++; - } - } - - console.log(`\n📊 Stats:`); - console.log(` Chat models: ${chatModels}`); - console.log(` Models with token pricing: ${modelsWithPricing}`); - } catch (error) { - console.error( - "✗ Failed to download pricing:", - error instanceof Error ? error.message : error, - ); - process.exit(1); - } -} - -downloadPricing(); From 6641fed9029de26858b28c139bad92e38c1825fd Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:21:21 +0100 Subject: [PATCH 15/29] Update report-template.ts --- lib/report-template.ts | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/lib/report-template.ts b/lib/report-template.ts index be37605..947a0d9 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -553,7 +553,7 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { `; From c8a222bd17bbadafd0ea9debe82fb874a3902429 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:27:07 +0100 Subject: [PATCH 17/29] Update AGENTS.md --- AGENTS.md | 268 ++++++++++++++++++++++++++++-------------------------- 1 file changed, 138 insertions(+), 130 deletions(-) diff --git a/AGENTS.md b/AGENTS.md index b38b6cb..7d89e91 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -1,6 +1,6 @@ ## Project Overview -AI SDK benchmarking tool built with Vercel AI SDK and Bun runtime. Tests AI agents with MCP (Model Context Protocol) server integration, specifically using the Svelte MCP server for agent benchmarks. Automatically discovers and runs all tests in the `tests/` directory and verifies generated components against test suites. +AI SDK benchmarking tool built with Vercel AI SDK and Bun runtime. Tests AI agents with MCP (Model Context Protocol) server integration using the Vercel AI Gateway. Automatically discovers and runs all tests in the `tests/` directory and verifies LLM-generated Svelte components against test suites. ## Development Commands @@ -8,125 +8,84 @@ AI SDK benchmarking tool built with Vercel AI SDK and Bun runtime. Tests AI agen # Install dependencies (runs patch-package automatically) bun install -# Run the main benchmark (discovers and runs all tests) -bun run index.ts +# Run the main benchmark (interactive CLI) +bun run start # Verify reference implementations against test suites bun run verify-tests -# Generate HTML report from most recent result +# Generate HTML reports from all result JSON files bun run generate-report.ts # Generate HTML report from specific result file bun run generate-report.ts results/result-2024-12-07-14-30-45.json +# Run unit tests for lib modules +bun run test:self + # Run TypeScript type checking bun tsc --noEmit -``` - -## Environment Variables - -### MODEL Configuration - -The `MODEL` environment variable determines which AI provider to use: - -**Anthropic Direct API:** -```bash -MODEL=anthropic/claude-haiku-4-5 -MODEL=anthropic/claude-sonnet-4 +# Format code with Prettier +bun run prettier ``` -**OpenAI Direct API:** +## Environment Variables -```bash -MODEL=openai/gpt-5 -MODEL=openai/gpt-5-mini -MODEL=openai/gpt-4o -``` +### Vercel AI Gateway -**OpenRouter (300+ models):** +The benchmark uses the Vercel AI Gateway for model access. Configuration: -```bash -MODEL=openrouter/anthropic/claude-sonnet-4 -MODEL=openrouter/google/gemini-pro -MODEL=openrouter/meta-llama/llama-3.1-405b-instruct -``` +1. Link to a Vercel project with AI Gateway enabled: `bun run vercel:link` +2. Pull environment variables: `bun run vercel:env:pull` -**LM Studio (Local models via OpenAI-compatible API):** - -```bash -MODEL=lmstudio/model-name -``` - -LM Studio runs a local OpenAI-compatible API server on `http://localhost:1234/v1`. Make sure LM Studio is running with a model loaded before using this provider. +Required environment variable: +- `VERCEL_OIDC_TOKEN`: OIDC token for Vercel AI Gateway authentication ### MCP Server Configuration -The `MCP_SERVER_URL` environment variable controls MCP (Model Context Protocol) integration. The tool automatically detects whether to use HTTP or StdIO transport based on the value format. - -**HTTP MCP Servers (Remote):** - -```bash -# Enable MCP with Svelte server (default for this benchmark) -MCP_SERVER_URL=https://mcp.svelte.dev/mcp - -# Use a different HTTP MCP server -MCP_SERVER_URL=https://your-mcp-server.com/mcp -``` +MCP integration is configured via the interactive CLI at runtime. Options: -**StdIO MCP Servers (Local):** +- **No MCP Integration**: Agent runs with built-in tools only +- **MCP over HTTP**: Uses HTTP transport (default: `https://mcp.svelte.dev/mcp`) +- **MCP over StdIO**: Uses local command (default: `npx -y @sveltejs/mcp`) -For local MCP servers, simply provide the command string (any non-HTTP value): - -```bash -# Use the default Svelte MCP server via npx -MCP_SERVER_URL=npx -y @sveltejs/mcp +## Architecture -# Use a custom local MCP server -MCP_SERVER_URL=node path/to/your/mcp-server.js +### Directory Structure -# Use with Bun runtime -MCP_SERVER_URL=bun run src/mcp-server.ts --verbose ``` - -**Disable MCP:** - -```bash -# Disable MCP integration (run without external tools) -MCP_SERVER_URL= +├── index.ts # Main entry point with interactive CLI +├── lib/ +│ ├── pricing.ts # Cost calculation from gateway pricing +│ ├── pricing.test.ts # Unit tests for pricing module +│ ├── test-discovery.ts # Test suite discovery and prompt building +│ ├── test-discovery.test.ts # Unit tests for test discovery +│ ├── output-test-runner.ts # Vitest runner for component verification +│ ├── output-test-runner.test.ts # Unit tests for output runner +│ ├── verify-references.ts # Reference implementation verification +│ ├── report.ts # Report generation orchestration +│ ├── report-template.ts # HTML report template generation +│ ├── report-styles.ts # CSS styles for HTML reports +│ └── tools/ +│ ├── index.ts # Tool exports +│ ├── result-write.ts # ResultWrite tool for final output +│ ├── result-write.test.ts # Unit tests for ResultWrite tool +│ ├── test-component.ts # TestComponent tool for iterative testing +│ └── test-component.test.ts # Unit tests for TestComponent tool +├── tests/ # Benchmark test suites +│ └── {test-name}/ +│ ├── Reference.svelte # Reference implementation +│ ├── test.ts # Vitest test file +│ └── prompt.md # Agent prompt +├── results/ # Benchmark results (JSON + HTML) +├── outputs/ # Temporary directory for test verification +└── patches/ # Patches for dependencies ``` -**Behavior:** - -- If `MCP_SERVER_URL` starts with `http://` or `https://`: Uses HTTP transport with that URL -- If `MCP_SERVER_URL` is set but not an HTTP URL: Uses StdIO transport, treating the value as a command string -- If `MCP_SERVER_URL` is empty or not set: Agent runs without MCP tools (only built-in tools) -- MCP transport type (HTTP or StdIO) and configuration are documented in the result JSON and HTML report - -### Required API Keys - -- `ANTHROPIC_API_KEY`: Required when using `anthropic/*` models -- `OPENAI_API_KEY`: Required when using `openai/*` models (get at https://platform.openai.com/api-keys) -- `OPENROUTER_API_KEY`: Required when using `openrouter/*` models (get at https://openrouter.ai/keys) -- No API key required for `lmstudio/*` models (runs locally) - -### Provider Routing - -The benchmark tool automatically routes to the correct provider based on the `MODEL` prefix: - -- `anthropic/*` → Direct Anthropic API -- `openai/*` → Direct OpenAI API -- `openrouter/*` → OpenRouter unified API -- `lmstudio/*` → LM Studio local server (OpenAI-compatible) - -This allows switching models and providers without any code changes. - -## Architecture - ### Test Suite Structure -Test suites are organized in the `tests/` directory with the following structure: +Benchmark test suites in `tests/` directory: ``` tests/ @@ -138,35 +97,63 @@ tests/ **Benchmark Workflow:** -1. `index.ts` discovers all test suites in `tests/` -2. For each test: +1. `index.ts` presents interactive CLI for model/MCP selection +2. Discovers all test suites in `tests/` +3. For each selected model and test: - Loads `prompt.md` and builds agent prompt - - Agent generates component code based on the prompt + - Agent generates component code using available tools - Agent calls `ResultWrite` tool with the component code - Component is written to `outputs/{test-name}/Component.svelte` - Test file is copied to `outputs/{test-name}/test.ts` - Vitest runs tests against the generated component - Results are collected (pass/fail, error messages) - Output directory is cleaned up -3. All results are saved to a timestamped JSON file -4. HTML report is generated with expandable sections for each test +4. All results are saved to timestamped JSON file +5. HTML report is generated with expandable sections for each test -**Reference Verification:** +### Agent Tools -- Run `bun run verify-tests` to validate reference implementations -- Each test file imports `Component.svelte` (not Reference.svelte directly) -- Verification system temporarily copies Reference.svelte → Component.svelte -- Tests use `@testing-library/svelte` for component testing -- Tests use `data-testid` attributes for element selection +**ResultWrite** (`lib/tools/result-write.ts`): +- Called when agent completes component implementation +- Signals the agent to stop (via `stopWhen` configuration) +- Accepts `content` parameter with Svelte component code + +**TestComponent** (`lib/tools/test-component.ts`): +- Optional tool for iterative development +- Runs component against test suite before final submission +- Returns pass/fail status and detailed error messages +- Enabled/disabled via interactive CLI + +### Interactive CLI + +The benchmark uses `@clack/prompts` for an interactive CLI that prompts for: + +1. **Model Selection**: Multi-select from Vercel AI Gateway available models +2. **MCP Integration**: Choose HTTP, StdIO, or no MCP +3. **TestComponent Tool**: Enable/disable iterative testing tool +4. **Pricing Confirmation**: Review and confirm cost calculation settings + +### Pricing System + +The pricing module (`lib/pricing.ts`) handles cost calculation: + +- Extracts pricing from Vercel AI Gateway model metadata +- Calculates costs based on input/output/cached tokens +- Supports cache read billing at reduced rates +- Displays costs in reports with per-million-token rates + +Key functions: +- `extractPricingFromGatewayModel()`: Parse gateway model pricing +- `buildPricingMap()`: Build lookup map from gateway models +- `calculateCost()`: Calculate total cost from token usage +- `formatCost()` / `formatMTokCost()`: Format costs for display ### Key Technologies - **Vercel AI SDK v5**: Agent framework with tool calling -- **@ai-sdk/anthropic**: Anthropic provider for direct API access -- **@ai-sdk/openai**: OpenAI provider for direct API access -- **@ai-sdk/openai-compatible**: OpenAI-compatible provider for LM Studio and other local servers -- **@openrouter/ai-sdk-provider**: OpenRouter provider for unified access to 300+ models +- **Vercel AI Gateway**: Unified access to multiple AI providers - **@ai-sdk/mcp**: MCP client integration (with custom patch) +- **@clack/prompts**: Interactive CLI prompts - **Bun Runtime**: JavaScript runtime (not Node.js) - **Vitest**: Test framework for component testing - **@testing-library/svelte**: Testing utilities for Svelte components @@ -176,33 +163,34 @@ tests/ The project uses `@ai-sdk/mcp` with a custom patch applied via `patch-package`: - Patch location: `patches/@ai-sdk+mcp+0.0.11.patch` -- Fixes: Handles missing event types in HTTP SSE responses by treating undefined events as "message" events -- MCP server: Configurable via `MCP_SERVER_URL` environment variable -- Default server: Svelte documentation server (`https://mcp.svelte.dev/mcp`) -- Can be disabled by leaving `MCP_SERVER_URL` empty +- Fixes: Handles missing event types in HTTP SSE responses +- Supports both HTTP and StdIO transports +- Configuration via interactive CLI at runtime ### Data Flow -1. Test discovery scans `tests/` directory for valid test suites -2. For each test: - a. Agent receives prompt with access to tools (built-in + optional MCP tools) +1. Interactive CLI collects configuration (models, MCP, tools) +2. Gateway provides available models and pricing +3. Test discovery scans `tests/` directory +4. For each model and test: + a. Agent receives prompt with access to tools (built-in + optional MCP) b. Agent iterates through steps, calling tools as needed - c. Agent stops when `ResultWrite` tool is called with component code + c. Agent stops when `ResultWrite` tool is called d. Component is written to `outputs/{test-name}/Component.svelte` e. Vitest runs test file against the generated component f. Test results are collected (pass/fail, error details) g. Output directory is cleaned up -3. All results aggregated into multi-test result object -4. Results written to `results/result-YYYY-MM-DD-HH-MM-SS.json` with metadata -5. HTML report generated at `results/result-YYYY-MM-DD-HH-MM-SS.html` -6. Report automatically opens in default browser +5. Results aggregated with pricing calculations +6. Results written to `results/result-YYYY-MM-DD-HH-MM-SS.json` +7. HTML report generated at `results/result-YYYY-MM-DD-HH-MM-SS.html` +8. Report automatically opens in default browser ### Output Files All results are saved in the `results/` directory with timestamped filenames: -- **JSON files**: `result-2024-12-07-14-30-45.json` - Complete execution trace with all test results -- **HTML files**: `result-2024-12-07-14-30-45.html` - Interactive visualization with expandable test sections +- **JSON files**: `result-2024-12-07-14-30-45.json` - Complete execution trace +- **HTML files**: `result-2024-12-07-14-30-45.html` - Interactive visualization **Multi-Test Result JSON Structure:** @@ -223,25 +211,44 @@ All results are saved in the `results/` directory with timestamped filenames: "duration": 150, "failedTests": [] } - }, - ... + } ], "metadata": { "mcpEnabled": true, "mcpServerUrl": "https://mcp.svelte.dev/mcp", + "mcpTransportType": "HTTP", "timestamp": "2024-12-07T14:30:45.123Z", - "model": "anthropic/claude-sonnet-4" + "model": "anthropic/claude-sonnet-4", + "pricingKey": "anthropic/claude-sonnet-4", + "pricing": { + "inputCostPerMTok": 3, + "outputCostPerMTok": 15, + "cacheReadCostPerMTok": 0.3 + }, + "totalCost": { + "inputCost": 0.003, + "outputCost": 0.015, + "cacheReadCost": 0.0003, + "totalCost": 0.0183, + "inputTokens": 1000, + "outputTokens": 1000, + "cachedInputTokens": 1000 + } } } ``` -This naming convention allows you to: +## Unit Tests + +Unit tests for library modules are in `lib/*.test.ts`: + +- `lib/pricing.test.ts` - Pricing extraction, calculation, formatting +- `lib/test-discovery.test.ts` - Test suite discovery and prompt building +- `lib/output-test-runner.test.ts` - Output directory management +- `lib/tools/result-write.test.ts` - ResultWrite tool behavior +- `lib/tools/test-component.test.ts` - TestComponent tool behavior -- Run multiple benchmarks without overwriting previous results -- Easily identify when each benchmark was run -- Compare results across different runs -- Track whether MCP was enabled for each run -- See per-test verification status +Run unit tests with: `bun run test:self` ## TypeScript Configuration @@ -258,12 +265,13 @@ This naming convention allows you to: - The MCP client import uses a direct path to the patched module: `./node_modules/@ai-sdk/mcp/dist/index.mjs` - Agent stops execution when the `ResultWrite` tool is called (configured via `stopWhen` option) +- Agent also stops after 10 steps maximum (configured via `stepCountIs(10)`) - The `outputs/` directory is used temporarily for test verification and is cleaned up after each test - HTML reports include expandable sections for each test with full step details - Test verification results show pass/fail status and failed test details - Token usage includes cached token counts when available - All result files are saved with timestamps to preserve historical benchmarks -- MCP integration can be toggled via `MCP_SERVER_URL` environment variable without code changes +- MCP integration can be configured via interactive CLI without code changes - MCP status is clearly indicated in both the JSON metadata and HTML report with a visual badge - Exit code is 0 if all tests pass, 1 if any tests fail -- LM Studio provider requires LM Studio to be running locally with a model loaded +- Pricing is fetched from Vercel AI Gateway model metadata at runtime From 7d8709cd903ed53883c14c77f9cd436397125934 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:28:27 +0100 Subject: [PATCH 18/29] Delete .gitkeep --- data/.gitkeep | 2 -- 1 file changed, 2 deletions(-) delete mode 100644 data/.gitkeep diff --git a/data/.gitkeep b/data/.gitkeep deleted file mode 100644 index 488db3c..0000000 --- a/data/.gitkeep +++ /dev/null @@ -1,2 +0,0 @@ -# This directory contains downloaded data files -# Run `bun run update-model-pricing` to update model-pricing.json From 1376cf6c5f0b271ea9533c866d90a1b1052b4ca5 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:31:16 +0100 Subject: [PATCH 19/29] wip --- results/result-2025-12-12-12-30-09.json | 1729 +++++++++++++++++++++++ results/result-2025-12-12-12-30-18.json | 721 ++++++++++ 2 files changed, 2450 insertions(+) create mode 100644 results/result-2025-12-12-12-30-09.json create mode 100644 results/result-2025-12-12-12-30-18.json diff --git a/results/result-2025-12-12-12-30-09.json b/results/result-2025-12-12-12-30-09.json new file mode 100644 index 0000000..05ee929 --- /dev/null +++ b/results/result-2025-12-12-12-30-09.json @@ -0,0 +1,1729 @@ +{ + "tests": [ + { + "testName": "snippets", + "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", + "steps": [ + { + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
