--- title: "Agently vs pydantic-ai" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentera-agently-vs-pydantic-pydantic-ai" tools: ["agentera-agently", "pydantic-pydantic-ai"] --- # Agently vs pydantic-ai Neutral, constraint-first comparison with live GitHub stats. | | [Agently](/tools/agentera-agently.md) | [pydantic-ai](/tools/pydantic-pydantic-ai.md) | | --- | --- | --- | | Tagline | [GenAI Application Development Framework] | GenAI Agent Framework, the Pydantic way | | Stars | 1,616 | 18,271 | | Forks | 175 | 2,316 | | Open issues | 8 | 501 | | Language | Python | Python | | Adopt for | Agently is a Python-based framework for developing GenAI applications that focuses on easy interaction with GenAI agents using structured data and event-driven flow management. It supports switching between different AI/ | Pydantic AI is a versatile agent framework for Python built by the Pydantic team to support GenAI workflows and applications. It integrates with multiple models and providers while offering robust observability features. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Pydantic AI is available under the MIT license, allowing for wide usage in various environments with fewer restrictions. | | Categories | AI Agents, Developer Tools | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [Agently](/tools/agentera-agently.md) | [pydantic-ai](/tools/pydantic-pydantic-ai.md) | | --- | --- | --- | | Open issues (now) | 8 | 501 | | Full report | [trust report](/tools/agentera-agently/trust.md) | [trust report](/tools/pydantic-pydantic-ai/trust.md) | **Typed relationship:** Agently _(alternative)_ pydantic-ai Agently is a GenAI application development framework that could be considered as an alternative to Pydantic AI for building AI-driven applications. ## Decision facts: Agently - **Requirements:** Min 2 GB RAM; Requires Python installation; Supports multiple GenAI agents including GPT, Claude, and others - **Adopt for:** Agently is a Python-based framework for developing GenAI applications that focuses on easy interaction with GenAI agents using structured data and event-driven flow management. It supports switching between different AI/ ## Decision facts: pydantic-ai - **Adopt for:** Pydantic AI is a versatile agent framework for Python built by the Pydantic team to support GenAI workflows and applications. It integrates with multiple models and providers while offering robust observability features. - **License detail:** Pydantic AI is available under the MIT license, allowing for wide usage in various environments with fewer restrictions. ## Choose when ### Choose Agently if… - License: Agently is Apache-2.0, pydantic-ai is MIT. - Requirements: Min 2 GB RAM; Requires Python installation; Supports multiple GenAI agents including GPT, Claude, and others. - Agently is a GenAI application development framework that could be considered as an alternative to Pydantic AI for building AI-driven applications. - Tags unique to Agently: ernie, deepseek, chatglm, claude. - Also covers Developer Tools. - When you need to manage complex GenAI application logic through structured outputs, observable actions, and maintainable workflows. ### Choose pydantic-ai if… - License: pydantic-ai is MIT, Agently is Apache-2.0. - Agently is a GenAI application development framework that could be considered as an alternative to Pydantic AI for building AI-driven applications. - Tags unique to pydantic-ai: genai, llm, python, pydantic. - Use Pydantic AI if you are already familiar with Pydantic or FastAPI, as it brings a similar design sensibility focused on ergonomics and ease of use. ## When NOT to use Agently - If your requirements do not include handling stateful interactions and complex event-driven flows within your GenAI applications. - When you prefer framework-agnostic development without a structured flow for managing the integration points between different AI models and tools, as Agently provides a more prescriptive architecture ## When NOT to use pydantic-ai - Avoid using Pydantic AI if you need specific features from a competitor tool that this framework doesn't explicitly support. For example, if your project relies heavily on an alternative framework's独特 - language_used_in_tool_development_and_public_api_codebase_libraries_and_frameworks_and_apis_and_their_versions_etc_which_version_of_fastapi_is_supported_or_required_if_applicable__for_when_to_use_and_ ## Common questions ### What is the difference between Agently and pydantic-ai? Agently: [GenAI Application Development Framework]. pydantic-ai: GenAI Agent Framework, the Pydantic way. See the comparison table for live GitHub stats and shared categories. ### When should I choose Agently over pydantic-ai? Choose Agently over pydantic-ai when License: Agently is Apache-2.0, pydantic-ai is MIT; Requirements: Min 2 GB RAM; Requires Python installation; Supports multiple GenAI agents including GPT, Claude, and others; Agently is a GenAI application development framework that could be considered as an alternative to Pydantic AI for building AI-driven applications; Tags unique to Agently: ernie, deepseek, chatglm, claude; Also covers Developer Tools; When you need to manage complex GenAI application logic through structured outputs, observable actions, and maintainable workflows. ### When should I choose pydantic-ai over Agently? Choose pydantic-ai over Agently when License: pydantic-ai is MIT, Agently is Apache-2.0; Agently is a GenAI application development framework that could be considered as an alternative to Pydantic AI for building AI-driven applications; Tags unique to pydantic-ai: genai, llm, python, pydantic; Use Pydantic AI if you are already familiar with Pydantic or FastAPI, as it brings a similar design sensibility focused on ergonomics and ease of use. ### When should I avoid Agently? If your requirements do not include handling stateful interactions and complex event-driven flows within your GenAI applications. When you prefer framework-agnostic development without a structured flow for managing the integration points between different AI models and tools, as Agently provides a more prescriptive architecture ### When should I avoid pydantic-ai? Avoid using Pydantic AI if you need specific features from a competitor tool that this framework doesn't explicitly support. For example, if your project relies heavily on an alternative framework's独特 language_used_in_tool_development_and_public_api_codebase_libraries_and_frameworks_and_apis_and_their_versions_etc_which_version_of_fastapi_is_supported_or_required_if_applicable__for_when_to_use_and_ ### Is Agently or pydantic-ai more popular on GitHub? pydantic-ai has more GitHub stars (18,271 vs 1,616). Stars measure visibility, not whether either tool fits your constraints. ### Are Agently and pydantic-ai open source? Yes - both are open-source projects on GitHub (Agently: Apache-2.0, pydantic-ai: MIT). ### Where can I find alternatives to Agently or pydantic-ai? GraphCanon lists graph-backed alternatives at /tools/agentera-agently/alternatives and /tools/pydantic-pydantic-ai/alternatives (/tools/agentera-agently/alternatives.md, /tools/pydantic-pydantic-ai/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/agentera-agently-vs-pydantic-pydantic-ai.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, Agently or pydantic-ai? Agently: Very active. pydantic-ai: 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 Agently and pydantic-ai? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: Agently: /tools/agentera-agently/trust; pydantic-ai: /tools/pydantic-pydantic-ai/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentera-agently`](/api/graphcanon/graph?tool=agentera-agently) - 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/_