The Document Chat API is a powerful tool that allows users to upload documents and chat with them, integrating directly with a SQL database to fetch relevant data for answering questions. This API uses advanced AI techniques to parse and understand both the document contents and database records to provide comprehensive answers.

• Document Interaction: Users can upload documents and ask questions based on the content.
• SQL Database Integration: Connects to a SQL database to use stored data in answering user queries.
• Flexible Deployment: Includes a Dockerfile for containerized deployment.

• Docker installed on your machine (optional)
• Python 3.8 or higher if running locally

1. Clone the repository:

git clone https://github.com/abdulzain6/Document-Chat-API.git
cd Document-Chat-API

2. Build and run the Docker container:

docker build -t document-chat-api .
docker run -p 8000:8000 document-chat-api

1. Install the required Python packages:

pip install -r requirements.txt

Configure the API by setting the following environment variables:

OPENAI_API_KEY=your_openai_api_key_here
DB_HOST=your_database_host
DB_USER=your_database_user
DB_PASSWORD=your_database_password
DB_NAME=your_database_name
DB_TABLE_NAMES=comma_separated_list_of_table_names

Start the API server (if not using Docker):

python api.py

Users can now upload documents and interact via the API endpoints to ask questions and receive answers based on the uploaded documents and connected SQL database data.

Contributions are highly encouraged. Please fork this repository, make your changes, and submit a pull request.