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## Framework Integrations
| Framework | Description |
| ------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------- |
| [AutoGen](/documentation/frameworks/autogen/) | Framework from Microsoft building LLM applications using multiple conversational agents. |
| [Canopy](/documentation/frameworks/canopy/) | Framework from Pinecone for building RAG applications using LLMs and knowledge bases. |
| [Cheshire Cat](/documentation/frameworks/cheshire-cat/) | Framework to create personalized AI assistants using custom data. |
| [DocArray](/documentation/frameworks/docarray/) | Python library for managing data in multi-modal AI applications. |
| [DSPy](/documentation/frameworks/dspy/) | Framework for algorithmically optimizing LM prompts and weights. |
| [Feast](/documentation/frameworks/feast/) | Open-source feature store to operate production ML systems at scale as a set of features. |
| [Fifty-One](/documentation/frameworks/fifty-one/) | Toolkit for building high-quality datasets and computer vision models. |
| [Genkit](/documentation/frameworks/genkit/) | Framework to build, deploy, and monitor production-ready AI-powered apps. |
| [Haystack](/documentation/frameworks/haystack/) | LLM orchestration framework to build customizable, production-ready LLM applications. |
| [Lakechain](/documentation/frameworks/lakechain/) | Python framework for deploying document processing pipelines on AWS using infrastructure-as-code. |
| [Langchain](/documentation/frameworks/langchain/) | Python framework for building context-aware, reasoning applications using LLMs. |
| [Langchain-Go](/documentation/frameworks/langchain-go/) | Go framework for building context-aware, reasoning applications using LLMs. |
| [Langchain4j](/documentation/frameworks/langchain4j/) | Java framework for building context-aware, reasoning applications using LLMs. |
| [LlamaIndex](/documentation/frameworks/llama-index/) | A data framework for building LLM applications with modular integrations. |
| [Mem0](/documentation/frameworks/mem0/) | Self-improving memory layer for LLM applications, enabling personalized AI experiences. |
| [MemGPT](/documentation/frameworks/memgpt/) | System to build LLM agents with long term memory & custom tools |
| [Pandas-AI](/documentation/frameworks/pandas-ai/) | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language |
| [Semantic Router](/documentation/frameworks/semantic-router/) | Python library to build a decision-making layer for AI applications using vector search. |
| [Spring AI](/documentation/frameworks/spring-ai/) | Java AI framework for building with Spring design principles such as portability and modular design. |
| [Sycamore](/documentation/frameworks/sycamore/) | Document processing engine for ETL, RAG, LLM-based applications, and analytics on unstructured data. |
| [txtai](/documentation/frameworks/txtai/) | Python library for semantic search, LLM orchestration and language model workflows. |
| [Vanna AI](/documentation/frameworks/vanna-ai/) | Python RAG framework for SQL generation and querying. |
| Framework | Description |
| ------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------- |
| [AutoGen](/documentation/frameworks/autogen/) | Framework from Microsoft building LLM applications using multiple conversational agents. |
| [Canopy](/documentation/frameworks/canopy/) | Framework from Pinecone for building RAG applications using LLMs and knowledge bases. |
| [Cheshire Cat](/documentation/frameworks/cheshire-cat/) | Framework to create personalized AI assistants using custom data. |
| [DocArray](/documentation/frameworks/docarray/) | Python library for managing data in multi-modal AI applications. |
| [DSPy](/documentation/frameworks/dspy/) | Framework for algorithmically optimizing LM prompts and weights. |
| [Feast](/documentation/frameworks/feast/) | Open-source feature store to operate production ML systems at scale as a set of features. |
| [Fifty-One](/documentation/frameworks/fifty-one/) | Toolkit for building high-quality datasets and computer vision models. |
| [Genkit](/documentation/frameworks/genkit/) | Framework to build, deploy, and monitor production-ready AI-powered apps. |
| [Haystack](/documentation/frameworks/haystack/) | LLM orchestration framework to build customizable, production-ready LLM applications. |
| [Lakechain](/documentation/frameworks/lakechain/) | Python framework for deploying document processing pipelines on AWS using infrastructure-as-code. |
| [Langchain](/documentation/frameworks/langchain/) | Python framework for building context-aware, reasoning applications using LLMs. |
| [Langchain-Go](/documentation/frameworks/langchain-go/) | Go framework for building context-aware, reasoning applications using LLMs. |
| [Langchain4j](/documentation/frameworks/langchain4j/) | Java framework for building context-aware, reasoning applications using LLMs. |
| [LlamaIndex](/documentation/frameworks/llama-index/) | A data framework for building LLM applications with modular integrations. |
| [Mem0](/documentation/frameworks/mem0/) | Self-improving memory layer for LLM applications, enabling personalized AI experiences. |
| [MemGPT](/documentation/frameworks/memgpt/) | System to build LLM agents with long term memory & custom tools |
| [Neo4j GraphRAG](/documentation/frameworks/neo4j-graphrag/) | Package to build graph retrieval augmented generation (GraphRAG) applications using Neo4j and Python. |
| [Pandas-AI](/documentation/frameworks/pandas-ai/) | Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language |
| [Ragbits](/documentation/frameworks/ragbits/) | Python package that offers essential "bits" for building powerful Retrieval-Augmented Generation (RAG) applications. |
| [Semantic Router](/documentation/frameworks/semantic-router/) | Python library to build a decision-making layer for AI applications using vector search. |
| [Spring AI](/documentation/frameworks/spring-ai/) | Java AI framework for building with Spring design principles such as portability and modular design. |
| [Sycamore](/documentation/frameworks/sycamore/) | Document processing engine for ETL, RAG, LLM-based applications, and analytics on unstructured data. |
| [txtai](/documentation/frameworks/txtai/) | Python library for semantic search, LLM orchestration and language model workflows. |
| [Vanna AI](/documentation/frameworks/vanna-ai/) | Python RAG framework for SQL generation and querying. |