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This is a FastAPI-based chat application that combines document management and role assignment features, utilizing the latest language model technology to provide intelligent responses.

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AnyChat

Welcome to AnyChat! This is a FastAPI-based chat application that combines document management and role assignment features, utilizing the latest language model technology to provide intelligent responses.

Features

  • Authentication and Authorization: Secure authentication and authorization using OAuth2 and JWT.
  • Chat Functionality: Real-time message handling with intelligent responses.
  • Document Management: Support for adding, updating, deleting, and listing documents with permission control.
  • Role Assignment: Flexible role and permission management system, supporting custom roles and permissions.

TODO List

Infrastructure

  • Design and implement complete database models (using SQLAlchemy ORM)
  • Establish database migration system (Alembic)
  • Implement containerized deployment (Docker & Docker Compose)
  • Set up CI/CD pipeline
  • Create configurations for development, testing, and production environments

User Management & Authentication

  • Complete user registration and login system
  • Password reset functionality
  • Email verification
  • OAuth third-party login integration (Google, GitHub, etc.)
  • JWT token refresh mechanism
  • Multi-factor authentication (optional)

Permission Management

  • Convert in-memory permission storage to database storage
  • Implement role-based access control (RBAC)
  • Fine-grained permission management (for documents and features)
  • Permission audit logging
  • User groups and team management

Document Management

  • Document version control
  • Document classification and tagging system
  • Multi-format document support (PDF, DOCX, Markdown, etc.)
  • Batch import/export functionality
  • Document sharing and collaboration features
  • Document permission management

RAG Engine Enhancements

  • Query preprocessing and rewriting
  • Hybrid retrieval (keywords + semantic)
  • Relevance ranking algorithm optimization
  • Dynamic context length adjustment
  • LLM prompt optimization
  • Citation accuracy verification
  • Enhanced multilingual support

Chat Functionality

  • Chat history persistence
  • Conversation context management
  • Message grouping and search
  • Conversation export functionality
  • Inline citations and annotations
  • File upload/sharing within chat

Monitoring & Analytics

  • User query logging system
  • Performance metrics dashboard
  • Usage statistics and reporting
  • User feedback collection mechanism
  • Answer quality evaluation
  • API usage monitoring

Frontend Interface

  • Responsive chat UI
  • Document management dashboard
  • Admin control panel
  • User settings page
  • Multi-theme support
  • Mobile-friendly design

Security Enhancements

  • API rate limiting
  • Input validation and sanitization
  • SQL injection protection
  • CSRF protection
  • Data encryption
  • Secure dependency management and auditing

Advanced Features

  • Multi-model support (switching between different LLMs)
  • Knowledge base auto-updates
  • Custom plugin system
  • API integration interface
  • Scheduled tasks and automation
  • Asynchronous processing for long-running tasks

Performance Optimization

  • Implement caching layer
  • Database index optimization
  • Vector retrieval performance tuning
  • Horizontal scaling support
  • Non-blocking processing for large documents
  • Batch processing for vector operations

Documentation & Support

  • API documentation (using Swagger/OpenAPI)
  • User manual
  • Developer documentation
  • Contribution guidelines
  • Examples and tutorials
  • Frequently asked questions

Getting Started

Environment Setup

  1. Clone the repository:

    git clone https://github.com/yourusername/anychat.git
    cd anychat
  2. Create and activate a virtual environment:

    python -m venv venv
    source venv/bin/activate  # For Windows use `venv\Scripts\activate`
  3. Install dependencies:

    pip install -r requirements.txt
  4. Configure environment variables: Create a .env file and add the following content:

    SECRET_KEY=your_secret_key
    ALGORITHM=HS256
    DB_TYPE=sqlite
    DB_CONNECTION=sqlite:///./app.db
    VECTOR_DB_TYPE=qdrant
    VECTOR_DB_URL=http://localhost:6333

Running the Application

  1. Start the application:

    uvicorn main:app --reload
  2. Open your browser and visit http://127.0.0.1:8000/docs to view the API documentation.

Testing

We provide detailed testing documentation. Please refer to TESTING.md for information on how to run and write test cases.

Contributing

We welcome contributions of any kind! Please read CONTRIBUTING.md for more information.

License

This project is open-sourced under the Apache 2.0 License.

Contact Us

If you have any questions or suggestions, please reach out to us via issues.

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This is a FastAPI-based chat application that combines document management and role assignment features, utilizing the latest language model technology to provide intelligent responses.

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