├── .gitignore ├── PydanticAI ├── .env.example ├── .gitignore ├── README.md ├── data │ ├── invoice_query.json │ ├── product_query.json │ └── shipping_query.json ├── requirements.txt └── src │ ├── introduction.py │ └── utils │ └── markdown.py ├── README.md ├── Reasoning_Models └── Llama3.1_(8B)-GRPO.ipynb ├── arize_ai-phoenix ├── .env.example ├── README.md ├── app.py ├── chainlit.md ├── requirements.txt └── storage_mini │ ├── default__vector_store.json │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json ├── chroma+langchain ├── .env.example ├── README.md ├── app.py └── requirements.txt ├── comet-ml-opik └── README.md ├── dspy ├── .env.example ├── .gitignore ├── README.md ├── label.pdf ├── rag.ipynb └── requirements.txt ├── google ├── gemini.ipynb └── requirements.txt ├── groq ├── .env.example ├── README.md ├── app.py └── groq-test.ipynb ├── knowledge-graph-rag ├── .env.example ├── README.md ├── data │ └── paul_graham │ │ └── paul_graham_essay.txt ├── example_hotels.html ├── knowledge_graph.ipynb ├── requirements.txt └── storage │ ├── default__vector_store.json │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json ├── langfuse ├── .env.example ├── README.md ├── app.py ├── chainlit.md ├── requirements.txt └── storage_mini │ ├── default__vector_store.json │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json ├── literalai ├── .env.example ├── RAG LlamaIndex.ipynb ├── README.md └── requirements.txt ├── llama_agents ├── .env.example ├── README.md ├── agentic_rag_toolservice.ipynb ├── data │ ├── GOOG-10-Q-Q1-2023.pdf │ └── goog-10-q-q1-2024.pdf ├── requirements.txt └── storage │ ├── q1-23 │ ├── default__vector_store.json │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json │ └── q1-24 │ ├── default__vector_store.json │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json ├── llamaindex ├── .env.example ├── README.md ├── app.py ├── rag.ipynb └── requirements.txt ├── mlflow └── README.md ├── neo4j ├── .env.example ├── README.md ├── data │ └── Graph_Retrieval-Augmented_Generation_A_Survey.pdf ├── requirements.txt ├── storage_hybrid_gemini │ ├── docstore.json │ ├── graph_store.json │ ├── image__vector_store.json │ └── index_store.json └── vector_graph_rag.ipynb ├── pinecone+langchain ├── .env.example ├── README.md ├── requirements.txt ├── rerank+llm.ipynb └── upsert.ipynb ├── property-store-graph-rag ├── .env.example ├── README.md ├── data │ └── Graph_Retrieval-Augmented_Generation_A_Survey.pdf ├── pg-storage │ ├── default__vector_store.json │ ├── docstore.json │ ├── image__vector_store.json │ └── index_store.json ├── property-graph-rag.ipynb └── requirements.txt ├── qdrant+langchain ├── README.md └── portfolio_manager │ ├── .env.example │ ├── app.py │ ├── data_insertion.ipynb │ ├── earning_report_analysis.py 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