Eino
by Community
The ultimate LLM/AI application development framework in Go.
OSS
Eino
Added 1 June 2026
Overview
Eino is an open-source framework for building LLM and AI applications in Go. It provides orchestration primitives for chaining and composing language model calls. The project is hosted on GitHub under the cloudwego organization.
Best for
Best for
Go developers who want to add LLM orchestration to their backend applications
Use cases
- Build multi-step LLM workflows and chains in Go
- Orchestrate calls to language models with structured outputs
- Develop AI features for Go-based backend services
Notes
Eino is an open-source framework for building LLM and AI applications in Go. It provides orchestration primitives for chaining and composing language model calls. The project is hosted on GitHub under the cloudwego organization.
11,579 stars on GitHub. Last updated 2026-06-01. Licensed Apache-2.0.
Use cases
- Build multi-step LLM workflows and chains in Go
- Orchestrate calls to language models with structured outputs
- Develop AI features for Go-based backend services
Pros
- Native Go performance and type safety
- Well-documented with growing community (11.5k stars)
- Simple orchestration abstractions without heavy dependencies
Cons
- Smaller ecosystem of integrations compared to Python frameworks
- Limited pre-built tooling for advanced AI tasks like RAG or agents
- Primarily targets Go developers, may not suit teams using other languages
Indexed from awesome-langchain and enriched against its public facts.
Pros
- Native Go performance and type safety
- Well-documented with growing community (11.5k stars)
- Simple orchestration abstractions without heavy dependencies
Cons
- Smaller ecosystem of integrations compared to Python frameworks
- Limited pre-built tooling for advanced AI tasks like RAG or agents
- Primarily targets Go developers, may not suit teams using other languages
Pairs with
Other entries in the index that connect to this one. Click through to see the chain.
Agency
Community
🕵️♂️ Library designed for developers eager to explore the potential of Large Language Models (LLMs) and other generative AI through a clean, effective, and Go-idiomatic approach.
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