OpenEvidence CI Integration
Overview
Set up CI/CD for OpenEvidence clinical decision support integrations: run unit tests with mocked evidence query and citation responses on every PR, validate live API connectivity for clinical queries on merge to main. OpenEvidence provides AI-powered medical evidence retrieval and clinical decision support, so CI pipelines verify query formatting, evidence parsing, citation extraction, and response quality scoring.
GitHub Actions Workflow
# .github/workflows/openevidence-ci.yml
name: OpenEvidence CI
on:
pull_request:
paths: ['src/openevidence/**', 'tests/**']
push:
branches: [main]
jobs:
unit-tests:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- run: npm ci
- run: npm test -- --reporter=verbose
integration-tests:
if: github.ref == 'refs/heads/main'
needs: unit-tests
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with: { node-version: '20' }
- run: npm ci
- run: npm run test:integration
env:
OPENEVIDENCE_API_KEY: ${{ secrets.OPENEVIDENCE_API_KEY }}
Mock-Based Unit Tests
// tests/openevidence-service.test.ts
import { describe, it, expect, vi } from 'vitest';
import { queryEvidence, extractCitations } from '../src/openevidence-service';
vi.mock('../src/openevidence-client', () => ({
OpenEvidenceClient: vi.fn().mockImplementation(() => ({
query: vi.fn().mockResolvedValue({
answer: 'Current evidence supports early intervention with GLP-1 agonists...',
confidence: 0.92,
citations: [
{ title: 'NEJM 2025 Meta-Analysis', doi: '10.1056/NEJMoa2501234', year: 2025 },
{ title: 'Lancet Diabetes Review', doi: '10.1016/S2213-8587(25)00123', year: 2025 },
],
evidenceLevel: 'high',
}),
listQueries: vi.fn().mockResolvedValue({
queries: [{ id: 'q_abc', question: 'GLP-1 efficacy', status: 'completed' }],
}),
})),
}));
describe('OpenEvidence Service', () => {
it('queries clinical evidence with citations', async () => {
const result = await queryEvidence('GLP-1 agonist efficacy for type 2 diabetes');
expect(result.confidence).toBeGreaterThan(0.9);
expect(result.citations).toHaveLength(2);
});
it('extracts citation DOIs from response', async () => {
const citations = await extractCitations('q_abc');
expect(citations[0].doi).toMatch(/^10\.\d+/);
});
});
