Openevidence performance tuning
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'Performance Tuning for OpenEvidence.
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SKILL.md
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OpenEvidence Performance Tuning
Overview
OpenEvidence's clinical API handles evidence query response times, citation batch retrieval, and complex multi-condition query optimization. Clinical evidence queries can take 2-5 seconds as the system searches across thousands of medical studies and synthesizes responses. Citation batch retrieval for systematic reviews generates heavy load when fetching 50-200 references per query. Caching evidence responses, batching citation fetches, and optimizing query specificity reduces clinician wait times by 50-70% and keeps complex queries within acceptable latency bounds.
Caching Strategy
const cache = new Map<string, { data: any; expiry: number }>();
const TTL = { evidence: 1_800_000, citations: 3_600_000, queries: 300_000 };
async function cached(key: string, ttlKey: keyof typeof TTL, fn: () => Promise<any>) {
const entry = cache.get(key);
if (entry && entry.expiry > Date.now()) return entry.data;
const data = await fn();
cache.set(key, { data, expiry: Date.now() + TTL[ttlKey] });
return data;
}
// Citations are stable (1hr). Evidence summaries update with new studies (30 min).
Batch Operations
async function fetchCitationsBatch(client: any, citationIds: string[], batchSize = 25) {
const results = [];
for (let i = 0; i < citationIds.length; i += batchSize) {
const batch = citationIds.slice(i, i + batchSize);
const res = await Promise.all(batch.map(id => client.getCitation(id)));
results.push(...res);
if (i + batchSize < citationIds.length) await new Promise(r => setTimeout(r, 500));
}
return results;
}
Connection Pooling
import { Agent } from 'https';
const agent = new Agent({ keepAlive: true, maxSockets: 6, maxFreeSockets: 3, timeout: 30_000 });
// Moderate socket count — evidence queries are sequential, citations parallel
Rate Limit Management
async function withRateLimit(fn: () => Promise<any>): Promise<any> {
try { return await fn(); }
catch (err: any) {
if (err.status === 429) {
const retryMs = parseInt(err.headers?.['retry-after'] || '10') * 1000;
await new Promise(r => setTimeout(r, retryMs));
return fn();
}
throw err;
}
}
Monitoring
const metrics = { queries: 0, citationFetches: 0, cacheHits: 0, avgLatencyMs: 0, errors: 0 };
function track(op: 'query' | 'citation', startMs: number, cached: boolean) {
metrics[op === 'query' ? 'queries' : 'citationFetches']++;
const lat = Date.now() - startMs;
metrics.avgLatencyMs = (metrics.avgLatencyMs * (metrics.queries - 1) + lat) / metrics.queries;
if (cached) metrics.cacheHits++;
}
Performance Checklist
- Cache evidence responses with 30-min TTL (studies update periodically)
- Cache citation metadata with 1-hour TTL (stable once published)
- Batch citation retrieval in groups of 25 with 500ms pauses
- Use specific condition + intervention queries instead of broad searches
- Prefetch commonly queried drug interaction evidence
- Enable HTTP keep-alive for persistent API connections
- Monitor average query latency (target < 3s for simple queries)
- Set client timeout to 30s for complex multi-condition queries
Error Handling
| Issue | Cause | Fix |
|---|---|---|
| Slow evidence query (> 5s) | Broad multi-condition search | Narrow query to specific condition + intervention |
| 429 on citation batch | Too many parallel citation fetches | Batch to 25, add 500ms delay between groups |
| Stale evidence summary | Cache too long for rapidly evolving topic | Reduce TTL for high-churn topics (e.g., COVID) |
| Timeout on complex query | Multi-study synthesis exceeding limit | Increase timeout to 30s, simplify query scope |
| Missing citations | Study not yet indexed | Retry after 24h, check study publication date |
Resources
- OpenEvidence Platform
- OpenEvidence API Docs
Next Steps
See openevidence-reference-architecture.