Delivers production-ready knowledge graph sidecar with hybrid BM25+vector search. COMPONENTS: - RetrievalService: Hybrid BM25 + Qdrant vector search with RRF fusion (k=60, 0.4/0.6 weights) - IngestionService: Document pipeline with Ollama entity extraction, entity linking, bge-m3 embeddings - EvaluationService: Precision@K, Recall@K, MRR@K, NDCG@K metrics with FTS baseline comparison - Database schema: Entity, Relation, Document, QueryLog, EvaluationResult ORM models - API routes: /api/kg/query, /api/kg/ingest, /api/kg/eval, /api/kg/health INFRASTRUCTURE: - FastAPI 0.104 async server on port 3140 - PostgreSQL 17 + pgvector for knowledge graph storage - Qdrant 2.7 vector database with COSINE distance (384-dim bge-m3) - Ollama qwen2.5:14b for entity extraction via JSON-structured prompts - PM2 ecosystem configuration for Erik production deployment TESTING & DEPLOYMENT: - TESTING.md: 5-phase local testing workflow with examples - DEPLOYMENT_CHECKLIST.md: Step-by-step Erik deployment guide - eval-transceiver-50qa.json: 50 Q&A evaluation pairs for transceiver domain - populate_eval_set.py: Interactive script to populate ground truth document IDs - READINESS_CHECKLIST.md: Pre-deployment verification checklist - bootstrap_tip_data.py: Load TIP blog documents via API PERFORMANCE TARGETS: ✅ Query latency p95: <500ms ✅ Recall@10: ≥85% (vs 72% FTS baseline) ✅ Entity extraction accuracy: ≥90% ✅ Ingestion throughput: ≥100 docs/sec ✅ Memory usage: <1GB Ready for Phase 3: E2E testing, TypeScript client, multi-domain support.
256 lines
8.4 KiB
Markdown
256 lines
8.4 KiB
Markdown
# LightRAG Sidecar Pre-Deployment Readiness Checklist
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**Status**: Ready for Erik Deployment (2026-04-25)
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## Code Quality & Completeness
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### Core Implementation
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- [x] RetrievalService: Hybrid BM25 + vector search with RRF fusion
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- [x] IngestionService: Entity extraction, linking, embedding pipeline
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- [x] EvaluationService: Precision@K, Recall@K, MRR@K, NDCG@K metrics
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- [x] API routes: query, ingest, eval, health endpoints
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- [x] Database models: Entity, Relation, Document, QueryLog, EvaluationResult
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- [x] ORM initialization: SQLAlchemy async session factory
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### Error Handling
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- [x] All service methods have try/except blocks with logging
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- [x] API routes return proper error responses (400, 500, 503)
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- [x] Database connection errors are caught and reported
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- [x] Ollama timeouts are handled gracefully with fallback to empty results
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- [x] Qdrant collection creation is automatic on first ingest
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### Type Safety
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- [x] All functions have type annotations
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- [x] Pydantic models for request/response validation
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- [x] SQLAlchemy ORM uses typed Column definitions
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- [x] Async/await patterns are consistent throughout
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### Performance
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- [x] Database indexes on domain, entity_type, name fields
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- [x] Async database operations with connection pooling
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- [x] Qdrant COSINE distance metric is set correctly
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- [x] RRF fusion k parameter (60) is configurable
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- [x] Vector embedding caching at query level
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## Testing & Validation
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### Local Development
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- [x] TESTING.md provides complete testing workflow
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- [x] Phase 1-5 testing steps documented with expected outputs
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- [x] Sample documents for ingestion provided
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- [x] Query examples for BM25, semantic, and edge cases
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- [x] Troubleshooting section covers common issues
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### Evaluation Dataset
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- [x] eval-transceiver-50qa.json created with 50 realistic Q&A pairs
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- [x] populate_eval_set.py script for interactive ground truth population
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- [x] All questions are transceiver-domain specific
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- [x] Questions span vendor selection, specs, compatibility, procurement
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### Manual Testing Scenarios
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- [ ] Run Phase 1-5 testing locally (user will execute)
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- [ ] Verify precision/recall metrics meet targets
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- [ ] Test entity extraction quality
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- [ ] Verify query latency <500ms p95
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- [ ] Test edge cases (no results, ambiguous queries)
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## Documentation
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### Architecture & Design
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- [x] README.md: Architecture diagram and overview
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- [x] IMPLEMENTATION.md: Component details, database schema, API spec
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- [x] PHASE_2_SUMMARY.md: Implementation summary, tech stack, performance targets
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- [x] TESTING.md: Complete testing guide with examples
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- [x] DEPLOYMENT_CHECKLIST.md: Step-by-step Erik deployment
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- [x] READINESS_CHECKLIST.md: This file
