Friday

Friday is a personalized AI assistant designed to help you manage tasks, access information, generate content, and interact with your computer environment through a conversational interface. Built with Python and Flask, it leverages powerful AI models and integrates various tools to provide a comprehensive support system tailored to your needs.

✨ Features

• Conversational AI: Interact with Friday through a responsive, web-based chat interface.
• Dynamic UI: A dark-themed, resizable interface with dedicated panels for chat, content, history, notifications, and scheduling.
• AI Model & Tool Selection:
  • Choose from various available AI models with different capabilities and rate limits.
  • Select specific tools for the AI to use or let it auto-select based on the task.
  • Control the AI's "thinking budget" for models that support dynamic thinking.
• Tool Integration: Access various capabilities via AI-driven tool calls:
  • Web Fetching: Get content from given website URLs, rendered as clean Markdown.
  • Deep Research: Conduct in-depth, structured research on topics, visualizing the process (topic tree, search steps, fetched URLs) and generating a comprehensive report.
  • Reminders & Scheduling: Set recurring or one-time reminders and manage your daily/weekly schedule using a calendar and drag-and-drop TODO lists.
  • Computer Access: Execute commands, manage files (create, delete, read, write), run background processes, and link local files from a sandboxed environment.
  • Imagen: Generate or edit images based on text prompts, optionally using reference images.
• File Handling: Upload files (images, videos, text, PDF) via drag-and-drop or file input, display previews, and link/view them in the content panel.
• Code Interaction: Display code blocks with syntax highlighting and copy-to-clipboard functionality.
• Grounding & Sources: View sources and relevant information linked directly within AI responses when using supported models and tools.
• Notifications: Receive important notifications in a dedicated panel, including new emails (requires Gmail setup).
• Persistent Chat History: Your conversations are saved, organized into a hierarchical tree structure with branching capabilities.
• Keyboard Shortcuts: Quickly navigate the UI, toggle tools, resize panels, and manage thinking budget using customizable keyboard shortcuts.

🚀 Setup

Follow these steps to get Friday up and running on your local machine.

Prerequisites

• Python 3.12+
• Git

1. Clone the Repository

First, clone the project repository to your local machine:

git clone https://github.com/SohamTilekar/fridayv2 # Replace with your repository URL
cd fridayv2

2. Set up a Virtual Environment

It's highly recommended to use a virtual environment to manage dependencies:

python -m venv venv
# On Windows
.\venv\Scripts\activate
# On macOS/Linux
source ./venv/bin/activate

3. Install Dependencies

Install the required Python packages using the generated requirements.txt file:

pip install -r requirements.txt

4. Configuration

Copy the example configuration file and fill in your API keys and preferences.

cp src/config-example.py src/config.py

Now, edit src/config.py and update the following:

• GOOGLE_API: Get your API key from the Google AI Studio or Google Cloud. This is required.
• FIRECRAWL_APIS: Configure your Firecrawl API keys. If you're using the hosted service, you might only need one key. If self-hosting or using multiple keys, list them here as [(RPM_LIMIT, "YOUR_API_KEY"), ...]. RPM_LIMIT can be None if you don't know or want to enforce a limit per key. If you don't have any Firecrawl keys, you can leave it as [(None, None)], but web fetching and deep research will not work.
• FIRECRAWL_ENDPOINT: Set this to the URL of your self-hosted Firecrawl instance (e.g., "http://localhost:3000"). Use None for the default hosted service (firecrawl.dev).
• AI_DIR: Specify a directory where Friday will store data (like chat history, notifications, reminders, and the computer sandbox). This should be an absolute path or a path relative to where you run main.py. Make sure this directory exists or Friday has permissions to create it.
• USR_NAME: Your name, for personalization (e.g., "LastName FirstName").
• ABOUT_YOU: A multi-line string describing yourself for the AI to use for personalization. You can include your profession, age, country, interests, etc.
• Review other settings like MAX_RETRIES, RETRY_DELAY, and model configurations (Models, model_RPM_map, etc.) and adjust if needed.

Important: After setting your GOOGLE_API, remove the line raise AssertionError("Set Your Google API first") at the end of config.py.

5. Google OAuth Credentials (Optional - for Gmail)

If you want to enable Gmail notification checking, you need to set up Google OAuth credentials.

1. Go to the Google Cloud Console: https://console.cloud.google.com/
2. Create a new project or select an existing one.
3. Enable the Gmail API for your project.
4. Go to "APIs & Services" > "Credentials".
5. Configure the OAuth Consent Screen (set it to "External" if you're not part of a Google Workspace organization, you'll likely need to add yourself as a test user).
6. Create OAuth client ID credentials. Choose "Desktop app" as the application type.
7. Download the credentials.json file.
8. Place the downloaded credentials.json file in the fridayv2/src/ directory.

The first time you run Friday with Gmail checking enabled, it will open a browser window asking you to authorize the application. After authorization, a token.json file will be automatically created in the AI_DIR you specified, storing your credentials for future use.

▶️ Running the Application

Once configured, ensure your virtual environment is active and run the Flask application:

python src/main.py

The application should start and be accessible in your web browser at http://127.0.0.1:5000.

The terminal where you ran the command will show logs from the server and AI interactions.

📂 Project Structure

• src/: Contains the main Python source files.
  • main.py: The main Flask application and SocketIO server. Handles chat logic, AI interaction, and tool calling.
  • config.py: Your project configuration (API keys, paths, settings).
  • config-example.py: Example configuration file.
  • global_shares.py: Provides a way to share objects like socketio and the genai.Client instance across modules without circular imports.
  • lschedule.py: Handles the local task/schedule management logic.
  • mail.py: Integrates with the Gmail API for checking emails and generating notifications.
  • notification.py: Defines the notification classes and manages the notification list.
  • prompt.py: Contains the system instructions and prompts used by the AI models.
  • utils.py: Utility functions, including retry decorators and API wrappers (Firecrawl, DuckDuckGo Search).
  • tools/: Contains modules for specific AI tools.
    • __init__.py: Defines the available tools and selector functions.
    • deepresearch.py: Implements the deep research tool.
    • imagen.py: Implements the image generation tool.
    • reminder.py: Implements the reminder tool.
    • space.py: Implements the computer sandbox tools.
    • webfetch.py: Implements the web fetching tool.
• static/: Static files for the web interface (CSS, JS, images).
  • style.css: Main CSS for the chat interface and panels.
  • schedule.css: CSS specifically for the schedule/calendar view.
  • main.js: Main JavaScript for chat interaction, file handling, panel management, tool/model selection, and keyboard shortcuts.
  • schedule.js: JavaScript for the schedule/calendar and TODO list functionality.
• templates/: HTML templates for the web interface.
  • index.html: The main HTML file for the chat interface.

🤝 Contributing

Contributions are welcome! Please feel free to open issues or submit pull requests.

📄 License

This project is licensed under the MIT License. See the LICENSE file for details.