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sam-2610/README.md

Hi, I'm Satyam

AI/ML engineering student from Ranchi, India. I build RAG systems and LLM agents, and I test them with small evaluation sets so I know what works.

Projects

Tech: Python, PyTorch, LangChain, LangGraph, ChromaDB, Pinecone, FastAPI, PostgreSQL, SQL, Docker, Streamlit

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  1. agentic-rag agentic-rag Public

    Multi-agent RAG system built with LangGraph. Routes each message to chat, cited document Q&A, or a restricted Python agent that writes, runs and fixes code to calculate and chart numbers. FastAPI +…

    Python 6

  2. Fast-Api Fast-Api Public

    Backend API for a social media app built with FastAPI and PostgreSQL. JWT login, posts (create, read, update, delete), user accounts and a vote/like system, with interactive docs at /docs.

    Python

  3. medical-chatbot medical-chatbot Public

    RAG medical chatbot that answers health questions only from indexed PDF guides, with page-level source citations. Refuses out-of-scope questions instead of guessing. Not medical advice.

    Python

  4. LocalText2SQL LocalText2SQL Public

    QLoRA fine-tuning of Llama-3.2-3B for text-to-SQL, scored by running the SQL. Execution accuracy 53% to 69% on 150 held-out questions.

    Python