Comparison
future-agi vs eval-view
Verdict
Pick future-agi if future-AGI is an open-source toolkit for evaluating and improving LLMs and AI agents. It includes features like tracing, evaluations, simulations, datasets, gateway operations, and guardrails; pick eval-view if regression testing for AI agents to detect behavioral changes and output quality regressions over time.
Markdown twin · future-agi alternatives · eval-view alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | future-agi | eval-view |
|---|---|---|
| Maintenance | Very active (1d since push) As of 3w · github_public_v1 | Very active (6d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Personal account As of 3w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- End-to-end platform for evaluating, observing, and improving LLM and AI agent applications
- eval-view
- Regression testing for AI agents
Stars
- future-agi
- 1.6k
- eval-view
- 126
Forks
- future-agi
- 449
- eval-view
- 21
Open issues
- future-agi
- 596
- eval-view
- 3
Language
- future-agi
- Python
- eval-view
- Python
Adopt for
- future-agi
- Future-AGI is an open-source toolkit for evaluating and improving LLMs and AI agents. It includes features like tracing, evaluations, simulations, datasets, gateway operations, and guardrails.
- eval-view
- Regression testing for AI agents to detect behavioral changes and output quality regressions over time.
Persona
- future-agi
- -
- eval-view
- -
Runtime
- future-agi
- -
- eval-view
- -
License
- future-agi
- Apache-2.0
- eval-view
- The software uses the Apache-2.0 license, offering permissive terms for use and distribution.
Last pushed
- future-agi
- Aug 1, 2026
- eval-view
- Jul 26, 2026
Categories
- future-agi
- AI Agents, Evaluation & Observability
- eval-view
- AI Agents, Evaluation & Observability
Trust and health
Days since push
- future-agi
- 1d
- eval-view
- 6d
Open issues (now)
- future-agi
- 596
- eval-view
- 3
Owner type
- future-agi
- Organization
- eval-view
- User
Full report
- future-agi
- Trust report
- eval-view
- Trust report
Choose future-agi if…
- Pricing: Future-AGI is open-source under the Apache 2.0 license, allowing for free use but with potential paid services through deployment and support channels..
- Requirements: Min 4 GB RAM; Requires Docker.
- Tags unique to future-agi: ai-gateway, docker-compose, evals, llm.
- - Use Future-AGI when you require an end-to-end evaluation platform that supports self-hosting through Docker Compose or VM-based services on public clouds.
When NOT to use future-agi
- - Avoid using Future-AGI if you require Kubernetes or Helm support as of the current state; though these are planned for future release, they are not yet available.
- - If your deployment strategy relies on a managed service like AWS Marketplace, consider other options since it is currently 'Coming Soon'.
Choose eval-view if…
- Pricing: Free to use under the terms of the Apache License, Version 2.0..
- Requirements: Python environment is required for installation and usage.; Installation with pip: `pip install evalview`; Offline support means no live API keys necessary for the basic diff functionality..
- Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing.
- When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls.
When NOT to use eval-view
- If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time.
- When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.
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 Aug 2, 2026
- GitHub forks (future-agi/future-agi) · observed Aug 2, 2026
- Last push (future-agi/future-agi) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (hidai25/eval-view) · observed Aug 2, 2026
- GitHub forks (hidai25/eval-view) · observed Aug 2, 2026
- Last push (hidai25/eval-view) · observed Jul 26, 2026
- License file (Apache-2.0) · observed Aug 2, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: future-agi 1.6k · eval-view 126 (synced Aug 2, 2026).
Common questions
- What is the difference between future-agi and eval-view?
- future-agi: End-to-end platform for evaluating, observing, and improving LLM and AI agent applications. eval-view: Regression testing for AI agents. 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: Future-AGI is open-source under the Apache 2.0 license, allowing for free use but with potential paid services through deployment and support channels.; Requirements: Min 4 GB RAM; Requires Docker; Tags unique to future-agi: ai-gateway, docker-compose, evals, llm; - Use Future-AGI when you require an end-to-end evaluation platform that supports self-hosting through Docker Compose or VM-based services on public clouds.
- When should I choose eval-view over future-agi?
- Choose eval-view over future-agi when Pricing: Free to use under the terms of the Apache License, Version 2.0.; Requirements: Python environment is required for installation and usage.; Installation with pip:
pip install evalview; Offline support means no live API keys necessary for the basic diff functionality.; Tags unique to eval-view: agent-benchmark, agent-evaluation, ai-agents, regression-testing; When you need to track and assess the behavior consistency of your AI agent across versions without involving live API calls. - When should I avoid future-agi?
- - Avoid using Future-AGI if you require Kubernetes or Helm support as of the current state; though these are planned for future release, they are not yet available. - If your deployment strategy relies on a managed service like AWS Marketplace, consider other options since it is currently 'Coming Soon'.
- When should I avoid eval-view?
- If you do not need to monitor specific behavioral characteristics such as tool call sequences and parameter consistency over time. When real-time output quality evaluation is critical, as eval-view's offline diffing does not provide immediate feedback on output changes without an LLM judge.
- Is future-agi or eval-view more popular on GitHub?
- future-agi has more GitHub stars (1,559 vs 126). 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: 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 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.