/awesome-sdks-for-ai-agents

A database of SDKs, frameworks, libraries, and tools for creating, monitoring, debugging and deploying autonomous AI agents

🎁 Awesome SDKs For AI Agents

Try out E2B's AI Playgrounds for agents, copilots, and AI apps

SDKs Repo Visual

Welcome to our list of AI agents SDKs. A database of SDKs, frameworks, libraries, and tools for creating, monitoring, debugging and deploying autonomous AI agents.

The list is done according to our best knowledge, although definitely not comprehensive. Discussion and feedback are appreciated! ❤️

Have anything to add?

Do you have something to add or improve about our list? Do it via pull request.

⭐ For any new project, please also include a suggestion for a category in the visual, where it fits the most, or suggest a new category. ⭐

🔎 Monitoring, Observability, Analytics

AgentOps creates tools to make agents actually work, e.g., graphs, monitoring, and replay analytics.

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Context is the product analytics platform for chat interfaces

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An open-source observability platform for GPT-3. Allows to track usage, costs, and latency with one line of code.

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Langfuse is an open-source analytics for LLM apps. The analytics is currently in a closed alph

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A unified platform for debugging, testing, evaluating, and monitoring LLM applications. LangSmith is now in closed beta.

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🎪 Orchestration

A dynamic AI Automation Platform for Interoperability & AI Agent Management

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🚧 Frameworks for Building Agents

Agents is an open-source library/framework for building autonomous language agents.

Description

  • Long-short Term Memory: Language agents in the library are equipped with both long-term memory implemented via VectorDB + Semantic Search and short-term memory (working memory) maintained and updated by an LLM.
  • Tool Usage: Language agents in the library can use any external tools via function-calling and developers can add customized tools/APIs here.
  • Web Navigation: Language agents in the library can use search engines to navigate the web and get useful information.
  • Multi-agent Communication: In addition to single language agents, the library supports building multi-agent systems in which language agents can communicate with other language agents and the environment. Different from most existing frameworks for multi-agent systems that use pre-defined rules to control the order for agents' action, Agents includes a controller function that dynamically decides which agent will perform the next action using an LLM by considering the previous actions, the environment, and the target of the current states. This makes multi-agent communication more flexible.
  • Human-Agent interaction: In addition to letting language agents communicate with each other in an environment, our framework seamlessly supports human users to play the role of the agent by himself/herself and input his/her own actions, and interact with other language agents in the environment.
  • Symbolic Control: Different from existing frameworks for language agents that only use a simple task description to control the entire multi-agent system over the whole task completion process, Agents allows users to use an SOP (Standard Operation Process) that defines subgoals/subtasks for the overall task to customize fine-grained workflows for the language agents.

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Axilla is a comprehensive end-to-end open-source LLM framework for TypeScript. It provides a family of modular libraries, which can be incrementally adopted, and together form an end-to-end opinionated framework for AI development. Axilla targets enterprises and allows them to develop AI applications. They provide a toolkit to orchestrate, monitor, and continuously improve AI applications in production.

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AutoGen is a framework by Microsoft that enables development of LLM applications using multiple agents that can converse with each other to solve task

Description

  • AutoGen agents are customizable, conversable, and seamlessly allow human participation
  • They can operate in various modes that employ combinations of LLMs, human inputs, and tools
  • AutoGen's design offers multiple advantages:
    • it gracefully navigates the strong but imperfect generation and reasoning abilities of these LLMs
    • it leverages human understanding and intelligence, while providing valuable automation through conversations between agents
      • it simplifies and unifies the implementation of complex LLM workflows as automated agent chats

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Chidori is a reactive runtime for building AI agents. It provides a framework for building AI agents that are reactive, observable, and robust. It supports building agents with Node.js, Python, and Rust. It is currently in alpha and is not yet ready for production use.

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Fixie is a platform for conversational AI that enables to build agents in any language. They have their own agent protocol.

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Haystack is an open-source LLM framework for building production-ready applications.

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A platform for deploying LLM agents with tools. They provide three types of agents: HfAgent uses inference endpoints for open-source models, LocalAgent uses a model of your choice locally and OpenAiAgent uses OpenAI closed models.

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LangChain is a framework designed to simplify the creation of applications using large language models.

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Rift is an AI-native language server for AI agents. It's an open-source VS Code extension that allows merging the output of code generation agents.

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Steamship is a platform that allows to build, scale, and monitor AI agents with serverless cloud hosting, vector search, webhooks, callbacks, and more.

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An open-source library for building AI-powered user interfaces.

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An open-source library that helps you to integrate OpenAI into your existing API infrastructure. You can use it to validate user input, enhance existing APIs with AI capabilities, and build APIs on top of AI Agents.

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☁️ Agents Cloud

E2b is an operating system for AI agents, that is, a set of tools, APIs, and cloud environments for agents.

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📈 Data Integration

LlamaIndex (formerly GPT Index) is a data framework for LLM applications to ingest, structure, and access private or domain-specific data.

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SID is a YC S23 company that makes data infrastructure for AI easy by letting AI devs connect to all of their customers' data with a single button and API. It is a fully-hosted retrieval pipeline that makes it easy to connect services like Google Mail, Notion, GDrive, or fully custom data. In one afternoon, you can connect to any data source you'd like and instantly scale to millions of users.

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Who's behind this?

This list is made by the team behind e2b. E2b is building an operation system of AI agents - that is, a set of tools, environments, SDKs and APIs. E2b is agnostic to your tech stack and aims to work with any tooling for building AI agents.

Join the community

Feel free to reach out to us at hello@e2b.dev. Check out also our database of AI agents.