* 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
380 lines
15 KiB
Python
380 lines
15 KiB
Python
"""
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Command-line interface for Hindsight API.
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Run the server with:
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hindsight-api
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Run as background daemon:
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hindsight-api --daemon
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Stop with Ctrl+C.
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"""
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import argparse
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import asyncio
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import atexit
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import os
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import signal
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import sys
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import warnings
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import uvicorn
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from . import MemoryEngine, __version__
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from .api import create_app
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from .banner import print_banner
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from .config import DEFAULT_WORKERS, ENV_WORKERS, HindsightConfig, get_config
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from .daemon import (
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DEFAULT_DAEMON_PORT,
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DEFAULT_IDLE_TIMEOUT,
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IdleTimeoutMiddleware,
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daemonize,
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)
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from .extensions import DefaultExtensionContext, OperationValidatorExtension, TenantExtension, load_extension
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# Filter deprecation warnings from third-party libraries
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warnings.filterwarnings("ignore", message="websockets.legacy is deprecated")
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warnings.filterwarnings("ignore", message="websockets.server.WebSocketServerProtocol is deprecated")
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# Disable tokenizers parallelism to avoid warnings
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os.environ["TOKENIZERS_PARALLELISM"] = "false"
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# Global reference for cleanup
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_memory: MemoryEngine | None = None
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def _cleanup():
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"""Synchronous cleanup function to stop resources on exit."""
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global _memory
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if _memory is not None and _memory._pg0 is not None:
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try:
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loop = asyncio.new_event_loop()
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loop.run_until_complete(_memory._pg0.stop())
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loop.close()
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print("\npg0 stopped.")
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except Exception as e:
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print(f"\nError stopping pg0: {e}")
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def _signal_handler(signum, frame):
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"""Handle SIGINT/SIGTERM to ensure cleanup."""
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print(f"\nReceived signal {signum}, shutting down...")
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_cleanup()
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sys.exit(0)
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def main():
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"""Main entry point for the CLI."""
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global _memory
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# Load configuration from environment (for CLI args defaults)
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config = get_config()
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parser = argparse.ArgumentParser(
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prog="hindsight-api",
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description="Hindsight API Server",
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)
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# Server options
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parser.add_argument(
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"--host", default=config.host, help=f"Host to bind to (default: {config.host}, env: HINDSIGHT_API_HOST)"
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)
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parser.add_argument(
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"--port",
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type=int,
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default=config.port,
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help=f"Port to bind to (default: {config.port}, env: HINDSIGHT_API_PORT)",
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)
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parser.add_argument(
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"--log-level",
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default=config.log_level,
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choices=["critical", "error", "warning", "info", "debug", "trace"],
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help=f"Log level (default: {config.log_level}, env: HINDSIGHT_API_LOG_LEVEL)",
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)
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# Development options
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parser.add_argument("--reload", action="store_true", help="Enable auto-reload on code changes (development only)")
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parser.add_argument(
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"--workers",
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type=int,
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default=int(os.getenv(ENV_WORKERS, str(DEFAULT_WORKERS))),
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help=f"Number of worker processes (env: {ENV_WORKERS}, default: {DEFAULT_WORKERS})",
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)
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# Access log options
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parser.add_argument("--access-log", action="store_true", help="Enable access log")
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parser.add_argument("--no-access-log", dest="access_log", action="store_false", help="Disable access log (default)")
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parser.set_defaults(access_log=False)
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# Proxy options
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parser.add_argument(
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"--proxy-headers", action="store_true", help="Enable X-Forwarded-Proto, X-Forwarded-For headers"
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)
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parser.add_argument(
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"--forwarded-allow-ips", default=None, help="Comma separated list of IPs to trust with proxy headers"
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)
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# SSL options
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parser.add_argument("--ssl-keyfile", default=None, help="SSL key file")
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parser.add_argument("--ssl-certfile", default=None, help="SSL certificate file")
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# Daemon mode options
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parser.add_argument(
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"--daemon",
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action="store_true",
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help=f"Run as background daemon (uses port {DEFAULT_DAEMON_PORT}, auto-exits after idle)",
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)
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parser.add_argument(
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"--idle-timeout",
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type=int,
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default=DEFAULT_IDLE_TIMEOUT,
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help=f"Idle timeout in seconds before auto-exit in daemon mode (default: {DEFAULT_IDLE_TIMEOUT})",
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)
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args = parser.parse_args()
