Feature/full stack integration#7
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- Add CORS middleware (allows frontend on port 5173) - Fix N+1 query in jobs/savedByMember (add SavedJob.job relationship) - Fix savedByMember loop to use relationship instead of re-querying DB
- Add Redis client (app/core/redis.py) with graceful fallback - Cache jobs/get (TTL 300s), jobs/search (TTL 120s), members/get (TTL 300s) - Invalidate cache on job update, close, save - Invalidate cache on member update, delete - Add Redis service to docker-compose.yml - Add redis==5.0.1 to requirements.txt
- Add get_optional_user dependency for unauthenticated access - Publish profile.viewed event with correct entity_id (profile owner) - Time-bucketed idempotency_key to prevent view inflation on refresh - Increment profile_views count on each unique view
Made-with: Cursor
- Load jobs from clean_jobs.csv (Kaggle LinkedIn Job 2023 dataset) - Load members from Resume.csv (Kaggle Resume dataset) - Top up to 10K using faker for missing records - Seed 10K connections, 10K applications, 5K saved jobs - Add Application model (applications table)
- Add connection pooling (pool_size=10, max_overflow=20, pool_recycle=1800) - Add compound indexes for analytics queries on job_postings, applications, members, connections, saved_jobs - Add topup_recruiters.py script to reach 10K recruiters - Update schema.sql with compound indexes
Made-with: Cursor
- 10K members, 10K recruiters, 10K jobs, 10K connections - 10K applications, 5K saved jobs, 500 companies - Load with: mysql -u root -p linkedin_simulation < datasets/linkedin_simulation_seed.sql
- Fix docker-compose to use environment vars instead of .env.example - Add healthcheck for MySQL so backend waits for DB to be ready Backend uses Docker service names (mysql, mongo, redis, kafka) - Add deploy.replicas config for scaling
- Run 4-config Scenario A benchmark against POST /jobs/search (port 8000, 100 threads, 60s) B: 1217ms / 74.9 req/s | B+S: 1119ms / 81.4 req/s B+S+K: 1156ms / 78.8 req/s | B+S+K+Other: 1197ms / 76.1 req/s - Update generate_chart.py with measured values and corrected annotations - Add scenario_A_read_benchmark.jmx targeting /jobs/search on port 8000 - Fix backend/requirements.txt: add cryptography for MySQL auth
- Add Career Coach slide-over on Jobs with portal-based drawer and recruiter-style polish - CareerCoachPanel with recruiterTheme, offline/API coaching helpers and tests - Align Agentic Copilot and charts with LinkedIn blue palette; integration docs and API env notes - Resume matcher utilities, Profile/Jobs wiring, mock analytics color tweaks Co-authored-by: Cursor <cursoragent@cursor.com>
- Polyfill DOMMatrix/Path2D in Vitest for pdfjs imports. - Jobs: sync selected job with filtered list; keyword search data-testid. - Jobs tests: industry + keyword filter via fireEvent.change; scoped queries. - package.json: add npm run ci (lint, test:run, build). Co-authored-by: Cursor <cursoragent@cursor.com>
…ons, analytics) - Backend: CORS for local Vite on any port, auth/me company_id, registration returns JWT, applications and analytics routes, redis_url in settings, health/ready. - Frontend: API client fix, DB-first MockDataContext, lazy routes + dynamic pdfjs load, unwrapSuccessEnvelope for jobs/applications/analytics. - Docs: root README quick start, docs/INTEGRATION.md, scripts/local-full-stack.sh. - Gitignore: env files, pycache, venv. Co-authored-by: Cursor <cursoragent@cursor.com>
- All 4 topics publishing correctly: job.viewed, job.saved, connection.requested, profile.viewed - consumer.py consuming and storing to MongoDB events collection - Idempotency working via unique index on idempotency_key - Added create_kafka_topics.sh for easy topic setup
Integration Complete - M3/M4 Backend + Full-Stack Features + Datasets MERGED COMPONENTS: - Core backend fixes: Redis config, MongoDB return True, Kafka yield fix - All 4 event types: job.viewed, profile.viewed, connection.requested, application.submitted - Redis caching (12x speedup verified) - Complete Kafka pipeline (55+ events in MongoDB) - Full-stack integration features - Docker healthchecks for reliable startup - Cryptography dependency added - Complete datasets: SQL seed + 2000+ resume PDFs - Performance benchmarks and charts RESOLVED CONFLICTS: - docker-compose.yml: Merged healthchecks + M3/M4 services - requirements.txt: Added cryptography==43.0.3 - router.py: Kept M3/M4 routes active, M5 routes commented - All route files preserved with Kafka integration
…h Kafka and Redis - Add application-service, messaging-service, analytics-service with Kafka and Redis - Per-service docker-compose.yml with include: in root compose
Integration fixes for May 5, 2026 demo: Infrastructure: - Add frontend Dockerfile with Node 20 for Vite compatibility - Add nginx configs for frontend SPA and API gateway routing - Fix Docker environment configs for container networking Backend Integration: - Update backend/.env for Docker container hostnames - Add idempotent MongoDB index creation to prevent crashes - Comment out duplicate indexes in analytics-service - Add resume upload script (1706 PDFs → MongoDB GridFS) Services Integrated: ✅ MySQL (10K jobs, members with MongoDB resume links) ✅ MongoDB (events, messages, threads, 1706 resumes) ✅ Redis (caching functional) ✅ Kafka (job.viewed, application.submitted events) ✅ api-backend (FastAPI M3/M4) ✅ application-service (M5/M6) ✅ messaging-service (M5/M6) ✅ analytics-service (M5/M6) ✅ api-gateway (NGINX routing) ✅ client (React frontend) All integration tests passed - ready for demo.
…on-seeddataRemote Add files via upload
- Add Python script to seed 10K resumes to MongoDB GridFS - Add script to sync MySQL resume URLs with GridFS file IDs - All 10,000 members now have PDF resumes in MongoDB - Resume URLs format: mongodb://resumes/member_XXXXXX - Cycles through 1,706 source PDFs to populate all members Database Status: ✅ MySQL: 10,000 members with GridFS URLs ✅ MongoDB: 10,000 resume files + 10,000 chunks ✅ Full cross-reference working
- Introduced a comprehensive integration test script for the LinkedIn simulation, covering end-to-end functionality across microservices. - Added .flake8 configuration for Python code style enforcement. - Created a new .gitignore file to manage ignored files. - Updated docker-compose.yml to include a new environment variable for demo seeding. - Added TEAM_SETUP_GUIDE.md for streamlined team onboarding and setup instructions. - Included merge.md for branch comparison documentation. - Removed outdated seed_data.py and linked SQL seed files to streamline data seeding process.
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Merge final working code to main