Comparison
continuous-eval vs ragas
Verdict
Pick continuous-eval if continuous-eval is a Python framework for evaluating large language models, with emphasis on evaluation metrics and information retrieval; pick ragas if ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights.
Markdown twin · continuous-eval alternatives · ragas alternatives
GraphCanon updated Sep 20, 2026
17views this month
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Trust & integrity
| Signal | continuous-eval | ragas |
|---|---|---|
| Maintenance | Steady (40d since push) As of Sep 20, 2026 · github_public_v1 | Slowing (207d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 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
- continuous-eval
- Data-Driven Evaluation for LLM-Powered Applications
- ragas
- Supercharge Your LLM Application Evaluations 🚀
Stars
- continuous-eval
- 517
- ragas
- 16k
Forks
- continuous-eval
- 38
- ragas
- 1.7k
Open issues
- continuous-eval
- 14
- ragas
- 601
Language
- continuous-eval
- Python
- ragas
- Python
Adopt for
- continuous-eval
- Continuous-eval is a Python framework for evaluating large language models, with emphasis on evaluation metrics and information retrieval.
- ragas
- Ragas is a Python-based tool designed to enhance the evaluation process of Large Language Model (LLM) applications through specialized workflows and performance insights.
Persona
- continuous-eval
- -
- ragas
- developer harness
Runtime
- continuous-eval
- -
- ragas
- -
License
- continuous-eval
- Continuous-eval is available under the Apache-2.0 license, allowing free use with attribution and no warranty provided by the authors.
- ragas
- Apache-2.0
Last pushed
- continuous-eval
- Aug 10, 2026
- ragas
- Feb 24, 2026
Categories
- continuous-eval
- Data & Retrieval, Evaluation & Observability
- ragas
- Evaluation & Observability
Trust and health
Maintenance
- continuous-eval
- Steady (60%)
- ragas
- Slowing (36%)
Days since push
- continuous-eval
- 40d
- ragas
- 207d
Open issues (now)
- continuous-eval
- 14
- ragas
- 601
Stars delta
- continuous-eval
- +1 (30d)
- ragas
- +395 (30d)
Open issues delta
- continuous-eval
- +2 (30d)
- ragas
- +39 (30d)
Full report
- continuous-eval
- Trust report
- ragas
- Trust report
Typed relationship
continuous-eval alternative ragasBoth `continuous-eval` and `ragas` aim to provide comprehensive evaluation capabilities for LLM applications, making them alternatives.
Shared compatibility
- Python · continuous-eval: Python runtime · ragas: Python runtime
Choose continuous-eval if…
- Pricing: The framework itself is open source and free to use, but enhanced or enterprise features may require additional cost..
- Both `continuous-eval` and `ragas` aim to provide comprehensive evaluation capabilities for LLM applications, making them alternatives.
- Tags unique to continuous-eval: evaluation-framework, evaluation-metrics, information retrieval, llm-evaluation.
- Also covers Data & Retrieval.
- When developing LLM-powered applications where a continuous evaluation of model performance over time is required.
When NOT to use continuous-eval
- If your project strictly focuses on small scale or simple applications that do not require robust evaluation metrics or information retrieval features.
- When working in environments where Python is not preferred, as continuous-eval is specifically built for Python applications.
Choose ragas if…
- Both `continuous-eval` and `ragas` aim to provide comprehensive evaluation capabilities for LLM applications, making them alternatives.
- Tags unique to ragas: evaluation, llm.
- When you need advanced tools tailored for evaluating LLM applications, as RAGAS offers specific optimizations not found in generic testing frameworks.
When NOT to use ragas
- If your application does not involve Large Language Models or if the evaluation needs are basic; RAGAS is optimized for LLM-specific evaluations which may be overkill for simpler systems.
- For projects that require real-time monitoring or continuous testing of live models where more dynamic observability tools might offer better support.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (relari-ai/continuous-eval) · observed Sep 20, 2026
- GitHub forks (relari-ai/continuous-eval) · observed Sep 20, 2026
- Last push (relari-ai/continuous-eval) · observed Aug 10, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 14, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (vibrantlabsai/ragas) · observed Sep 20, 2026
- GitHub forks (vibrantlabsai/ragas) · observed Sep 20, 2026
- Last push (vibrantlabsai/ragas) · observed Feb 24, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: continuous-eval 517 · ragas 16k (synced Sep 20, 2026).
Common questions
- What is the difference between continuous-eval and ragas?
- continuous-eval: Data-Driven Evaluation for LLM-Powered Applications. ragas: Supercharge Your LLM Application Evaluations 🚀. See the comparison table for live GitHub stats and shared categories.
- When should I choose continuous-eval over ragas?
- Choose continuous-eval over ragas when Pricing: The framework itself is open source and free to use, but enhanced or enterprise features may require additional cost.; Both
continuous-evalandragasaim to provide comprehensive evaluation capabilities for LLM applications, making them alternatives; Tags unique to continuous-eval: evaluation-framework, evaluation-metrics, information retrieval, llm-evaluation; Also covers Data & Retrieval; When developing LLM-powered applications where a continuous evaluation of model performance over time is required. - When should I choose ragas over continuous-eval?
- Choose ragas over continuous-eval when Both
continuous-evalandragasaim to provide comprehensive evaluation capabilities for LLM applications, making them alternatives; Tags unique to ragas: evaluation, llm; When you need advanced tools tailored for evaluating LLM applications, as RAGAS offers specific optimizations not found in generic testing frameworks. - When should I avoid continuous-eval?
- If your project strictly focuses on small scale or simple applications that do not require robust evaluation metrics or information retrieval features. When working in environments where Python is not preferred, as continuous-eval is specifically built for Python applications.
- When should I avoid ragas?
- If your application does not involve Large Language Models or if the evaluation needs are basic; RAGAS is optimized for LLM-specific evaluations which may be overkill for simpler systems. For projects that require real-time monitoring or continuous testing of live models where more dynamic observability tools might offer better support.
- Is continuous-eval or ragas more popular on GitHub?
- ragas has more GitHub stars (15,783 vs 517). Stars measure visibility, not whether either tool fits your constraints.
- Are continuous-eval and ragas open source?
- Yes - both are open-source projects on GitHub (continuous-eval: Apache-2.0, ragas: Apache-2.0).
- Where can I find alternatives to continuous-eval or ragas?
- GraphCanon lists graph-backed alternatives at continuous-eval alternatives and ragas alternatives (continuous-eval markdown twin, ragas 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, continuous-eval or ragas?
- continuous-eval: Steady. ragas: 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 continuous-eval and ragas?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: continuous-eval trust report; ragas trust report.