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    " + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
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      \n
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      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
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      • \\n {/each}\\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
    " + }, + "output": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 531, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1343, + "outputTokens": 185, + "totalTokens": 1528, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "tools": [ + { + "type": "function", + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "type": "function", + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "toolChoice": { + "type": "auto" + }, + "prompt": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 856, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + } + ], + "headers": { + "user-agent": "ai/5.0.108" + } + } + }, + "response": { + "id": "aitxt-ZzotIzKEpYN6OhWDXoZ48jN9", + "timestamp": "2025-12-12T11:30:04.461Z", + "modelId": "anthropic/claude-haiku-4.5", + "headers": { + "access-control-allow-headers": "Content-Type, Authorization, ai-gateway-auth-method, ai-gateway-protocol-version, ai-model-id, ai-language-model-id, ai-language-model-specification-version, ai-language-model-streaming, http-referer, x-title", + "access-control-allow-methods": "GET, POST, PUT, PATCH, DELETE, OPTIONS", + "access-control-allow-origin": "*", + "cache-control": "public, max-age=0, must-revalidate", + "content-encoding": "br", + "content-type": "application/json", + "date": "Fri, 12 Dec 2025 11:30:04 GMT", + "server": "Vercel", + "strict-transport-security": "max-age=63072000; includeSubDomains; preload", + "transfer-encoding": "chunked", + "vary": "rsc, next-router-state-tree, next-router-prefetch, next-router-segment-prefetch", + "x-matched-path": "/v1/ai/language-model", + "x-vercel-cache": "MISS", + "x-vercel-id": "arn1::fra1::lh9lm-1765539002817-f6a60243f189" + }, + "body": { + "content": [ + { + "type": "text", + "text": "Let me check the Svelte 5 syntax for snippets. It seems the syntax needs adjustment:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", + "toolName": "TestComponent", + "input": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
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      \n {#each books as book}\n
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      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 531, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + } + ] + }, + "providerMetadata": { + "anthropic": { + "usage": { + "input_tokens": 1343, + "output_tokens": 185, + "cache_creation_input_tokens": 0, + "cache_read_input_tokens": 0, + "cache_creation": { + "ephemeral_5m_input_tokens": 0, + "ephemeral_1h_input_tokens": 0 + }, + "service_tier": "standard" + }, + "cacheCreationInputTokens": 0, + "stopSequence": null, + "container": null + }, + "gateway": { + "routing": { + "originalModelId": "anthropic/claude-haiku-4.5", + "resolvedProvider": "anthropic", + "resolvedProviderApiModelId": "claude-haiku-4-5-20251001", + "internalResolvedModelId": "anthropic:claude-haiku-4-5-20251001", + "fallbacksAvailable": [ + "vertexAnthropic", + "bedrock" + ], + "internalReasoning": "Selected anthropic as preferred provider for claude-haiku-4.5. 2 fallback(s) available: vertexAnthropic, bedrock", + "planningReasoning": "System credentials planned for: anthropic, vertexAnthropic, bedrock. Total execution order: anthropic(system) → vertexAnthropic(system) → bedrock(system)", + "canonicalSlug": "anthropic/claude-haiku-4.5", + "finalProvider": "anthropic", + "attempts": [ + { + "provider": "anthropic", + "internalModelId": "anthropic:claude-haiku-4-5-20251001", + "providerApiModelId": "claude-haiku-4-5-20251001", + "credentialType": "system", + "success": true, + "startTime": 236225.32592, + "endTime": 237832.401505, + "statusCode": 200 + } + ], + "modelAttemptCount": 1, + "modelAttempts": [ + { + "modelId": "anthropic/claude-haiku-4.5", + "canonicalSlug": "anthropic/claude-haiku-4.5", + "success": false, + "providerAttemptCount": 0, + "providerAttempts": [] + } + ], + "totalProviderAttemptCount": 0 + }, + "cost": "0.002268", + "marketCost": "0.002268", + "generationId": "gen_01KC956EEQ836SH8K22PGW3P7Q", + "billableWebSearchCalls": 0 + } + } + }, + { + "content": [ + { + "type": "text", + "text": "Let me try a different approach with snippet definition:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + }, + "output": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 523 + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1624, + "outputTokens": 175, + "totalTokens": 1799, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "tools": [ + { + "type": "function", + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "type": "function", + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "toolChoice": { + "type": "auto" + }, + "prompt": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 856, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me check the Svelte 5 syntax for snippets. It seems the syntax needs adjustment:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_01BYh1Mxmbnt5ZETuE8NqnEQ", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + }, + "output": { + "success": true + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 1841, + "outputTokens": 179, + "totalTokens": 2020, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "tools": [ + { + "type": "function", + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "type": "function", + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "toolChoice": { + "type": "auto" + }, + "prompt": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": false, + "message": "0 of 0 tests failed", + "passed": 0, + "failed": 0, + "total": 0, + "duration": 856, + "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Let me check the Svelte 5 syntax for snippets. It seems the syntax needs adjustment:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", + "toolName": "TestComponent", + "input": { + "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 523 + } + } + } + ] + } + ], + "headers": { + "user-agent": "ai/5.0.108" + } + } + }, + "response": { + "id": "aitxt-uPv3FPEIDjBOlVFnGWAEZfyV", + "timestamp": "2025-12-12T11:30:09.437Z", + "modelId": "anthropic/claude-haiku-4.5", + "headers": { + "access-control-allow-headers": "Content-Type, Authorization, ai-gateway-auth-method, ai-gateway-protocol-version, ai-model-id, ai-language-model-id, ai-language-model-specification-version, ai-language-model-streaming, http-referer, x-title", + "access-control-allow-methods": "GET, POST, PUT, PATCH, DELETE, OPTIONS", + "access-control-allow-origin": "*", + "cache-control": "public, max-age=0, must-revalidate", + "content-encoding": "br", + "content-type": "application/json", + "date": "Fri, 12 Dec 2025 11:30:09 GMT", + "server": "Vercel", + "strict-transport-security": "max-age=63072000; includeSubDomains; preload", + "transfer-encoding": "chunked", + "vary": "rsc, next-router-state-tree, next-router-prefetch, next-router-segment-prefetch", + "x-matched-path": "/v1/ai/language-model", + "x-vercel-cache": "MISS", + "x-vercel-id": "arn1::fra1::jn742-1765539007682-c680276ff667" + }, + "body": { + "content": [ + { + "type": "text", + "text": "Perfect! The tests pass. Now let me submit the final component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_01BYh1Mxmbnt5ZETuE8NqnEQ", + "toolName": "ResultWrite", + "input": "{\"content\":\"\\n\\n{#snippet title(bookTitle)}\\n {bookTitle}\\n{/snippet}\\n\\n
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      • \\n {/each}\\n
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      \n {#each books as book}\n
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      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " + } + } + ] + }, + { + "role": "tool", + "content": [ + { + "type": "tool-result", + "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", + "toolName": "TestComponent", + "output": { + "type": "json", + "value": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 523 + } + } + } + ] + }, + { + "role": "assistant", + "content": [ + { + "type": "text", + "text": "Perfect! The tests pass. Now let me submit the final component:" + }, + { + "type": "tool-call", + "toolCallId": "toolu_01BYh1Mxmbnt5ZETuE8NqnEQ", + "toolName": "ResultWrite", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", + "steps": [ + { + "content": [ + { + "type": "text", + "text": "I'll create a Svelte 5 component that demonstrates the basic use of snippets with the specified requirements. Let me start by implementing and testing the component." + }, + { + "type": "tool-call", + "toolCallId": "toolu_01M46JwgEXQhJi9GXLrWHsUJ", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n\t{bookTitle}\n{/snippet}\n\n
      \n\t{#each books as book}\n\t\t
    • \n\t\t\t{@render title(book)}\n\t\t
      • \n\t{/each}\n
    " + } + }, + { + "type": "tool-result", + "toolCallId": "toolu_01M46JwgEXQhJi9GXLrWHsUJ", + "toolName": "TestComponent", + "input": { + "content": "\n\n{#snippet title(bookTitle)}\n\t{bookTitle}\n{/snippet}\n\n
      \n\t{#each books as book}\n\t\t
    • \n\t\t\t{@render title(book)}\n\t\t
      • \n\t{/each}\n
    " + }, + "output": { + "success": true, + "message": "All 3 tests passed!", + "passed": 3, + "failed": 0, + "total": 3, + "duration": 503 + }, + "dynamic": false + } + ], + "finishReason": "tool-calls", + "usage": { + "inputTokens": 868, + "outputTokens": 200, + "totalTokens": 1068, + "cachedInputTokens": 0 + }, + "warnings": [], + "request": { + "body": { + "tools": [ + { + "type": "function", + "name": "ResultWrite", + "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + }, + { + "type": "function", + "name": "TestComponent", + "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", + "inputSchema": { + "$schema": "http://json-schema.org/draft-07/schema#", + "type": "object", + "properties": { + "content": { + "description": "The complete Svelte component code to test", + "type": "string" + } + }, + "required": [ + "content" + ], + "additionalProperties": false + } + } + ], + "toolChoice": { + "type": "auto" + }, + "prompt": [ + { + "role": "user", + "content": [ + { + "type": "text", + "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
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      • \n\t{/each}\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
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      • \n\t{/each}\n
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+import { getTimestampedFilename } from "./lib/utils.ts"; import { discoverTests, buildAgentPrompt, @@ -244,21 +245,6 @@ async function selectOptions(): Promise { }; } -/** - * Generate a timestamped filename - */ -function getTimestampedFilename(prefix: string, extension: string): string { - const now = new Date(); - const year = now.getFullYear(); - const month = String(now.getMonth() + 1).padStart(2, "0"); - const day = String(now.getDate()).padStart(2, "0"); - const hours = String(now.getHours()).padStart(2, "0"); - const minutes = String(now.getMinutes()).padStart(2, "0"); - const seconds = String(now.getSeconds()).padStart(2, "0"); - - return `${prefix}-${year}-${month}-${day}-${hours}-${minutes}-${seconds}.${extension}`; -} - /** * Parse a command string into command and args * Example: "npx -y @sveltejs/mcp" -> { command: "npx", args: ["-y", "@sveltejs/mcp"] } @@ -679,9 +665,9 @@ async function main() { mkdirSync(resultsDir, { recursive: true }); } - // Generate timestamped filenames - const jsonFilename = getTimestampedFilename("result", "json"); - const htmlFilename = getTimestampedFilename("result", "html"); + // Generate timestamped filenames with model name + const jsonFilename = getTimestampedFilename("result", "json", modelId); + const htmlFilename = getTimestampedFilename("result", "html", modelId); const jsonPath = `${resultsDir}/${jsonFilename}`; const htmlPath = `${resultsDir}/${htmlFilename}`; diff --git a/lib/utils.test.ts b/lib/utils.test.ts new file mode 100644 index 0000000..2a8139c --- /dev/null +++ b/lib/utils.test.ts @@ -0,0 +1,76 @@ +import { describe, it, expect } from "vitest"; +import { sanitizeModelName, getTimestampedFilename } from "./utils.ts"; + +describe("sanitizeModelName", () => { + it("replaces slashes with dashes", () => { + expect(sanitizeModelName("anthropic/claude-sonnet-4")).toBe( + "anthropic-claude-sonnet-4", + ); + }); + + it("replaces special characters with dashes", () => { + expect(sanitizeModelName("model@version")).toBe("model-version"); + expect(sanitizeModelName("model_name")).toBe("model-name"); + expect(sanitizeModelName("model name")).toBe("model-name"); + }); + + it("preserves dots", () => { + expect(sanitizeModelName("gpt-4.0")).toBe("gpt-4.0"); + expect(sanitizeModelName("model.v1.2.3")).toBe("model.v1.2.3"); + }); + + it("preserves alphanumeric characters", () => { + expect(sanitizeModelName("gpt4o")).toBe("gpt4o"); + expect(sanitizeModelName("claude3")).toBe("claude3"); + }); + + it("handles multiple consecutive special characters", () => { + expect(sanitizeModelName("model///name")).toBe("model---name"); + expect(sanitizeModelName("model@#$name")).toBe("model---name"); + }); +}); + +describe("getTimestampedFilename", () => { + const fixedDate = new Date("2025-12-12T14:30:45Z"); + + it("generates filename without model name", () => { + const result = getTimestampedFilename("result", "json", undefined, fixedDate); + expect(result).toBe("result-2025-12-12-14-30-45.json"); + }); + + it("generates filename with simple model name", () => { + const result = getTimestampedFilename("result", "json", "gpt-4o", fixedDate); + expect(result).toBe("result-2025-12-12-14-30-45-gpt-4o.json"); + }); + + it("generates filename with model name containing slashes", () => { + const result = getTimestampedFilename( + "result", + "json", + "anthropic/claude-sonnet-4", + fixedDate, + ); + expect(result).toBe("result-2025-12-12-14-30-45-anthropic-claude-sonnet-4.json"); + }); + + it("generates filename with model name containing special characters", () => { + const result = getTimestampedFilename( + "result", + "html", + "model@v1.2.3", + fixedDate, + ); + expect(result).toBe("result-2025-12-12-14-30-45-model-v1.2.3.html"); + }); + + it("handles different file extensions", () => { + const result = getTimestampedFilename("output", "txt", "test-model", fixedDate); + expect(result).toBe("output-2025-12-12-14-30-45-test-model.txt"); + }); + + it("pads single-digit months and days", () => { + const earlyDate = new Date("2025-01-05T08:09:07Z"); + const result = getTimestampedFilename("result", "json", undefined, earlyDate); + expect(result).toBe("result-2025-01-05-08-09-07.json"); + }); +}); diff --git a/lib/utils.ts b/lib/utils.ts new file mode 100644 index 0000000..208d5d8 --- /dev/null +++ b/lib/utils.ts @@ -0,0 +1,29 @@ +/** + * Sanitize model name for filesystem use + */ +export function sanitizeModelName(modelName: string): string { + return modelName.replace(/[^a-zA-Z0-9.]/g, "-"); +} + +/** + * Generate a timestamped filename with optional model name + * Uses UTC time for consistent timestamps across timezones + */ +export function getTimestampedFilename( + prefix: string, + extension: string, + modelName?: string, + now: Date = new Date(), +): string { + const year = now.getUTCFullYear(); + const month = String(now.getUTCMonth() + 1).padStart(2, "0"); + const day = String(now.getUTCDate()).padStart(2, "0"); + const hours = String(now.getUTCHours()).padStart(2, "0"); + const minutes = String(now.getUTCMinutes()).padStart(2, "0"); + const seconds = String(now.getUTCSeconds()).padStart(2, "0"); + + const timestamp = `${year}-${month}-${day}-${hours}-${minutes}-${seconds}`; + const modelSuffix = modelName ? `-${sanitizeModelName(modelName)}` : ""; + + return `${prefix}-${timestamp}${modelSuffix}.