GH Repository · NirDiamant
Controllable-RAG-Agent
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
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genaidockerpythonJupyter Notebookopenailanggraphagent-applangchainragllmagentllmsadvanced-rag
A GitHub repository by NirDiamant implementing an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses graph-based algorithms, built with LangChain and LangGraph, and is written in Python with Jupyter Notebooks.
Use it when you need a controllable, graph-structured RAG agent for complex question answering rather than a simple retrieval pipeline.
Use it to
- Study an advanced graph-based RAG implementation
- Build a controllable RAG agent with LangGraph
- Adapt the pipeline to your own question-answering data
- Run the notebooks locally via the provided Docker toolchain
For Python developers building LLM-based RAG applications
- Role
- agent-app
- Language
- Jupyter Notebook
- Licence
- Apache-2.0
- Forks
- 268
- Last push
- 2026-09-15
topicsragagentlanggraphllmpythonquestion-answering