--- title: "forge vs langchain" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoinezambelli-forge-vs-brainlid-langchain" tools: ["antoinezambelli-forge", "brainlid-langchain"] --- # forge vs langchain *GraphCanon updated Aug 14, 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 langchain if langChain framework tailored for Elixir projects. [forge](https://github.com/antoinezambelli/forge) reports 2.2k GitHub stars, 173 forks, and 4 open issues, last pushed Aug 13, 2026. [langchain](https://hexdocs.pm/langchain/) has 1.2k stars, 212 forks, and 30 open issues, last pushed Aug 6, 2026. Figures are from public GitHub metadata via [forge's repository](https://github.com/antoinezambelli/forge) and [langchain's repository](https://github.com/brainlid/langchain). | | [forge](/tools/antoinezambelli-forge.md) | [langchain](/tools/brainlid-langchain.md) | | --- | --- | --- | | Tagline | A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows | Elixir implementation of a LangChain style framework for integrating with and leveraging LLMs. | | Stars | 2,217 | 1,192 | | Forks | 173 | 212 | | Open issues | 4 | 30 | | Language | Python | Elixir | | 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. | LangChain framework tailored for Elixir projects | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | AI Agents, LLM Frameworks | LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [forge](/tools/antoinezambelli-forge.md) | [langchain](/tools/brainlid-langchain.md) | | --- | --- | --- | | Days since push | 0d | 1d | | Open issues (now) | 4 | 30 | | Full report | [trust report](/tools/antoinezambelli-forge/trust.md) | [trust report](/tools/brainlid-langchain/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: langchain - **Requirements:** Requires at least Elixir 1.17; Add `langchain` to dep list in `mix.exs` for installation - **Adopt for:** LangChain framework tailored for Elixir projects ## Choose when ### Choose forge if… - forge is primarily Python; langchain is Elixir. - License: forge is MIT, langchain 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. - Also covers AI Agents. - 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 langchain if… - langchain is primarily Elixir; forge is Python. - License: langchain is Other, forge is MIT. - Requirements: Requires at least Elixir 1.17; Add `langchain` to dep list in `mix.exs` for installation. - Tags unique to langchain: ai, anthropic, bumblebee, chatgpt. - You are working on an Elixir project and want to integrate advanced Language Model capabilities. ## 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 langchain - Your project is not written in Elixir, as this framework does not offer official support for other programming languages. - If your requirements mandate a non-Elixir environment or dependency ecosystem, such as Python which has more mature LLM frameworks. ## Common questions ### What is the difference between forge and langchain? forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. langchain: Elixir implementation of a LangChain style framework for integrating with and leveraging LLMs.. See the comparison table for live GitHub stats and shared categories. ### When should I choose forge over langchain? Choose forge over langchain when forge is primarily Python; langchain is Elixir; License: forge is MIT, langchain 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; Also covers AI Agents; 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 langchain over forge? Choose langchain over forge when langchain is primarily Elixir; forge is Python; License: langchain is Other, forge is MIT; Requirements: Requires at least Elixir 1.17; Add `langchain` to dep list in `mix.exs` for installation; Tags unique to langchain: ai, anthropic, bumblebee, chatgpt; You are working on an Elixir project and want to integrate advanced Language Model capabilities. ### 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 langchain? Your project is not written in Elixir, as this framework does not offer official support for other programming languages. If your requirements mandate a non-Elixir environment or dependency ecosystem, such as Python which has more mature LLM frameworks. ### Is forge or langchain more popular on GitHub? forge has more GitHub stars (2,217 vs 1,192). Stars measure visibility, not whether either tool fits your constraints. ### Are forge and langchain open source? Yes - both are open-source projects on GitHub (forge: MIT, langchain: Other). ### Where can I find alternatives to forge or langchain? GraphCanon lists graph-backed alternatives at [forge alternatives](/tools/antoinezambelli-forge/alternatives) and [langchain alternatives](/tools/brainlid-langchain/alternatives) ([forge markdown twin](/tools/antoinezambelli-forge/alternatives.md), [langchain markdown twin](/tools/brainlid-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/antoinezambelli-forge-vs-brainlid-langchain.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, forge or langchain? forge: Very 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 forge and langchain? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [forge trust report](/tools/antoinezambelli-forge/trust); [langchain trust report](/tools/brainlid-langchain/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/_