Welcome to the Banking FAQ Assistant repository! This project demonstrates how to build a scalable, RAG-powered conversational AI using LangDB.ai and LangChain. Perfect for creating intelligent banking chatbots that can answer questions about loans, interest rates, and general banking services.
- RAG-Powered Responses: Leverages Retrieval-Augmented Generation for accurate banking information
- Seamless LangDB.ai Integration: Uses LangDB.ai's optimized API endpoints for LLM interactions
- Streamlit UI: Clean and responsive chat interface
- Conversation Memory: Maintains context throughout the chat session
- Advanced AI Observability: Leverage AI analytics and operational visibility through LangDB.ai
- Free Starter Credit: Begin with $10 free credit from LangDB.ai!
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Clone the Repository:
git clone https://github.com./langdb/langdb-samples.git cd langdb-samples
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Set Up Your Environment:
conda create -n banking-bot python=3.10 conda activate banking-bot pip install -r requirements.txt
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Configure Environment Variables:
# For Windows: set LANGDB_API_KEY=your-langdb-api-key # For macOS/Linux: export LANGDB_API_KEY=your-langdb-api-key
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Run the Application:
streamlit run main.py
examples/
└── langchain/
└── langchain-rag-bot/
├── main.py # Main application file
├── requirements.txt # Project dependencies
└── README.md # Documentation
Update the following constants in main.py
:
LANGDB_API_URL = "https://api.us-east-1.langdb.ai/your-project-id/v1"
- Start the application using Streamlit
- Enter banking-related questions in the chat interface
- Receive AI-powered responses based on the banking context
- The conversation history is maintained throughout the session
To begin using this chatbot, check out our Blog for detailed tutorials and best practices. Don't forget to claim your $10 free credit from LangDB.ai to experiment with these features!
Contributions are welcome! Please feel free to submit a Pull Request.
This project is licensed under the MIT License.
Build smarter banking interactions with AI! 🏦 🤖