LLM Evaluator ⚖️

LLM-as-a-Judge evaluation system powered by Langfuse. Uses GPT-5-nano to score AI outputs.

When to Use

• Evaluating quality of search results or AI responses
• Scoring traces for relevance, accuracy, hallucination detection
• Batch scoring recent unscored traces
• Quality assurance on agent outputs

Usage

# Test with sample cases
python3 {baseDir}/scripts/evaluator.py test

# Score a specific Langfuse trace
python3 {baseDir}/scripts/evaluator.py score <trace_id>

# Score with specific evaluator only
python3 {baseDir}/scripts/evaluator.py score <trace_id> --evaluators relevance

# Backfill scores on recent unscored traces
python3 {baseDir}/scripts/evaluator.py backfill --limit 20

Evaluators

| Evaluator | Measures | Scale | |-----------|----------|-------| | relevance | Response relevance to query | 0–1 | | accuracy | Factual correctness | 0–1 | | hallucination | Made-up information detection | 0–1 | | helpfulness | Overall usefulness | 0–1 |

Credits

Built by M. Abidi | agxntsix.ai YouTube | GitHub Part of the AgxntSix Skill Suite for OpenClaw agents.

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