--- title: "eval-view vs ragtune" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/hidai25-eval-view-vs-metawake-ragtune" tools: ["hidai25-eval-view", "metawake-ragtune"] --- # eval-view vs ragtune *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 ragtune if ragtune is a command-line tool for evaluating and optimizing retrieval-augmented generation systems, supporting various vector databases and embedding models. [eval-view](https://evalview.com) reports 134 GitHub stars, 24 forks, and 2 open issues, last pushed Sep 5, 2026. [ragtune](https://github.com/metawake/ragtune) has 13 stars, 1 forks, and 0 open issues, last pushed Mar 25, 2026. Figures are from public GitHub metadata via [eval-view's repository](https://github.com/hidai25/eval-view) and [ragtune's repository](https://github.com/metawake/ragtune). | | [eval-view](/tools/hidai25-eval-view.md) | [ragtune](/tools/metawake-ragtune.md) | | --- | --- | --- | | Tagline | Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI | Tools for inspecting, debugging, benchmarking, and tuning RAG retrieval | | Stars | 134 | 13 | | Forks | 24 | 1 | | Open issues | 2 | 0 | | Language | Python | Go | | 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 | Ragtune is a command-line tool for evaluating and optimizing retrieval-augmented generation systems, supporting various vector databases and embedding models. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT License | | Categories | AI Agents, Evaluation & Observability | Developer Tools, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [eval-view](/tools/hidai25-eval-view.md) | [ragtune](/tools/metawake-ragtune.md) | | --- | --- | --- | | Maintenance | Active (82%) | Slowing (36%) | | Days since push | 13d | 176d | | Open issues (now) | 2 | 0 | | Stars delta | +8 (30d) | 0 (30d) | | Open issues delta | -1 (30d) | 0 (30d) | | Full report | [trust report](/tools/hidai25-eval-view/trust.md) | [trust report](/tools/metawake-ragtune/trust.md) | ## 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: ragtune - **Pricing:** freemium - Free and open-source under the MIT License. - **Requirements:** Min 2 GB RAM; Go installation is required to use Ragtune. - **Adopt for:** Ragtune is a command-line tool for evaluating and optimizing retrieval-augmented generation systems, supporting various vector databases and embedding models. - **License detail:** MIT License ## Choose when ### Choose eval-view if… - eval-view is primarily Python; ragtune is Go. - License: eval-view is Apache-2.0, ragtune is MIT. - Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents. - Also covers AI Agents. - 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 ragtune if… - ragtune is primarily Go; eval-view is Python. - License: ragtune is MIT, eval-view is Apache-2.0. - Pricing: Free and open-source under the MIT License.. - Requirements: Min 2 GB RAM; Go installation is required to use Ragtune.. - Tags unique to ragtune: benchmarking, chroma, embeddings, metrics. - Also covers Developer Tools. - When you need to inspect, debug, benchmark, and tune the retrieval layer of your RAG systems specifically. ## 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 ragtune - If your project does not involve retrieval-augmented generation systems or if you are not using supported vector databases. - When you prefer a tool that is not written in Go or does not offer command-line interface capabilities. ## Common questions ### What is the difference between eval-view and ragtune? eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. ragtune: Tools for inspecting, debugging, benchmarking, and tuning RAG retrieval. See the comparison table for live GitHub stats and shared categories. ### When should I choose eval-view over ragtune? Choose eval-view over ragtune when eval-view is primarily Python; ragtune is Go; License: eval-view is Apache-2.0, ragtune is MIT; Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, ai-agents; Also covers AI Agents; 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 ragtune over eval-view? Choose ragtune over eval-view when ragtune is primarily Go; eval-view is Python; License: ragtune is MIT, eval-view is Apache-2.0; Pricing: Free and open-source under the MIT License.; Requirements: Min 2 GB RAM; Go installation is required to use Ragtune.; Tags unique to ragtune: benchmarking, chroma, embeddings, metrics; Also covers Developer Tools; When you need to inspect, debug, benchmark, and tune the retrieval layer of your RAG systems specifically. ### 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 ragtune? If your project does not involve retrieval-augmented generation systems or if you are not using supported vector databases. When you prefer a tool that is not written in Go or does not offer command-line interface capabilities. ### Is eval-view or ragtune more popular on GitHub? eval-view has more GitHub stars (134 vs 13). Stars measure visibility, not whether either tool fits your constraints. ### Are eval-view and ragtune open source? Yes - both are open-source projects on GitHub (eval-view: Apache-2.0, ragtune: MIT). ### Where can I find alternatives to eval-view or ragtune? GraphCanon lists graph-backed alternatives at [eval-view alternatives](/tools/hidai25-eval-view/alternatives) and [ragtune alternatives](/tools/metawake-ragtune/alternatives) ([eval-view markdown twin](/tools/hidai25-eval-view/alternatives.md), [ragtune markdown twin](/tools/metawake-ragtune/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-metawake-ragtune.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, eval-view or ragtune? eval-view: Active. ragtune: 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 eval-view and ragtune? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [eval-view trust report](/tools/hidai25-eval-view/trust); [ragtune trust report](/tools/metawake-ragtune/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/_