junfanz1/Cognito-LangGraph-RAG-Chatbot
This project implements an advanced Retrieval Augmented Generation (RAG) workflow to enhance question-answering accuracy and reduce LLM hallucinations. It leverages LangGraph to create a stateful, multi-step process that includes document retrieval, relevance grading, and web search fallback.
This project creates a smart chatbot that answers user questions based on a collection of documents or web searches. You provide the bot with natural language questions and a list of URLs containing relevant information. It then delivers accurate, contextually relevant answers, even for complex queries, by intelligently sifting through information and refining its responses. This tool is ideal for anyone who needs to quickly get reliable answers from extensive documentation or online resources.
No commits in the last 6 months.
Use this if you need to build a documentation bot or a sophisticated Q&A system that minimizes incorrect or 'made-up' answers from AI and provides reliable information based on specified sources.
Not ideal if you're looking for a simple, out-of-the-box chatbot for casual conversation or if your use case doesn't require grounding answers in specific documentation.
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Language
Python
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Last pushed
Mar 16, 2025
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