69dec8ec34
* feat: add comprehensive OpenTelemetry tracing - Add tool execution spans for reflect operations - Add tool call information (names, params) to spans - Change verification scope from 'test' to 'verification' - Add hindsight.reflect_generation span for done() processing - Implement no-op tracer for improved code readability - Update documentation for OTEL configuration - Resolve merge conflicts from rebase * fix: properly serialize Pydantic models in span recording - Add _serialize_for_span() helper to handle Pydantic models - Update all providers to use the helper function - Fixes test failures with 'Object of type X is not JSON serializable' * feat: add Grafana LGTM stack for unified local observability Add Grafana LGTM (Loki, Grafana, Tempo, Mimir) as the recommended local development observability stack. This provides traces, metrics, and logs in a single Docker container instead of separate tools. Changes: - Add scripts/dev/grafana/ with docker-compose and README - Add scripts/dev/start-grafana.sh startup script - Update .env.example to reference Grafana LGTM - Update configuration docs to emphasize Grafana LGTM as primary option - Reorder OTLP backend list to show Grafana LGTM first Benefits: - Single container vs multiple separate tools (Jaeger, SigNoz, etc.) - ~515MB image with full observability stack - Compatible with existing OTLP configuration - Simpler local development setup * chore: remove SigNoz scripts and references Remove SigNoz observability stack in favor of Grafana LGTM as the sole recommended local development tracing solution. Changes: - Delete scripts/dev/signoz/ directory and all SigNoz configurations - Delete scripts/dev/start-signoz.sh startup script - Remove SigNoz references from .env.example - Remove SigNoz from OTLP backends list in configuration docs Grafana LGTM provides the same capabilities (traces, metrics, logs) in a simpler single-container setup. * feat: add consolidation span hierarchy for tracing Add parent-child span structure for consolidation operations: - hindsight.consolidation: Parent span for each memory being processed - hindsight.consolidation_recall: Child span for finding related observations - LLM call span: Automatically created by LLM provider (scope="consolidation") This enables detailed timing breakdown in Grafana Tempo: - Total consolidation time per memory - Time spent in recall - Time spent in LLM call - Time spent executing actions (create/update) All consolidation tests pass (31/31). * feat: add Prometheus metrics and GenAI dashboard to Grafana stack Add comprehensive metrics and dashboarding to the Grafana LGTM stack: Metrics Collection: - Configure Prometheus to scrape Hindsight API /metrics endpoint - Scrape interval: 10 seconds - Targets hindsight-api on host.docker.internal:8888 GenAI Dashboard: - Pre-configured dashboard with 6 panels: - LLM call rate (by provider/model) - LLM call duration (p50/p95 by scope) - Token usage - input tokens/sec by scope - Token usage - output tokens/sec by scope - Operations rate (retain/recall/reflect/consolidation) - Operation duration p95 by operation type Configuration: - Mount prometheus.yml for metrics scraping - Mount dashboards directory for auto-provisioning - Add host.docker.internal mapping for container->host access - Dashboard provisioning with auto-reload every 10s Documentation: - Updated README with metrics viewing instructions - Added PromQL query examples - Documented dashboard access and navigation This provides full observability: traces (Tempo) + metrics (Prometheus/Mimir) + dashboards (Grafana) * refactor: merge Grafana setup into existing monitoring stack Consolidate the separate scripts/dev/grafana/ setup into the existing scripts/dev/monitoring/ stack, using Grafana LGTM (Loki, Grafana, Tempo, Mimir). Changes: - Remove separate scripts/dev/grafana/ directory and start-grafana.sh - Rewrite scripts/dev/monitoring/start.sh to use Docker + Grafana LGTM (was: download native Prometheus/Grafana binaries) - Add docker-compose.yaml for Grafana LGTM container - Add prometheus.yml for scraping Hindsight API metrics - Mount existing dashboards from monitoring/grafana/dashboards/ - Add comprehensive README.md Benefits: - Single unified monitoring command: ./scripts/dev/start-monitoring.sh - Uses existing dashboard files (hindsight-operations, hindsight-llm, hindsight-api-service) - Simpler setup: Docker-based vs downloading/running native binaries - Full observability: traces + metrics + logs + dashboards in one