# Tracing System Implementation Status

## ✅ What's Complete

### Core Infrastructure
- [x] TracingManager with lazy loading
- [x] Configuration system with env vars
- [x] Privacy controls and opt-out mechanisms
- [x] Circuit breaker for reliability
- [x] Adaptive sampling (10% default, 100% errors)
- [x] Async tracer with background workers
- [x] Bounded queues with overflow handling

### Telemetry (Anonymous Usage)
- [x] TelemetryCollector implementation
- [x] Event sanitization (no PII)
- [x] OTLP format matching automagik-spark exactly
- [x] HTTP sender implementation
- [x] Batch processing
- [x] System info collection

### Observability (Detailed Traces)
- [x] Provider interface
- [x] LangWatch provider with HTTP sending
- [x] Trace context management
- [x] LLM call tracking
- [x] Tool execution tracking

### Integration Helpers
- [x] CLI decorator for command tracking
- [x] API middleware for request tracking
- [x] Event types for all scenarios

## ❌ What's Missing

### Critical Integration Points
1. **AutomagikAgent Integration**
   - Base class doesn't import or use tracing
   - No sampling decisions
   - No telemetry events being sent

2. **CLI Integration**
   - CLI commands don't use @track_cli_command
   - No telemetry for agent/session/tool commands

3. **API Integration**
   - FastAPI app doesn't add TelemetryMiddleware
   - No request tracking

4. **Startup Integration**
   - Tracing manager not initialized at startup
   - No startup telemetry event

## 🚦 Current Data Flow Status

### Telemetry to namastex.ai
- **Status**: ❌ NOT SENDING
- **Reason**: Integration not added to agents/CLI/API
- **Ready**: ✅ All infrastructure ready

### LangWatch Observability
- **Status**: ❌ NOT SENDING
- **Reason**: No API key configured, not integrated
- **Ready**: ✅ Provider implementation complete

## 📋 Integration Checklist

To start collecting telemetry, you need to:

1. [ ] Add tracing import to AutomagikAgent base class
2. [ ] Wrap agent run() method with tracing
3. [ ] Add @track_cli_command to CLI commands
4. [ ] Add TelemetryMiddleware to FastAPI app
5. [ ] Set AUTOMAGIK_TELEMETRY_ENABLED=true in .env
6. [ ] (Optional) Add LANGWATCH_API_KEY for observability

## 🔍 Quick Verification

Once integrated, verify with:

```python
# Check if telemetry is working
from automagik.tracing import get_tracing_manager
tracing = get_tracing_manager()

print(f"Telemetry enabled: {tracing.config.telemetry_enabled}")
print(f"Endpoint: {tracing.config.telemetry_endpoint}")
print(f"Anonymous ID: {tracing.telemetry.anonymous_id if tracing.telemetry else 'N/A'}")

# After running some commands
if tracing.telemetry:
    metrics = tracing.telemetry.get_metrics()
    print(f"Events queued: {metrics['tracer']['queued']}")
    print(f"Events sent: {metrics['tracer']['processed']}")
```

## 📊 Expected Telemetry Format

When integrated, telemetry will send OTLP spans to https://telemetry.namastex.ai matching this format:

```json
{
  "resourceSpans": [{
    "resource": {
      "attributes": [
        {"key": "service.name", "value": {"stringValue": "automagik-agents"}},
        {"key": "service.version", "value": {"stringValue": "1.0.0"}},
        {"key": "service.organization", "value": {"stringValue": "namastex"}},
        {"key": "user.id", "value": {"stringValue": "anonymous-hash-id"}},
        {"key": "session.id", "value": {"stringValue": "session-uuid"}}
      ]
    },
    "scopeSpans": [{
      "spans": [{
        "name": "agent.run",
        "attributes": [
          {"key": "system.os", "value": {"stringValue": "Linux"}},
          {"key": "system.python_version", "value": {"stringValue": "3.12.0"}},
          {"key": "event.agent_name", "value": {"stringValue": "simple"}},
          {"key": "event.framework", "value": {"stringValue": "pydantic_ai"}},
          {"key": "event.success", "value": {"boolValue": true}},
          {"key": "event.duration_ms", "value": {"doubleValue": 1234.5}}
        ]
      }]
    }]
  }]
}
```

## 🎯 Next Steps

The tracing system is fully implemented but NOT YET INTEGRATED. To start collecting data:

1. Follow the integration steps in INTEGRATION_GUIDE.md
2. Add the decorators/middleware to existing code
3. Configure environment variables
4. Deploy and monitor

The infrastructure is performant, privacy-preserving, and ready to use!