fleet-memory/hindsight-api/hindsight_api/main.py
Nicolò Boschi 69dec8ec34
feat: add otel traceability (#330)
* 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
2026-02-10 12:20:48 +01:00

380 lines
15 KiB
Python

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