How to build an LLM PROJECT – Q&A System Based on Google Gemini AI, LangChain, and your CSV
How to build the LLM Project Q&A system using Google Gemini AI, LangChain, and CSV files, follow these steps:
1. Set Up Environment
- Install required libraries:
Streamlit,LangChain,FAISS,Google Generative AI API. - Ensure CSV data is ready for use.
2. Data Preparation
- Prepare your CSV file containing FAQ data (questions and answers) for vectorization.
3. LangChain Setup
- Use LangChain to create a retrieval-based pipeline, setting up a vector store with FAISS for question matching.
4. Integrate Google Gemini AI
- Set up Google Generative AI for answering non-exact matches or context-rich queries.
5. Build UI with Streamlit
- Develop a simple user interface with Streamlit to display responses.
6. Deploy
- Test and deploy the system on a server or local environment.
This allows businesses to automate customer service with a sophisticated Q&A bot.
For a complete solution, refer to LLM Project – Q&A System.omplete solution, refer to LLM Project – Q&A System.