${extension}`; +} From 5b7f10fcd32c704eaadf628e65fd6ef3a8ef7464 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:40:40 +0100 Subject: [PATCH 21/29] cleanup --- index.ts | 79 ++++------------------------------------------------ lib/utils.ts | 73 ++++++++++++++++++++++++++++++++++++++++++++++++ 2 files changed, 79 insertions(+), 73 deletions(-) diff --git a/index.ts b/index.ts index 27557a5..7c561c0 100644 --- a/index.ts +++ b/index.ts @@ -9,7 +9,12 @@ import { type PricingInfo, type TotalCostInfo, } from "./lib/report.ts"; -import { getTimestampedFilename } from "./lib/utils.ts"; +import { + getTimestampedFilename, + isHttpUrl, + extractResultWriteContent, + calculateTotalCost, +} from "./lib/utils.ts"; import { discoverTests, buildAgentPrompt, @@ -26,10 +31,8 @@ import { buildPricingMap, lookupPricingFromMap, getModelPricingDisplay, - calculateCost, formatCost, formatMTokCost, - type ModelPricing, type ModelPricingLookup, type GatewayModel, } from "./lib/pricing.ts"; @@ -259,76 +262,6 @@ function parseCommandString(commandString: string): { return { command, args }; } -/** - * Check if a string is an HTTP/HTTPS URL - */ -function isHttpUrl(str: string): boolean { - return str.startsWith("http://") || str.startsWith("https://"); -} - -/** - * Extract ResultWrite content from agent steps - */ -function extractResultWriteContent(steps: unknown[]): string | null { - for (const step of steps) { - const s = step as { - content?: Array<{ - type: string; - toolName?: string; - input?: { content: string }; - }>; - }; - if (s.content) { - for (const content of s.content) { - if ( - content.type === "tool-call" && - content.toolName === "ResultWrite" - ) { - return content.input?.content ?? null; - } - } - } - } - return null; -} - -/** - * Calculate total cost from test results - */ -function calculateTotalCost( - tests: SingleTestResult[], - pricing: ModelPricing, -): TotalCostInfo { - let totalInputTokens = 0; - let totalOutputTokens = 0; - let totalCachedInputTokens = 0; - - for (const test of tests) { - for (const step of test.steps) { - totalInputTokens += step.usage.inputTokens; - totalOutputTokens += step.usage.outputTokens; - totalCachedInputTokens += step.usage.cachedInputTokens ?? 0; - } - } - - const costResult = calculateCost( - pricing, - totalInputTokens, - totalOutputTokens, - totalCachedInputTokens, - ); - - return { - inputCost: costResult.inputCost, - outputCost: costResult.outputCost, - cacheReadCost: costResult.cacheReadCost, - totalCost: costResult.totalCost, - inputTokens: totalInputTokens, - outputTokens: totalOutputTokens, - cachedInputTokens: totalCachedInputTokens, - }; -} - /** * Run a single test with the AI agent */ diff --git a/lib/utils.ts b/lib/utils.ts index 208d5d8..af3a88d 100644 --- a/lib/utils.ts +++ b/lib/utils.ts @@ -1,3 +1,6 @@ +import { calculateCost, type ModelPricing } from "./pricing.ts"; +import type { SingleTestResult, TotalCostInfo } from "./report.ts"; + /** * Sanitize model name for filesystem use */ @@ -27,3 +30,73 @@ export function getTimestampedFilename( return `${prefix}-${timestamp}${modelSuffix}.${extension}`; } + +/** + * Check if a string is an HTTP/HTTPS URL + */ +export function isHttpUrl(str: string): boolean { + return str.startsWith("http://") || str.startsWith("https://"); +} + +/** + * Extract ResultWrite content from agent steps + */ +export function extractResultWriteContent(steps: unknown[]): string | null { + for (const step of steps) { + const s = step as { + content?: Array<{ + type: string; + toolName?: string; + input?: { content: string }; + }>; + }; + if (s.content) { + for (const content of s.content) { + if ( + content.type === "tool-call" && + content.toolName === "ResultWrite" + ) { + return content.input?.content ?? null; + } + } + } + } + return null; +} + +/** + * Calculate total cost from test results + */ +export function calculateTotalCost( + tests: SingleTestResult[], + pricing: ModelPricing, +): TotalCostInfo { + let totalInputTokens = 0; + let totalOutputTokens = 0; + let totalCachedInputTokens = 0; + + for (const test of tests) { + for (const step of test.steps) { + totalInputTokens += step.usage.inputTokens; + totalOutputTokens += step.usage.outputTokens; + totalCachedInputTokens += step.usage.cachedInputTokens ?? 0; + } + } + + const costResult = calculateCost( + pricing, + totalInputTokens, + totalOutputTokens, + totalCachedInputTokens, + ); + + return { + inputCost: costResult.inputCost, + outputCost: costResult.outputCost, + cacheReadCost: costResult.cacheReadCost, + totalCost: costResult.totalCost, + inputTokens: totalInputTokens, + outputTokens: totalOutputTokens, + cachedInputTokens: totalCachedInputTokens, + }; +} From 89cb80802dffc7b925a0c4f7934a898bbfa37802 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 12:51:45 +0100 Subject: [PATCH 22/29] clean up useless comments --- generate-report.ts | 7 ----- index.ts | 47 -------------------------------- lib/output-test-runner.ts | 28 -------------------- lib/pricing.ts | 53 ------------------------------------- lib/report-template.ts | 37 -------------------------- lib/report.ts | 22 --------------- lib/test-discovery.ts | 9 ------- lib/tools/test-component.ts | 2 -- lib/utils.ts | 16 ----------- lib/verify-references.ts | 31 ---------------------- 10 files changed, 252 deletions(-) diff --git a/generate-report.ts b/generate-report.ts index 0dcd1b2..ffd28ae 100644 --- a/generate-report.ts +++ b/generate-report.ts @@ -1,14 +1,10 @@ import { generateReport } from "./lib/report.ts"; import { readdirSync } from "node:fs"; -/** - * Get all result files from the results directory - */ function getAllResultFiles(): string[] { const resultsDir = "results"; const files = readdirSync(resultsDir); - // Filter for result JSON files const resultFiles = files.filter( (file) => file.startsWith("result-") && file.endsWith(".json"), ); @@ -17,18 +13,15 @@ function getAllResultFiles(): string[] { throw new Error("No result files found in results/ directory"); } - // Sort by filename (which includes timestamp) in descending order resultFiles.sort((a, b) => b.localeCompare(a)); return resultFiles.map((file) => `${resultsDir}/${file}`); } -// Get all result JSON files const resultFiles = getAllResultFiles(); console.log(`Found ${resultFiles.length} result file(s) to process\n`); -// Generate HTML report for each JSON file for (const jsonPath of resultFiles) { const htmlPath = jsonPath.replace(/\.json$/, ".html"); console.log(`Generating report: ${jsonPath} -> ${htmlPath}`); diff --git a/index.ts b/index.ts index 7c561c0..db4ea06 100644 --- a/index.ts +++ b/index.ts @@ -61,16 +61,12 @@ interface SelectOptionsResult { pricing: PricingValidationResult; } -/** - * Validate pricing for selected models and get user confirmation - */ async function validateAndConfirmPricing( models: string[], pricingMap: Map, ): Promise { const lookups = new Map(); - // Look up pricing for each model from the pre-built map for (const modelId of models) { const lookup = lookupPricingFromMap(modelId, pricingMap); lookups.set(modelId, lookup); @@ -80,7 +76,6 @@ async function validateAndConfirmPricing( const modelsWithoutPricing = models.filter((m) => lookups.get(m) === null); if (modelsWithoutPricing.length === 0) { - // All models have pricing - show details and let user choose const pricingLines = models.map((modelId) => { const lookup = lookups.get(modelId)!; const display = getModelPricingDisplay(lookup.pricing); @@ -101,7 +96,6 @@ async function validateAndConfirmPricing( return { enabled: usePricing, lookups }; } else { - // Some or all models don't have pricing const lines: string[] = []; if (modelsWithoutPricing.length > 0) { @@ -145,7 +139,6 @@ async function selectOptions(): Promise { const available_models = await gateway.getAvailableModels(); - // Build pricing map from gateway models const gatewayModels = available_models.models as GatewayModel[]; const pricingMap = buildPricingMap(gatewayModels); @@ -182,7 +175,6 @@ async function selectOptions(): Promise { const selectedModels = models.filter((model) => model !== "custom"); - // Validate pricing for selected models using the pre-built map const pricing = await validateAndConfirmPricing(selectedModels, pricingMap); const mcp_integration = await select({ @@ -248,10 +240,6 @@ async function selectOptions(): Promise { }; } -/** - * Parse a command string into command and args - * Example: "npx -y @sveltejs/mcp" -> { command: "npx", args: ["-y", "@sveltejs/mcp"] } - */ function parseCommandString(commandString: string): { command: string; args: string[]; @@ -262,9 +250,6 @@ function parseCommandString(commandString: string): { return { command, args }; } -/** - * Run a single test with the AI agent - */ async function runSingleTest( test: TestDefinition, model: LanguageModel, @@ -279,14 +264,12 @@ async function runSingleTest( const prompt = buildAgentPrompt(test); try { - // Build tools object with conditional tools const tools = { ResultWrite: resultWriteTool, ...(testComponentEnabled && { TestComponent: testComponentTool(test) }), ...(mcpClient ? await mcpClient.tools() : {}), }; - // Create agent for this test let stepCounter = 0; const agent = new Agent({ model, @@ -327,14 +310,12 @@ async function runSingleTest( }, }); - // Run the agent console.log(" ⏳ Running agent..."); if (testComponentEnabled) { console.log(" 📋 TestComponent tool is available"); } const result = await agent.generate({ prompt }); - // Extract the generated component code const resultWriteContent = extractResultWriteContent(result.steps); if (!resultWriteContent) { @@ -350,7 +331,6 @@ async function runSingleTest( console.log(" ✓ Component generated"); - // Run test verification console.log(" ⏳ Verifying against tests..."); const verification = await runTestVerification(test, resultWriteContent); @@ -369,7 +349,6 @@ async function runSingleTest( } } - // Clean up this test's output directory cleanupTestEnvironment(test.name); return { @@ -399,27 +378,21 @@ async function runSingleTest( } } -// Main execution async function main() { const { models, mcp, testingTool, pricing } = await selectOptions(); - // Get MCP server URL/command from environment (optional) const mcpServerUrl = mcp; const mcpEnabled = !!mcp; - // Check if TestComponent tool is disabled const testComponentEnabled = testingTool; - // Determine MCP transport type const isHttpTransport = mcpServerUrl && isHttpUrl(mcpServerUrl); const mcpTransportType = isHttpTransport ? "HTTP" : "StdIO"; - // Print configuration header console.log("\n╔════════════════════════════════════════════════════╗"); console.log("║ SvelteBench 2.0 - Multi-Test ║"); console.log("╚════════════════════════════════════════════════════╝"); - // Print models with pricing info console.log("\n📋 Models:"); for (const modelId of models) { const lookup = pricing.lookups.get(modelId); @@ -434,10 +407,8 @@ async function main() { } } - // Print pricing status console.log(`\n💰 Pricing: ${pricing.enabled ? "Enabled" : "Disabled"}`); - // Print MCP config console.log(`🔌 MCP Integration: ${mcpEnabled ? "Enabled" : "Disabled"}`); if (mcpEnabled) { console.log(` Transport: ${mcpTransportType}`); @@ -448,12 +419,10 @@ async function main() { } } - // Print tool config console.log( `🧪 TestComponent Tool: ${testComponentEnabled ? "Enabled" : "Disabled"}`, ); - // Discover all tests console.log("\n📁 Discovering tests..."); const tests = discoverTests(); console.log( @@ -465,14 +434,11 @@ async function main() { process.exit(1); } - // Set up outputs directory setupOutputsDirectory(); - // Conditionally create MCP client based on transport type let mcpClient: Awaited> | null = null; if (mcpEnabled) { if (isHttpTransport) { - // HTTP transport mcpClient = await createMCPClient({ transport: { type: "http", @@ -480,7 +446,6 @@ async function main() { }, }); } else { - // StdIO transport - treat mcpServerUrl as command string const { command, args } = parseCommandString(mcpServerUrl!); mcpClient = await createMCPClient({ transport: new StdioMCPTransport({ @@ -498,7 +463,6 @@ async function main() { console.log(`🤖 Running benchmark for model: ${modelId}`); console.log("═".repeat(50)); - // Get pre-validated pricing for this model const pricingLookup = pricing.enabled ? (pricing.lookups.get(modelId) ?? null) : null; @@ -509,10 +473,8 @@ async function main() { ); } - // Get the model from gateway const model = gateway.languageModel(modelId); - // Run all tests const testResults: SingleTestResult[] = []; const startTime = Date.now(); @@ -532,7 +494,6 @@ async function main() { const totalDuration = Date.now() - startTime; - // Print summary console.log("\n" + "═".repeat(50)); console.log("📊 Test Summary"); console.log("═".repeat(50)); @@ -563,7 +524,6 @@ async function main() { `Total: ${passed} passed, ${failed} failed, ${skipped} skipped (${(totalDuration / 1000).toFixed(1)}s)`, ); - // Calculate total cost if pricing is available let totalCost: TotalCostInfo | null = null; let pricingInfo: PricingInfo | null = null; @@ -592,19 +552,16 @@ async function main() { console.log(`Total cost: ${formatCost(totalCost.totalCost)}`); } - // Ensure results directory exists const resultsDir = "results"; if (!existsSync(resultsDir)) { mkdirSync(resultsDir, { recursive: true }); } - // Generate timestamped filenames with model name const jsonFilename = getTimestampedFilename("result", "json", modelId); const htmlFilename = getTimestampedFilename("result", "html", modelId); const jsonPath = `${resultsDir}/${jsonFilename}`; const htmlPath = `${resultsDir}/${htmlFilename}`; - // Build the result data const resultData: MultiTestResultData = { tests: testResults, metadata: { @@ -619,18 +576,14 @@ async function main() { }, }; - // Save result JSON writeFileSync(jsonPath, JSON.stringify(resultData, null, 2)); console.log(`\n✓ Results saved to ${jsonPath}`); - // Generate HTML report await generateReport(jsonPath, htmlPath); } - // Clean up outputs directory cleanupOutputsDirectory(); - // Exit with appropriate code process.exit(totalFailed > 0 ? 1 : 0); } diff --git a/lib/output-test-runner.ts b/lib/output-test-runner.ts index eedf615..6298afd 100644 --- a/lib/output-test-runner.ts +++ b/lib/output-test-runner.ts @@ -27,9 +27,6 @@ export interface TestVerificationResult { failedTests?: FailedTest[]; } -/** - * Ensure the outputs directory exists and is clean - */ export function setupOutputsDirectory(): void { if (existsSync(OUTPUTS_DIR)) { rmSync(OUTPUTS_DIR, { recursive: true, force: true }); @@ -37,47 +34,32 @@ export function setupOutputsDirectory(): void { mkdirSync(OUTPUTS_DIR, { recursive: true }); } -/** - * Clean up the outputs directory - */ export function cleanupOutputsDirectory(): void { if (existsSync(OUTPUTS_DIR)) { rmSync(OUTPUTS_DIR, { recursive: true, force: true }); } } -/** - * Prepare the outputs directory for a specific test - * - Creates a subdirectory for the test - * - Copies the test.ts file - * - Writes the LLM-generated component - */ export function prepareTestEnvironment( test: TestDefinition, componentCode: string, ): string { const testDir = join(OUTPUTS_DIR, test.name); - // Create the test directory if (existsSync(testDir)) { rmSync(testDir, { recursive: true, force: true }); } mkdirSync(testDir, { recursive: true }); - // Write the LLM-generated component as Component.svelte const componentPath = join(testDir, "Component.svelte"); writeFileSync(componentPath, componentCode, "utf-8"); - // Copy the test file const testFilePath = join(testDir, "test.ts"); copyFileSync(test.testFile, testFilePath); return testDir; } -/** - * Clean up a specific test's output directory - */ export function cleanupTestEnvironment(testName: string): void { const testDir = join(OUTPUTS_DIR, testName); if (existsSync(testDir)) { @@ -85,9 +67,6 @@ export function cleanupTestEnvironment(testName: string): void { } } -/** - * Run vitest on the generated component and return the results - */ export async function runTestVerification( test: TestDefinition, componentCode: string, @@ -95,11 +74,9 @@ export async function runTestVerification( const startTime = Date.now(); try { - // Prepare the test environment const testDir = prepareTestEnvironment(test, componentCode); const testFilePath = join(testDir, "test.ts"); - // Run vitest programmatically const vitest = await startVitest("test", [testFilePath], { watch: false, reporters: ["verbose"], @@ -123,7 +100,6 @@ export async function runTestVerification( const failedTests: FailedTest[] = []; const allErrors: string[] = []; - // Get unhandled errors const unhandledErrors = vitest.state.getUnhandledErrors(); for (const error of unhandledErrors) { const errorMessage = @@ -131,7 +107,6 @@ export async function runTestVerification( allErrors.push(errorMessage); } - // Calculate success/failure let passed = true; let numTests = 0; let numFailed = 0; @@ -154,7 +129,6 @@ export async function runTestVerification( passed = false; } - // Add module errors const moduleErrors = module.errors(); for (const error of moduleErrors) { if (error.message) { @@ -176,7 +150,6 @@ export async function runTestVerification( if (result.state === "failed") { numFailed++; - // Build full test name from ancestor titles const ancestorTitles: string[] = []; let parent = t.parent; while (parent && "name" in parent) { @@ -195,7 +168,6 @@ export async function runTestVerification( ? `${ancestorTitles.join(" > ")} > ${t.name}` : t.name; - // Collect error messages const errorMessages: string[] = []; if (result.errors) { for (const testError of result.errors) { diff --git a/lib/pricing.ts b/lib/pricing.ts index b3bfb75..74f39df 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -1,6 +1,3 @@ -/** - * Model pricing information - */ export interface ModelPricing { inputCostPerToken: number; outputCostPerToken: number; @@ -8,9 +5,6 @@ export interface ModelPricing { cacheCreationInputTokenCost?: number; } -/** - * Cost calculation result - */ export interface CostCalculation { inputCost: number; outputCost: number; @@ -21,26 +15,17 @@ export interface CostCalculation { cachedInputTokens: number; } -/** - * Model pricing data with per-million-token rates for display - */ export interface ModelPricingDisplay { inputCostPerMTok: number; outputCostPerMTok: number; cacheReadCostPerMTok?: number; } -/** - * Result of looking up a model's pricing - */ export interface ModelPricingLookup { pricing: ModelPricing; matchedKey: string; } -/** - * Vercel AI Gateway pricing format from getAvailableModels() - */ export interface GatewayPricing { input?: string; output?: string; @@ -48,9 +33,6 @@ export interface GatewayPricing { cacheCreationInputTokens?: string; } -/** - * Vercel AI Gateway model format from getAvailableModels() - */ export interface GatewayModel { id: string; name: string; @@ -64,10 +46,6 @@ export interface GatewayModel { modelType: string; } -/** - * Extract ModelPricing from a Vercel AI Gateway model - * Returns null if no pricing information is available - */ export function extractPricingFromGatewayModel( model: GatewayModel, ): ModelPricing | null { @@ -77,11 +55,9 @@ export function extractPricingFromGatewayModel( const { pricing } = model; - // Parse string values to numbers const inputCost = pricing.input ? parseFloat(pricing.input) : 0; const outputCost = pricing.output ? parseFloat(pricing.output) : 0; - // If both are zero or NaN, no valid pricing if ((inputCost === 0 || isNaN(inputCost)) && (outputCost === 0 || isNaN(outputCost))) { return null; } @@ -108,10 +84,6 @@ export function extractPricingFromGatewayModel( return result; } -/** - * Build a pricing lookup map from gateway models - * Returns a map of model ID to pricing lookup result - */ export function buildPricingMap( models: GatewayModel[], ): Map { @@ -132,9 +104,6 @@ export function buildPricingMap( return map; } -/** - * Look up pricing for a specific model ID from pre-built pricing map - */ export function lookupPricingFromMap( modelId: string, pricingMap: Map, @@ -142,9 +111,6 @@ export function lookupPricingFromMap( return pricingMap.get(modelId) ?? null; } -/** - * Get pricing display information (cost per million tokens) - */ export function getModelPricingDisplay( pricing: ModelPricing, ): ModelPricingDisplay { @@ -158,30 +124,17 @@ export function getModelPricingDisplay( }; } -/** - * Calculate the cost for given token usage - * - * Billing model explanation: - * - inputTokens: Total input tokens reported by the API (includes cached) - * - cachedInputTokens: Subset of input tokens that were cache hits - * - Cached tokens are billed at a reduced rate (cacheReadInputTokenCost) - * - Uncached input tokens (inputTokens - cachedInputTokens) are billed at full rate - * - Output tokens are always billed at the output rate - */ export function calculateCost( pricing: ModelPricing, inputTokens: number, outputTokens: number, cachedInputTokens: number = 0, ): CostCalculation { - // Uncached input tokens are billed at full input rate const uncachedInputTokens = inputTokens - cachedInputTokens; const inputCost = uncachedInputTokens * pricing.inputCostPerToken; - // Output tokens billed at output rate const outputCost = outputTokens * pricing.outputCostPerToken; - // Cached tokens billed at reduced cache read rate (or free if not specified) const cacheReadCost = cachedInputTokens * (pricing.cacheReadInputTokenCost ?? 0); @@ -196,9 +149,6 @@ export function calculateCost( }; } -/** - * Format a cost value as USD string - */ export function formatCost(cost: number): string { if (cost === 0) return "$0.00"; if (cost < 0.01) { @@ -210,9 +160,6 @@ export function formatCost(cost: number): string { return `$${cost.toFixed(2)}`; } -/** - * Format per-million-token cost - */ export function formatMTokCost(costPerMTok: number): string { if (costPerMTok === 0) return "$0"; if (costPerMTok < 0.01) { diff --git a/lib/report-template.ts b/lib/report-template.ts index d8977c2..5f159dc 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -3,7 +3,6 @@ import type { MultiTestResultData, SingleTestResult } from "./report.ts"; import { getReportStyles } from "./report-styles.ts"; import { formatCost, formatMTokCost } from "./pricing.ts"; -// Type definitions for content blocks interface TextBlock { type: "text"; text: string; @@ -43,9 +42,6 @@ interface Step { [key: string]: unknown; } -/** - * Escape HTML special characters - */ function escapeHtml(text: string): string { const map: Record = { "&": "&", @@ -61,9 +57,6 @@ function escapeHtml(text: string): string { return result; } -/** - * Format timestamp to readable date - */ function formatTimestamp(timestamp: string): string { const date = new Date(timestamp); return date.toLocaleString("en-US", { @@ -76,17 +69,11 @@ function formatTimestamp(timestamp: string): string { }); } -/** - * Get first N lines of code - */ function getFirstLines(code: string, numLines: number): string { const lines = code.split("\n"); return lines.slice(0, numLines).join("\n"); } -/** - * Render a single content block based on its type - */ function renderContentBlock(block: ContentBlock): string { if (block.type === "text") { return `
    ${escapeHtml(block.text)}
    `; @@ -111,9 +98,6 @@ function renderContentBlock(block: ContentBlock): string { return ""; } -/** - * Render verification result section - */ function renderVerificationResult( verification: TestVerificationResult | null, ): string { @@ -160,9 +144,6 @@ function renderVerificationResult(
    • `; } -/** - * Render steps for a single test - */ function renderSteps(steps: Step[]): string { return steps .map((step, index) => { @@ -196,9 +177,6 @@ function renderSteps(steps: Step[]): string { .join("\n"); } -/** - * Render a single test's section - */ function renderTestSection(test: SingleTestResult, index: number): string { const totalTokens = test.steps.reduce( (sum, step) => sum + step.usage.totalTokens, @@ -219,7 +197,6 @@ function renderTestSection(test: SingleTestResult, index: number): string { const stepsHtml = renderSteps(test.steps); const verificationHtml = renderVerificationResult(test.verification); - // Generate unique ID for this test's component code const componentId = `component-${test.testName.replace(/[^a-zA-Z0-9]/g, "-")}`; const resultWriteHtml = test.resultWriteContent @@ -268,9 +245,6 @@ function renderTestSection(test: SingleTestResult, index: number): string { `; } -/** - * Render pricing section HTML - */ function renderPricingSection(data: MultiTestResultData): string { const { metadata } = data; const { pricing, totalCost, pricingKey } = metadata; @@ -279,7 +253,6 @@ function renderPricingSection(data: MultiTestResultData): string { return ""; } - // Build pricing info rows let pricingInfoHtml = ""; if (pricing) { const pricingKeyDisplay = pricingKey @@ -298,7 +271,6 @@ function renderPricingSection(data: MultiTestResultData): string { `; } - // Build cost breakdown let costBreakdownHtml = ""; if (totalCost) { const uncachedInputTokens = totalCost.inputTokens - totalCost.cachedInputTokens; @@ -343,9 +315,6 @@ function renderPricingSection(data: MultiTestResultData): string { `; } -/** - * Get additional styles for pricing section - */ function getPricingStyles(): string { return ` .pricing-section { @@ -458,9 +427,6 @@ function getPricingStyles(): string { `; } -/** - * Generate HTML report from multi-test result data - */ export function generateMultiTestHtml(data: MultiTestResultData): string { const metadata = data.metadata; const totalTests = data.tests.length; @@ -490,7 +456,6 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { ` : ""; - // Cost display in header const costDisplay = metadata.totalCost ? `${formatCost(metadata.totalCost.totalCost)}` : ""; @@ -567,13 +532,11 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { const collapseText = button.querySelector('.collapse-text'); if (preview.style.display === 'none') { - // Show preview preview.style.display = 'block'; full.style.display = 'none'; expandText.style.display = 'inline'; collapseText.style.display = 'none'; } else { - // Show full preview.style.display = 'none'; full.style.display = 'block'; expandText.style.display = 'none'; diff --git a/lib/report.ts b/lib/report.ts index e1a4227..a81bcee 100644 --- a/lib/report.ts +++ b/lib/report.ts @@ -2,7 +2,6 @@ import { readFile, writeFile } from "node:fs/promises"; import type { TestVerificationResult } from "./output-test-runner.ts"; import { generateMultiTestHtml } from "./report-template.ts"; -// Type definitions for result.json structure interface TextBlock { type: "text"; text: string; @@ -66,18 +65,12 @@ interface Step { [key: string]: unknown; } -/** - * Pricing information embedded in metadata - */ export interface PricingInfo { inputCostPerMTok: number; outputCostPerMTok: number; cacheReadCostPerMTok?: number; } -/** - * Total cost calculation for a test run - */ export interface TotalCostInfo { inputCost: number; outputCost: number; @@ -99,7 +92,6 @@ interface Metadata { totalCost?: TotalCostInfo | null; } -// Single test result within a multi-test run export interface SingleTestResult { testName: string; prompt: string; @@ -108,43 +100,31 @@ export interface SingleTestResult { verification: TestVerificationResult | null; } -// Multi-test result data structure export interface MultiTestResultData { tests: SingleTestResult[]; metadata: Metadata; } -// Legacy single-test result data structure (for backward compatibility) interface LegacyResultData { steps: Step[]; resultWriteContent?: string | null; metadata?: Metadata; } -/** - * Generate HTML report from result.json file - * Supports both legacy single-test and new multi-test formats - * @param resultPath - Path to the result.json file - * @param outputPath - Path where the HTML report will be saved - * @param openBrowser - Whether to open the report in the default browser (default: true) - */ export async function generateReport( resultPath: string, outputPath: string, openBrowser = true, ): Promise { try { - // Read and parse the result.json file const jsonContent = await readFile(resultPath, "utf-8"); const data = JSON.parse(jsonContent); let html: string; - // Check if it's the new multi-test format if ("tests" in data && Array.isArray(data.tests)) { html = generateMultiTestHtml(data as MultiTestResultData); } else { - // Legacy format - convert to multi-test format for consistent rendering const legacyData = data as LegacyResultData; const multiTestData: MultiTestResultData = { tests: [ @@ -166,12 +146,10 @@ export async function generateReport( html = generateMultiTestHtml(multiTestData); } - // Write the HTML file await writeFile(outputPath, html, "utf-8"); console.log(`✓ Report generated successfully: ${outputPath}`); - // Open the report in the default browser if (openBrowser) { Bun.spawn(["open", outputPath]); } diff --git a/lib/test-discovery.ts b/lib/test-discovery.ts index 6329cde..7896309 100644 --- a/lib/test-discovery.ts +++ b/lib/test-discovery.ts @@ -11,9 +11,6 @@ export interface TestDefinition { prompt: string; } -/** - * Discover all test suites in the tests/ directory and load their prompts - */ export function discoverTests(): TestDefinition[] { const testsDir = join(process.cwd(), "tests"); const definitions: TestDefinition[] = []; @@ -31,13 +28,11 @@ export function discoverTests(): TestDefinition[] { const promptFile = join(entryPath, "prompt.md"); const componentFile = join(entryPath, "Component.svelte"); - // Validate that required files exist if ( existsSync(referenceFile) && existsSync(testFile) && existsSync(promptFile) ) { - // Load the prompt content const prompt = readFileSync(promptFile, "utf-8"); definitions.push({ @@ -62,15 +57,11 @@ export function discoverTests(): TestDefinition[] { console.error("Error discovering tests:", error); } - // Sort by name for consistent ordering definitions.sort((a, b) => a.name.localeCompare(b.name)); return definitions; } -/** - * Build a prompt for the AI agent including the test requirements - */ export function buildAgentPrompt(test: TestDefinition): string { return `${test.prompt} diff --git a/lib/tools/test-component.ts b/lib/tools/test-component.ts index 4b5c221..4f2d3dd 100644 --- a/lib/tools/test-component.ts +++ b/lib/tools/test-component.ts @@ -22,7 +22,6 @@ export function testComponentTool(test: TestDefinition) { try { const result = await runTestVerification(test, content); - // Clean up the test environment after running cleanupTestEnvironment(test.name); if (result.passed) { @@ -54,7 +53,6 @@ export function testComponentTool(test: TestDefinition) { }; } } catch (error) { - // Ensure cleanup even on error cleanupTestEnvironment(test.name); console.log(`[TestComponent] ✗ Error running tests`); return { diff --git a/lib/utils.ts b/lib/utils.ts index af3a88d..00f5973 100644 --- a/lib/utils.ts +++ b/lib/utils.ts @@ -1,17 +1,10 @@ import { calculateCost, type ModelPricing } from "./pricing.ts"; import type { SingleTestResult, TotalCostInfo } from "./report.ts"; -/** - * Sanitize model name for filesystem use - */ export function sanitizeModelName(modelName: string): string { return modelName.replace(/[^a-zA-Z0-9.]/g, "-"); } -/** - * Generate a timestamped filename with optional model name - * Uses UTC time for consistent timestamps across timezones - */ export function getTimestampedFilename( prefix: string, extension: string, @@ -31,16 +24,10 @@ export function getTimestampedFilename( return `${prefix}-${timestamp}${modelSuffix}.${extension}`; } -/** - * Check if a string is an HTTP/HTTPS URL - */ export function isHttpUrl(str: string): boolean { return str.startsWith("http://") || str.startsWith("https://"); } -/** - * Extract ResultWrite content from agent steps - */ export function extractResultWriteContent(steps: unknown[]): string | null { for (const step of steps) { const s = step as { @@ -64,9 +51,6 @@ export function extractResultWriteContent(steps: unknown[]): string | null { return null; } -/** - * Calculate total cost from test results - */ export function calculateTotalCost( tests: SingleTestResult[], pricing: ModelPricing, diff --git a/lib/verify-references.ts b/lib/verify-references.ts index 87e767e..2b77eb4 100644 --- a/lib/verify-references.ts +++ b/lib/verify-references.ts @@ -33,9 +33,6 @@ interface TestResult { failedTests?: FailedTest[]; } -/** - * Load all test definitions from the tests/ directory - */ export function loadTestDefinitions(): TestDefinition[] { const testsDir = join(process.cwd(), "tests"); const definitions: TestDefinition[] = []; @@ -53,7 +50,6 @@ export function loadTestDefinitions(): TestDefinition[] { const promptFile = join(entryPath, "prompt.md"); const componentFile = join(entryPath, "Component.svelte"); - // Validate that required files exist if (existsSync(referenceFile) && existsSync(testFile)) { definitions.push({ name: entry, @@ -77,16 +73,10 @@ export function loadTestDefinitions(): TestDefinition[] { return definitions; } -/** - * Copy Reference.svelte to Component.svelte - */ export function copyReferenceToComponent(testDef: TestDefinition): void { copyFileSync(testDef.referenceFile, testDef.componentFile); } -/** - * Clean up Component.svelte file - */ export function cleanupComponent(testDef: TestDefinition): void { if (existsSync(testDef.componentFile)) { try { @@ -97,14 +87,10 @@ export function cleanupComponent(testDef: TestDefinition): void { } } -/** - * Run vitest on a specific test file and return the results - */ export async function runTest(testDef: TestDefinition): Promise { const startTime = Date.now(); try { - // Run vitest programmatically const vitest = await startVitest("test", [testDef.testFile], { watch: false, reporters: ["verbose"], @@ -128,7 +114,6 @@ export async function runTest(testDef: TestDefinition): Promise { const failedTests: FailedTest[] = []; const allErrors: string[] = []; - // Get unhandled errors const unhandledErrors = vitest.state.getUnhandledErrors(); for (const error of unhandledErrors) { const errorMessage = @@ -136,7 +121,6 @@ export async function runTest(testDef: TestDefinition): Promise { allErrors.push(errorMessage); } - // Calculate success/failure let passed = true; let numTests = 0; let numFailed = 0; @@ -159,7 +143,6 @@ export async function runTest(testDef: TestDefinition): Promise { passed = false; } - // Add module errors const moduleErrors = module.errors(); for (const error of moduleErrors) { if (error.message) { @@ -181,7 +164,6 @@ export async function runTest(testDef: TestDefinition): Promise { if (result.state === "failed") { numFailed++; - // Build full test name from ancestor titles const ancestorTitles: string[] = []; let parent = t.parent; while (parent && "name" in parent) { @@ -200,7 +182,6 @@ export async function runTest(testDef: TestDefinition): Promise { ? `${ancestorTitles.join(" > ")} > ${t.name}` : t.name; - // Collect error messages const errorMessages: string[] = []; if (result.errors) { for (const testError of result.errors) { @@ -254,9 +235,6 @@ export async function runTest(testDef: TestDefinition): Promise { } } -/** - * Print summary of test results - */ export function printSummary(results: TestResult[]): void { console.log("\n=== Test Verification Summary ===\n"); @@ -291,9 +269,6 @@ export function printSummary(results: TestResult[]): void { } } -/** - * Main function to verify all reference implementations - */ export async function verifyAllReferences(): Promise { console.log("Discovering test suites..."); const tests = loadTestDefinitions(); @@ -310,11 +285,9 @@ export async function verifyAllReferences(): Promise { console.log(`Running tests/${test.name}...