a88ea918bf8fb11d9edbd01f8f3c9d827f2f6126
5
Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
  poimenandrock
|
a88ea918bf |
test: production ingest E2E test suite with enhanced logging (#55)
## Summary
Production testing of ingest + embedding pipeline with api-gw integration.
## Root Cause
9 SQL migrations in `crates/mem-store/migrations/` not applied to production database.
Missing tables:
- `memory_entity`
- `memory_edge`
- `memory_edge_temporal`
- Vector embeddings tables
- And 15+ more schema objects
Evidence from logs:
```
WARN: Failed to save entity Docker:
error returned from database: relation "memory_entity" does not exist
```
## Deliverables
- `test_prod_ingest_real.sh` - Full E2E test against K8s + api-gw
- `apply_migrations.sh` - Manual schema migration (backup)
- `collect_prod_logs.sh` - Pod log collection before/after
- `run_production_test.sh` - Test orchestrator
- `tests/integration_ingest_with_gw.rs` - Integration test
- `tests/unit_ingest_logging.rs` - Unit tests for extraction
- Enhanced logging in `ingest_worker.rs` - Per-record event tracking
## Next Steps
1. Trigger "DB Migration" workflow in Forgejo Actions
2. This applies all 9 migrations from `crates/mem-store/migrations/`
3. Pod restart (automatic)
4. Re-run E2E test - should pass completely
**ETA:** ~15 minutes (3-5 min migrations + 2 min restart + verification)
## How to Test Locally
```bash
./test_prod_ingest_real.sh --verbose
```
Requires:
- kubectl access to poimen namespace
- Port-forwarding to memory-service
---------
Co-authored-by: rock <[email protected]>
Reviewed-on: #55
Co-authored-by: poimen <[email protected]>
|
||
|
poimenandrock
|
4169effd8a |
feat: complete observability stack (O1-O13) (#52)
## Complete Observability Stack (O1-O13) Implements all 13 observability issues in a single PR. 119 metrics total. ### Commits (one per issue) | Issue | Title | Metrics | |-------|-------|---------| | **O10** | Prometheus metrics module + /metrics endpoint | Foundation | | **O1** | Instrument ingest handler | I1-I12 (12) | | **O2** | Instrument query handler | Q1-Q12 (12) | | **O3** | Instrument context endpoint | C1-C8 (8) | | **O4** | Relevance judge | R1-R9 (9) | | **O5** | Write volume + storage metrics | W1-W12 (12) | | **O6** | Pod resource observability | P1-P13 | | **O7** | Availability + dependency health | A1-A10 (10) | | **O8** | Ingest rate pattern tracking | IR1-IR10 (10) | | **O9** | Postgres internal observability | PG1-PG33 | | **O11** | Grafana dashboard | 12 panels | | **O12** | Prometheus alerting rules | 11 alerts | | **O13** | Relevance evaluation CronJob | K8s manifest | ### Key Changes - **metrics.rs**: Zero-dependency Prometheus metrics (Counter, Gauge, Histogram, Timer) - **GET /metrics**: Prometheus text exposition format endpoint - **Ingest/Query/Context handlers**: Instrumented with latency, errors, auth failures - **Health check**: DB dependency check with latency tracking - **Background task**: Periodic DB stats collection (entity/edge counts, pool stats) - **Relevance judge**: Threshold-based eval with precision/recall/F1 tracking - **Grafana dashboard**: 12 panels covering all metric groups - **Alert rules**: 11 PrometheusRule alerts (availability, latency, errors, quality) - **CronJob**: Periodic relevance evaluation with sample queries ### Testing - 506 tests passing (0 failures) - All metrics modules have unit tests - Relevance judge: 4 tests ### Deploy ```bash # Grafana dashboard kubectl apply -f k8s/infra/grafana-dashboard.json # Prometheus alerts kubectl apply -f k8s/infra/prometheus-alerts.yaml # Relevance eval CronJob kubectl apply -f k8s/infra/relevance-eval-cronjob.yaml ``` Closes #27 #28 #29 #30 #31 #32 #33 #34 #35 #36 #37 #38 #39 --------- Co-authored-by: rock <[email protected]> Reviewed-on: #52 Co-authored-by: poimen <[email protected]> |
||
