--- title: "langchain vs palico-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-palico-ai-palico-ai" tools: ["langchain-ai-langchain", "palico-ai-palico-ai"] --- # langchain vs palico-ai *GraphCanon updated Jul 11, 2026* ## Verdict Pick langchain when langchain is primarily Python; palico-ai is TypeScript; pick palico-ai when palico-ai is primarily TypeScript; langchain is Python. [langchain](https://docs.langchain.com/langchain/) reports 142k GitHub stars, 24k forks, and 419 open issues, last pushed Jul 11, 2026. [palico-ai](https://www.palico.ai/) has 343 stars, 28 forks, and 6 open issues, last pushed Nov 26, 2024. Figures are from public GitHub metadata via [langchain's repository](https://github.com/langchain-ai/langchain) and [palico-ai's repository](https://github.com/palico-ai/palico-ai). | | [langchain](/tools/langchain-ai-langchain.md) | [palico-ai](/tools/palico-ai-palico-ai.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | Build, Improve Performance, and Productionize your AI Application | | Stars | 141,504 | 343 | | Forks | 23,516 | 28 | | Open issues | 419 | 6 | | Language | Python | TypeScript | | 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. | MIT | | Categories | LLM Frameworks, AI Agents | LLM Frameworks, AI Agents, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [palico-ai](/tools/palico-ai-palico-ai.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 591d | | Open issues (now) | 419 | 6 | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/palico-ai-palico-ai/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. ## Choose when ### Choose langchain if… - langchain is primarily Python; palico-ai is TypeScript. - 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, gemini, deepagents, generative-ai. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ### Choose palico-ai if… - palico-ai is primarily TypeScript; langchain is Python. - Tags unique to palico-ai: autogen, ai, javascript, docker. - Also covers Evaluation & Observability. ## 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 palico-ai - Last GitHub push was 592 days ago (dormant maintenance, Nov 26, 2024). Validate activity before betting a new project on palico-ai. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ## Common questions ### What is the difference between langchain and palico-ai? langchain: The agent engineering platform.. palico-ai: Build, Improve Performance, and Productionize your AI Application. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over palico-ai? Choose langchain over palico-ai when langchain is primarily Python; palico-ai is TypeScript; 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, gemini, deepagents, generative-ai; * 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 palico-ai over langchain? Choose palico-ai over langchain when palico-ai is primarily TypeScript; langchain is Python; Tags unique to palico-ai: autogen, ai, javascript, docker; Also covers Evaluation & Observability. ### 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 palico-ai? Last GitHub push was 592 days ago (dormant maintenance, Nov 26, 2024). Validate activity before betting a new project on palico-ai. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers. ### Is langchain or palico-ai more popular on GitHub? langchain has more GitHub stars (141,504 vs 343). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and palico-ai open source? Yes - both are open-source projects on GitHub (langchain: MIT, palico-ai: MIT). ### Where can I find alternatives to langchain or palico-ai? GraphCanon lists graph-backed alternatives at [langchain alternatives](/tools/langchain-ai-langchain/alternatives) and [palico-ai alternatives](/tools/palico-ai-palico-ai/alternatives) ([langchain markdown twin](/tools/langchain-ai-langchain/alternatives.md), [palico-ai markdown twin](/tools/palico-ai-palico-ai/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-palico-ai-palico-ai.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or palico-ai? langchain: Very active. palico-ai: Dormant. 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 palico-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain trust report](/tools/langchain-ai-langchain/trust); [palico-ai trust report](/tools/palico-ai-palico-ai/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/_