GitHub - chayansraj/Agentic-RAG-with-evalution-Langchain: Retrieval systems are fundamental to many AI applications, efficiently identifying relevant information from large datasets.

Advanced Agentic RAG.

Retrieval systems are fundamental to many AI applications, efficiently identifying relevant information from large datasets.

RAG evalution done with benchmarking RAG outputs with different embeddings, chunks, reader LLM, Eval LLM.

Name		Name	Last commit message	Last commit date
Latest commit History 163 Commits
__pycache__		__pycache__
rag		rag
vector database		vector database
.gitignore		.gitignore
README.md		README.md
ReAct agent.ipynb		ReAct agent.ipynb
agent with memory.ipynb		agent with memory.ipynb
agent_with_checkpoints.png		agent_with_checkpoints.png
app_deployment.ipynb		app_deployment.ipynb
chain.ipynb		chain.ipynb
initial_conf.ipynb		initial_conf.ipynb
llm_summarization.ipynb		llm_summarization.ipynb
requirements.txt		requirements.txt
router.ipynb		router.ipynb
state_schema_and_reducer.ipynb		state_schema_and_reducer.ipynb
trim_filter_messages.ipynb		trim_filter_messages.ipynb
utils.py		utils.py

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