{"id":19027324,"url":"https://github.com/codealchemyml/graph-based-rag-system","last_synced_at":"2026-05-18T07:32:26.122Z","repository":{"id":261843485,"uuid":"885458382","full_name":"CodeAlchemyML/graph-based-rag-system","owner":"CodeAlchemyML","description":"This project involves implementing a graph-based RAG system using Langgraph and Langchain for a cybersecurity use case. 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It builds a dynamic graph from cybersecurity data, which can answer specific penetration testing-related questions.\n\n---\n**Requirements:**\n\n- Language: ![Python](https://img.shields.io/badge/-Python-3776AB?style=flat-square\u0026logo=python\u0026logoColor=white)\n- Dependency: ![Poetry](https://img.shields.io/badge/Package%20Manager-Poetry-blue?logo=poetry)\n- API: ![FastAPI](https://img.shields.io/badge/-FastAPI-009688?style=flat-square\u0026logo=fastapi\u0026logoColor=white)\n- Database: Chroma Vector Database, with ingestion support from ![MongoDB](https://img.shields.io/badge/Database-MongoDB-green?logo=mongodb)\n\n---\n**Implementation:**\n\n- *Graph Entity Design:* Defining entities (hosts, ports, services) and relationships dynamically based on the HackTheBox data and walkthroughs.\n- *Data Ingestion:* Building an ingestion pipeline to handle irregular data updates.\n- *Inference Pipeline:* Answering Cybersecurity-related queries using graph-based RAG with optimized response times.\n\n---\n**Usage:**\n\n- Setup the Python environment with Poetry.\n- Run the graph pipeline and ingestion process.\n- Query the graph for penetration testing insights.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodealchemyml%2Fgraph-based-rag-system","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcodealchemyml%2Fgraph-based-rag-system","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcodealchemyml%2Fgraph-based-rag-system/lists"}