--- title: "langchain-tutorials vs autogen" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/gkamradt-langchain-tutorials-vs-microsoft-autogen" tools: ["gkamradt-langchain-tutorials", "microsoft-autogen"] --- # langchain-tutorials vs autogen *GraphCanon updated Jul 11, 2026* ## Verdict Pick langchain-tutorials when langchain-tutorials is primarily Jupyter Notebook; autogen is Python; pick autogen when autogen is primarily Python; langchain-tutorials is Jupyter Notebook. [langchain-tutorials](https://github.com/gkamradt/langchain-tutorials) reports 7.5k GitHub stars, 2.0k forks, and 15 open issues, last pushed Aug 5, 2024. [autogen](https://microsoft.github.io/autogen/) has 60k stars, 9.0k forks, and 945 open issues, last pushed Apr 15, 2026. Figures are from public GitHub metadata via [langchain-tutorials's repository](https://github.com/gkamradt/langchain-tutorials) and [autogen's repository](https://github.com/microsoft/autogen). | | [langchain-tutorials](/tools/gkamradt-langchain-tutorials.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Tagline | Overview and tutorial of the LangChain Library | A programming framework for agentic AI | | Stars | 7,468 | 59,658 | | Forks | 2,018 | 8,983 | | Open issues | 15 | 945 | | Language | Jupyter Notebook | Python | | Adopt for | - | AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models. | | Persona | - | - | | Runtime | - | - | | License | - | CC-BY-4.0 | | Categories | LLM Frameworks, Vector Databases, Developer Tools | LLM Frameworks, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain-tutorials](/tools/gkamradt-langchain-tutorials.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Steady (60%) | | Days since push | 705d | 87d | | Open issues (now) | 15 | 945 | | Owner type | User | Organization | | Security scan | 174 low (174 low) | No lockfile | | Full report | [trust report](/tools/gkamradt-langchain-tutorials/trust.md) | [trust report](/tools/microsoft-autogen/trust.md) | ## Decision facts: autogen - **Requirements:** Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure. - **Adopt for:** AutoGen is a Python-based framework for developing and managing agentic AI systems. It includes the AutoGen Studio for no-code GUI setup, integrating with various models. ## Choose when ### Choose langchain-tutorials if… - langchain-tutorials is primarily Jupyter Notebook; autogen is Python. - Tags unique to langchain-tutorials: jupyter notebook. - Also covers Vector Databases, Developer Tools. ### Choose autogen if… - autogen is primarily Python; langchain-tutorials is Jupyter Notebook. - Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.. - Tags unique to autogen: llm-framework, autogen, agents, ai. - Also covers AI Agents. - You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ## When NOT to use langchain-tutorials - Last GitHub push was 705 days ago (dormant maintenance, Aug 5, 2024). Validate activity before betting a new project on langchain-tutorials. - 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. - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ## When NOT to use autogen - If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. - When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. - You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities. ## Common questions ### What is the difference between langchain-tutorials and autogen? langchain-tutorials: Overview and tutorial of the LangChain Library. autogen: A programming framework for agentic AI. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain-tutorials over autogen? Choose langchain-tutorials over autogen when langchain-tutorials is primarily Jupyter Notebook; autogen is Python; Tags unique to langchain-tutorials: jupyter notebook; Also covers Vector Databases, Developer Tools. ### When should I choose autogen over langchain-tutorials? Choose autogen over langchain-tutorials when autogen is primarily Python; langchain-tutorials is Jupyter Notebook; Requirements: Min 4 GB RAM; AutoGen requires Python 3.10 or later.; Ensure security when connecting to MCP servers due to the potential for local command execution and sensitive information exposure.; Tags unique to autogen: llm-framework, autogen, agents, ai; Also covers AI Agents; You need a framework that supports integration with multiple AI models via OpenAI's chat completion client. ### When should I avoid langchain-tutorials? Last GitHub push was 705 days ago (dormant maintenance, Aug 5, 2024). Validate activity before betting a new project on langchain-tutorials. 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. Developer Tools: A gateway is overkill when you're pinned to a single provider and model. ### When should I avoid autogen? If you require tools supporting multiple programming languages beyond Python, as AutoGen is strictly a Python-based framework. When deploying in environments where connecting to external servers (like those used by MCP) could pose security risks or is prohibited. You need solutions which do not involve additional installations for server components such as `playwright/mcp`, as AutoGen requires this setup for certain functionalities. ### Is langchain-tutorials or autogen more popular on GitHub? autogen has more GitHub stars (59,658 vs 7,468). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain-tutorials and autogen open source? Yes - both are open-source projects on GitHub. ### Where can I find alternatives to langchain-tutorials or autogen? GraphCanon lists graph-backed alternatives at [langchain-tutorials alternatives](/tools/gkamradt-langchain-tutorials/alternatives) and [autogen alternatives](/tools/microsoft-autogen/alternatives) ([langchain-tutorials markdown twin](/tools/gkamradt-langchain-tutorials/alternatives.md), [autogen markdown twin](/tools/microsoft-autogen/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/gkamradt-langchain-tutorials-vs-microsoft-autogen.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain-tutorials or autogen? langchain-tutorials: Dormant. autogen: Steady. 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-tutorials and autogen? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [langchain-tutorials trust report](/tools/gkamradt-langchain-tutorials/trust); [autogen trust report](/tools/microsoft-autogen/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=gkamradt-langchain-tutorials`](/api/graphcanon/graph?tool=gkamradt-langchain-tutorials) - 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/_