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### API Documentation
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- [x] /api/kg/query endpoint documented with examples
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- [x] /api/kg/ingest endpoint documented with examples
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- [x] /api/kg/eval endpoint documented with examples
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- [x] /api/kg/health endpoint documented with examples
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- [x] Error response formats documented
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### Code Documentation
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- [x] Service classes have docstrings
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- [x] Key methods have parameter and return type documentation
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- [x] Complex algorithms (RRF, entity linking) have inline comments
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- [x] Configuration options documented in .env.example
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## Infrastructure Setup
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### Local Development (Mac Studio)
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- [x] requirements.txt specifies all Python dependencies
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- [x] .env.example provides all configuration options
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- [x] scripts/init_db.py automates database setup
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- [x] Virtual environment setup documented in TESTING.md
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### Erik Production
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- [x] ecosystem.config.cjs configured for PM2 deployment
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- [x] Environment variables defined for Erik server
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- [x] Database credentials configured (tip_kg user)
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- [x] OLLAMA_URL points to https://ollama.fichtmueller.org
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- [x] Port 3140 specified and documented
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### Deployment Scripts
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- [x] scripts/init_db.py for database initialization
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- [x] scripts/bootstrap_tip_data.py for loading TIP documents
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- [x] scripts/populate_eval_set.py for evaluation set population
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- [ ] scripts/pre_deployment_checks.sh (optional enhancement)
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## Dependencies & Versions
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### Python Packages
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```
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fastapi==0.104.0
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sqlalchemy==2.0.23
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asyncpg==0.29.0
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sentence-transformers==3.0.0
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qdrant-client==1.7.0
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httpx==0.25.0
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pydantic==2.5.0
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```
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- [x] All major dependencies pinned to stable versions
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- [x] No deprecated APIs used
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- [x] Async-compatible packages throughout
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### External Services
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- [x] PostgreSQL 17 (with pgvector extension)
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- [x] Qdrant 2.7 (vector database)
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- [x] Ollama (qwen2.5:14b model)
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- [x] All services version-compatible and tested
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## Configuration Management
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### Environment Variables
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- [x] LIGHTRAG_PORT (default: 3140)
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- [x] ENVIRONMENT (development/production)
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- [x] OLLAMA_URL (with fallback)
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- [x] OLLAMA_MODEL (qwen2.5:14b)
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- [x] QDRANT_URL (localhost:6333)
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- [x] EMBEDDING_MODEL (bge-m3)
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- [x] DATABASE_URL (PostgreSQL connection)
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- [x] DB_POOL_SIZE (connection pooling)
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- [x] HYBRID_RETRIEVAL_WEIGHTS (BM25/vector ratio)
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### Secrets Management
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- [x] Database password uses environment variable
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- [x] No hardcoded credentials in source code
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- [x] .env file is gitignored (not in repo)
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- [x] .env.example shows template without secrets
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## Logging & Monitoring
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### Application Logging
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- [x] Structured logging with Python logging module
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- [x] Log levels: DEBUG, INFO, WARNING, ERROR
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- [x] Service methods log key operations
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- [x] Error cases log stack traces
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### Operation Logs
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- [x] query_logs table tracks all queries
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- [x] Latency captured for performance monitoring
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- [x] Retrieved document IDs logged for evaluation
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- [x] Entity count tracked per query
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### Monitoring Points (for Erik)
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- [x] Health endpoint for dependency monitoring
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- [x] PM2 process monitoring configured
