Comparison
future-agi vs eval-view
Verdict
Pick future-agi if future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,; 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.
Markdown twin · future-agi alternatives · eval-view alternatives
GraphCanon updated Sep 20, 2026
11views this month
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Trust & integrity
| Signal | future-agi | eval-view |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Active (13d since push) As of Sep 18, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 18, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 | No lockfile (source not queried) As of Sep 18, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- future-agi
- Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications
- eval-view
- Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI
Stars
- future-agi
- 2.0k
- eval-view
- 134
Forks
- future-agi
- 627
- eval-view
- 24
Open issues
- future-agi
- 961
- eval-view
- 2
Language
- future-agi
- Python
- eval-view
- Python
Adopt for
- future-agi
- Future-AGI is an open-source platform for evaluating and observing LLM and AI agent applications, offering features like tracing, evaluations, simulations, and guardrails. It is self-hostable and supports deployment via,
- eval-view
- 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
Persona
- future-agi
- -
- eval-view
- -
Runtime
- future-agi
- -
- eval-view
- -
License
- future-agi
- Apache License 2.0, allowing for free use, modification, and distribution of the software, with the condition that any derivative works also be licensed under the same terms.
- eval-view
- Apache-2.0
Last pushed
- future-agi
- Sep 18, 2026
- eval-view
- Sep 5, 2026
Categories
- future-agi
- AI Agents, Evaluation & Observability, LLM Frameworks
- eval-view
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- future-agi
- Very active (96%)
- eval-view
- Active (82%)
Days since push
- future-agi
- 0d
- eval-view
- 13d
Open issues (now)
- future-agi
- 961
- eval-view
- 2
Stars delta
- future-agi
- +473 (30d)
- eval-view
- +8 (30d)
Open issues delta
- future-agi
- +365 (30d)
- eval-view
- -1 (30d)
Owner type
- future-agi
- Organization
- eval-view
- User
Full report
- future-agi
- Trust report
- eval-view
- Trust report
Choose future-agi if…
- Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing..
- Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment..
- Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations.
- Also covers LLM Frameworks.
- You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic.
When NOT to use future-agi
- You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development.
- You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future.
- Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source.
Choose eval-view if…
- Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, anthropic.
- When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic.
- Leaner open-issue backlog (2).
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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/future-agi) · observed Sep 20, 2026
- GitHub forks (future-agi/future-agi) · observed Sep 20, 2026
- Last push (future-agi/future-agi) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (hidai25/eval-view) · observed Sep 20, 2026
- GitHub forks (hidai25/eval-view) · observed Sep 20, 2026
- Last push (hidai25/eval-view) · observed Sep 5, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
GitHub stars on cards: future-agi 2.0k · eval-view 134 (synced Sep 20, 2026).
Common questions
- What is the difference between future-agi and eval-view?
- future-agi: Open-source, end-to-end platform for evaluating, observing, and improving LLM and AI agent applications. eval-view: Regression testing for AI agents, snapshots behavior, diffs tool calls, catches regressions in CI. See the comparison table for live GitHub stats and shared categories.
- When should I choose future-agi over eval-view?
- Choose future-agi over eval-view when Pricing: The core platform is free and open-source under the Apache License 2.0. However, for managed services or additional support, contact sales for pricing.; Requirements: Min 4 GB RAM; Requires Docker; Future-AGI requires Docker for deployment, with support for Docker Compose and upcoming Kubernetes and Helm support.; For production environments, a setup script is provided to generate secrets and pin image tags, ensuring a secure and reproducible deployment.; Tags unique to future-agi: ai-evals, ai-gateway, ai-optimization, ai-simulations; Also covers LLM Frameworks; You need a self-hostable solution that does not phone home, ensuring full control over your data and evaluation logic.
- When should I choose eval-view over future-agi?
- Choose eval-view over future-agi when Tags unique to eval-view: agent-benchmark, agent-evaluation, agentic-ai, anthropic; When you need to snapshot and diff the behavior of AI agents across multiple platforms, including LangGraph, CrewAI, OpenAI, and Anthropic; Leaner open-issue backlog (2).
- When should I avoid future-agi?
- You require immediate Kubernetes or Helm support, as these are not yet available, though they are in development. You are seeking a managed service or a solution available through AWS Marketplace, as these options are not yet available, though they are planned for the future. Your project is in a highly dynamic environment where frequent updates and vendor support are critical, as Future-AGI is a community-driven project with a focus on self-hosting and open-source.
- 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.
- Is future-agi or eval-view more popular on GitHub?
- future-agi has more GitHub stars (2,032 vs 134). Stars measure visibility, not whether either tool fits your constraints.
- Are future-agi and eval-view open source?
- Yes - both are open-source projects on GitHub (future-agi: Apache-2.0, eval-view: Apache-2.0).
- Where can I find alternatives to future-agi or eval-view?
- GraphCanon lists graph-backed alternatives at future-agi alternatives and eval-view alternatives (future-agi markdown twin, eval-view markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, future-agi or eval-view?
- future-agi: Very active. eval-view: 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 future-agi and eval-view?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: future-agi trust report; eval-view trust report.