--- title: "forge vs lagent" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/antoinezambelli-forge-vs-internlm-lagent" tools: ["antoinezambelli-forge", "internlm-lagent"] --- # forge vs lagent *GraphCanon updated Aug 16, 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 lagent if lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. [forge](https://github.com/antoinezambelli/forge) reports 2.2k GitHub stars, 173 forks, and 4 open issues, last pushed Aug 13, 2026. [lagent](https://github.com/InternLM/lagent) has 2.3k stars, 238 forks, and 24 open issues, last pushed Aug 3, 2026. Figures are from public GitHub metadata via [forge's repository](https://github.com/antoinezambelli/forge) and [lagent's repository](https://github.com/InternLM/lagent). | | [forge](/tools/antoinezambelli-forge.md) | [lagent](/tools/internlm-lagent.md) | | --- | --- | --- | | Tagline | A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows | A lightweight framework for building LLM-based agents | | Stars | 2,217 | 2,276 | | Forks | 173 | 238 | | Open issues | 4 | 24 | | Language | Python | Python | | 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. | lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. | | Persona | - | - | | Runtime | - | - | | License | MIT | lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. | | 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) | [lagent](/tools/internlm-lagent.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 12d | | Open issues (now) | 4 | 24 | | Stars delta | Unknown | +8 (30d) | | Open issues delta | Unknown | +1 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/antoinezambelli-forge/trust.md) | [trust report](/tools/internlm-lagent/trust.md) | ## Shared compatibility - **Python**: [forge](/tools/antoinezambelli-forge.md) - Python runtime; [lagent](/tools/internlm-lagent.md) - Python runtime ## 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: lagent - **Pricing:** freemium - Available freely due to its open-source nature, but customization or enterprise support might involve additional costs. - **Adopt for:** lagent is a Python framework aimed at streamlining the creation of lightweight Large Language Model (LLM) agents. - **License detail:** lagent is open-source under the Apache-2.0 license, allowing for broad use and modification with attribution. ## Choose when ### Choose forge if… - License: forge is MIT, lagent is Apache-2.0. - 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 lagent if… - License: lagent is Apache-2.0, forge is MIT. - Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.. - Tags unique to lagent: agent, gpt, llm, transformers. - When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ## 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 lagent - Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. - Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ## Common questions ### What is the difference between forge and lagent? forge: A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows. lagent: A lightweight framework for building LLM-based agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose forge over lagent? Choose forge over lagent when License: forge is MIT, lagent is Apache-2.0; 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 lagent over forge? Choose lagent over forge when License: lagent is Apache-2.0, forge is MIT; Pricing: Available freely due to its open-source nature, but customization or enterprise support might involve additional costs.; Tags unique to lagent: agent, gpt, llm, transformers; When you need a streamlined approach to develop LLM-based agents with minimal overhead, lagent can be particularly advantageous due to its lightweight design. ### 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 lagent? Avoid using lagent if your project necessitates integration with a broader set of tools that are not natively supported by this framework, as it offers limited out-of-the-box extensibility. Steer clear if you need robust scalability features right from the start. While lightweight, lagent may require additional custom work to handle more demanding scaling requirements. ### Is forge or lagent more popular on GitHub? lagent has more GitHub stars (2,276 vs 2,217). Stars measure visibility, not whether either tool fits your constraints. ### Are forge and lagent open source? Yes - both are open-source projects on GitHub (forge: MIT, lagent: Apache-2.0). ### Where can I find alternatives to forge or lagent? GraphCanon lists graph-backed alternatives at [forge alternatives](/tools/antoinezambelli-forge/alternatives) and [lagent alternatives](/tools/internlm-lagent/alternatives) ([forge markdown twin](/tools/antoinezambelli-forge/alternatives.md), [lagent markdown twin](/tools/internlm-lagent/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-internlm-lagent.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, forge or lagent? forge: Very active. lagent: 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 lagent? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [forge trust report](/tools/antoinezambelli-forge/trust); [lagent trust report](/tools/internlm-lagent/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/_