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#!/usr/bin/env python3
"""
Compare /api/search latency + diversity with and without MMR.
"""
import os
import statistics
import time
import requests
BASE_URL = os.getenv("BIOFLOW_API_URL", "http://localhost:8000")
QUERIES = [
"EGFR inhibitor",
"BRCA1 breast cancer",
"kinase inhibitor therapy",
"TP53 mutation cancer",
"lung cancer EGFR signaling",
]
def run_batch(use_mmr: bool, runs: int = 10):
latencies = []
diversities = []
for i in range(runs):
q = QUERIES[i % len(QUERIES)]
t0 = time.perf_counter()
r = requests.post(
f"{BASE_URL}/api/search",
json={"query": q, "top_k": 20, "use_mmr": use_mmr, "modality": "auto"},
timeout=30,
)
dt = (time.perf_counter() - t0) * 1000.0
if r.status_code != 200:
continue
data = r.json()
latencies.append(dt)
if data.get("diversity_score") is not None:
diversities.append(float(data.get("diversity_score") or 0))
return latencies, diversities
if __name__ == "__main__":
print("MMR Benchmark")
lat_no, div_no = run_batch(False, runs=10)
lat_yes, div_yes = run_batch(True, runs=10)
def _stats(xs):
if not xs:
return "n/a"
return f"p50={statistics.median(xs):.1f}ms avg={statistics.mean(xs):.1f}ms"
print(f"MMR OFF: {_stats(lat_no)} | diversity avg={statistics.mean(div_no) if div_no else 'n/a'}")
print(f"MMR ON : {_stats(lat_yes)} | diversity avg={statistics.mean(div_yes) if div_yes else 'n/a'}")
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