GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
ARES is a Python-based tool for automated evaluation of RAG systems, offering scoring and comparison functionalities.
Good fit when
- Use ARES when you need to evaluate RAG systems with specific criteria such as context relevance, answer faithfulness, and answer relevance.
- Consider ARES if you have a human preference validation set of at least 50 annotated query-document-answer triples, and a larger set of unlabeled triples for scoring.
Avoid when
- Do not use ARES if you lack the necessary human-annotated datasets for evaluation criteria or if you do not have a large set of unlabeled triples for scoring.
- Avoid ARES if your machine does not meet the requirements, such as having over 100 GB of available disk space and a compatible GPU like the A100.
- Requirements:
- Requires over 100 GB of available disk space and a compatible GPU like the A100.; Installation of conda and gcc is necessary for setup.
Observed Sep 18, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Dormant (538d since push)
- As of Sep 18, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 18, 2026
- Security (OSV)
- 344 low (344 low)
- As of Sep 18, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
pip install ARESSimilar tools
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Evidence and technical details
Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.
Overview
ARES is a Python-based tool for automated evaluation of RAG (Retrieval-Augmented Generation) systems, providing scoring and comparison functionalities.
Capability facts
- CLI
- CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 18, 2026
- Languages
- python
Source: github.language+pyproject.toml · Sep 18, 2026
Categories
Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 18, 2026)
### Machine requirements and setup when not using OpenAI APISource link
Source: README excerpt (regex_v1, Sep 18, 2026)
```python pip install ares-aiSource link
Tags
README
⚙️ Installation <a id="section1" </a <hr To install ARES, run the following commands: Optional: Initalize OpenAI or TogetherAI API key with the following command: 📝 Requirements <a id="section2" </a <hr To implement ARES for scoring your RAG system and comparing to other R...
For agents
This page has a .md twin and JSON over the API.