--- title: "langchain vs LangGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-langgptai-langgpt" tools: ["langchain-ai-langchain", "langgptai-langgpt"] --- # langchain vs LangGPT *GraphCanon updated Aug 7, 2026* ## Verdict Pick langchain if langChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect; pick LangGPT if langGPT: A structured & meta-prompt design framework. [langchain](https://docs.langchain.com/langchain/) reports 144k GitHub stars, 24k forks, and 463 open issues, last pushed Aug 7, 2026. [LangGPT](https://github.com/langgptai) has 12k stars, 936 forks, and 0 open issues, last pushed Jul 16, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [LangGPT's repository](https://github.com/langgptai/LangGPT). | | [langchain](/tools/langchain-ai-langchain.md) | [LangGPT](/tools/langgptai-langgpt.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | A pioneering framework for structured & meta-prompt design | | Stars | 143,615 | 12,378 | | Forks | 23,930 | 936 | | Open issues | 463 | 0 | | Language | Python | Jupyter Notebook | | Adopt for | LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect | LangGPT: A structured & meta-prompt design framework. | | Persona | - | - | | Runtime | - | - | | License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | Apache-2.0 | | Categories | AI Agents, LLM Frameworks | Developer Tools, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [LangGPT](/tools/langgptai-langgpt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 11d | | Open issues (now) | 463 | 0 | | Stars delta | +2.3k (30d) | Unknown | | Open issues delta | +57 (30d) | Unknown | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/langgptai-langgpt/trust.md) | ## Decision facts: langchain - **Pricing:** freemium - LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI. - **Adopt for:** LangChain is an open-source platform designed specifically for building agents and applications that leverage large language models (LLMs). It provides a standard framework to develop interoperable components and connect - **License detail:** MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. ## Decision facts: LangGPT - **Adopt for:** LangGPT: A structured & meta-prompt design framework. ## Choose when ### Choose langchain if… - langchain is primarily Python; LangGPT is Jupyter Notebook. - License: langchain is MIT, LangGPT is Apache-2.0. - Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.. - Tags unique to langchain: agents, ai-agents, anthropic, deepagents. - Also covers AI Agents, LLM Frameworks. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose LangGPT if… - LangGPT is primarily Jupyter Notebook; langchain is Python. - License: LangGPT is Apache-2.0, langchain is MIT. - Tags unique to LangGPT: claude, deeplearning, framework, gpt-4. - Also covers Developer Tools, Model Training. - You need advanced tools to create structured prompts for robust training setups ## When NOT to use langchain - * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. - * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth - * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ## When NOT to use LangGPT - The project requires simple prompt creation, not leveraging structured or meta-prompt designs - Your team lacks expertise in Jupyter Notebook as a development environment ## Common questions ### What is the difference between langchain and LangGPT? langchain: The agent engineering platform.. LangGPT: A pioneering framework for structured & meta-prompt design. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over LangGPT? Choose langchain over LangGPT when langchain is primarily Python; LangGPT is Jupyter Notebook; License: langchain is MIT, LangGPT is Apache-2.0; Pricing: LangChain itself is open-source and free to use. However, it might rely on paid services or premium models from external platforms like OpenAI.; Tags unique to langchain: agents, ai-agents, anthropic, deepagents; Also covers AI Agents, LLM Frameworks; * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### When should I choose LangGPT over langchain? Choose LangGPT over langchain when LangGPT is primarily Jupyter Notebook; langchain is Python; License: LangGPT is Apache-2.0, langchain is MIT; Tags unique to LangGPT: claude, deeplearning, framework, gpt-4; Also covers Developer Tools, Model Training; You need advanced tools to create structured prompts for robust training setups. ### When should I avoid langchain? * When working on smaller, less complex projects where full-scale integration with sophisticated components is not necessary as LangChain's extensive features might introduce unnecessary complexity. * If you are primarily focused on JavaScript or TypeScript development as the primary focus of LangChain is Python. Although there is a JS/TS equivalent (LangChain.js), it may not offer the same depth * For projects requiring heavy customization at lower levels, where a more granular control over individual components is required rather than working with an integrated framework. ### When should I avoid LangGPT? The project requires simple prompt creation, not leveraging structured or meta-prompt designs Your team lacks expertise in Jupyter Notebook as a development environment ### Is langchain or LangGPT more popular on GitHub? langchain has more GitHub stars (143,615 vs 12,378). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and LangGPT open source? Yes - both are open-source projects on GitHub (langchain: MIT, LangGPT: Apache-2.0). ### Where can I find alternatives to langchain or LangGPT? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [LangGPT alternatives](/tools/langgptai-langgpt/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [LangGPT markdown twin](/tools/langgptai-langgpt/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/langchain-ai-langchain-vs-langgptai-langgpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or LangGPT? langchain: Very active. LangGPT: Active. 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 langchain and LangGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [LangGPT trust report](/tools/langgptai-langgpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=langchain-ai-langchain`](/api/graphcanon/graph?tool=langchain-ai-langchain) - 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/_