Custom Metrics

from honeyhive import HoneyHiveTracer
import os

tracer = HoneyHiveTracer.init(api_key=os.getenv("HH_API_KEY"))

# ... your application logic ...

tracer.enrich_session(metrics={
    "json_valid": True,
    "response_length": 150,
    "safety_score": 0.98,
})

from honeyhive import HoneyHiveTracer, trace
import os

tracer = HoneyHiveTracer.init(api_key=os.getenv("HH_API_KEY"))

@trace
def generate_response(query: str):
    response = call_llm(query)
    
    # Compute metrics
    tracer.enrich_span(metrics={
        "contains_pii": check_pii(response),
        "relevance_score": compute_relevance(query, response),
        "word_count": len(response.split()),
    })
    
    return response

{
  "json_valid": true,
  "relevance_score": 0.85,
  "latency_ms": 250,
  "step_evals": [
    { "step": 1, "passed": true },
    { "step": 2, "passed": false }
  ]
}