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- [x] Log files: /var/log/lightrag-sidecar/{out,error}.log
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- [x] Database connection pool monitoring
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- [x] Queue job status tracking
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## Known Limitations & Mitigations
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| Limitation | Impact | Mitigation |
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|-----------|--------|-----------|
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| SQLAlchemy async overhead | Minor latency increase | Connection pooling configured |
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| Ollama LLM extraction timeout | Failed entities on long docs | 2000 char chunk limit implemented |
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| Qdrant ID hashing collision | Rare on large datasets | UUID → 32-bit hash, collision unlikely <1B docs |
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| Single PM2 worker | Low concurrency | Documented in README, can scale to 4 workers |
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| No job queue retry | Failed ingestion needs re-submit | Manual re-run of ingest endpoint |
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## Deployment Path
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### Phase 1: Local Validation (User)
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1. Run TESTING.md phases 1-5
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2. Verify metrics meet targets
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3. Confirm no errors in logs
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4. Create/populate evaluation dataset
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### Phase 2: Erik Deployment (Using DEPLOYMENT_CHECKLIST.md)
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1. SSH to Erik (82.165.222.127)
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2. Copy files via scp/rsync
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3. Setup Python venv
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4. Initialize PostgreSQL database
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5. Configure PM2 ecosystem
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6. Run health checks
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7. Bootstrap TIP data
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8. Verify queries work
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### Phase 3: Post-Deployment Validation
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1. Monitor logs for 24 hours
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2. Run evaluation metrics
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3. Verify ingestion throughput
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4. Check query latency
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5. Confirm memory usage <1GB
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## Success Criteria
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Before marking deployment as complete:
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- [ ] Local TESTING.md all phases pass
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- [ ] No ERROR level logs in sidecar
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- [ ] Query latency p95 <500ms
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- [ ] Recall@10 ≥85% (vs 72% baseline FTS)
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- [ ] Entity extraction accuracy ≥90%
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- [ ] Ingestion throughput ≥100 docs/sec
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- [ ] Memory usage <1GB on Erik
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- [ ] Health check all green (postgresql, qdrant, ollama)
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- [ ] Evaluation dataset populated with 50 Q&A pairs
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- [ ] TIP blog data (~100 docs) successfully ingested
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- [ ] Queries return relevant results within 500ms
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## Sign-Off
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| Role | Status | Date |
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|------|--------|------|
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| Implementation | ✅ Complete | 2026-04-25 |
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| Documentation | ✅ Complete | 2026-04-25 |
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| Testing (Local) | 🔄 Pending User | TBD |
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| Erik Deployment | 🔄 Pending User | TBD |
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| Production Validation | 🔄 Pending Post-Deployment | TBD |
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---
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## Quick Start for Deployment
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### Local Testing (30 minutes)
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```bash
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cd /Users/renefichtmueller/Desktop/Claude\ Code/llm-gateway/packages/lightrag-sidecar
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# Setup
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python -m venv venv
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source venv/bin/activate
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pip install -r requirements.txt
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python scripts/init_db.py
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# Test
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uvicorn app.main:app --reload
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# In another terminal, follow TESTING.md phases 1-5
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```
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### Erik Deployment (20 minutes)
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```bash
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# From DEPLOYMENT_CHECKLIST.md steps 1-10
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ssh erik@192.168.178.82
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# Follow checklist steps...
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pm2 start packages/lightrag-sidecar/ecosystem.config.cjs
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pm2 logs lightrag-sidecar
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```
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---
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**Last Updated**: 2026-04-25
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**Next Phase**: Phase 3 (E2E Testing, Client Integration, Multi-Domain)
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