`); try { - // Copy Reference.svelte to Component.svelte copyReferenceToComponent(test); console.log(" ✓ Copied Reference.svelte → Component.svelte"); - // Run the test const result = await runTest(test); results.push(result); @@ -331,7 +304,6 @@ export async function verifyAllReferences(): Promise { console.log("\n Failed tests:"); for (const failed of result.failedTests) { console.log(`✗ ${failed.fullName}`); - // Print error message with indentation const errorLines = failed.errorMessage.split("\n"); for (const line of errorLines) { if (line.trim()) { @@ -343,16 +315,13 @@ export async function verifyAllReferences(): Promise { } } } finally { - // Always cleanup Component.svelte cleanupComponent(test); console.log(" ✓ Cleaned up Component.svelte\n"); } } - // Print summary printSummary(results); - // Return exit code const allPassed = results.every((r) => r.passed); return allPassed ? 0 : 1; } From 58be0c03b6ec46007c1e85d9ef51c0b979c88143 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 13:15:17 +0100 Subject: [PATCH 23/29] wip --- lib/pricing.test.ts | 17 +++--- lib/pricing.ts | 14 ++--- lib/utils.test.ts | 128 +++++++++++++++++++++++++++++++++++++++++--- 3 files changed, 138 insertions(+), 21 deletions(-) diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index 661080b..253a235 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -64,7 +64,7 @@ describe("extractPricingFromGatewayModel", () => { expect(pricing).toBeNull(); }); - it("should return null for model with empty pricing object", () => { + it("should throw error for model with empty pricing object", () => { const model: GatewayModel = { id: "local/model", name: "Local Model", @@ -72,11 +72,12 @@ describe("extractPricingFromGatewayModel", () => { modelType: "language", }; - const pricing = extractPricingFromGatewayModel(model); - expect(pricing).toBeNull(); + expect(() => extractPricingFromGatewayModel(model)).toThrowError( + /Invalid pricing/, + ); }); - it("should handle invalid pricing values gracefully", () => { + it("should throw error for invalid pricing values", () => { const model: GatewayModel = { id: "test/model", name: "Test Model", @@ -87,11 +88,9 @@ describe("extractPricingFromGatewayModel", () => { modelType: "language", }; - const pricing = extractPricingFromGatewayModel(model); - - expect(pricing).not.toBeNull(); - expect(pricing!.inputCostPerToken).toBe(0); - expect(pricing!.outputCostPerToken).toBe(0.000015); + expect(() => extractPricingFromGatewayModel(model)).toThrowError( + /Invalid pricing/, + ); }); }); diff --git a/lib/pricing.ts b/lib/pricing.ts index 74f39df..c8db89d 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -55,16 +55,18 @@ export function extractPricingFromGatewayModel( const { pricing } = model; - const inputCost = pricing.input ? parseFloat(pricing.input) : 0; - const outputCost = pricing.output ? parseFloat(pricing.output) : 0; + const inputCost = pricing.input ? parseFloat(pricing.input) : NaN; + const outputCost = pricing.output ? parseFloat(pricing.output) : NaN; - if ((inputCost === 0 || isNaN(inputCost)) && (outputCost === 0 || isNaN(outputCost))) { - return null; + if (isNaN(inputCost) || isNaN(outputCost)) { + throw new Error( + `Invalid pricing for model ${model.id}: input and output pricing must be valid numbers.`, + ); } const result: ModelPricing = { - inputCostPerToken: isNaN(inputCost) ? 0 : inputCost, - outputCostPerToken: isNaN(outputCost) ? 0 : outputCost, + inputCostPerToken: inputCost, + outputCostPerToken: outputCost, }; if (pricing.cachedInputTokens) { diff --git a/lib/utils.test.ts b/lib/utils.test.ts index 2a8139c..12977e4 100644 --- a/lib/utils.test.ts +++ b/lib/utils.test.ts @@ -1,5 +1,11 @@ import { describe, it, expect } from "vitest"; -import { sanitizeModelName, getTimestampedFilename } from "./utils.ts"; +import { + sanitizeModelName, + getTimestampedFilename, + calculateTotalCost, +} from "./utils.ts"; +import type { ModelPricing } from "./pricing.ts"; +import type { SingleTestResult } from "./report.ts"; describe("sanitizeModelName", () => { it("replaces slashes with dashes", () => { @@ -34,12 +40,22 @@ describe("getTimestampedFilename", () => { const fixedDate = new Date("2025-12-12T14:30:45Z"); it("generates filename without model name", () => { - const result = getTimestampedFilename("result", "json", undefined, fixedDate); + const result = getTimestampedFilename( + "result", + "json", + undefined, + fixedDate, + ); expect(result).toBe("result-2025-12-12-14-30-45.json"); }); it("generates filename with simple model name", () => { - const result = getTimestampedFilename("result", "json", "gpt-4o", fixedDate); + const result = getTimestampedFilename( + "result", + "json", + "gpt-4o", + fixedDate, + ); expect(result).toBe("result-2025-12-12-14-30-45-gpt-4o.json"); }); @@ -50,7 +66,9 @@ describe("getTimestampedFilename", () => { "anthropic/claude-sonnet-4", fixedDate, ); - expect(result).toBe("result-2025-12-12-14-30-45-anthropic-claude-sonnet-4.json"); + expect(result).toBe( + "result-2025-12-12-14-30-45-anthropic-claude-sonnet-4.json", + ); }); it("generates filename with model name containing special characters", () => { @@ -64,13 +82,111 @@ describe("getTimestampedFilename", () => { }); it("handles different file extensions", () => { - const result = getTimestampedFilename("output", "txt", "test-model", fixedDate); + const result = getTimestampedFilename( + "output", + "txt", + "test-model", + fixedDate, + ); expect(result).toBe("output-2025-12-12-14-30-45-test-model.txt"); }); it("pads single-digit months and days", () => { const earlyDate = new Date("2025-01-05T08:09:07Z"); - const result = getTimestampedFilename("result", "json", undefined, earlyDate); + const result = getTimestampedFilename( + "result", + "json", + undefined, + earlyDate, + ); expect(result).toBe("result-2025-01-05-08-09-07.json"); }); }); + +describe("calculateTotalCost", () => { + const pricing: ModelPricing = { + inputCostPerToken: 1.0 / 1_000_000, + outputCostPerToken: 2.0 / 1_000_000, + cacheReadInputTokenCost: 0.1 / 1_000_000, + }; + + it("calculates zero cost for empty results", () => { + const tests: SingleTestResult[] = []; + const result = calculateTotalCost(tests, pricing); + + expect(result).toEqual({ + inputCost: 0, + outputCost: 0, + cacheReadCost: 0, + totalCost: 0, + inputTokens: 0, + outputTokens: 0, + cachedInputTokens: 0, + }); + }); + + it("aggregates usage from multiple steps and tests", () => { + const tests: SingleTestResult[] = [ + { + testName: "test1", + prompt: "p1", + resultWriteContent: null, + verification: {} as any, + steps: [ + { + usage: { + inputTokens: 100, + outputTokens: 50, + cachedInputTokens: 10, + }, + } as any, + { + usage: { + inputTokens: 200, + outputTokens: 100, + cachedInputTokens: 0, + }, + } as any, + ], + }, + { + testName: "test2", + prompt: "p2", + resultWriteContent: null, + verification: {} as any, + steps: [ + { + usage: { + inputTokens: 300, + outputTokens: 150, + cachedInputTokens: 20, + }, + } as any, + ], + }, + ]; + + // Total Input: 100 + 200 + 300 = 600 + // Total Output: 50 + 100 + 150 = 300 + // Total Cached: 10 + 0 + 20 = 30 + // Uncached Input: 600 - 30 = 570 + + // Costs (per Token): + // Input: 570 * (1.0 / 1e6) = 0.00057 + // Output: 300 * (2.0 / 1e6) = 0.0006 + // Cache: 30 * (0.1 / 1e6) = 0.000003 + // Total: 0.00057 + 0.0006 + 0.000003 = 0.001173 + + const result = calculateTotalCost(tests, pricing); + + expect(result).toEqual({ + inputCost: 0.00057, + outputCost: 0.0006, + cacheReadCost: 0.000003, + totalCost: 0.001173, + inputTokens: 600, + outputTokens: 300, + cachedInputTokens: 30, + }); + }); +}); \ No newline at end of file From 60304ffd42493daa72e132eee5eb391c3ab68928 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 13:26:29 +0100 Subject: [PATCH 24/29] Update pricing.test.ts --- lib/pricing.test.ts | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/lib/pricing.test.ts b/lib/pricing.test.ts index 253a235..c5edfc8 100644 --- a/lib/pricing.test.ts +++ b/lib/pricing.test.ts @@ -169,17 +169,17 @@ describe("calculateCost", () => { expect(result.inputTokens).toBe(1000); expect(result.outputTokens).toBe(500); expect(result.cachedInputTokens).toBe(0); - expect(result.inputCost).toBeCloseTo(0.003); // 1000 * $3/MTok + expect(result.inputCost).toBe(0.003); // 1000 * $3/MTok expect(result.outputCost).toBeCloseTo(0.0075); // 500 * $15/MTok expect(result.cacheReadCost).toBe(0); - expect(result.totalCost).toBeCloseTo(0.0105); + expect(result.totalCost).toBe(0.0105); }); it("should default cachedInputTokens to 0", () => { const result = calculateCost(basePricing, 1000, 500); expect(result.cachedInputTokens).toBe(0); - expect(result.inputCost).toBeCloseTo(0.003); + expect(result.inputCost).toBe(0.003); }); }); @@ -212,7 +212,7 @@ describe("calculateCost", () => { const result = calculateCost(pricingWithCache, 1000, 500, 1000); expect(result.inputCost).toBe(0); - expect(result.cacheReadCost).toBeCloseTo(0.0003); // 1000 * $0.30/MTok + expect(result.cacheReadCost).toBe(0.0003); // 1000 * $0.30/MTok }); }); @@ -229,9 +229,9 @@ describe("calculateCost", () => { it("should handle large token counts", () => { const result = calculateCost(basePricing, 1_000_000, 500_000, 0); - expect(result.inputCost).toBeCloseTo(3); // 1M * $3/MTok - expect(result.outputCost).toBeCloseTo(7.5); // 500K * $15/MTok - expect(result.totalCost).toBeCloseTo(10.5); + expect(result.inputCost).toBe(3); // 1M * $3/MTok + expect(result.outputCost).toBe(7.5); // 500K * $15/MTok + expect(result.totalCost).toBe(10.5); }); it("should handle pricing with zero costs", () => { @@ -283,7 +283,7 @@ describe("formatMTokCost", () => { it("should format per-MTok costs >= $0.01 with 2 decimal places", () => { expect(formatMTokCost(0.01)).toBe("$0.01"); - expect(formatMTokCost(0.30)).toBe("$0.30"); + expect(formatMTokCost(0.3)).toBe("$0.30"); expect(formatMTokCost(3)).toBe("$3.00"); expect(formatMTokCost(15)).toBe("$15.00"); }); @@ -314,7 +314,7 @@ describe("getModelPricingDisplay", () => { expect(display.inputCostPerMTok).toBe(3); expect(display.outputCostPerMTok).toBe(15); - expect(display.cacheReadCostPerMTok).toBeCloseTo(0.3); + expect(display.cacheReadCostPerMTok).toBe(0.3); }); it("should handle zero costs", () => { From 3025df5d827589d149a8510740361aff76f100d5 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 19:04:51 +0100 Subject: [PATCH 25/29] format --- AGENTS.md | 4 ++++ index.ts | 9 ++++++--- lib/report-template.ts | 20 ++++++++++++++------ lib/utils.test.ts | 2 +- package.json | 1 - 5 files changed, 25 insertions(+), 11 deletions(-) diff --git a/AGENTS.md b/AGENTS.md index 7d89e91..3e7c825 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -40,6 +40,7 @@ The benchmark uses the Vercel AI Gateway for model access. Configuration: 2. Pull environment variables: `bun run vercel:env:pull` Required environment variable: + - `VERCEL_OIDC_TOKEN`: OIDC token for Vercel AI Gateway authentication ### MCP Server Configuration @@ -114,11 +115,13 @@ tests/ ### Agent Tools **ResultWrite** (`lib/tools/result-write.ts`): + - Called when agent completes component implementation - Signals the agent to stop (via `stopWhen` configuration) - Accepts `content` parameter with Svelte component code **TestComponent** (`lib/tools/test-component.ts`): + - Optional tool for iterative development - Runs component against test suite before final submission - Returns pass/fail status and detailed error messages @@ -143,6 +146,7 @@ The pricing module (`lib/pricing.ts`) handles cost calculation: - Displays costs in reports with per-million-token rates Key functions: + - `extractPricingFromGatewayModel()`: Parse gateway model pricing - `buildPricingMap()`: Build lookup map from gateway models - `calculateCost()`: Calculate total cost from token usage diff --git a/index.ts b/index.ts index db4ea06..85721f6 100644 --- a/index.ts +++ b/index.ts @@ -111,7 +111,9 @@ async function validateAndConfirmPricing( for (const modelId of modelsWithPricing) { const lookup = lookups.get(modelId)!; const display = getModelPricingDisplay(lookup.pricing); - lines.push(` ✓ ${modelId} (${formatMTokCost(display.inputCostPerMTok)}/MTok in)`); + lines.push( + ` ✓ ${modelId} (${formatMTokCost(display.inputCostPerMTok)}/MTok in)`, + ); } } @@ -463,8 +465,9 @@ async function main() { console.log(`🤖 Running benchmark for model: ${modelId}`); console.log("═".repeat(50)); - const pricingLookup = - pricing.enabled ? (pricing.lookups.get(modelId) ?? null) : null; + const pricingLookup = pricing.enabled + ? (pricing.lookups.get(modelId) ?? null) + : null; if (pricingLookup) { const display = getModelPricingDisplay(pricingLookup.pricing); diff --git a/lib/report-template.ts b/lib/report-template.ts index 5f159dc..403b033 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -258,7 +258,7 @@ function renderPricingSection(data: MultiTestResultData): string { const pricingKeyDisplay = pricingKey ? `${escapeHtml(pricingKey)}` : ""; - + pricingInfoHtml = `
    Model Pricing: @@ -273,8 +273,9 @@ function renderPricingSection(data: MultiTestResultData): string { let costBreakdownHtml = ""; if (totalCost) { - const uncachedInputTokens = totalCost.inputTokens - totalCost.cachedInputTokens; - + const uncachedInputTokens = + totalCost.inputTokens - totalCost.cachedInputTokens; + costBreakdownHtml = `
    @@ -287,13 +288,17 @@ function renderPricingSection(data: MultiTestResultData): string { ${totalCost.outputTokens.toLocaleString()} ${formatCost(totalCost.outputCost)}
    - ${totalCost.cachedInputTokens > 0 ? ` + ${ + totalCost.cachedInputTokens > 0 + ? `
    Cached tokens: ${totalCost.cachedInputTokens.toLocaleString()} ⚡ ${formatCost(totalCost.cacheReadCost)}
    - ` : ""} + ` + : "" + }
    Total Cost: @@ -473,7 +478,10 @@ export function generateMultiTestHtml(data: MultiTestResultData): string { const pricingHtml = renderPricingSection(data); - const styles = getReportStyles() + getPricingStyles() + ` + const styles = + getReportStyles() + + getPricingStyles() + + ` .cost-badge { background: var(--success); color: white; diff --git a/lib/utils.test.ts b/lib/utils.test.ts index 12977e4..c3ad8df 100644 --- a/lib/utils.test.ts +++ b/lib/utils.test.ts @@ -189,4 +189,4 @@ describe("calculateTotalCost", () => { cachedInputTokens: 30, }); }); -}); \ No newline at end of file +}); diff --git a/package.json b/package.json index 8dc581f..bc6c87f 100644 --- a/package.json +++ b/package.json @@ -7,7 +7,6 @@ "start": "bun run vercel:env:pull && bun ./index.ts", "postinstall": "patch-package", "update": "bun update --interactive", - "update-model-pricing": "bun run scripts/update-model-pricing.ts", "verify-tests": "bun run verify-references.ts", "prettier": "prettier --write .", "tsc": "tsc --noEmit", From c774385860bfc45712b54507e983ab38885930e8 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 19:06:03 +0100 Subject: [PATCH 26/29] Update index.ts --- index.ts | 16 ++-------------- 1 file changed, 2 insertions(+), 14 deletions(-) diff --git a/index.ts b/index.ts index 85721f6..ab96951 100644 --- a/index.ts +++ b/index.ts @@ -49,22 +49,10 @@ import { } from "@clack/prompts"; import { gateway } from "ai"; -interface PricingValidationResult { - enabled: boolean; - lookups: Map; -} - -interface SelectOptionsResult { - models: string[]; - mcp: string | undefined; - testingTool: boolean; - pricing: PricingValidationResult; -} - async function validateAndConfirmPricing( models: string[], pricingMap: Map, -): Promise { +) { const lookups = new Map(); for (const modelId of models) { @@ -136,7 +124,7 @@ async function validateAndConfirmPricing( } } -async function selectOptions(): Promise { +async function selectOptions() { intro("🚀 Svelte AI Bench"); const available_models = await gateway.getAvailableModels(); From 60ad12f518a3e6a7103f3af745221c4a82698e96 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 19:13:03 +0100 Subject: [PATCH 27/29] Update test.yml --- .github/workflows/test.