container - Standard ports: Grafana on 3000, OTLP on 4317/4318 Architecture: - Grafana LGTM container (~515MB) provides all components - Dashboards auto-provisioned from monitoring/grafana/dashboards/ - Prometheus scrapes host.docker.internal:8888/metrics - Shared hindsight-network for future service-to-service tracing * fix: run monitoring stack in foreground for easy Ctrl+C stop Change docker-compose from detached (-d) to foreground mode. Users can now stop the stack with Ctrl+C instead of needing to run docker-compose down separately. * fix: remove invalid home dashboard path and obsolete version field - Remove GF_DASHBOARDS_DEFAULT_HOME_DASHBOARD_PATH environment variable (was pointing to wrong path causing 'Failed to load home dashboard' error) - Remove obsolete 'version' field from docker-compose.yaml (docker-compose v2+ doesn't require version field) * fix: load Hindsight dashboards in Grafana LGTM Mount Hindsight dashboard JSON files and custom provisioning config to make dashboards visible in Grafana. Changes: - Mount hindsight-operations.json, hindsight-llm.json, hindsight-api-service.json to /otel-lgtm/ - Create grafana-dashboards.yaml with all dashboard providers (default + Hindsight) - Mount custom provisioning config to override LGTM default All 3 Hindsight dashboards now appear in Grafana UI with metrics from Prometheus scraping the Hindsight API /metrics endpoint. * fix: configure Prometheus to scrape Hindsight API metrics Update prometheus.yml to include both OTLP receiver config (from LGTM) and scrape_configs for pulling metrics from Hindsight API. Changes: - Mount prometheus.yml to /otel-lgtm/prometheus.yaml (where LGTM reads it) - Add scrape_configs section to pull from host.docker.internal:8888/metrics - Keep OTLP receiver configuration for trace metrics - Set scrape_interval to 5s Verified: Prometheus now successfully scrapes hindsight_llm_calls_total and other Hindsight metrics. Dashboards now show live data! * feat: add comprehensive tracing for recall and improve reflect/mental_model_refresh spans - Add recall operation tracing with parent-child span hierarchy - Parent: hindsight.recall with attributes (bank_id, query, fact_types, etc.) - Children: recall_embedding, recall_retrieval, recall_fusion, recall_rerank - Fixed context propagation using start_as_current_span() - Improve reflect tracing spans - Remove reflect_generation spans, use reflect instead - Change done() tool processing to hindsight.reflect_tool_call - Fix mental_model_refresh span nesting - Add _skip_span parameter to reflect_async to avoid duplicate hindsight.reflect spans - Mental model refresh now has clean span hierarchy without nested reflect parent - Add comprehensive tracing verification tests - Test span hierarchy and attributes for all operations - Verify parent-child relationships - 5 passing tests covering recall, reflect, consolidation, and mental_model_refresh * refactor: remove redundant is_tracing_enabled() checks - Remove all is_tracing_enabled() conditional checks before tracing calls - NoOpTracer/NoOpSpan handle disabled tracing automatically - Simplify code by always calling tracer methods directly - Fix NoOpTracer.start_as_current_span() to yield NoOpSpan instead of None Changes: - memory_engine.py: Remove 5 is_tracing_enabled checks in recall spans - agent.py: Remove 2 is_tracing_enabled checks in reflect tool spans - tracing.py: Fix NoOpTracer context manager to yield proper NoOpSpan This eliminates ~50 lines of redundant conditional code while maintaining identical behavior. * docs: simplify distributed tracing section in monitoring.md - Make tracing documentation more concise - Focus on span hierarchy and attributes - Remove verbose troubleshooting and performance sections - Keep configuration.md for env vars only |
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Website
This website is built using Docusaurus, a modern static website generator.
Installation
npm install
Local Development
npm start
This command starts a local development server and opens up a browser window. Most changes are reflected live without having to restart the server.
Build
npm run build
This command generates static content into the build directory and can be served using any static contents hosting service.
Deployment
Using SSH:
USE_SSH=true npm run deploy
Not using SSH:
GIT_USER=<Your GitHub username> npm run deploy
If you are using GitHub pages for hosting, this command is a convenient way to build the website and push to the gh-pages branch.