cloudwego

    cloudwego/eino

    The ultimate LLM/AI application development framework in Go.

    ai
    llm
    ai-application
    ai-framework
    langchain
    langchain-for-go
    langchaingo
    Go
    Apache-2.0
    13.4K stars
    1.2K forks
    13.4K GitHub watchers
    Updated Oct 26, 2026
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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 7 days ago, with 41 contributors on GitHub.

    Peaked at #18 in the weekly ranking the week of Apr 19, its best in the past year.

    Use Cases & Benefits

    • Provides a Go framework for developing large language model (LLM) and AI applications with reusable components and orchestration capabilities.
    • Ensures strong type safety, concurrency management, and stream processing tailored to Go conventions for scalable and reliable AI app development.
    • Use for building complex LLM workflows that require flexible data flow and concurrency control in Go environments.
    • Use for creating AI agents that integrate chat models with external tools using graph-based orchestration and callback aspects.
    • Use for developing AI applications that need real-time streaming data handling and customizable lifecycle callbacks.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present
    • Code of conduct: present

    Watch-outs

    No watch-outs from GStars' checks.

    General guidance from repository metadata, not legal advice. How we score

    From the README

    Eino['aino] (pronounced similarly to "I know") aims to be the ultimate LLM application development framework in Golang. Drawing inspirations from many excellent LLM application development frameworks in the open-source community such as LangChain & LlamaIndex, etc., as well as learning from cutting-edge research and real world applications, Eino offers an LLM application development framework that emphasizes on simplicity, scalability, reliability and effectiveness that better aligns with Golang programming conventions.

    Of course, you can do that, Eino provides lots of useful components to use out of the box. But you can do more by using orchestration, for three reasons:

    Eino provides three set of APIs for orchestration

    Let's create a simple chain: a ChatTemplate followed by a ChatModel.

    Now let's create a graph that uses a ChatModel to generate answer or tool calls, then uses a ToolsNode to execute those tools if needed.

    Now let's create a workflow that flexibly maps input & output at the field level:

    Now let's create a 'ReAct' agent: A ChatModel binds to Tools. It receives input Messages and decides independently whether to call the Tool or output the final result. The execution result of the Tool will again become the input Message for the ChatModel and serve as the context for the next round of independent judgment.

    We provide a complete implementation for ReAct Agent out of the box in the flow package. Check out the code here: flow/agent/react

    Excerpt from the cloudwego/eino README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Aug 28: +7Sep 4: +4

    +926 stars over 90 days across 11 snapshot days; best day +7 on Aug 28.

    Forks

    1.2K+111

    Open issues

    270+134

    Compared with peers in AI

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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