Database Interaction and Chat Application

This application is built using FastAPI and enables users to connect to both SQL and NoSQL databases, perform queries, and interact through a chat interface. It leverages LangFlow components for database interactions and response generation.

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Project Setup and Installation

Pre-requisites

Before starting, ensure the following are in place:

• Python Version: 3.10 or higher
• Docker: Make sure Docker is installed and running on your server machine
• Docker Compose: Ensure Docker Compose is installed for building and running the containers

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Installation and Setup

Step 1: Clone the Repository

Start by cloning this repository to your server using the following command:

git clone https://github.com/MuhammadAdil-Developer/langflow-chatbot
cd langflow-chat

Step 2: Run with Docker Compose

Option 1: Run in Attached Mode (with logs)

docker-compose up --build

This command will:

• Build and start container
• Show real-time logs in your terminal
• Useful for initial testing and debugging

Option 2: Run in Detached Mode (background)

docker-compose up -d --build

This will:

• Build and start container in the background
• Allow continued use of your terminal
• Containers run in the background

Step 3: Managing Your Containers

View container status:

docker-compose ps

Check logs in detached mode:

docker-compose logs -f

Stop containers:

docker-compose stop

Remove containers (preserves data):

docker-compose down

Restart services:

docker-compose restart

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Accessing the Application

After the server starts, you can access the application through:

• Main Application: http://your-seerver-ip:8080/chat
• API Documentation: http://your-seerver-ip/docs

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API Endpoints

1. Connect to Database

• Endpoint: POST /connect-db
• Description: Connects to a specified SQL or NoSQL database
• Request Body:

{
  "question": "Your question here"
}

2. Chat Interface

• Endpoint: POST /chat
• Description: Sends a question to the connected database and retrieves a response
• Request Body:

{
  "question": "Your question here",
  "db_name": "Database name",
  "database_uri": "Database URI",
  "collection_name": "Collection name",
  "db_type": "sql or nosql"
}

3. Get Chat History

• Endpoint: GET /chat
• Description: Retrieves the chat history for a user session

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Error Handling

The application includes error handling for various scenarios, including:

• Invalid database URIs
• Connection failures
• Query execution errors

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Future Enhancements

• Add support for additional database types
• Improve chat interface with more conversational AI features
• Implement authentication for secure API access

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Troubleshooting

If you encounter any issues during setup or while running the project, check the following:

Docker Compose Build Errors:

• Ensure Docker is properly installed and running
• Check for any missing dependencies
• Verify network connectivity for database connections
• Ensure required ports are available