--- title: "forge vs 12-factor-agents" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoinezambelli-forge-vs-humanlayer-12-factor-agents" tools: ["antoinezambelli-forge", "humanlayer-12-factor-agents"] --- # forge vs 12-factor-agents *GraphCanon updated Aug 18, 2026* ## Verdict Pick forge if developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge; pick 12-factor-agents if a TypeScript-based framework focused on applying 12-factor principles to build production-ready software with large language models. [forge](https://github.com/antoinezambelli/forge) reports 2.2k GitHub stars, 173 forks, and 4 open issues, last pushed Aug 13, 2026. [12-factor-agents](https://github.com/humanlayer/12-factor-agents) has 25k stars, 1.9k forks, and 26 open issues, last pushed Sep 21, 2025. Figures are from public GitHub metadata via [forge's repository](https://github.com/antoinezambelli/forge) and [12-factor-agents's repository](https://github.com/humanlayer/12-factor-agents). | | [forge](/tools/antoinezambelli-forge.md) | [12-factor-agents](/tools/humanlayer-12-factor-agents.md) | | --- | --- | --- | | Tagline | A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows | Principles for building production-ready LLM-powered software | | Stars | 2,217 | 25,353 | | Forks | 173 | 1,918 | | Open issues | 4 | 26 | | Language | Python | TypeScript | | Adopt for | Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge. | A TypeScript-based framework focused on applying 12-factor principles to build production-ready software with large language models. | | Persona | - | - | | Runtime | - | - | | License | MIT | The content and images are licensed under CC BY-SA 4.0, while the code is covered by the Apache 2.0 License. | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [forge](/tools/antoinezambelli-forge.md) | [12-factor-agents](/tools/humanlayer-12-factor-agents.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 330d | | Open issues (now) | 4 | 26 | | Stars delta | Unknown | +966 (30d) | | Open issues delta | Unknown | 0 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/antoinezambelli-forge/trust.md) | [trust report](/tools/humanlayer-12-factor-agents/trust.md) | ## Decision facts: forge - **Requirements:** Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case. - **Adopt for:** Developers working on self-hosted LLM tooling who need flexibility in backend setup and seamless integration of function calling in multi-step workflows might benefit from Forge. ## Decision facts: 12-factor-agents - **Pricing:** freemium - Free to use with open-source licenses - **Requirements:** Min 4 GB RAM; Requires Docker; Requires a solid understanding of TypeScript and familiarity with concepts like prompt engineering and context window management. - **Adopt for:** A TypeScript-based framework focused on applying 12-factor principles to build production-ready software with large language models. - **License detail:** The content and images are licensed under CC BY-SA 4.0, while the code is covered by the Apache 2.0 License. ## Choose when ### Choose forge if… - forge is primarily Python; 12-factor-agents is TypeScript. - License: forge is MIT, 12-factor-agents is Other. - Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.. - Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework. - forge ships Docker support for self-hosted deployment. - - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic. ### Choose 12-factor-agents if… - 12-factor-agents is primarily TypeScript; forge is Python. - License: 12-factor-agents is Other, forge is MIT. - Pricing: Free to use with open-source licenses. - Requirements: Min 4 GB RAM; Requires Docker; Requires a solid understanding of TypeScript and familiarity with concepts like prompt engineering and context window management.. - Tags unique to 12-factor-agents: 12-factor, agents, ai, context-window. - You are specifically developing AI agents or LLM-powered applications in TypeScript and need a structured guideline grounded in the 12-factor app principles. ## When NOT to use forge - - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services. ## When NOT to use 12-factor-agents - If your project requires languages other than TypeScript or if your application already has a strong foundation not necessarily aligning with the 12-factor app principles. - When you’re looking for comprehensive deployment automation tools rather than guidance on building LLM-powered agents and ensuring their reliability in production environments. ## Common questions ### What is the difference between forge and 12-factor-agents? forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. 12-factor-agents: Principles for building production-ready LLM-powered software. See the comparison table for live GitHub stats and shared categories. ### When should I choose forge over 12-factor-agents? Choose forge over 12-factor-agents when forge is primarily Python; 12-factor-agents is TypeScript; License: forge is MIT, 12-factor-agents is Other; Requirements: Min 4 GB RAM; Requires Docker; Requires Python 3.12+ and a running LLM backend.; Can be set up with local backends (e.g., llama.cpp) or Anthropic via its API, requiring an API key for the latter case.; Tags unique to forge: agentic-ai, function-calling, multi-step-workflows, python-framework; forge ships Docker support for self-hosted deployment; - You require an agnostic backend setup, such as local LLM backends like llama.cpp or cloud-based services with Anthropic. ### When should I choose 12-factor-agents over forge? Choose 12-factor-agents over forge when 12-factor-agents is primarily TypeScript; forge is Python; License: 12-factor-agents is Other, forge is MIT; Pricing: Free to use with open-source licenses; Requirements: Min 4 GB RAM; Requires Docker; Requires a solid understanding of TypeScript and familiarity with concepts like prompt engineering and context window management.; Tags unique to 12-factor-agents: 12-factor, agents, ai, context-window; You are specifically developing AI agents or LLM-powered applications in TypeScript and need a structured guideline grounded in the 12-factor app principles. ### When should I avoid forge? - If your application does not require flexibility in backend selection, and you prefer a single cloud provider like Anthropic without local setup. - For scenarios where simplicity of setup outweighs the need for customization in function calling and workflow management. - When working within environments strictly regulated against self-hosted infrastructure or requiring fully managed services. ### When should I avoid 12-factor-agents? If your project requires languages other than TypeScript or if your application already has a strong foundation not necessarily aligning with the 12-factor app principles. When you’re looking for comprehensive deployment automation tools rather than guidance on building LLM-powered agents and ensuring their reliability in production environments. ### Is forge or 12-factor-agents more popular on GitHub? 12-factor-agents has more GitHub stars (25,353 vs 2,217). Stars measure visibility, not whether either tool fits your constraints. ### Are forge and 12-factor-agents open source? Yes - both are open-source projects on GitHub (forge: MIT, 12-factor-agents: Other). ### Where can I find alternatives to forge or 12-factor-agents? GraphCanon lists graph-backed alternatives at [forge alternatives](/tools/antoinezambelli-forge/alternatives) and [12-factor-agents alternatives](/tools/humanlayer-12-factor-agents/alternatives) ([forge markdown twin](/tools/antoinezambelli-forge/alternatives.md), [12-factor-agents markdown twin](/tools/humanlayer-12-factor-agents/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/antoinezambelli-forge-vs-humanlayer-12-factor-agents.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, forge or 12-factor-agents? forge: Very active. 12-factor-agents: 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 forge and 12-factor-agents? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [forge trust report](/tools/antoinezambelli-forge/trust); [12-factor-agents trust report](/tools/humanlayer-12-factor-agents/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=antoinezambelli-forge`](/api/graphcanon/graph?tool=antoinezambelli-forge) - 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/_