The NavShiksha Chatbot is an intelligent conversational AI designed to assist users by providing relevant and accurate responses based on a knowledge base. It leverages state-of-the-art AI frameworks such as LangChain and FAISS to implement a Retrieval-Augmented Generation (RAG) approach for enhanced conversational capabilities.
The chatbot is built to integrate seamlessly with the NavShiksha website, offering a user-friendly and efficient solution for answering queries and improving user engagement.
- Retrieval-Augmented Generation (RAG): Combines pre-trained language models with a custom knowledge base for precise and contextually relevant responses.
- FAISS Similarity Index: Efficient and scalable vector similarity search to retrieve the most relevant knowledge snippets.
- LangChain Integration: Enables dynamic chaining of prompts and responses for fluid and context-aware conversations.
- Knowledge Base Support: Easily customizable knowledge base that can be updated as per requirements.
- Web Integration: Designed for seamless embedding into the NavShiksha website.
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Knowledge Base Creation:
- Information is processed and embedded into vector representations using a pre-trained language model.
- FAISS (Facebook AI Similarity Search) is used to index and retrieve the closest matching vectors based on user queries.
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RAG Workflow:
- The chatbot takes user input and retrieves relevant context from the knowledge base.
- A pre-trained language model generates a response based on the retrieved information.
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LangChain:
- Manages prompt engineering and integrates retrieval and generation processes.
- Python 3.8 or higher
- pip (Python package manager)
- A pre-trained language model (e.g., OpenAI GPT, HuggingFace Transformers)
- Clone the repository:
git clone https://github.com/your-username/navshiksha-chatbot.git cd navshiksha-chatbot