--- title: "chainlit vs langchain" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/chainlit-chainlit-vs-langchain-ai-langchain" tools: ["chainlit-chainlit", "langchain-ai-langchain"] --- # chainlit vs langchain *GraphCanon updated Jul 12, 2026* ## Verdict Pick chainlit if chainlit is a Python-based tool designed to streamline the development process of conversational AI applications, allowing developers to quickly build and interact with these apps; 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. [chainlit](https://docs.chainlit.io) reports 12k GitHub stars, 1.7k forks, and 126 open issues, last pushed Jun 11, 2026. [langchain](https://docs.langchain.com/langchain/) has 142k stars, 24k forks, and 419 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [chainlit's repository](https://github.com/Chainlit/chainlit) and [langchain's repository](https://github.com/langchain-ai/langchain). | | [chainlit](/tools/chainlit-chainlit.md) | [langchain](/tools/langchain-ai-langchain.md) | | --- | --- | --- | | Tagline | Build Conversational AI in minutes ⚡️ | The agent engineering platform. | | Stars | 12,293 | 141,504 | | Forks | 1,724 | 23,516 | | Open issues | 126 | 419 | | Language | Python | Python | | Adopt for | Chainlit is a Python-based tool designed to streamline the development process of conversational AI applications, allowing developers to quickly build and interact with these apps. | 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 | Apache-2.0 | MIT License, allowing free use for both personal and commercial purposes under its stipulated terms. | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [chainlit](/tools/chainlit-chainlit.md) | [langchain](/tools/langchain-ai-langchain.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 29d | 0d | | Open issues (now) | 126 | 419 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/chainlit-chainlit/trust.md) | [trust report](/tools/langchain-ai-langchain/trust.md) | ## Shared compatibility - **Python**: [chainlit](/tools/chainlit-chainlit.md) - Python runtime; [langchain](/tools/langchain-ai-langchain.md) - Python runtime ## Decision facts: chainlit - **Adopt for:** Chainlit is a Python-based tool designed to streamline the development process of conversational AI applications, allowing developers to quickly build and interact with these apps. ## 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 chainlit if… - License: chainlit is Apache-2.0, langchain is MIT. - Tags unique to chainlit: langchain, llm, openai, openai-chatgpt. - - When you want to develop conversational AI applications rapidly using familiar Python syntax. ### Choose langchain if… - License: langchain is MIT, chainlit 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. - * When aiming to build complex AI-powered agents or applications requiring high-level capabilities like planning, subagent interaction, and file system operations. ## When NOT to use chainlit - - Avoid if your development team is not comfortable with Python as Chainlit relies heavily on its ecosystem for rapid conversational AI development. - - Not suitable if you require customization in low-level components, as it abstracts a lot of these away to provide quick builds. ## 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. ## Common questions ### What is the difference between chainlit and langchain? chainlit: Build Conversational AI in minutes ⚡️. langchain: The agent engineering platform.. See the comparison table for live GitHub stats and shared categories. ### When should I choose chainlit over langchain? Choose chainlit over langchain when License: chainlit is Apache-2.0, langchain is MIT; Tags unique to chainlit: langchain, llm, openai, openai-chatgpt; - When you want to develop conversational AI applications rapidly using familiar Python syntax. ### When should I choose langchain over chainlit? Choose langchain over chainlit when License: langchain is MIT, chainlit 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; * 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 avoid chainlit? - Avoid if your development team is not comfortable with Python as Chainlit relies heavily on its ecosystem for rapid conversational AI development. - Not suitable if you require customization in low-level components, as it abstracts a lot of these away to provide quick builds. ### 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. ### Is chainlit or langchain more popular on GitHub? langchain has more GitHub stars (141,504 vs 12,293). Stars measure visibility, not whether either tool fits your constraints. ### Are chainlit and langchain open source? Yes - both are open-source projects on GitHub (chainlit: Apache-2.0, langchain: MIT). ### Where can I find alternatives to chainlit or langchain? GraphCanon lists graph-backed alternatives at [chainlit alternatives](/tools/chainlit-chainlit/alternatives) and [langchain alternatives](/tools/langchain-ai-langchain/alternatives) ([chainlit markdown twin](/tools/chainlit-chainlit/alternatives.md), [langchain markdown twin](/tools/langchain-ai-langchain/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/chainlit-chainlit-vs-langchain-ai-langchain.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, chainlit or langchain? chainlit: Active. langchain: Very 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 chainlit and langchain? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [chainlit trust report](/tools/chainlit-chainlit/trust); [langchain trust report](/tools/langchain-ai-langchain/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=chainlit-chainlit`](/api/graphcanon/graph?tool=chainlit-chainlit) - 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/_