|
poimenandrock
|
d7a36ce9e8 |
ci: optimize build + deploy + migrate workflows (#51)
## Optimize CI/CD Workflows ### Changes #### build.yaml - **Merge 3 cargo steps → 1 compile pass**: `cargo build`, `cargo test`, `cargo clippy` now run in single invocation, reusing compiled artifacts - **Remove `cargo clean`**: Eliminated wasteful step that deleted artifacts before Docker build - **Add secret validation**: Registry credentials checked before login (fail-fast) #### deploy.yaml - **Skip checkout**: Removed unnecessary git clone - **Fetch SHA via Gitea API**: Query latest commit directly instead of cloning - **Reuse existing token**: Use `FORGEJO_REGISTRY_TOKEN` for Gitea API auth (already has privileges) - **Validate image exists**: Check SHA image exists before tagging as latest (prevents tagging non-existent images) - **Add secret validation**: Registry credentials checked before login (fail-fast) #### migrate.yaml - **Merge schema verification**: Schema inspect result reused in both changed + manual paths - **Fix manual trigger errors**: Manual mode now fails on first migration error (was silently masking with `|| true`) - **Track failures**: Explicit FAILED flag tracks migration errors across loop ### Benefits - **Speed**: Fewer compiles, no unnecessary clones, reuse artifacts - **Reliability**: Secret validation catches configuration issues early - **Safety**: Image existence check prevents tagging phantom images - **Clarity**: Merged steps have descriptive names, explicit error handling ### Testing - Branch: `ci/optimize-workflows` - Ready to merge to `main` after review --------- Co-authored-by: rock <[email protected]> Reviewed-on: #51 Co-authored-by: poimen <[email protected]> |
||
|
poimenandrock
|
9f70109c1d |
feat: scale memory-db to 3 replicas for HA (#50)
✅ All 3 replicas running and synced - memory-db-1 (primary) - memory-db-2 (replica, LSN 0/9000060) - memory-db-3 (replica, LSN 0/9000060) Cluster status: healthy Production-ready for failover. --------- Co-authored-by: rock <[email protected]> Reviewed-on: #50 Co-authored-by: poimen <[email protected]> |
||
|
poimenandrock
|
fb61de6b47 |
feat: LLM entity + fact extraction pipeline (Zep paper alignment) (#48)
## Changes
### Entity Extraction
- Switch from WikiLinkFallbackExtractor to LlmEntityExtractor when LLM_ENDPOINT set
- `clean_llm_response()`: strips `<think>` tags, markdown fences, extracts JSON
- Handle array responses (Ollama returns `[...]` not `{entities: [...]}`)
- EntityType custom Deserialize: unknown variants → Unknown (no crash)
- Increase timeout 30s→90s, max_tokens 500→1500 for reasoning models
- Graceful reflection fallback: keep entities if verification fails
### Fact Extraction (NEW)
- LlmFactExtractor: LLM-based relationship extraction between entity pairs
- Validates source/target against known entity list (drops hallucinated edges)
- Same robust JSON cleaning for reasoning models + Ollama
- IngestWorker auto-selects LLM vs Simple based on LLM_ENDPOINT env
### K8s Deployment
- Add `command: ["/app/mem"]` (fix args replacing CMD)
- Add LLM_ENDPOINT, LLM_MODEL env vars for in-cluster LLM
## E2E Tested (local Ollama qwen2.5:3b)
- 12 entities extracted (person, tool, concept, organization)
- 5 edges with relationships and facts
- 781 tests pass
## Zep Paper Alignment (§2.2)
- Entity extraction + resolution (§2.2.1)
- Fact extraction between entity pairs (§2.2.2)
- Temporal edge invalidation ready (t_valid/t_invalid schema)
- Reflection verification (§2.2.1, graceful fallback)
---------
Co-authored-by: rock <[email protected]>
Reviewed-on: #48
Co-authored-by: poimen <[email protected]>
|