--- title: "langchain vs LLMStack" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/langchain-ai-langchain-vs-trypromptly-llmstack" tools: ["langchain-ai-langchain", "trypromptly-llmstack"] --- # langchain vs LLMStack Neutral, constraint-first comparison with live GitHub stats. | | [langchain](/tools/langchain-ai-langchain.md) | [LLMStack](/tools/trypromptly-llmstack.md) | | --- | --- | --- | | Tagline | The agent engineering platform. | No-code multi-agent framework for building LLM Agents and applications | | Stars | 141,278 | 2,304 | | Forks | 23,481 | 347 | | Open issues | 406 | 23 | | Language | Python | Python | | Adopt for | LangChain is an open-source Python framework focused on building agents and LLM-powered applications with built-in support for interoperable components and third-party integrations. It offers a suite of tools including ' | LLMStack is a no-code multi-agent framework for building and deploying generative AI applications, chatbots, and workflows that integrate with your data and business processes through a simple visual interface. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [langchain](/tools/langchain-ai-langchain.md) | [LLMStack](/tools/trypromptly-llmstack.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 573d | | Open issues (now) | 406 | 23 | | Security scan | No lockfile | Not scanned | | Full report | [trust report](/tools/langchain-ai-langchain/trust.md) | [trust report](/tools/trypromptly-llmstack/trust.md) | **Typed relationship:** langchain _(alternative)_ LLMStack LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities. ## Shared compatibility - **Python**: [langchain](/tools/langchain-ai-langchain.md) - Python runtime; [LLMStack](/tools/trypromptly-llmstack.md) - Python runtime ## Decision facts: langchain - **Pricing:** freemium - LangChain is available free of cost due to its open-source nature. However, certain advanced features or services provided through LangSmith may have associated costs that are not detailed in this un- - **Adopt for:** LangChain is an open-source Python framework focused on building agents and LLM-powered applications with built-in support for interoperable components and third-party integrations. It offers a suite of tools including ' ## Decision facts: LLMStack - **Pricing:** unknown - Pricing details are not provided in the repository data. You can check LLMStack's official site or contact their sales for more details. - **Requirements:** Min 4 GB RAM; Requires Docker; Docker is required to run jobs within LLMStack.; For Windows users, WSL2 (Windows Subsystem for Linux) must be installed. - **Adopt for:** LLMStack is a no-code multi-agent framework for building and deploying generative AI applications, chatbots, and workflows that integrate with your data and business processes through a simple visual interface. ## Choose when ### Choose langchain if… - License: langchain is MIT, LLMStack is Other. - Pricing: LangChain is available free of cost due to its open-source nature. However, certain advanced features or services provided through LangSmith may have associated costs that are not detailed in this un-. - LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities. - Tags unique to langchain: multiagent, langchain, framework, ai-agents. - You are developing complex AI applications that require advanced customization or agent orchestration with LangGraph. ### Choose LLMStack if… - License: LLMStack is Other, langchain is MIT. - Pricing: Pricing details are not provided in the repository data. You can check LLMStack's official site or contact their sales for more details.. - Requirements: Min 4 GB RAM; Requires Docker; Docker is required to run jobs within LLMStack.; For Windows users, WSL2 (Windows Subsystem for Linux) must be installed.. - LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities. - Tags unique to LLMStack: platform, generative-ai, ai-agents-framework, no-code-ai. - You need to create complex generative AI agents or workflows and want to avoid coding. ## When NOT to use langchain - If you are seeking simpler or standalone tools without the complexity of chaining interoperable components. - When your project requires language support other than Python, as LangChain’s core is built around Python with limited JS/TS options. - Your development environment does not allow for open-source tooling under MIT license. ## When NOT to use LLMStack - You require extensive customization that goes beyond the no-code capabilities of LLMStack. - Your organization enforces strict security practices that do not allow for cloud deployments or third-party services integration without thorough scrutiny. - The need for real-time, high-throughput data processing where latency could be introduced by using a no-code solution. ## Common questions ### What is the difference between langchain and LLMStack? langchain: The agent engineering platform.. LLMStack: No-code multi-agent framework for building LLM Agents and applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose langchain over LLMStack? Choose langchain over LLMStack when License: langchain is MIT, LLMStack is Other; Pricing: LangChain is available free of cost due to its open-source nature. However, certain advanced features or services provided through LangSmith may have associated costs that are not detailed in this un-; LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities; Tags unique to langchain: multiagent, langchain, framework, ai-agents; You are developing complex AI applications that require advanced customization or agent orchestration with LangGraph. ### When should I choose LLMStack over langchain? Choose LLMStack over langchain when License: LLMStack is Other, langchain is MIT; Pricing: Pricing details are not provided in the repository data. You can check LLMStack's official site or contact their sales for more details.; Requirements: Min 4 GB RAM; Requires Docker; Docker is required to run jobs within LLMStack.; For Windows users, WSL2 (Windows Subsystem for Linux) must be installed.; LLMStack can be considered an alternative to LangChain since both platforms provide means to build, manage, and deploy AI agents, but LLMStack emphasizes a no-code experience whereas LangChain provides more direct engineering capabilities; Tags unique to LLMStack: platform, generative-ai, ai-agents-framework, no-code-ai; You need to create complex generative AI agents or workflows and want to avoid coding. ### When should I avoid langchain? If you are seeking simpler or standalone tools without the complexity of chaining interoperable components. When your project requires language support other than Python, as LangChain’s core is built around Python with limited JS/TS options. Your development environment does not allow for open-source tooling under MIT license. ### When should I avoid LLMStack? You require extensive customization that goes beyond the no-code capabilities of LLMStack. Your organization enforces strict security practices that do not allow for cloud deployments or third-party services integration without thorough scrutiny. The need for real-time, high-throughput data processing where latency could be introduced by using a no-code solution. ### Is langchain or LLMStack more popular on GitHub? langchain has more GitHub stars (141,278 vs 2,304). Stars measure visibility, not whether either tool fits your constraints. ### Are langchain and LLMStack open source? Yes - both are open-source projects on GitHub (langchain: MIT, LLMStack: Other). ### Where can I find alternatives to langchain or LLMStack? GraphCanon lists graph-backed alternatives at /tools/langchain-ai-langchain/alternatives and /tools/trypromptly-llmstack/alternatives (/tools/langchain-ai-langchain/alternatives.md, /tools/trypromptly-llmstack/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 /compare/langchain-ai-langchain-vs-trypromptly-llmstack.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, langchain or LLMStack? langchain: Very active. LLMStack: 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 LLMStack? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: langchain: /tools/langchain-ai-langchain/trust; LLMStack: /tools/trypromptly-llmstack/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/_