Live Conversational Threads

This application is designed to enhance conversation flow by intelligently identifying and managing conversational threads in real-time. The system subtly captures and organizes discussion threads to maintain context and enable a more smoother and coherent conversation, built with FastAPI backend and React frontend.

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Table of Contents

• Demo
• Project Structure
• Prerequisites
• Backend Setup
• Frontend Setup
• Running the Application
• Environment Variables
• Database Setup
• API Documentation
• Troubleshooting
• Contributing
• License

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Demo

• Live Conversational Threads Presentation (YouTube)

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Project Structure

live_conversational_threads/
├── lct_python_backend/     # Python FastAPI backend
│   ├── backend.py         # Main backend application
│   ├── db.py              # Database connection
│   ├── db_helpers.py      # Database helper functions
│   └── requirements.txt   # Backend dependencies
├── lct_app/               # React frontend application
│   ├── src/               # Source code
│   ├── package.json       # Frontend dependencies
│   └── vite.config.js     # Vite configuration
├── requirements.txt       # (duplicate of backend requirements)
└── README.md              # This file

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Prerequisites

• Python 3.8+ (Conda or venv recommended)
• Node.js 18+ and npm 9+
• PostgreSQL (for backend database)

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Backend Setup

1. Create and activate a Python environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

   Or use Conda:

   conda create -n lct_env python=3.8
   conda activate lct_env

2. Install backend dependencies:

   pip install -r lct_python_backend/requirements.txt

3. Configure environment variables:

   • Set the following environment variables in your shell or system (e.g., export on Unix, set on Windows):

     export ANTHROPIC_API_KEY=your_anthropic_api_key
     export ASSEMBLYAI_API_KEY=your_assemblyai_api_key
     export ASSEMBLYAI_WS_URL=wss://api.assemblyai.com/v2/realtime/ws?sample_rate=16000
     export PERPLEXITY_API_KEY=your_perplexity_api_key
     export GOOGLEAI_API_KEY=your_googleai_api_key
     export GCS_BUCKET_NAME=your_gcs_bucket
     export GCS_FOLDER=your_gcs_folder
     export DATABASE_URL=postgresql://user:password@localhost:5432/yourdb

   • On Windows (PowerShell):

     $env:ANTHROPIC_API_KEY="your_anthropic_api_key"
     # ...and so on for each variable

   • These must be set in your environment before starting the backend.

4. Set up the PostgreSQL database (see Database Setup).

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Frontend Setup

1. Navigate to the frontend directory:

   cd lct_app

2. Install Node.js dependencies:

   npm install

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Running the Application

1. Start the Backend Server

From the project root (with your Python environment activated and environment variables set):

cd lct_python_backend
uvicorn backend:lct_app --reload --port 8080

• The backend API will be available at http://localhost:8080

2. Start the Frontend Development Server

In a new terminal:

cd lct_app
npm run dev

• The frontend will be available at http://localhost:5173

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Environment Variables

Backend required variables:

• ANTHROPIC_API_KEY — API key for Anthropic Claude
• ASSEMBLYAI_API_KEY — API key for AssemblyAI
• ASSEMBLYAI_WS_URL — AssemblyAI websocket URL
• PERPLEXITY_API_KEY — API key for Perplexity
• GOOGLEAI_API_KEY — API key for Google GenAI
• GCS_BUCKET_NAME — Google Cloud Storage bucket name
• GCS_FOLDER — GCS folder for storing files
• DATABASE_URL — PostgreSQL connection string (e.g., postgresql://user:password@localhost:5432/yourdb)

Frontend:

• No environment variables required for local development.

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Database Setup

• You must have a running PostgreSQL instance.
• The backend expects a conversations table. Example schema:

  CREATE TABLE conversations (
      id TEXT PRIMARY KEY,
      file_name TEXT,
      no_of_nodes INTEGER,
      gcs_path TEXT,
      created_at TIMESTAMP
  );

• Adjust or extend the schema as needed for your use case.

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API Documentation

Once the backend server is running, access:

• Swagger UI: http://localhost:8080/docs
• ReDoc: http://localhost:8080/redoc

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Troubleshooting

• Database connection errors:
  • Ensure your DATABASE_URL is correct and PostgreSQL is running.
  • The required tables must exist before starting the backend.
• CORS errors:
  • The backend is configured to allow requests from http://localhost:5173.
• API key errors:
  • Double-check all required environment variables are set in your environment.
• Port conflicts:
  • Change the ports in the run commands if 8080 or 5173 are in use.

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Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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License

This project is licensed under the GNU General Public License v3.0 (GPLv3).

You are free to use, modify, and distribute this software under the terms of the GPLv3.

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Commercial Use

If you would like to use this software in a closed-source or commercial product, or if you're interested in a commercial license with different terms (e.g., without the GPL's copyleft requirements), please contact me to discuss options:

Email: [email protected] GitHub: https://github.com/aditya-adiga