---
title: Frameworks 
weight: 20
---

## 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.                                     |
| [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.                |
| [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. |
| [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.                                                |