Multi-Tenant AI Customer Support Chatbot

A sophisticated AI-powered customer support chatbot system that allows different businesses to have their own isolated chatbot with custom knowledge bases and FAQ data.

Features

• Multi-Tenant Architecture: Each business has its own isolated chatbot
• GPT-4 Integration: Powered by OpenAI's GPT-4 for intelligent responses
• Knowledge Base Management: Upload documents (PDF, DOC, DOCX, TXT, CSV, XLSX)
• FAQ Management: Upload FAQ spreadsheets or add individual Q&A pairs
• Multiple Integration Channels: Slack, WhatsApp, and webhook integrations
• Vector Embedding: Efficient semantic search with FAISS vector database

Quick Start

Prerequisites

• Python 3.11+
• OpenAI API Key
• PostgreSQL (optional, SQLite works for development)

Installation

1. Clone this repository:

   git clone <repository-url>
   cd multi-tenant-chatbot
   

2. Install dependencies:

   pip install -r requirements.txt
   

3. Run the setup script:

   python setup.py
   

4. Edit the .env file with your OpenAI API key and other settings:

   OPENAI_API_KEY=your-key-here
   

5. Start the application:

   uvicorn app.main:app --reload
   

The API will be available at http://localhost:8000

Project Structure

multi_tenant_chatbot/
├── app/                    # Main application package
│   ├── auth/               # Authentication models
│   ├── tenants/            # Tenant management models
│   ├── knowledge_base/     # Document processing
│   ├── chatbot/            # Chatbot engine
│   ├── integrations/       # Platform integrations
│   ├── database.py         # Database connection setup
│   ├── config.py           # Configuration settings
│   └── main.py             # Application entry point
├── uploads/                # Uploaded document storage
├── vector_db/              # Vector embeddings storage
├── temp/                   # Temporary file storage
├── requirements.txt        # Python dependencies
├── setup.py                # Setup script
└── .env                    # Environment variables

API Endpoints

The API includes the following endpoints:

• Authentication: /auth/token
• Tenant Management: /tenants/
• Knowledge Base: /knowledge-base/
• Chatbot: /chatbot/chat
• Integrations:
  • Slack: /integrations/slack/events
  • WhatsApp: /integrations/whatsapp/webhook
  • Webhook: /integrations/webhook/chat

Using the Chatbot

1. Create a tenant with an API key
2. Upload knowledge base documents and FAQs
3. Send messages to the chatbot API:

import requests

response = requests.post(
    "http://localhost:8000/chatbot/chat",
    headers={"X-API-Key": "your-tenant-api-key"},
    json={
        "message": "Hello, I need help with my order",
        "user_identifier": "customer123"
    }
)

print(response.json())

Environment Variables

Variable	Description	Default
DATABASE_URL	Database connection string	sqlite:///./chatbot.db
JWT_SECRET_KEY	Secret key for JWT tokens	your-secret-key
OPENAI_API_KEY	OpenAI API key	None
VECTOR_DB_PATH	Path to vector database	./vector_db
SLACK_SIGNING_SECRET	Slack signing secret	None
SLACK_BOT_TOKEN	Slack bot token	None
TWILIO_ACCOUNT_SID	Twilio account SID	None
TWILIO_AUTH_TOKEN	Twilio auth token	None

License

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

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.# botbackend