--- title: "langchain vs py-gpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-szczyglis-dev-py-gpt" tools: ["langchain-ai-langchain", "szczyglis-dev-py-gpt"] --- # langchain vs py-gpt *GraphCanon updated Jul 15, 2026* ## Verdict Pick langchain when license: langchain is MIT, py-gpt is Other; pick py-gpt when license: py-gpt is Other, langchain is MIT. [langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 14, 2026. [py-gpt](https://pygpt.net) has 1.9k stars, 333 forks, and 61 open issues, last pushed Feb 6, 2026. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [py-gpt's repository](https://github.com/szczyglis-dev/py-gpt). | | [langchain](/tools/langchain-ai-langchain.md) | [py-gpt](/tools/szczyglis-dev-py-gpt.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe | | Stars | 141,713 | 1,851 | | Forks | 23,545 | 333 | | Open issues | 419 | 61 | | Language | Python | Python | | 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 | - | | Persona | - | - | | Runtime | - | - | | License | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | Other | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [py-gpt](/tools/szczyglis-dev-py-gpt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 159d | | Open issues (now) | 419 | 61 | | Owner type | Organization | User | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/szczyglis-dev-py-gpt/trust.md) | ## Shared compatibility - **Python**: [langchain](/tools/langchain-ai-langchain.md) - Python runtime; [py-gpt](/tools/szczyglis-dev-py-gpt.md) - Python runtime ## 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. ## Choose when ### Choose langchain if… - License: langchain is MIT, py-gpt is Other. - 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, chatgpt. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose py-gpt if… - License: py-gpt is Other, langchain is MIT. - Tags unique to py-gpt: ai, ai-assistant, artificial-intelligence, autonomous-agent. - Also covers Vector Databases. ## 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 py-gpt - Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between langchain and py-gpt? langchain: The agent engineering platform.. py-gpt: Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over py-gpt? Choose langchain over py-gpt when License: langchain is MIT, py-gpt is Other; 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, chatgpt; * 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 py-gpt over langchain? Choose py-gpt over langchain when License: py-gpt is Other, langchain is MIT; Tags unique to py-gpt: ai, ai-assistant, artificial-intelligence, autonomous-agent; Also covers Vector Databases. ### 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 py-gpt? Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is langchain or py-gpt more popular on GitHub? langchain has more GitHub stars (141,713 vs 1,851). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and py-gpt open source? Yes - both are open-source projects on GitHub (langchain: MIT, py-gpt: Other). ### Where can I find alternatives to langchain or py-gpt? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [py-gpt alternatives](/tools/szczyglis-dev-py-gpt/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [py-gpt markdown twin](/tools/szczyglis-dev-py-gpt/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-szczyglis-dev-py-gpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or py-gpt? langchain: Very active. py-gpt: 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 langchain and py-gpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [py-gpt trust report](/tools/szczyglis-dev-py-gpt/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/_