vectara / open-rag-eval
RAG evaluation without the need for "golden answers"
Why this job: says: rag; topics: rag, retrieval-augmented-generation
What it does
- Standard Metrics. Provides TREC-RAG evaluation metrics ready to use. See METRICS.md for detailed documentation.
- Modular Architecture. Easily add custom evaluation metrics or integrate with any RAG pipeline.
- Detailed Reporting. Generates per-query scores and intermediate outputs for debugging and analysis.
- Visualization. Compare results across different configurations or runs with plotting utilities.
Get started
pip install open-rag-evalYou need: Python: Version 3.9 or higher.; OpenAI API Key: Required for the default LLM judge model used in some metrics. Set this as an environment variable: export OPENAI_API_KEY='your-api-key'; Factual Consistency Evaluation: For hallucination detection, you can choose between two options:
- Maintenance
- Active
- Last commit 32 days ago
- Stars
- 422
- +3 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.3.0
- Released 10 months ago
- Built with
- Python
- 100% of the code
Is it looked after?
- Contributors
- 2
- Last 90 days
- Issues
- 76% closed
- 10 still open
- Pull requests
- 109 merged
- 8 waiting
- Releases
- 14
- 2 in the last year
- Contributing guide (opens in new tab)
- Security policy (opens in new tab)
- No code of conduct
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More: languages, topics and project record
Languages
- Python 100%
- Dockerfile <1%
- Makefile <1%
Topics
- evaluation-metrics
- metrics
- rag
- rag-evaluation
- retrieval-augmented-generation
- vectara
Project record
- JobRAG and search
- StatusListed
- Commits220
- Forks32
- Watching5
- Stars in 28 days+10
- CreatedNov 26, 2024
- First seen by usNov 7, 2026
- CheckedNov 7, 2026