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 5333154..51a7fdf 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -24,5 +24,8 @@ jobs: - name: Install dependencies run: bun install + - name: TypeScript type check + run: bun run tsc + - name: Run tests run: bun test From 5b258d4daf1895f55a4f8d8f684f7ed9b90a8e24 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 19:13:52 +0100 Subject: [PATCH 28/29] infer types --- index.ts | 13 +++++-------- lib/output-test-runner.ts | 14 +++++++------- lib/pricing.ts | 14 +++++++------- lib/report-template.ts | 20 ++++++++++---------- lib/report.ts | 6 +++--- lib/test-discovery.ts | 8 ++++---- lib/utils.ts | 10 +++++----- lib/verify-references.ts | 20 ++++++++++---------- package.json | 1 - 9 files changed, 51 insertions(+), 55 deletions(-) diff --git a/index.ts b/index.ts index ab96951..b4a4bb3 100644 --- a/index.ts +++ b/index.ts @@ -5,9 +5,6 @@ import { writeFileSync, mkdirSync, existsSync } from "node:fs"; import { generateReport, type SingleTestResult, - type MultiTestResultData, - type PricingInfo, - type TotalCostInfo, } from "./lib/report.ts"; import { getTimestampedFilename, @@ -426,7 +423,7 @@ async function main() { setupOutputsDirectory(); - let mcpClient: Awaited> | null = null; + let mcpClient = null; if (mcpEnabled) { if (isHttpTransport) { mcpClient = await createMCPClient({ @@ -466,7 +463,7 @@ async function main() { const model = gateway.languageModel(modelId); - const testResults: SingleTestResult[] = []; + const testResults = []; const startTime = Date.now(); for (let i = 0; i < tests.length; i++) { @@ -515,8 +512,8 @@ async function main() { `Total: ${passed} passed, ${failed} failed, ${skipped} skipped (${(totalDuration / 1000).toFixed(1)}s)`, ); - let totalCost: TotalCostInfo | null = null; - let pricingInfo: PricingInfo | null = null; + let totalCost = null; + let pricingInfo = null; if (pricingLookup) { totalCost = calculateTotalCost(testResults, pricingLookup.pricing); @@ -553,7 +550,7 @@ async function main() { const jsonPath = `${resultsDir}/${jsonFilename}`; const htmlPath = `${resultsDir}/${htmlFilename}`; - const resultData: MultiTestResultData = { + const resultData = { tests: testResults, metadata: { mcpEnabled, diff --git a/lib/output-test-runner.ts b/lib/output-test-runner.ts index 6298afd..59de519 100644 --- a/lib/output-test-runner.ts +++ b/lib/output-test-runner.ts @@ -27,14 +27,14 @@ export interface TestVerificationResult { failedTests?: FailedTest[]; } -export function setupOutputsDirectory(): void { +export function setupOutputsDirectory() { if (existsSync(OUTPUTS_DIR)) { rmSync(OUTPUTS_DIR, { recursive: true, force: true }); } mkdirSync(OUTPUTS_DIR, { recursive: true }); } -export function cleanupOutputsDirectory(): void { +export function cleanupOutputsDirectory() { if (existsSync(OUTPUTS_DIR)) { rmSync(OUTPUTS_DIR, { recursive: true, force: true }); } @@ -43,7 +43,7 @@ export function cleanupOutputsDirectory(): void { export function prepareTestEnvironment( test: TestDefinition, componentCode: string, -): string { +) { const testDir = join(OUTPUTS_DIR, test.name); if (existsSync(testDir)) { @@ -60,7 +60,7 @@ export function prepareTestEnvironment( return testDir; } -export function cleanupTestEnvironment(testName: string): void { +export function cleanupTestEnvironment(testName: string) { const testDir = join(OUTPUTS_DIR, testName); if (existsSync(testDir)) { rmSync(testDir, { recursive: true, force: true }); @@ -70,7 +70,7 @@ export function cleanupTestEnvironment(testName: string): void { export async function runTestVerification( test: TestDefinition, componentCode: string, -): Promise { +) { const startTime = Date.now(); try { @@ -97,8 +97,8 @@ export async function runTestVerification( await vitest.close(); const testModules = vitest.state.getTestModules(); - const failedTests: FailedTest[] = []; - const allErrors: string[] = []; + const failedTests = []; + const allErrors = []; const unhandledErrors = vitest.state.getUnhandledErrors(); for (const error of unhandledErrors) { diff --git a/lib/pricing.ts b/lib/pricing.ts index c8db89d..46429fa 100644 --- a/lib/pricing.ts +++ b/lib/pricing.ts @@ -48,7 +48,7 @@ export interface GatewayModel { export function extractPricingFromGatewayModel( model: GatewayModel, -): ModelPricing | null { +) { if (!model.pricing) { return null; } @@ -88,7 +88,7 @@ export function extractPricingFromGatewayModel( export function buildPricingMap( models: GatewayModel[], -): Map { +) { const map = new Map(); for (const model of models) { @@ -109,13 +109,13 @@ export function buildPricingMap( export function lookupPricingFromMap( modelId: string, pricingMap: Map, -): ModelPricingLookup | null { +) { return pricingMap.get(modelId) ?? null; } export function getModelPricingDisplay( pricing: ModelPricing, -): ModelPricingDisplay { +) { return { inputCostPerMTok: pricing.inputCostPerToken * 1_000_000, outputCostPerMTok: pricing.outputCostPerToken * 1_000_000, @@ -131,7 +131,7 @@ export function calculateCost( inputTokens: number, outputTokens: number, cachedInputTokens: number = 0, -): CostCalculation { +) { const uncachedInputTokens = inputTokens - cachedInputTokens; const inputCost = uncachedInputTokens * pricing.inputCostPerToken; @@ -151,7 +151,7 @@ export function calculateCost( }; } -export function formatCost(cost: number): string { +export function formatCost(cost: number) { if (cost === 0) return "$0.00"; if (cost < 0.01) { return `$${cost.toFixed(6)}`; @@ -162,7 +162,7 @@ export function formatCost(cost: number): string { return `$${cost.toFixed(2)}`; } -export function formatMTokCost(costPerMTok: number): string { +export function formatMTokCost(costPerMTok: number) { if (costPerMTok === 0) return "$0"; if (costPerMTok < 0.01) { return `$${costPerMTok.toFixed(4)}`; diff --git a/lib/report-template.ts b/lib/report-template.ts index 403b033..2ecb63a 100644 --- a/lib/report-template.ts +++ b/lib/report-template.ts @@ -42,7 +42,7 @@ interface Step { [key: string]: unknown; } -function escapeHtml(text: string): string { +function escapeHtml(text: string) { const map: Record = { "&": "&", "<": "<", @@ -57,7 +57,7 @@ function escapeHtml(text: string): string { return result; } -function formatTimestamp(timestamp: string): string { +function formatTimestamp(timestamp: string) { const date = new Date(timestamp); return date.toLocaleString("en-US", { year: "numeric", @@ -69,12 +69,12 @@ function formatTimestamp(timestamp: string): string { }); } -function getFirstLines(code: string, numLines: number): string { +function getFirstLines(code: string, numLines: number) { const lines = code.split("\n"); return lines.slice(0, numLines).join("\n"); } -function renderContentBlock(block: ContentBlock): string { +function renderContentBlock(block: ContentBlock) { if (block.type === "text") { return `
    ${escapeHtml(block.text)}
    `; } else if (block.type === "tool-call") { @@ -100,7 +100,7 @@ function renderContentBlock(block: ContentBlock): string { function renderVerificationResult( verification: TestVerificationResult | null, -): string { +) { if (!verification) { return `
    ⊘ @@ -144,7 +144,7 @@ function renderVerificationResult(
    `; } -function renderSteps(steps: Step[]): string { +function renderSteps(steps: Step[]) { return steps .map((step, index) => { const assistantContentHtml = @@ -177,7 +177,7 @@ function renderSteps(steps: Step[]): string { .join("\n"); } -function renderTestSection(test: SingleTestResult, index: number): string { +function renderTestSection(test: SingleTestResult, index: number) { const totalTokens = test.steps.reduce( (sum, step) => sum + step.usage.totalTokens, 0, @@ -245,7 +245,7 @@ function renderTestSection(test: SingleTestResult, index: number): string { `; } -function renderPricingSection(data: MultiTestResultData): string { +function renderPricingSection(data: MultiTestResultData) { const { metadata } = data; const { pricing, totalCost, pricingKey } = metadata; @@ -320,7 +320,7 @@ function renderPricingSection(data: MultiTestResultData): string { `; } -function getPricingStyles(): string { +function getPricingStyles() { return ` .pricing-section { background: var(--surface); @@ -432,7 +432,7 @@ function getPricingStyles(): string { `; } -export function generateMultiTestHtml(data: MultiTestResultData): string { +export function generateMultiTestHtml(data: MultiTestResultData) { const metadata = data.metadata; const totalTests = data.tests.length; const passedTests = data.tests.filter((t) => t.verification?.passed).length; diff --git a/lib/report.ts b/lib/report.ts index a81bcee..c7e50bf 100644 --- a/lib/report.ts +++ b/lib/report.ts @@ -115,18 +115,18 @@ export async function generateReport( resultPath: string, outputPath: string, openBrowser = true, -): Promise { +) { try { const jsonContent = await readFile(resultPath, "utf-8"); const data = JSON.parse(jsonContent); - let html: string; + let html; if ("tests" in data && Array.isArray(data.tests)) { html = generateMultiTestHtml(data as MultiTestResultData); } else { const legacyData = data as LegacyResultData; - const multiTestData: MultiTestResultData = { + const multiTestData = { tests: [ { testName: "Legacy Test", diff --git a/lib/test-discovery.ts b/lib/test-discovery.ts index 7896309..414292b 100644 --- a/lib/test-discovery.ts +++ b/lib/test-discovery.ts @@ -11,9 +11,9 @@ export interface TestDefinition { prompt: string; } -export function discoverTests(): TestDefinition[] { +export function discoverTests() { const testsDir = join(process.cwd(), "tests"); - const definitions: TestDefinition[] = []; + const definitions = []; try { const entries = readdirSync(testsDir); @@ -45,7 +45,7 @@ export function discoverTests(): TestDefinition[] { prompt, }); } else { - const missing: string[] = []; + const missing = []; if (!existsSync(referenceFile)) missing.push("Reference.svelte"); if (!existsSync(testFile)) missing.push("test.ts"); if (!existsSync(promptFile)) missing.push("prompt.md"); @@ -62,7 +62,7 @@ export function discoverTests(): TestDefinition[] { return definitions; } -export function buildAgentPrompt(test: TestDefinition): string { +export function buildAgentPrompt(test: TestDefinition) { return `${test.prompt} IMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting.`; diff --git a/lib/utils.ts b/lib/utils.ts index 00f5973..e3cb01c 100644 --- a/lib/utils.ts +++ b/lib/utils.ts @@ -1,7 +1,7 @@ import { calculateCost, type ModelPricing } from "./pricing.ts"; import type { SingleTestResult, TotalCostInfo } from "./report.ts"; -export function sanitizeModelName(modelName: string): string { +export function sanitizeModelName(modelName: string) { return modelName.replace(/[^a-zA-Z0-9.]/g, "-"); } @@ -10,7 +10,7 @@ export function getTimestampedFilename( extension: string, modelName?: string, now: Date = new Date(), -): string { +) { const year = now.getUTCFullYear(); const month = String(now.getUTCMonth() + 1).padStart(2, "0"); const day = String(now.getUTCDate()).padStart(2, "0"); @@ -24,11 +24,11 @@ export function getTimestampedFilename( return `${prefix}-${timestamp}${modelSuffix}.${extension}`; } -export function isHttpUrl(str: string): boolean { +export function isHttpUrl(str: string) { return str.startsWith("http://") || str.startsWith("https://"); } -export function extractResultWriteContent(steps: unknown[]): string | null { +export function extractResultWriteContent(steps: unknown[]) { for (const step of steps) { const s = step as { content?: Array<{ @@ -54,7 +54,7 @@ export function extractResultWriteContent(steps: unknown[]): string | null { export function calculateTotalCost( tests: SingleTestResult[], pricing: ModelPricing, -): TotalCostInfo { +) { let totalInputTokens = 0; let totalOutputTokens = 0; let totalCachedInputTokens = 0; diff --git a/lib/verify-references.ts b/lib/verify-references.ts index 2b77eb4..cbd9ee9 100644 --- a/lib/verify-references.ts +++ b/lib/verify-references.ts @@ -33,9 +33,9 @@ interface TestResult { failedTests?: FailedTest[]; } -export function loadTestDefinitions(): TestDefinition[] { +export function loadTestDefinitions() { const testsDir = join(process.cwd(), "tests"); - const definitions: TestDefinition[] = []; + const definitions = []; try { const entries = readdirSync(testsDir); @@ -73,11 +73,11 @@ export function loadTestDefinitions(): TestDefinition[] { return definitions; } -export function copyReferenceToComponent(testDef: TestDefinition): void { +export function copyReferenceToComponent(testDef: TestDefinition) { copyFileSync(testDef.referenceFile, testDef.componentFile); } -export function cleanupComponent(testDef: TestDefinition): void { +export function cleanupComponent(testDef: TestDefinition) { if (existsSync(testDef.componentFile)) { try { unlinkSync(testDef.componentFile); @@ -87,7 +87,7 @@ export function cleanupComponent(testDef: TestDefinition): void { } } -export async function runTest(testDef: TestDefinition): Promise { +export async function runTest(testDef: TestDefinition) { const startTime = Date.now(); try { @@ -111,8 +111,8 @@ export async function runTest(testDef: TestDefinition): Promise { await vitest.close(); const testModules = vitest.state.getTestModules(); - const failedTests: FailedTest[] = []; - const allErrors: string[] = []; + const failedTests = []; + const allErrors = []; const unhandledErrors = vitest.state.getUnhandledErrors(); for (const error of unhandledErrors) { @@ -235,7 +235,7 @@ export async function runTest(testDef: TestDefinition): Promise { } } -export function printSummary(results: TestResult[]): void { +export function printSummary(results: TestResult[]) { console.log("\n=== Test Verification Summary ===\n"); const totalSuites = results.length; @@ -269,7 +269,7 @@ export function printSummary(results: TestResult[]): void { } } -export async function verifyAllReferences(): Promise { +export async function verifyAllReferences() { console.log("Discovering test suites..."); const tests = loadTestDefinitions(); console.log(`Found ${tests.length} test suite(s)\n`); @@ -279,7 +279,7 @@ export async function verifyAllReferences(): Promise { return 1; } - const results: TestResult[] = []; + const results = []; for (const test of tests) { console.log(`Running tests/${test.name}...`); diff --git a/package.json b/package.json index bc6c87f..b0d317f 100644 --- a/package.json +++ b/package.json @@ -10,7 +10,6 @@ "verify-tests": "bun run verify-references.ts", "prettier": "prettier --write .", "tsc": "tsc --noEmit", - "test:self": "bun vitest run lib/*.test.ts", "vercel:link": "vercel link", "vercel:env:pull": "vercel env pull .env.local --yes" }, From 89eb51d575dbea2a23496454d3e5979a8172a611 Mon Sep 17 00:00:00 2001 From: Stanislav Khromov Date: Fri, 12 Dec 2025 19:16:06 +0100 Subject: [PATCH 29/29] remove --- results/result-2025-12-09-21-21-09.json | 1317 ----------------- results/result-2025-12-09-21-45-46.json | 41 - results/result-2025-12-09-21-46-37.json | 1314 ----------------- results/result-2025-12-09-21-48-12.json | 1152 --------------- results/result-2025-12-12-12-30-09.json | 1729 ----------------------- results/result-2025-12-12-12-30-18.json | 721 ---------- 6 files changed, 6274 deletions(-) delete mode 100644 results/result-2025-12-09-21-21-09.json delete mode 100644 results/result-2025-12-09-21-45-46.json delete mode 100644 results/result-2025-12-09-21-46-37.json delete mode 100644 results/result-2025-12-09-21-48-12.json delete mode 100644 results/result-2025-12-12-12-30-09.json delete mode 100644 results/result-2025-12-12-12-30-18.json diff --git a/results/result-2025-12-09-21-21-09.json b/results/result-2025-12-09-21-21-09.json deleted file mode 100644 index 594953b..0000000 --- a/results/result-2025-12-09-21-21-09.json +++ /dev/null @@ -1,1317 +0,0 @@ -{ - "tests": [ - { - "testName": "snippets", - "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", - "steps": [ - { - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 883, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1051, - "outputTokens": 200, - "totalTokens": 1251, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_01562bGRbRaD6S9CFSVvt2Zj", - "timestamp": "2025-12-09T20:20:59.042Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "450000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:20:57Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:20:58Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:20:56Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "540000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:20:57Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab734be0aaf5571-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:20:58 GMT", - "request-id": "req_011CVwjZ9rDdqfdEJKY9bMJX", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1440", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_01562bGRbRaD6S9CFSVvt2Zj", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ], - "stop_reason": "tool_use", - "stop_sequence": null, - "usage": { - "input_tokens": 1051, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "output_tokens": 200, - "service_tier": "standard" - } - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "toolName": "TestComponent", - "input": { - "content": "\n\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":883,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_01YByZt9JMxEvvzn28wqrJz4", - "timestamp": "2025-12-09T20:21:04.964Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "449000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:21:01Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:21:01Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:21:00Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "539000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:21:01Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab734d46b5f5571-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:21:01 GMT", - "request-id": "req_011CVwjZR9DrEQg9g6UpNybB", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1582", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_01YByZt9JMxEvvzn28wqrJz4", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" - }, - { - "type": "tool_use", - "id": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 883, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 549 - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1637, - "outputTokens": 190, - "totalTokens": 1827, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":883,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" - }, - { - "type": "tool_use", - "id": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ], - "stop_reason": "tool_use", - "stop_sequence": null, - "usage": { - "input_tokens": 1637, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "output_tokens": 190, - "service_tier": "standard" - } - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