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# Daemon mode handling
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if args.daemon:
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# Use port from args (may be custom for profiles)
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if args.port == config.port: # No custom port specified
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args.port = DEFAULT_DAEMON_PORT
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args.host = "127.0.0.1" # Only bind to localhost for security
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# Fork into background
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# No lockfile needed - port binding prevents duplicate daemons
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daemonize()
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# Print banner (not in daemon mode)
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if not args.daemon:
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print()
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print_banner()
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# Configure Python logging based on log level
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# Update config with CLI override if provided
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if args.log_level != config.log_level:
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config = HindsightConfig(
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database_url=config.database_url,
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database_schema=config.database_schema,
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llm_provider=config.llm_provider,
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llm_api_key=config.llm_api_key,
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llm_model=config.llm_model,
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llm_base_url=config.llm_base_url,
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llm_max_concurrent=config.llm_max_concurrent,
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llm_max_retries=config.llm_max_retries,
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llm_initial_backoff=config.llm_initial_backoff,
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llm_max_backoff=config.llm_max_backoff,
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llm_timeout=config.llm_timeout,
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llm_vertexai_project_id=config.llm_vertexai_project_id,
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llm_vertexai_region=config.llm_vertexai_region,
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llm_vertexai_service_account_key=config.llm_vertexai_service_account_key,
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retain_llm_provider=config.retain_llm_provider,
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retain_llm_api_key=config.retain_llm_api_key,
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retain_llm_model=config.retain_llm_model,
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retain_llm_base_url=config.retain_llm_base_url,
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retain_llm_max_concurrent=config.retain_llm_max_concurrent,
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retain_llm_max_retries=config.retain_llm_max_retries,
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retain_llm_initial_backoff=config.retain_llm_initial_backoff,
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retain_llm_max_backoff=config.retain_llm_max_backoff,
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retain_llm_timeout=config.retain_llm_timeout,
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reflect_llm_provider=config.reflect_llm_provider,
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reflect_llm_api_key=config.reflect_llm_api_key,
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reflect_llm_model=config.reflect_llm_model,
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reflect_llm_base_url=config.reflect_llm_base_url,
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reflect_llm_max_concurrent=config.reflect_llm_max_concurrent,
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reflect_llm_max_retries=config.reflect_llm_max_retries,
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reflect_llm_initial_backoff=config.reflect_llm_initial_backoff,
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reflect_llm_max_backoff=config.reflect_llm_max_backoff,
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reflect_llm_timeout=config.reflect_llm_timeout,
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consolidation_llm_provider=config.consolidation_llm_provider,
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consolidation_llm_api_key=config.consolidation_llm_api_key,
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consolidation_llm_model=config.consolidation_llm_model,
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consolidation_llm_base_url=config.consolidation_llm_base_url,
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consolidation_llm_max_concurrent=config.consolidation_llm_max_concurrent,
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consolidation_llm_max_retries=config.consolidation_llm_max_retries,
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consolidation_llm_initial_backoff=config.consolidation_llm_initial_backoff,
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consolidation_llm_max_backoff=config.consolidation_llm_max_backoff,
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consolidation_llm_timeout=config.consolidation_llm_timeout,
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embeddings_provider=config.embeddings_provider,
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embeddings_local_model=config.embeddings_local_model,
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embeddings_local_force_cpu=config.embeddings_local_force_cpu,
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embeddings_tei_url=config.embeddings_tei_url,
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embeddings_openai_base_url=config.embeddings_openai_base_url,
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embeddings_cohere_base_url=config.embeddings_cohere_base_url,
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reranker_provider=config.reranker_provider,
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reranker_local_model=config.reranker_local_model,
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reranker_local_force_cpu=config.reranker_local_force_cpu,
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reranker_local_max_concurrent=config.reranker_local_max_concurrent,
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reranker_tei_url=config.reranker_tei_url,
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reranker_tei_batch_size=config.reranker_tei_batch_size,
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reranker_tei_max_concurrent=config.reranker_tei_max_concurrent,
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reranker_max_candidates=config.reranker_max_candidates,
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reranker_cohere_base_url=config.reranker_cohere_base_url,
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host=args.host,
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port=args.port,
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log_level=args.log_level,
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log_format=config.log_format,
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mcp_enabled=config.mcp_enabled,
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graph_retriever=config.graph_retriever,
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mpfp_top_k_neighbors=config.mpfp_top_k_neighbors,
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recall_max_concurrent=config.recall_max_concurrent,
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recall_connection_budget=config.recall_connection_budget,
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retain_max_completion_tokens=config.retain_max_completion_tokens,
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retain_chunk_size=config.retain_chunk_size,
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retain_extract_causal_links=config.retain_extract_causal_links,
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retain_extraction_mode=config.retain_extraction_mode,
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retain_custom_instructions=config.retain_custom_instructions,
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enable_observations=config.enable_observations,
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consolidation_batch_size=config.consolidation_batch_size,
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consolidation_max_tokens=config.consolidation_max_tokens,
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skip_llm_verification=config.skip_llm_verification,
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lazy_reranker=config.lazy_reranker,
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run_migrations_on_startup=config.run_migrations_on_startup,
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db_pool_min_size=config.db_pool_min_size,
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db_pool_max_size=config.db_pool_max_size,
