Secure attachments#95
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Stop flattening user content to text in the enclave. Convert OpenAI-format content parts (text / image_url / file) into LangChain v1 standard content blocks so images and PDFs reach the provider natively instead of being dropped. Text-only content still collapses to a plain string. No new dependencies: the pinned langchain-* versions already translate standard image/file blocks to each provider's native API.
… attachments in request hash - validate_attachments(): reject image/PDF parts when the target model's LangChain profile explicitly lacks support (fails open for unknown models), and enforce a 30 MB inline attachment cap. Wired into create_chat_completion so it covers both the direct and OHTTP-inner paths. - Request hashing now canonicalizes multimodal user content, replacing inline base64 with a sha256 digest so the signed request commits to the exact attachment bytes without bloating the hashed payload.
…#94) * image gen format fixes (#91) * testing image format fix * review fixes * lint fix * Minimize attachment handling: keep provider-native image pass-through Revert the bespoke image-conversion path in convert_messages to main's raw pass-through (text/image parts already convert correctly to every provider's native API, so images keep working untouched). Only file/PDF parts are rewritten to LangChain standard file blocks, since Anthropic needs a 'document' block and rejects OpenAI's raw file shape. Capability gating, the per-request size cap, and request-hash canonicalization are retained. Drop the design doc. --------- Co-authored-by: Aniket Dixit <47004499+dixitaniket@users.noreply.github.com> Co-authored-by: Claude <noreply@anthropic.com>
…l-hrY9f # Conflicts: # tee_gateway/controllers/chat_controller.py # tee_gateway/llm_backend.py # tee_gateway/test/test_tee_core.py
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