mburaksayici/RAG-Boilerplate

RAG boilerplate with semantic/propositional chunking, hybrid search (BM25 + dense), LLM reranking, query enhancement agents, CrewAI orchestration, Qdrant vector search, Redis/Mongo sessioning, Celery ingestion pipeline, Gradio UI, and an evaluation suite (Hit-Rate, MRR, hybrid configs).

37
/ 100
Emerging

This system helps developers build sophisticated AI applications that can 'chat' with custom data. It takes raw text documents, processes them using advanced chunking and search techniques, and allows users to ask questions and receive answers based on the content. The target user is a software developer or AI engineer looking to create conversational AI experiences over domain-specific information.

Use this if you are an AI developer or engineer building a Retrieval Augmented Generation (RAG) system and need a robust, pre-configured framework for handling data ingestion, search, conversation management, and evaluation.

Not ideal if you are a non-technical end-user simply looking for an off-the-shelf chatbot for your data without any development or customization.

AI-development conversational-AI RAG-systems information-retrieval LLM-applications
No License No Package No Dependents
Maintenance 6 / 25
Adoption 8 / 25
Maturity 5 / 25
Community 18 / 25

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Stars

65

Forks

14

Language

Python

License

Last pushed

Nov 18, 2025

Commits (30d)

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