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db_command_timeout=config.db_command_timeout,
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db_acquire_timeout=config.db_acquire_timeout,
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worker_enabled=config.worker_enabled,
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worker_id=config.worker_id,
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worker_poll_interval_ms=config.worker_poll_interval_ms,
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worker_max_retries=config.worker_max_retries,
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worker_http_port=config.worker_http_port,
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worker_max_slots=config.worker_max_slots,
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worker_consolidation_max_slots=config.worker_consolidation_max_slots,
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reflect_max_iterations=config.reflect_max_iterations,
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mental_model_refresh_concurrency=config.mental_model_refresh_concurrency,
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otel_traces_enabled=config.otel_traces_enabled,
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otel_exporter_otlp_endpoint=config.otel_exporter_otlp_endpoint,
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otel_exporter_otlp_headers=config.otel_exporter_otlp_headers,
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otel_service_name=config.otel_service_name,
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otel_deployment_environment=config.otel_deployment_environment,
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)
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config.configure_logging()
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if not args.daemon:
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config.log_config()
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# Register cleanup handlers
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atexit.register(_cleanup)
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signal.signal(signal.SIGINT, _signal_handler)
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signal.signal(signal.SIGTERM, _signal_handler)
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# Load operation validator extension if configured
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operation_validator = load_extension("OPERATION_VALIDATOR", OperationValidatorExtension)
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if operation_validator:
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import logging
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logging.info(f"Loaded operation validator: {operation_validator.__class__.__name__}")
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# Load tenant extension if configured
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tenant_extension = load_extension("TENANT", TenantExtension)
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if tenant_extension:
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import logging
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logging.info(f"Loaded tenant extension: {tenant_extension.__class__.__name__}")
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# Create MemoryEngine (reads configuration from environment)
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_memory = MemoryEngine(
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operation_validator=operation_validator,
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tenant_extension=tenant_extension,
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run_migrations=config.run_migrations_on_startup,
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)
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# Set extension context on tenant extension (needed for schema provisioning)
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if tenant_extension:
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extension_context = DefaultExtensionContext(
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database_url=config.database_url,
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memory_engine=_memory,
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)
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tenant_extension.set_context(extension_context)
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logging.info("Extension context set on tenant extension")
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# Create FastAPI app
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app = create_app(
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memory=_memory,
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http_api_enabled=True,
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mcp_api_enabled=config.mcp_enabled,
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mcp_mount_path="/mcp",
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initialize_memory=True,
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)
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# Wrap with idle timeout middleware in daemon mode
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idle_middleware = None
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if args.daemon:
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idle_middleware = IdleTimeoutMiddleware(app, idle_timeout=args.idle_timeout)
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app = idle_middleware
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# Prepare uvicorn config
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# When using workers or reload, we must use import string so each worker can import the app
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use_import_string = args.workers > 1 or args.reload
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# Check for uvloop availability
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try:
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import uvloop # noqa: F401
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loop_impl = "uvloop"
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print("uvloop available, will use for event loop")
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except ImportError:
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loop_impl = "asyncio"
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print("uvloop not installed, using default asyncio event loop")
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uvicorn_config = {
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"app": "hindsight_api.server:app" if use_import_string else app,
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"host": args.host,
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"port": args.port,
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"log_level": args.log_level,
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"access_log": args.access_log,
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"proxy_headers": args.proxy_headers,
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"ws": "wsproto", # Use wsproto instead of websockets to avoid deprecation warnings
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"loop": loop_impl, # Explicitly set event loop implementation
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}
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# Add optional parameters if provided
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if args.reload:
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uvicorn_config["reload"] = True
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if args.workers > 1:
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uvicorn_config["workers"] = args.workers
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if args.forwarded_allow_ips:
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uvicorn_config["forwarded_allow_ips"] = args.forwarded_allow_ips
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if args.ssl_keyfile:
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uvicorn_config["ssl_keyfile"] = args.ssl_keyfile
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if args.ssl_certfile:
|
|
uvicorn_config["ssl_certfile"] = args.ssl_certfile
|
|
|
|
# Print startup info (not in daemon mode)
|
|
if not args.daemon:
|
|
from .banner import print_startup_info
|
|
|
|
print_startup_info(
|
|
host=args.host,
|
|
port=args.port,
|
|
database_url=config.database_url,
|
|
llm_provider=config.llm_provider,
|
|
llm_model=config.llm_model,
|
|
embeddings_provider=config.embeddings_provider,
|
|
reranker_provider=config.reranker_provider,
|
|
mcp_enabled=config.mcp_enabled,
|
|
version=__version__,
|
|
)
|
|
|
|
# Start idle checker in daemon mode
|
|
if idle_middleware is not None:
|
|
# Start the idle checker in a background thread with its own event loop
|
|
import logging
|
|
import threading
|
|
|
|
def run_idle_checker():
|
|
import time
|
|
|
|
time.sleep(2) # Wait for uvicorn to start
|
|
try:
|
|
loop = asyncio.new_event_loop()
|
|
asyncio.set_event_loop(loop)
|
|
loop.run_until_complete(idle_middleware._check_idle())
|
|
except Exception as e:
|
|
logging.error(f"Idle checker error: {e}", exc_info=True)
|
|
|
|
threading.Thread(target=run_idle_checker, daemon=True).start()
|
|
|
|
uvicorn.run(**uvicorn_config)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|