fleet-memory/CLAUDE.md
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

283 lines
10 KiB
Markdown

# CLAUDE.md
This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
## Project Overview
Hindsight is an agent memory system that provides long-term memory for AI agents using biomimetic data structures. Memories are organized as:
- **World facts**: General knowledge ("The sky is blue")
- **Experience facts**: Personal experiences ("I visited Paris in 2023")
- **Mental models**: Consolidated knowledge synthesized from facts ("User prefers functional programming patterns")
## Development Commands
### API Server (Python/FastAPI)
```bash
# Start API server (loads .env automatically)
./scripts/dev/start-api.sh
# Run all tests (parallelized with pytest-xdist)
cd hindsight-api && uv run pytest tests/
# Run specific test file
cd hindsight-api && uv run pytest tests/test_http_api_integration.py -v
# Run single test function
cd hindsight-api && uv run pytest tests/test_retain.py::test_retain_simple -v
# Lint and format
cd hindsight-api && uv run ruff check .
cd hindsight-api && uv run ruff format .
# Type checking (uses ty - extremely fast type checker from Astral)
cd hindsight-api && uv run ty check hindsight_api/
```
### Control Plane (Next.js)
```bash
./scripts/dev/start-control-plane.sh
# Or manually:
cd hindsight-control-plane && npm run dev
```
### Documentation Site (Docusaurus)
```bash
./scripts/dev/start-docs.sh
```
### Generating Clients/OpenAPI
```bash
# Regenerate OpenAPI spec after API changes (REQUIRED after changing endpoints)
./scripts/generate-openapi.sh
# Regenerate all client SDKs (Python, TypeScript, Rust)
./scripts/generate-clients.sh
```
### Benchmarks
```bash
./scripts/benchmarks/run-longmemeval.sh
./scripts/benchmarks/run-locomo.sh
./scripts/benchmarks/start-visualizer.sh # View results at localhost:8001
```
## Architecture
### Monorepo Structure
- **hindsight-api/**: Core FastAPI server with memory engine (Python, uv)
- **hindsight/**: Embedded Python bundle (hindsight-all package)
- **hindsight-control-plane/**: Admin UI (Next.js, npm)
- **hindsight-cli/**: CLI tool (Rust, cargo, uses progenitor for API client)
- **hindsight-clients/**: Generated SDK clients (Python, TypeScript, Rust)
- **hindsight-docs/**: Docusaurus documentation site
- **hindsight-integrations/**: Framework integrations (LiteLLM, OpenAI)
- **hindsight-dev/**: Development tools and benchmarks
### Core Engine (hindsight-api/hindsight_api/engine/)
- `memory_engine.py`: Main orchestrator (~170KB) for retain/recall/reflect operations
- `llm_wrapper.py`: LLM abstraction supporting OpenAI, Anthropic, Gemini, Groq, Ollama, LM Studio
- `embeddings.py`: Embedding generation (local sentence-transformers or TEI)
- `cross_encoder.py`: Reranking (local or TEI)
- `entity_resolver.py`: Entity extraction and normalization
- `query_analyzer.py`: Query intent analysis
**retain/**: Memory ingestion pipeline
- `orchestrator.py`: Coordinates the retain flow
- `fact_extraction.py`: LLM-based fact extraction from content
- `link_utils.py`: Entity link creation and management
**search/**: Multi-strategy retrieval
- `retrieval.py`: Main retrieval orchestrator
- `graph_retrieval.py`: Entity/relationship graph traversal
- `mpfp_retrieval.py`: Multi-Path Fact Propagation retrieval
- `fusion.py`: Reciprocal rank fusion for combining results
- `reranking.py`: Cross-encoder reranking
### API Layer (hindsight-api/hindsight_api/api/)
- `http.py`: FastAPI HTTP routers (~80KB) for all REST endpoints
- `mcp.py`: Model Context Protocol server implementation
Main operations:
- **Retain**: Store memories, extracts facts/entities/relationships
- **Recall**: Retrieve memories via 4 parallel strategies (semantic, BM25, graph, temporal) + reranking
- **Reflect**: Disposition-aware reasoning using memories and mental models.
### Database
PostgreSQL with pgvector. Schema managed via Alembic migrations in `hindsight-api/hindsight_api/alembic/`. Migrations run automatically on API startup.
Key tables: `banks`, `memory_units`, `documents`, `entities`, `entity_links`
### Adding Database Migrations
1. **Create a new migration file** in `hindsight-api/hindsight_api/alembic/versions/`:
- File name format: `<revision_id>_<description>.py` (e.g., `f1a2b3c4d5e6_add_new_index.py`)
- Use a unique hex revision ID (12 chars)
- Set `down_revision` to the previous migration's revision ID
2. **Migration template**:
```python
"""Description of the migration
Revision ID: f1a2b3c4d5e6
Revises: <previous_revision_id>
Create Date: YYYY-MM-DD
"""
from collections.abc import Sequence
from alembic import context, op
revision: str = "f1a2b3c4d5e6"
down_revision: str | Sequence[str] | None = "<previous_revision_id>"
branch_labels: str | Sequence[str] | None = None
depends_on: str | Sequence[str] | None = None
def _get_schema_prefix() -> str:
"""Get schema prefix for table names (required for multi-tenant support)."""
