--- title: "eval-view vs agent-framework" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hidai25-eval-view-vs-microsoft-agent-framework" tools: ["hidai25-eval-view", "microsoft-agent-framework"] --- # eval-view vs agent-framework *GraphCanon updated Sep 20, 2026* ## Verdict Pick eval-view if eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and; pick agent-framework if the agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments. [eval-view](https://evalview.com) reports 134 GitHub stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. [agent-framework](https://aka.ms/agent-framework) has 14k stars, 2.3k forks, and 605 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [eval-view's repository](https://github.com/hidai25/eval-view) and [agent-framework's repository](https://github.com/microsoft/agent-framework). | | [eval-view](/tools/hidai25-eval-view.md) | [agent-framework](/tools/microsoft-agent-framework.md) | | --- | --- | --- | | Tagline | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | Framework for building and deploying AI agents and multi-agent workflows | | Stars | 134 | 13,573 | | Forks | 24 | 2,335 | | Open issues | 2 | 605 | | Language | Python | Python | | Adopt for | Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and | The agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Developer Tools | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [eval-view](/tools/hidai25-eval-view.md) | [agent-framework](/tools/microsoft-agent-framework.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 13d | 0d | | Open issues (now) | 2 | 605 | | Stars delta | +8 (30d) | +855 (30d) | | Open issues delta | -1 (30d) | -80 (30d) | | Owner type | User | Organization | | Full report | [trust report](/tools/hidai25-eval-view/trust.md) | [trust report](/tools/microsoft-agent-framework/trust.md) | ## Shared compatibility - **Python**: [eval-view](/tools/hidai25-eval-view.md) - Python runtime; [agent-framework](/tools/microsoft-agent-framework.md) - Python runtime ## Decision facts: eval-view - **Adopt for:** Eval-view is a Python-based tool for regression testing of AI agents, supporting multiple platforms like LangGraph, CrewAI, OpenAI, and Anthropic. It snapshots AI behavior and detects regressions through diffing tool and ## Decision facts: agent-framework - **Requirements:** Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages. - **Adopt for:** The agent-framework provides tools for developers to build and deploy AI agents and multi-agent workflows in Python and .NET environments. ## Choose when ### Choose eval-view if… - License: eval-view is Apache-2.0, agent-framework is MIT. - Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, anthropic. - Also covers Evaluation & Observability. - eval-view ships Docker support for self-hosted deployment. - When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### Choose agent-framework if… - License: agent-framework is MIT, eval-view is Apache-2.0. - Requirements: Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages.. - Tags unique to agent-framework: agent-framework, agents, multi-agent, orchestration. - Also covers Developer Tools. - Choose agent-framework if your project requires support for both Python and .NET, allowing you to develop across different ecosystems. ## When NOT to use eval-view - If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. - When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. - If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. - If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ## When NOT to use agent-framework - Avoid using the agent-framework if your team does not have proficiency in either Python or.NET, as this may cause difficulties in leveraging its features effectively. - Do not opt for agent-framework if you only need lightweight support for AI agents without a comprehensive orchestration and deployment framework. ## Common questions ### What is the difference between eval-view and agent-framework? eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. agent-framework: Framework for building and deploying AI agents and multi-agent workflows. See the comparison table for live GitHub stats and shared categories. ### When should I choose eval-view over agent-framework? Choose eval-view over agent-framework when License: eval-view is Apache-2.0, agent-framework is MIT; Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, anthropic; Also covers Evaluation & Observability; eval-view ships Docker support for self-hosted deployment; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic. ### When should I choose agent-framework over eval-view? Choose agent-framework over eval-view when License: agent-framework is MIT, eval-view is Apache-2.0; Requirements: Python version 3.6 or newer is required for Python installations.; The .NET Core SDK must be installed for utilizing the .NET packages.; Tags unique to agent-framework: agent-framework, agents, multi-agent, orchestration; Also covers Developer Tools; Choose agent-framework if your project requires support for both Python and .NET, allowing you to develop across different ecosystems. ### When should I avoid eval-view? If you are working exclusively with AI platforms not supported by eval-view, such as those not listed among LangGraph, CrewAI, OpenAI, and Anthropic. When you do not require regression testing or behavior snapshotting for your AI agents, as eval-view is specifically designed for these purposes. If you are looking for a tool that does not involve backend API charges for executing your agent, as eval-view does not skip these charges even with the --no-judge flag. If you need a tool that automatically handles the migration from the OpenAI Assistants API to the Responses API without manual intervention, as eval-view requires following a migration guide for this. ### When should I avoid agent-framework? Avoid using the agent-framework if your team does not have proficiency in either Python or.NET, as this may cause difficulties in leveraging its features effectively. Do not opt for agent-framework if you only need lightweight support for AI agents without a comprehensive orchestration and deployment framework. ### Is eval-view or agent-framework more popular on GitHub? agent-framework has more GitHub stars (13,573 vs 134). Stars measure visibility, not whether either tool fits your constraints. ### Are eval-view and agent-framework open source? Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, agent-framework: MIT). ### Where can I find alternatives to eval-view or agent-framework? GraphCanon lists graph-backed alternatives at [eval-view alternatives](/tools/hidai25-eval-view/alternatives) and [agent-framework alternatives](/tools/microsoft-agent-framework/alternatives) ([eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md), [agent-framework markdown twin](/tools/microsoft-agent-framework/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/hidai25-eval-view-vs-microsoft-agent-framework.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, eval-view or agent-framework? eval-view: Active. agent-framework: 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 eval-view and agent-framework? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [eval-view trust report](/tools/hidai25-eval-view/trust); [agent-framework trust report](/tools/microsoft-agent-framework/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=hidai25-eval-view`](/api/graphcanon/graph?tool=hidai25-eval-view) - 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/_