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      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 549 - } - } - } - ] - } - ] - }, - "providerMetadata": { - "anthropic": { - "usage": { - "input_tokens": 1637, - "output_tokens": 190, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "service_tier": "standard" - }, - "cacheCreationInputTokens": 0, - "stopSequence": null, - "container": null - } - } - }, - { - "content": [ - { - "type": "text", - "text": "Perfect! All tests passed. Now let me submit the final component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
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      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": true - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1869, - "outputTokens": 181, - "totalTokens": 2050, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_011EpTxmk8ddcgGBHj5aBjjH", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":883,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I see there's a syntax error. In Svelte 5, the snippet definition should use a different syntax. Let me correct this:" - }, - { - "type": "tool_use", - "id": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":609,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me try a different approach - snippet declarations in Svelte 5 should be in the template area:" - }, - { - "type": "tool_use", - "id": "toolu_01LYHAJeqTB3qhNYz6brNyhG", - "name": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_01LYHAJeqTB3qhNYz6brNyhG", - "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":549}" - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_01XLwdY3Phr2FzR5wBEtFzhL", - "timestamp": "2025-12-09T20:21:09.449Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "449000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:21:08Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:21:09Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:21:08Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "539000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:21:08Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab73506494b5571-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:21:09 GMT", - "request-id": "req_011CVwja1GKBgXYfdmgBpmto", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1277", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_01XLwdY3Phr2FzR5wBEtFzhL", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! All tests passed. Now let me submit the final component:" - }, - { - "type": "tool_use", - "id": "toolu_018hisFMvwP6DvXdmuFZ6w19", - "name": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
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      • \n {/each}\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_016DLcXLvNt7YsfwXLdUymfx", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 609, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me try a different approach - snippet declarations in Svelte 5 should be in the template area:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01LYHAJeqTB3qhNYz6brNyhG", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 549 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! All tests passed. Now let me submit the final component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_018hisFMvwP6DvXdmuFZ6w19", - "toolName": "ResultWrite", - "output": { - "type": "json", - "value": { - "success": true - } - } - } - ] - } - ] - }, - "providerMetadata": { - "anthropic": { - "usage": { - "input_tokens": 1869, - "output_tokens": 181, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "service_tier": "standard" - }, - "cacheCreationInputTokens": 0, - "stopSequence": null, - "container": null - } - } - } - ], - "resultWriteContent": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
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    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", - "steps": [], - "resultWriteContent": null, - "verification": { - "testName": "snippets", - "passed": false, - "numTests": 0, - "numPassed": 0, - "numFailed": 0, - "duration": 0, - "error": "anthropic/claude-haiku-4-5 is not a valid model ID" - } - } - ], - "metadata": { - "mcpEnabled": false, - "mcpServerUrl": null, - "mcpTransportType": null, - "timestamp": "2025-12-09T20:45:46.019Z", - "model": "openrouter/anthropic/claude-haiku-4-5", - "pricingKey": "claude-haiku-4-5", - "pricing": { - "inputCostPerMTok": 1, - "outputCostPerMTok": 5, - "cacheReadCostPerMTok": 0.09999999999999999 - }, - "totalCost": { - "inputCost": 0, - "outputCost": 0, - "cacheReadCost": 0, - "totalCost": 0, - "inputTokens": 0, - "outputTokens": 0, - "cachedInputTokens": 0 - } - } -} \ No newline at end of file diff --git a/results/result-2025-12-09-21-46-37.json b/results/result-2025-12-09-21-46-37.json deleted file mode 100644 index 3112711..0000000 --- a/results/result-2025-12-09-21-46-37.json +++ /dev/null @@ -1,1314 +0,0 @@ -{ - "tests": [ - { - "testName": "snippets", - "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", - "steps": [ - { - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 841, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1051, - "outputTokens": 198, - "totalTokens": 1249, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_01DS8ULCCUfKKRtFwjfhNV5d", - "timestamp": "2025-12-09T20:46:29.821Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "450000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:28Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:29Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:28Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "540000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:28Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab75a22b9b27bf6-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:46:29 GMT", - "request-id": "req_011CVwmW4EXTmTBuUVPpZP98", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1497", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_01DS8ULCCUfKKRtFwjfhNV5d", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "name": "TestComponent", - "input": { - "content": "\n\n
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      \n {#each books as book}\n
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      • \n {/each}\n
    \n" - }, - "output": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 532 - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1345, - "outputTokens": 209, - "totalTokens": 1554, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_019g2cMRiK4VhszbmqGcsy4Y", - "timestamp": "2025-12-09T20:46:32.255Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "449000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:31Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:32Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:31Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "539000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:31Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab75a339bff7bf6-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:46:32 GMT", - "request-id": "req_011CVwmWFnJfuTLjFR9c1b5C", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1342", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_019g2cMRiK4VhszbmqGcsy4Y", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool_use", - "id": "toolu_019MyaVX5GgJzVQUum78NnHt", - "name": "TestComponent", - "input": { - "content": "\n\n
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    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ], - "stop_reason": "tool_use", - "stop_sequence": null, - "usage": { - "input_tokens": 1345, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "output_tokens": 209, - "service_tier": "standard" - } - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 841, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 532 - } - } - } - ] - } - ] - }, - "providerMetadata": { - "anthropic": { - "usage": { - "input_tokens": 1345, - "output_tokens": 209, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "service_tier": "standard" - }, - "cacheCreationInputTokens": 0, - "stopSequence": null, - "container": null - } - } - }, - { - "content": [ - { - "type": "text", - "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 507 - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1596, - "outputTokens": 198, - "totalTokens": 1794, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "claude-haiku-4-5", - "max_tokens": 64000, - "messages": [ - { - "role": "user", - "content": [ - { - "type": "text", - "text": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool_use", - "id": "toolu_019MyaVX5GgJzVQUum78NnHt", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_019MyaVX5GgJzVQUum78NnHt", - "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":532}" - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_0115H2AdNyJVdf2CVmdKGKUC", - "timestamp": "2025-12-09T20:46:34.552Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "449000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:33Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:34Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:33Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "539000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:33Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab75a40dac77bf6-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:46:34 GMT", - "request-id": "req_011CVwmWQpmjsJMAGdzg9RBv", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1526", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_0115H2AdNyJVdf2CVmdKGKUC", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" - }, - { - "type": "tool_use", - "id": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "name": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ], - "stop_reason": "tool_use", - "stop_sequence": null, - "usage": { - "input_tokens": 1596, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "output_tokens": 198, - "service_tier": "standard" - } - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 841, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 532 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 507 - } - } - } - ] - } - ] - }, - "providerMetadata": { - "anthropic": { - "usage": { - "input_tokens": 1596, - "output_tokens": 198, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "service_tier": "standard" - }, - "cacheCreationInputTokens": 0, - "stopSequence": null, - "container": null - } - } - }, - { - "content": [ - { - "type": "text", - "text": "Perfect! The Svelte 5 snippet syntax is working correctly. Now let me submit the final component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool_use", - "id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":841,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool_use", - "id": "toolu_019MyaVX5GgJzVQUum78NnHt", - "name": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_019MyaVX5GgJzVQUum78NnHt", - "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":532}" - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" - }, - { - "type": "tool_use", - "id": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "name": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "user", - "content": [ - { - "type": "tool_result", - "tool_use_id": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":507}" - } - ] - } - ], - "tools": [ - { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - }, - { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "input_schema": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - ], - "tool_choice": { - "type": "auto" - } - } - }, - "response": { - "id": "msg_01BFnwhJq5A4XexxHPadVe7X", - "timestamp": "2025-12-09T20:46:36.650Z", - "modelId": "claude-haiku-4-5-20251001", - "headers": { - "anthropic-organization-id": "5bffe07c-068c-4d07-8ed5-05e67e1655ee", - "anthropic-ratelimit-input-tokens-limit": "450000", - "anthropic-ratelimit-input-tokens-remaining": "449000", - "anthropic-ratelimit-input-tokens-reset": "2025-12-09T20:46:36Z", - "anthropic-ratelimit-output-tokens-limit": "90000", - "anthropic-ratelimit-output-tokens-remaining": "90000", - "anthropic-ratelimit-output-tokens-reset": "2025-12-09T20:46:36Z", - "anthropic-ratelimit-requests-limit": "1000", - "anthropic-ratelimit-requests-remaining": "999", - "anthropic-ratelimit-requests-reset": "2025-12-09T20:46:35Z", - "anthropic-ratelimit-tokens-limit": "540000", - "anthropic-ratelimit-tokens-remaining": "539000", - "anthropic-ratelimit-tokens-reset": "2025-12-09T20:46:36Z", - "cf-cache-status": "DYNAMIC", - "cf-ray": "9ab75a4f0a6b7bf6-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:46:36 GMT", - "request-id": "req_011CVwmWaZugZcAquU6w44uw", - "server": "cloudflare", - "strict-transport-security": "max-age=31536000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "x-envoy-upstream-service-time": "1355", - "x-robots-tag": "none" - }, - "body": { - "model": "claude-haiku-4-5-20251001", - "id": "msg_01BFnwhJq5A4XexxHPadVe7X", - "type": "message", - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! The Svelte 5 snippet syntax is working correctly. Now let me submit the final component:" - }, - { - "type": "tool_use", - "id": "toolu_01RVFWJzvFLvZtsduDXT7zTx", - "name": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ], - "stop_reason": "tool_use", - "stop_sequence": null, - "usage": { - "input_tokens": 1836, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "output_tokens": 190, - "service_tier": "standard" - } - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the book titles. Let me start by implementing and testing it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01AcscpuP4WpXyMQZYUzoXKb", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 841, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the syntax. In Svelte 5, the snippet syntax might be different. Let me try with the correct snippet declaration:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {book}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_019MyaVX5GgJzVQUum78NnHt", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 532 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Great! The tests are passing. However, let me try to implement this properly with Svelte 5 snippets syntax using `#snippet`:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_012kiBuyMBsADkHJ43yvMzzV", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 507 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! The Svelte 5 snippet syntax is working correctly. Now let me submit the final component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01RVFWJzvFLvZtsduDXT7zTx", - "toolName": "ResultWrite", - "output": { - "type": "json", - "value": { - "success": true - } - } - } - ] - } - ] - }, - "providerMetadata": { - "anthropic": { - "usage": { - "input_tokens": 1836, - "output_tokens": 190, - "cache_creation_input_tokens": 0, - "cache_read_input_tokens": 0, - "cache_creation": { - "ephemeral_5m_input_tokens": 0, - "ephemeral_1h_input_tokens": 0 - }, - "service_tier": "standard" - }, - "cacheCreationInputTokens": 0, - "stopSequence": null, - "container": null - } - } - } - ], - "resultWriteContent": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n", - "verification": { - "testName": "snippets", - "passed": true, - "numTests": 3, - "numPassed": 3, - "numFailed": 0, - "duration": 468 - } - } - ], - "metadata": { - "mcpEnabled": false, - "mcpServerUrl": null, - "mcpTransportType": null, - "timestamp": "2025-12-09T20:46:37.128Z", - "model": "anthropic/claude-haiku-4-5", - "pricingKey": "claude-haiku-4-5", - "pricing": { - "inputCostPerMTok": 1, - "outputCostPerMTok": 5, - "cacheReadCostPerMTok": 0.09999999999999999 - }, - "totalCost": { - "inputCost": 0.005828, - "outputCost": 0.003975, - "cacheReadCost": 0, - "totalCost": 0.009803, - "inputTokens": 5828, - "outputTokens": 795, - "cachedInputTokens": 0 - } - } -} \ No newline at end of file diff --git a/results/result-2025-12-09-21-48-12.json b/results/result-2025-12-09-21-48-12.json deleted file mode 100644 index fdf38a2..0000000 --- a/results/result-2025-12-09-21-48-12.json +++ /dev/null @@ -1,1152 +0,0 @@ -{ - "tests": [ - { - "testName": "snippets", - "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", - "steps": [ - { - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 827, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1051, - "outputTokens": 201, - "totalTokens": 1252, - "reasoningTokens": 0, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "anthropic/claude-haiku-4.5", - "messages": [ - { - "role": "user", - "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ], - "tools": [ - { - "type": "function", - "function": { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - }, - { - "type": "function", - "function": { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - } - ], - "tool_choice": "auto" - } - }, - "response": { - "id": "gen-1765313278-2tTFQlOjDEkBYaENUhMY", - "timestamp": "2025-12-09T20:48:01.151Z", - "modelId": "anthropic/claude-haiku-4.5", - "headers": { - "access-control-allow-origin": "*", - "cf-ray": "9ab75c574e969920-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:47:59 GMT", - "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", - "referrer-policy": "no-referrer, strict-origin-when-cross-origin", - "server": "cloudflare", - "transfer-encoding": "chunked", - "vary": "Accept-Encoding", - "x-content-type-options": "nosniff" - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 508, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1348, - "outputTokens": 185, - "totalTokens": 1533, - "reasoningTokens": 0, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "anthropic/claude-haiku-4.5", - "messages": [ - { - "role": "user", - "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - }, - { - "role": "assistant", - "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", - "tool_calls": [ - { - "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
