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Langgraph Rag Agentic App

This is a LangChain + LangGraph + FastAPI-based RAG (Retrieval-Augmented Generation) app that lets you upload a set of URLs, stores their content into a vector database (Astra DB), and intelligently answers questions by choosing between searching Wikipedia or your uploaded content.

Overview

I built a production-ready LangGraph app that allows users to upload URLs, extract and embed their content, and dynamically answer questions using either a vector database or Wikipedia. The system intelligently routes queries using an LLM and serves the entire workflow via a FastAPI backend, fully containerized for deployment.

My Role & Contributions

Tech Stack

Python FastAPI LangGraph LangChain Groq Astra DB: UV WikiPedia API Docker

Implementation Details

  • Results and Feedback Loop: If the execution succeeds, the results are returned to the user. If not, the process loops intelligently until a working query is created or it provides a helpful error message.
  • Swagger UI 1
    View on GitHub