--- title: "lingoose vs langchaingo" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/henomis-lingoose-vs-tmc-langchaingo" tools: ["henomis-lingoose", "tmc-langchaingo"] --- # lingoose vs langchaingo *GraphCanon updated Aug 22, 2026* ## Verdict Pick lingoose if linGoose is a Go-centric framework specialized for building and managing AI/LLM applications. It supports specific libraries like OpenAI and Pinecone; pick langchaingo if langChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. [lingoose](https://simonevellei.com/lingoose) reports 834 GitHub stars, 76 forks, and 16 open issues, last pushed Mar 15, 2026. [langchaingo](https://tmc.github.io/langchaingo/) has 9.6k stars, 1.1k forks, and 410 open issues, last pushed Jan 11, 2026. Figures are from public GitHub metadata via [lingoose's repository](https://github.com/henomis/lingoose) and [langchaingo's repository](https://github.com/tmc/langchaingo). | | [lingoose](/tools/henomis-lingoose.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Tagline | Go framework for building AI/LLM applications | LangChain for Go, the easiest way to write LLM-based programs in Go | | Stars | 834 | 9,600 | | Forks | 76 | 1,135 | | Open issues | 16 | 410 | | Language | Go | Go | | Adopt for | LinGoose is a Go-centric framework specialized for building and managing AI/LLM applications. It supports specific libraries like OpenAI and Pinecone. | LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | LLM Frameworks, Model Training | Developer Tools, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [lingoose](/tools/henomis-lingoose.md) | [langchaingo](/tools/tmc-langchaingo.md) | | --- | --- | --- | | Days since push | 160d | 208d | | Open issues (now) | 16 | 410 | | Stars delta | -1 (30d) | Unknown | | Open issues delta | 0 (30d) | Unknown | | Full report | [trust report](/tools/henomis-lingoose/trust.md) | [trust report](/tools/tmc-langchaingo/trust.md) | ## Decision facts: lingoose - **Adopt for:** LinGoose is a Go-centric framework specialized for building and managing AI/LLM applications. It supports specific libraries like OpenAI and Pinecone. ## Decision facts: langchaingo - **Adopt for:** LangChainGo simplifies the integration of Large Language Models into Go projects through easy-to-use APIs and composability. ## Choose when ### Choose lingoose if… - Tags unique to lingoose: chatgpt, embeddings, index, llm. - Also covers Model Training. - You are working primarily with the Go language in your development environment. ### Choose langchaingo if… - Tags unique to langchaingo: langchain. - Also covers Developer Tools. - - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ## When NOT to use lingoose - If your team is not proficient in Go, as LinGoose relies heavily on this language for its operations. - You need extensive features tailored to other programming languages besides Go; LinGoose does not offer equivalent support. ## When NOT to use langchaingo - - If your project strictly adheres to another programming language where other implementations of LangChain are available. - - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ## Common questions ### What is the difference between lingoose and langchaingo? lingoose: Go framework for building AI/LLM applications. langchaingo: LangChain for Go, the easiest way to write LLM-based programs in Go. See the comparison table for live GitHub stats and shared categories. ### When should I choose lingoose over langchaingo? Choose lingoose over langchaingo when Tags unique to lingoose: chatgpt, embeddings, index, llm; Also covers Model Training; You are working primarily with the Go language in your development environment. ### When should I choose langchaingo over lingoose? Choose langchaingo over lingoose when Tags unique to langchaingo: langchain; Also covers Developer Tools; - You are working on a project that requires LLM-based capabilities, but prefer to code in Go. ### When should I avoid lingoose? If your team is not proficient in Go, as LinGoose relies heavily on this language for its operations. You need extensive features tailored to other programming languages besides Go; LinGoose does not offer equivalent support. ### When should I avoid langchaingo? - If your project strictly adheres to another programming language where other implementations of LangChain are available. - When your application requires heavy customization at the framework level that might not be directly supported within LangChainGo’s current implementation. ### Is lingoose or langchaingo more popular on GitHub? langchaingo has more GitHub stars (9,600 vs 834). Stars measure visibility, not whether either tool fits your constraints. ### Are lingoose and langchaingo open source? Yes - both are open-source projects on GitHub (lingoose: MIT, langchaingo: MIT). ### Where can I find alternatives to lingoose or langchaingo? GraphCanon lists graph-backed alternatives at [lingoose alternatives](/tools/henomis-lingoose/alternatives) and [langchaingo alternatives](/tools/tmc-langchaingo/alternatives) ([lingoose markdown twin](/tools/henomis-lingoose/alternatives.md), [langchaingo markdown twin](/tools/tmc-langchaingo/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/henomis-lingoose-vs-tmc-langchaingo.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, lingoose or langchaingo? lingoose: Slowing. langchaingo: Slowing. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for lingoose and langchaingo? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [lingoose trust report](/tools/henomis-lingoose/trust); [langchaingo trust report](/tools/tmc-langchaingo/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=henomis-lingoose`](/api/graphcanon/graph?tool=henomis-lingoose) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_