jiangxinke/Agentic-RAG-R1

Agentic RAG R1 Framework via Reinforcement Learning

54
/ 100
Established

This framework helps AI/ML researchers and developers enhance the reasoning and search capabilities of their large language models (LLMs). By training a base LLM with reinforcement learning, you can feed in complex questions and external knowledge bases to get back more accurate and contextually rich answers. It's designed for those building advanced AI applications that require autonomous decision-making and deep information retrieval.

393 stars.

Use this if you are developing an AI application where a base language model needs to perform complex searches and generate highly accurate, fact-checked responses by autonomously deciding what information to retrieve and how to use it.

Not ideal if you are a business user looking for a ready-to-use chatbot or a simple RAG solution without extensive AI model development and training.

AI Development Natural Language Processing Reinforcement Learning Knowledge Retrieval LLM Fine-tuning
No Package No Dependents
Maintenance 10 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 18 / 25

How are scores calculated?

Stars

393

Forks

46

Language

Python

License

Apache-2.0

Last pushed

Feb 16, 2026

Commits (30d)

0

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