Open-Source AI Agent Frameworks

AstrBot brings AI assistants into messaging apps such as Telegram, Discord, Slack, QQ and WeCom. It's an open source platform under AGPL-3.0 for people building personal companions, customer support bots or team automation. You can run it on your own computer or server, including through Docker, or use its desktop app for browser-style chat.

TEN Framework is a self-hosted framework for developers building voice AI agents and multimodal conversational apps. It focuses on low-latency, real-time conversations and supports both RTC and WebSocket connections. You can run its agent examples locally with Docker or deploy them on your own server.

Cheshire Cat is a self-hosted Python framework for people learning how AI agents work or building custom assistants for research and creative projects. It pairs a local web chat interface with an API, so you can test an agent in conversation and use it inside another application. It's open source under GPL-3.0.

Agent S is an open-source AI agent framework that controls ordinary desktop and web applications through the screen, mouse and keyboard. It runs on macOS, Windows and Linux and is aimed at developers, computer-use researchers and people building automation for their own desktops. You describe the task in natural language; the agent clicks, types and scrolls without requiring an API integration or a separate script for each application.

AG2 is an open-source Python framework for developers and researchers building systems where AI agents share work. The code uses the Apache 2.0 license.

LangChain is an MIT-licensed open-source framework for developers building AI agents and applications powered by LLMs. It provides a shared interface for models, tools and data connections, so developers can change providers or test workflows without rebuilding the whole application.

Google ADK is an open-source AI agent framework for developers building applications that carry out multi-step tasks. You can run agents locally in Docker or on your own infrastructure, and connect them to locally running models through adapters. The framework is optimized for Gemini but supports other models and providers. Its Python repository uses the Apache 2.0 license.

aichat brings Ollama and cloud AI services into the same terminal interface for developers and people who work at the command line. It runs locally on macOS, Linux and Windows, with Android support through Termux. Model processing happens through the backend you choose: Ollama supports local models, while providers such as OpenAI, Claude and Gemini process requests in the cloud.

Semantic Kernel is an MIT-licensed SDK for developers adding AI agents to their applications. It supports local models through Ollama, LMStudio and ONNX, alongside cloud services such as OpenAI and Azure OpenAI. You choose the model backend. The SDK runs on Windows, macOS and Linux and supports C#, Python and Java.

Inspect AI is a Python framework for researchers and developers testing language models and AI agents. Developed by the UK AI Security Institute and Meridian Labs, it evaluates coding, reasoning, knowledge, behavior and multimodal understanding, including tasks where agents must take actions to succeed.

mistral.rs is an open source inference engine for running models on your own computer or self-hosted server. It's for developers building AI applications and people who want local chat, multimodal models and agent tools in the same runtime. The Rust project uses the MIT license.

DocsGPT is an MIT-licensed, open-source platform for teams that want AI search, assistants and agents over their own documents. It can run on your servers with local models, including fully air-gapped deployments where documents and questions stay inside your network. Answers include the source title and page number so readers can check the evidence.

Letta is an open-source platform for AI agents that retain memory across conversations and use experience to improve over time. Formerly called MemGPT, it's for people building or using assistants that need continuity beyond a single chat. Agents can run locally or on a self-hosted server.

txtai is a Python framework for developers building search applications, chat with their data, and AI agents on their own hardware or servers. Its embeddings database combines sparse and dense vector search with graphs and relational data, so the same system can find related content and supply context to language models. It's open source under Apache 2.0.

DSPy is a Python framework for developers building AI applications whose tasks need clear inputs, predictable output types, and measurable results. You define what a language model should produce, then compose those tasks into a larger program. It's open source under the MIT license.

smolagents is an open-source Python library for developers building AI agents that carry out tasks by writing and executing Python. Its CodeAgent can combine tool calls with loops, conditionals, and calculations in one action. This approach suits tasks that need several operations, rather than a single model response.

CrewAI is an open-source Python framework for developers building workflows with multiple AI agents on their own hardware or servers. It supports local models through Ollama and defaults to the OpenAI API for model requests. The framework uses the MIT license; a separate commercial platform provides managed deployment and governance, with on-premise and cloud options.

LlamaIndex is an MIT-licensed Python framework for developers building AI agents and apps that answer questions using their own data. It connects documents and other sources to language models, then helps an app find the relevant material when a user asks something. Its open source framework can work with models served through Ollama.

LangChain4j is an Apache 2.0 open-source Java library for developers building chatbots, assistants and AI agents in JVM applications. It connects application code to local LLM backends such as Ollama as well as cloud providers such as OpenAI and Google Vertex AI. Where model requests go depends on the backend you choose.

RubyLLM is an MIT-licensed AI framework for developers building Ruby and Rails applications with local or hosted models. Its shared API lets an application switch between Ollama, cloud providers such as Anthropic and OpenAI, and OpenAI-compatible endpoints without rewriting its model integration. The framework runs in your application; model processing happens at the local or hosted backend you choose.

MaxKB is a self-hosted AI agent platform for organizations building customer support bots, internal knowledge assistants and business automation. It combines answers grounded in company documents with workflows that can call functions and MCP tools. You can run it on your own server through Docker and use it through a browser.

Hexabot is a self-hosted AI workflow automation platform for teams building customer service assistants and business automations. It connects conversations to actions across websites, messaging platforms, social channels and custom entry points. You can run it on-premise or in your own cloud, with workflows, memory and customer data in infrastructure you control.

BAML is a programming language for developers building AI agents, with typed model calls and local tracing built into the language. It runs standalone on macOS, Linux and Windows, or alongside an existing application. The language is open source under Apache 2.0, and works offline.

OpenAI Agents SDK is an open-source Python framework for developers building AI apps that need to use tools, delegate tasks, or work across multiple steps. Its runtime manages agent turns and conversation state while letting developers express workflows in ordinary Python. It uses the MIT license.

Haystack is a Python framework for developers building self-hosted AI agents, document search, and apps that answer questions using their own data. Its modular pipelines let teams control which information reaches a model and inspect how retrieval, memory, tools, and generation contribute to an answer. It's open source under Apache 2.0.

Vercel AI SDK is a TypeScript library for developers building chatbots, generative interfaces, and AI agents. It gives an application one way to work with models from providers such as OpenAI, Anthropic, and Google, so teams can change providers without rebuilding the parts of their app that handle responses. It suits developers who want control over the application they build while choosing how it connects to model services.