Comparison
deepeval vs agent-learning-kit
Verdict
Pick deepeval if deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies; pick agent-learning-kit if agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB.
Markdown twin · deepeval alternatives · agent-learning-kit alternatives
GraphCanon updated 3w
vs
Trust & integrity
| Signal | deepeval | agent-learning-kit |
|---|---|---|
| Maintenance | Very active (1d since push) As of 3w · github_public_v1 | Very active (0d since push) As of 3w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 3w · github_public_v1 | Not a fork · Organization 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
- deepeval
- LLM Evaluation Framework.
- agent-learning-kit
- Evaluation Framework for all your AI related Workflows
Stars
- deepeval
- 17k
- agent-learning-kit
- 118
Forks
- deepeval
- 1.7k
- agent-learning-kit
- 43
Open issues
- deepeval
- 404
- agent-learning-kit
- 6
Language
- deepeval
- Python
- agent-learning-kit
- Python
Adopt for
- deepeval
- Deepeval is a Python-based framework designed for evaluating large language models with an array of metrics and evaluation methodologies.
- agent-learning-kit
- Agent-learning-kit is a Python framework for evaluating AI-related workflows with modules for faithfulness assessment, embedding similarity analysis, and feedback loop integration via ChromaDB.
Persona
- deepeval
- -
- agent-learning-kit
- -
Runtime
- deepeval
- -
- agent-learning-kit
- -
License
- deepeval
- Apache-2.0 License
- agent-learning-kit
- Apache-2.0
Last pushed
- deepeval
- Jul 27, 2026
- agent-learning-kit
- Aug 1, 2026
Categories
- deepeval
- Evaluation & Observability
- agent-learning-kit
- Evaluation & Observability
Trust and health
Days since push
- deepeval
- 1d
- agent-learning-kit
- 0d
Open issues (now)
- deepeval
- 404
- agent-learning-kit
- 6
Full report
- deepeval
- Trust report
- agent-learning-kit
- Trust report
Shared compatibility
- Python · deepeval: Python runtime · agent-learning-kit: Python runtime
Choose deepeval if…
- Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities..
- Tags unique to deepeval: llm-evaluation, metrics.
- When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
When NOT to use deepeval
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill.
- In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
Choose agent-learning-kit if…
- Tags unique to agent-learning-kit: ai-agents, ci-cd, ml.
- When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed.
- More recently updated (last pushed Aug 1, 2026).
When NOT to use agent-learning-kit
- If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit.
- When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (confident-ai/deepeval) · observed Jul 28, 2026
- GitHub forks (confident-ai/deepeval) · observed Jul 28, 2026
- Last push (confident-ai/deepeval) · observed Jul 27, 2026
- License file (Apache-2.0) · observed Jul 28, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (future-agi/agent-learning-kit) · observed Aug 1, 2026
- GitHub forks (future-agi/agent-learning-kit) · observed Aug 1, 2026
- Last push (future-agi/agent-learning-kit) · observed Aug 1, 2026
- License file (Apache-2.0) · observed Aug 1, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deepeval 17k · agent-learning-kit 118 (synced Jul 28, 2026).
Common questions
- What is the difference between deepeval and agent-learning-kit?
- deepeval: LLM Evaluation Framework.. agent-learning-kit: Evaluation Framework for all your AI related Workflows. See the comparison table for live GitHub stats and shared categories.
- When should I choose deepeval over agent-learning-kit?
- Choose deepeval over agent-learning-kit when Requirements: Requires Python environment and familiarity with large language models to effectively utilize Deepeval's capabilities.; Tags unique to deepeval: llm-evaluation, metrics; When developing large language models and you need a comprehensive evaluation framework to measure their performance across various metrics.
- When should I choose agent-learning-kit over deepeval?
- Choose agent-learning-kit over deepeval when Tags unique to agent-learning-kit: ai-agents, ci-cd, ml; When you need comprehensive evaluation of your AI models including faithfulness checks using DeBERTa NLI model installed; More recently updated (last pushed Aug 1, 2026).
- When should I avoid deepeval?
- For small-scale applications that do not require the depth of metrics and evaluations offered by Deepeval, as it might be overkill. In situations where there is a need for real-time performance monitoring, since Deepeval focuses more on post-development evaluation rather than continuous runtime analysis.
- When should I avoid agent-learning-kit?
- If your workflow does not align with the specific evaluation criteria and methods supported by agent-learning-kit. When you seek a framework that integrates with backend systems other than those provided as optional extras, such as MongoDB or DynamoDB instead of ChromaDB.
- Is deepeval or agent-learning-kit more popular on GitHub?
- deepeval has more GitHub stars (17,226 vs 118). Stars measure visibility, not whether either tool fits your constraints.
- Are deepeval and agent-learning-kit open source?
- Yes - both are open-source projects on GitHub (deepeval: Apache-2.0, agent-learning-kit: Apache-2.0).
- Where can I find alternatives to deepeval or agent-learning-kit?
- GraphCanon lists graph-backed alternatives at deepeval alternatives and agent-learning-kit alternatives (deepeval markdown twin, agent-learning-kit 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, deepeval or agent-learning-kit?
- deepeval: Very active. agent-learning-kit: 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 deepeval and agent-learning-kit?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deepeval trust report; agent-learning-kit trust report.