| AutoGen |
Framework from Microsoft building LLM applications using multiple conversational agents. |
| Camel |
Framework to build and use LLM-based agents for real-world task solving |
| Canopy |
Framework from Pinecone for building RAG applications using LLMs and knowledge bases. |
| Cheshire Cat |
Framework to create personalized AI assistants using custom data. |
| CrewAI |
CrewAI is a framework to build automated workflows using multiple AI agents that perform complex tasks. |
| Dagster |
Python framework for data orchestration with integrated lineage, observability. |
| DeepEval |
Python framework for testing large language model systems. |
| DocArray |
Python library for managing data in multi-modal AI applications. |
| DSPy |
Framework for algorithmically optimizing LM prompts and weights. |
| dsRAG |
High-performance Python retrieval engine for unstructured data. |
| Dynamiq |
Dynamiq is all-in-one Gen AI framework, designed to streamline the development of AI-powered applications. |
| Feast |
Open-source feature store to operate production ML systems at scale as a set of features. |
| Fifty-One |
Toolkit for building high-quality datasets and computer vision models. |
| Genkit |
Framework to build, deploy, and monitor production-ready AI-powered apps. |
| Haystack |
LLM orchestration framework to build customizable, production-ready LLM applications. |
| HoneyHive |
AI observability and evaluation platform that provides tracing and monitoring tools for GenAI pipelines. |
| Lakechain |
Python framework for deploying document processing pipelines on AWS using infrastructure-as-code. |
| Langchain |
Python framework for building context-aware, reasoning applications using LLMs. |
| Langchain-Go |
Go framework for building context-aware, reasoning applications using LLMs. |
| Langchain4j |
Java framework for building context-aware, reasoning applications using LLMs. |
| LangGraph |
Python, Javascript libraries for building stateful, multi-actor applications. |
| LlamaIndex |
A data framework for building LLM applications with modular integrations. |
| Mastra |
Typescript framework to build AI applications and features quickly. |
| Mirror Security |
Python framework for vector encryption and access control. |
| Mem0 |
Self-improving memory layer for LLM applications, enabling personalized AI experiences. |
| Neo4j GraphRAG |
Package to build graph retrieval augmented generation (GraphRAG) applications using Neo4j and Python. |
| NLWeb |
A framework to turn websites into chat-ready data using schema.org and associated data formats. |
| OpenAI Agents |
Python framework for managing multiple AI agents that can work together. |
| Pandas-AI |
Python library to query/visualize your data (CSV, XLSX, PostgreSQL, etc.) in natural language |
| Ragbits |
Python package that offers essential "bits" for building powerful Retrieval-Augmented Generation (RAG) applications. |
| Rig-rs |
Rust library for building scalable, modular, and ergonomic LLM-powered applications. |
| Semantic Router |
Python library to build a decision-making layer for AI applications using vector search. |
| SmolAgents |
Barebones library for agents. Agents write python code to call tools and orchestrate other agent. |
| Solon |
A lightweight, high-performance Java enterprise framework |
| Spring AI |
Java AI framework for building with Spring design principles such as portability and modular design. |
| Superduper |
Framework for building flexible, compositional AI apps which may be applied directly to databases. |
| Sycamore |
Document processing engine for ETL, RAG, LLM-based applications, and analytics on unstructured data. |
| Testcontainers |
Framework for providing throwaway, lightweight instances of systems for testing |
| txtai |
Python library for semantic search, LLM orchestration and language model workflows. |
| Vanna AI |
Python RAG framework for SQL generation and querying. |