schema = context.config.get_main_option("target_schema")
return f'"{schema}".' if schema else ""
def upgrade() -> None:
schema = _get_schema_prefix()
op.execute(f"CREATE INDEX ... ON {schema}table_name(...)")
def downgrade() -> None:
schema = _get_schema_prefix()
op.execute(f"DROP INDEX IF EXISTS {schema}index_name")
```
3. **Run migrations locally**:
```bash
# Set database URL and run migrations
uv run hindsight-admin run-db-migration
# Run on a specific tenant schema
uv run hindsight-admin run-db-migration --schema tenant_xyz
```
## Key Conventions
### Code Quality
**Always run the lint script after making Python or TypeScript/Node changes:**
```bash
./scripts/hooks/lint.sh
```
This runs the same checks as the pre-commit hook (Ruff for Python, ESLint/Prettier for TypeScript).
### Memory Banks
- Each bank is an isolated memory store (like a "brain" for one user/agent)
- Banks have dispositions (skepticism, literalism, empathy traits 1-5) affecting reflect
- Banks can have background context
- Bank isolation is strict - no cross-bank data leakage
### API Design
- All endpoints operate on a single bank per request
- Multi-bank queries are client responsibility to orchestrate
- Disposition traits only affect reflect, not recall
### Control Plane API Routes
When adding or modifying parameters in the dataplane API (hindsight-api), you must also update the control plane routes that proxy to it:
1. **API Routes** (`hindsight-control-plane/src/app/api/`):
- `recall/route.ts` - proxies to `/v1/default/banks/{bank_id}/memories/recall`
- `reflect/route.ts` - proxies to `/v1/default/banks/{bank_id}/reflect`
- `memories/retain/route.ts` - proxies to `/v1/default/banks/{bank_id}/memories/retain`
- Other routes follow the same pattern
2. **Client types** (`hindsight-control-plane/src/lib/api.ts`):
- Update the TypeScript type definitions for `recall()`, `reflect()`, `retain()` etc.
3. **Checklist when adding new API parameters**:
- Add parameter extraction in the route handler (destructure from `body`)
- Pass the parameter to the SDK call
- Update the client type definition in `lib/api.ts`
- Update any UI components that need to use the new parameter
### Python Style
- Python 3.11+, type hints required
- Async throughout (asyncpg, async FastAPI)
- Pydantic models for request/response
- Ruff for linting (line-length 120)
- No Python files at project root - maintain clean directory structure
- **Never use multi-item tuple return values** - prefer dataclass or Pydantic model for structured returns
### Type Safety with Pydantic Models
**NEVER use raw `dict` types for structured data.** Always use Pydantic models:
- Use Pydantic `BaseModel` for all data structures passed between functions
- Add `@field_validator` for type coercion (e.g., ensuring datetimes are timezone-aware)
- Avoid `dict.get()` patterns - use typed model attributes instead
- Parse external data (JSON, API responses) into Pydantic models at the boundary
- This catches type errors at parse time, not deep in business logic
```python
# BAD - error-prone dict access
def process(data: dict) -> str:
return data.get("name", "") # No validation, silent failures
# GOOD - typed and validated
class UserData(BaseModel):
name: str
created_at: datetime
@field_validator("created_at", mode="before")
@classmethod
def ensure_tz_aware(cls, v):
if isinstance(v, str):
v = datetime.fromisoformat(v.replace("Z", "+00:00"))
if v.tzinfo is None:
return v.replace(tzinfo=timezone.utc)
return v
def process(data: UserData) -> str:
return data.name # Type-safe, validated at construction
```
### TypeScript Style
- Next.js App Router for control plane
- Tailwind CSS with shadcn/ui components
### Adding New API Configuration Flags
When adding a new environment variable configuration:
1. **config.py** (`hindsight-api/hindsight_api/config.py`):
- Add `ENV_*` constant for the environment variable name
- Add `DEFAULT_*` constant for the default value
- Add field to `HindsightConfig` dataclass
- Add initialization in `from_env()` method
2. **main.py** (`hindsight-api/hindsight_api/main.py`):
- Add field to the manual `HindsightConfig()` constructor call (search for "CLI override")
3. **Use the config** in code:
```python
from ...config import get_config
config = get_config()
value = config.your_new_field
```
4. **Documentation** (`hindsight-docs/docs/developer/configuration.md`):
- Add to appropriate section table with Variable, Description, Default
## Environment Setup
```bash
cp .env.example .env
# Edit .env with LLM API key
# Python deps
uv sync --directory hindsight-api/
# Node deps (uses npm workspaces)
npm install
```
Required env vars:
- `HINDSIGHT_API_LLM_PROVIDER`: openai, anthropic, gemini, groq, ollama, lmstudio
- `HINDSIGHT_API_LLM_API_KEY`: Your API key
- `HINDSIGHT_API_LLM_MODEL`: Model name (e.g., o3-mini, claude-sonnet-4-20250514)
Optional (uses local models by default):
- `HINDSIGHT_API_EMBEDDINGS_PROVIDER`: local (default) or tei
- `HINDSIGHT_API_RERANKER_PROVIDER`: local (default) or tei
- `HINDSIGHT_API_DATABASE_URL`: External PostgreSQL (uses embedded pg0 by default)