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      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 827, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 508, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - } - ] - }, - "providerMetadata": { - "openrouter": { - "provider": "Amazon Bedrock", - "reasoning_details": [], - "usage": { - "promptTokens": 1348, - "promptTokensDetails": { - "cachedTokens": 0 - }, - "completionTokens": 185, - "completionTokensDetails": { - "reasoningTokens": 0 - }, - "totalTokens": 1533, - "cost": 0.00225027 - } - } - } - }, - { - "content": [ - { - "type": "text", - "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerMetadata": { - "openrouter": { - "reasoning_details": [] - } - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 521 - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1629, - "outputTokens": 186, - "totalTokens": 1815, - "reasoningTokens": 0, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "anthropic/claude-haiku-4.5", - "messages": [ - { - "role": "user", - "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - }, - { - "role": "assistant", - "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", - "tool_calls": [ - { - "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" - } - } - ] - }, - { - "role": "tool", - "tool_call_id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":827,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - }, - { - "role": "assistant", - "content": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:", - "tool_calls": [ - { - "id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" - } - } - ] - }, - { - "role": "tool", - "tool_call_id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":508,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - } - ], - "tools": [ - { - "type": "function", - "function": { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - }, - { - "type": "function", - "function": { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - } - ], - "tool_choice": "auto" - } - }, - "response": { - "id": "gen-1765313285-cXUgg1XpbsQi9AUgVJx2", - "timestamp": "2025-12-09T20:48:08.501Z", - "modelId": "anthropic/claude-haiku-4.5", - "headers": { - "access-control-allow-origin": "*", - "cf-ray": "9ab75c82fedc9920-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:48:07 GMT", - "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", - "referrer-policy": "no-referrer, strict-origin-when-cross-origin", - "server": "cloudflare", - "transfer-encoding": "chunked", - "vary": "Accept-Encoding", - "x-content-type-options": "nosniff" - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 827, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 508, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 521 - } - } - } - ] - } - ] - }, - "providerMetadata": { - "openrouter": { - "provider": "Amazon Bedrock", - "reasoning_details": [], - "usage": { - "promptTokens": 1629, - "promptTokensDetails": { - "cachedTokens": 0 - }, - "completionTokens": 186, - "completionTokensDetails": { - "reasoningTokens": 0 - }, - "totalTokens": 1815, - "cost": 0.00253341 - } - } - } - }, - { - "content": [ - { - "type": "text", - "text": "Perfect! The component passes all tests. Now let me submit the final implementation:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerMetadata": { - "openrouter": { - "reasoning_details": [] - } - } - }, - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "output": { - "success": true - }, - "dynamic": false - } - ], - "finishReason": "tool-calls", - "usage": { - "inputTokens": 1857, - "outputTokens": 183, - "totalTokens": 2040, - "reasoningTokens": 0, - "cachedInputTokens": 0 - }, - "warnings": [], - "request": { - "body": { - "model": "anthropic/claude-haiku-4.5", - "messages": [ - { - "role": "user", - "content": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - }, - { - "role": "assistant", - "content": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:", - "tool_calls": [ - { - "id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" - } - } - ] - }, - { - "role": "tool", - "tool_call_id": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":827,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - }, - { - "role": "assistant", - "content": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:", - "tool_calls": [ - { - "id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" - } - } - ] - }, - { - "role": "tool", - "tool_call_id": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "content": "{\"success\":false,\"message\":\"0 of 0 tests failed\",\"passed\":0,\"failed\":0,\"total\":0,\"duration\":508,\"error\":\"/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\\nhttps://svelte.dev/e/js_parse_error\"}" - }, - { - "role": "assistant", - "content": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:", - "tool_calls": [ - { - "id": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "type": "function", - "function": { - "name": "TestComponent", - "arguments": "{\"content\":\"\\n\\n{#snippet title(bookTitle)}\\n {bookTitle}\\n{/snippet}\\n\\n
      \\n {#each books as book}\\n
    • \\n {@render title(book)}\\n
      • \\n {/each}\\n
    \\n\"}" - } - } - ] - }, - { - "role": "tool", - "tool_call_id": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "content": "{\"success\":true,\"message\":\"All 3 tests passed!\",\"passed\":3,\"failed\":0,\"total\":3,\"duration\":521}" - } - ], - "tools": [ - { - "type": "function", - "function": { - "name": "ResultWrite", - "description": "Write your final Svelte component code. Call this when you have completed implementing the component and are ready to submit.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - }, - { - "type": "function", - "function": { - "name": "TestComponent", - "description": "Test your Svelte component against the test suite. Use this to verify your implementation and get feedback on any failing tests before submitting with ResultWrite. Returns detailed information about which tests passed or failed.", - "parameters": { - "$schema": "http://json-schema.org/draft-07/schema#", - "type": "object", - "properties": { - "content": { - "description": "The complete Svelte component code to test", - "type": "string" - } - }, - "required": [ - "content" - ], - "additionalProperties": false - } - } - } - ], - "tool_choice": "auto" - } - }, - "response": { - "id": "gen-1765313289-24sHvpTHhwj6FV298zOu", - "timestamp": "2025-12-09T20:48:11.690Z", - "modelId": "anthropic/claude-haiku-4.5", - "headers": { - "access-control-allow-origin": "*", - "cf-ray": "9ab75c9a4c369920-ARN", - "connection": "keep-alive", - "content-encoding": "gzip", - "content-type": "application/json", - "date": "Tue, 09 Dec 2025 20:48:10 GMT", - "permissions-policy": "payment=(self \"https://checkout.stripe.com\" \"https://connect-js.stripe.com\" \"https://js.stripe.com\" \"https://*.js.stripe.com\" \"https://hooks.stripe.com\")", - "referrer-policy": "no-referrer, strict-origin-when-cross-origin", - "server": "cloudflare", - "transfer-encoding": "chunked", - "vary": "Accept-Encoding", - "x-content-type-options": "nosniff" - }, - "messages": [ - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you specified.\n\nLet me start by implementing and testing the component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01Ww5ZtkNP5wnx8hcRuepwkE", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 827, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me fix the snippet syntax. In Svelte 5, snippets are defined differently:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01VEhmqcjksPib73k3R3mdHo", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 508, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me try the correct Svelte 5 snippet syntax outside of the script tag:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01J3gEY1wWKHB3xCRR3DQht7", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 521 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! The component passes all tests. Now let me submit the final implementation:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n" - }, - "providerOptions": { - "openrouter": { - "reasoning_details": [] - } - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_bdrk_01XjvMmt58Hc4NYJmYkPavp3", - "toolName": "ResultWrite", - "output": { - "type": "json", - "value": { - "success": true - } - } - } - ] - } - ] - }, - "providerMetadata": { - "openrouter": { - "provider": "Amazon Bedrock", - "reasoning_details": [], - "usage": { - "promptTokens": 1857, - "promptTokensDetails": { - "cachedTokens": 0 - }, - "completionTokens": 183, - "completionTokensDetails": { - "reasoningTokens": 0 - }, - "totalTokens": 2040, - "cost": 0.00274428 - } - } - } - } - ], - "resultWriteContent": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    \n", - "verification": { - "testName": "snippets", - "passed": true, - "numTests": 3, - "numPassed": 3, - "numFailed": 0, - "duration": 532 - } - } - ], - "metadata": { - "mcpEnabled": false, - "mcpServerUrl": null, - "mcpTransportType": null, - "timestamp": "2025-12-09T20:48:12.235Z", - "model": "openrouter/anthropic/claude-haiku-4.5", - "pricingKey": "openrouter/anthropic/claude-haiku-4.5", - "pricing": { - "inputCostPerMTok": 1, - "outputCostPerMTok": 5, - "cacheReadCostPerMTok": 0.09999999999999999 - }, - "totalCost": { - "inputCost": 0.005885, - "outputCost": 0.003775, - "cacheReadCost": 0, - "totalCost": 0.00966, - "inputTokens": 5885, - "outputTokens": 755, - "cachedInputTokens": 0 - } - } -} \ No newline at end of file diff --git a/results/result-2025-12-12-12-30-09.json b/results/result-2025-12-12-12-30-09.json deleted file mode 100644 index 05ee929..0000000 --- a/results/result-2025-12-12-12-30-09.json +++ /dev/null @@ -1,1729 +0,0 @@ -{ - "tests": [ - { - "testName": "snippets", - "prompt": "# Snippet Component Task\n\nCreate a simple Svelte 5 component that demonstrates the basic use of snippets.\n\n## Requirements:\n\n1. Create a component with a hardcoded array of 3 book titles (strings) - \"The Lord of the Rings\", \"To Kill a Mockingbird\", and \"1984\"\n2. Create a snippet called `title` that takes a book title string as a parameter\n3. The snippet should display the book title in a `` element with `data-testid=\"book-title\"`\n4. Use the `{@render ...}` syntax to render the snippet for each book title in a list\n5. Each rendered title should be wrapped in a `
  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
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      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - } - ], - "headers": { - "user-agent": "ai/5.0.108" - } - } - }, - "response": { - "id": "aitxt-E74XwjB7Z6vvElqLixUPz2L8", - "timestamp": "2025-12-12T11:30:00.904Z", - "modelId": "anthropic/claude-haiku-4.5", - "headers": { - "access-control-allow-headers": "Content-Type, Authorization, ai-gateway-auth-method, ai-gateway-protocol-version, ai-model-id, ai-language-model-id, ai-language-model-specification-version, ai-language-model-streaming, http-referer, x-title", - "access-control-allow-methods": "GET, POST, PUT, PATCH, DELETE, OPTIONS", - "access-control-allow-origin": "*", - "cache-control": "public, max-age=0, must-revalidate", - "content-encoding": "br", - "content-type": "application/json", - "date": "Fri, 12 Dec 2025 11:30:00 GMT", - "server": "Vercel", - "strict-transport-security": "max-age=63072000; includeSubDomains; preload", - "transfer-encoding": "chunked", - "vary": "rsc, next-router-state-tree, next-router-prefetch, next-router-segment-prefetch", - "x-matched-path": "/v1/ai/language-model", - "x-vercel-cache": "MISS", - "x-vercel-id": "arn1::fra1::c6fd6-1765538999297-da6342c9beed" - }, - "body": { - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", - "toolName": "TestComponent", - "input": "{\"content\":\"\\n\\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", - "toolName": "TestComponent", - "input": { - "content": "\n\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", - "toolName": "TestComponent", - "input": { - "content": "\n\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the use of snippets with the requirements you've specified. Let me implement and test it." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", - "toolName": "TestComponent", - "input": { - "content": "\n\n
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    " - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_01UhF5dBYjZf8QkCwFDmEDmV", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 856, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:2 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me check the Svelte 5 syntax for snippets. It seems the syntax needs adjustment:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", - "toolName": "TestComponent", - "input": { - "content": "\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_018qJsXizyf6btsVrVkphHAV", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": false, - "message": "0 of 0 tests failed", - "passed": 0, - "failed": 0, - "total": 0, - "duration": 531, - "error": "/Users/k/Documents/GitHub/ai-sdk-bench/outputs/snippets/Component.svelte:4:10 Unexpected token\nhttps://svelte.dev/e/js_parse_error" - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Let me try a different approach with snippet definition:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
    " - } - } - ] - }, - { - "role": "tool", - "content": [ - { - "type": "tool-result", - "toolCallId": "toolu_019JPFijcXVrNk9inFRjSYr8", - "toolName": "TestComponent", - "output": { - "type": "json", - "value": { - "success": true, - "message": "All 3 tests passed!", - "passed": 3, - "failed": 0, - "total": 3, - "duration": 523 - } - } - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "Perfect! The tests pass. Now let me submit the final component:" - }, - { - "type": "tool-call", - "toolCallId": "toolu_01BYh1Mxmbnt5ZETuE8NqnEQ", - "toolName": "ResultWrite", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n {bookTitle}\n{/snippet}\n\n
      \n {#each books as book}\n
    • \n {@render title(book)}\n
      • \n {/each}\n
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      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n", - "steps": [ - { - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the basic use of snippets with the specified requirements. Let me start by implementing and testing the component." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01M46JwgEXQhJi9GXLrWHsUJ", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n\t{bookTitle}\n{/snippet}\n\n
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      • \n
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      • \n
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      • \n
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  • ` element with `data-testid=\"book-item\"`\n\n## Example HTML structure:\n\n```html\n
      \n
    • The Lord of the Rings
      • \n
    • To Kill a Mockingbird
      • \n
    • 1984
      • \n
    \n```\n\nPlease implement this component using Svelte 5 runes.\n\n\nIMPORTANT: When you have finished implementing the component, use the ResultWrite tool to output your final Svelte component code. Only output the component code itself, no explanations or markdown formatting." - } - ] - }, - { - "role": "assistant", - "content": [ - { - "type": "text", - "text": "I'll create a Svelte 5 component that demonstrates the basic use of snippets with the specified requirements. Let me start by implementing and testing the component." - }, - { - "type": "tool-call", - "toolCallId": "toolu_01M46JwgEXQhJi9GXLrWHsUJ", - "toolName": "TestComponent", - "input": { - "content": "\n\n{#snippet title(bookTitle)}\n\t{bookTitle}\n{/snippet}\n\n
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      \n\t{#each books as book}\n\t\t
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      \n\t{#each books as book}\n\t\t
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      • \n\t{/each}\n
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      • \n\t{/each}\n
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