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feature/update-plotly
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4 Commits

Author SHA1 Message Date
Chris Coutinho c8d9cc24e0 refactor: migrate asyncio to anyio for consistent structured concurrency 
Replace asyncio primitives with anyio equivalents throughout the codebase
to establish a single async pattern. This provides better structured
concurrency with automatic cancellation on errors and aligns with the
pytest anyio configuration.

Changes:
- hybrid.py: Replace asyncio.gather() with anyio task groups
- token_broker.py: Replace asyncio.Lock() with anyio.Lock()
- storage.py: Replace asyncio.run() with anyio.run()
- app.py: Replace tg.start_soon() with await tg.start() for task status
- processor.py: Add task_status parameter for structured startup
- scanner.py: Add task_status parameter for structured startup
- CLAUDE.md: Update async/await patterns guidance

The change from start_soon() to await tg.start() enables proper task
initialization signaling, ensuring background tasks are ready before
proceeding. This follows anyio best practices for structured concurrency.

All 118 unit tests pass with the new implementation.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-16 03:51:45 +01:00
Chris Coutinho c97f12d47e feat: Add OAuth token and database metrics (Phases 3-4) 
Complete Prometheus instrumentation for OAuth token operations
and additional database operations to populate empty dashboard panels.

OAuth Token Metrics (Phase 4):
- unified_verifier.py:
  * Token validation cache hits/misses
  * JWT verification success/failure/error
  * Introspection validation results
  * Audience validation failures
- context_helper.py:
  * Token exchange cache hits/misses
  * RFC 8693 exchange success/error

Database Metrics (Phase 3 completion):
- storage.py:
  * get_refresh_token() with timing
  * delete_refresh_token() with timing
  * All operations record duration and success/error status

These metrics populate the following dashboard panels:
- Token Validations (by method and result)
- Token Cache Hit Rate
- Token Exchange Operations
- Database Operations (refresh token CRUD)
- Database Operation Duration

Part of PR #295 - Complete metrics instrumentation
 2025-11-13 16:23:00 +01:00
Chris Coutinho a667d7c59c feat: Add metrics instrumentation for queue, health, and database operations 
Implement Prometheus metrics to populate empty Grafana dashboard panels.

## Phase 1: Queue Size Metrics ✅
**File**: `processor.py`
- Track vector sync queue depth in real-time
- Update metric after receiving and processing each document
- Update metric during timeout (empty queue)
- Enables: "Processing Queue Depth" panel

## Phase 2: Health Check Metrics ✅
**File**: `app.py`
- Add Nextcloud connectivity check with timing
- Add Qdrant health check with timing
- Record dependency health status (up/down)
- Record health check duration
- Enables: 4 health status panels + health check duration panel

## Phase 3: Database Operation Metrics (Partial) ⏳
**File**: `storage.py`
- Instrument `store_refresh_token()` method
- Track SQLite INSERT operation timing and success/error status
- Enables: Partial data for database operation latency panel

## Metrics Now Exposed

### Queue Metrics:
- `mcp_vector_sync_queue_size` - Real-time queue depth

### Health Metrics:
- `mcp_dependency_health{dependency="nextcloud"}` - UP/DOWN status
- `mcp_dependency_health{dependency="qdrant"}` - UP/DOWN status
- `mcp_dependency_check_duration_seconds{dependency}` - Health check latency

### Database Metrics:
- `mcp_db_operations_total{db="sqlite",operation="insert"}` - Operation count
- `mcp_db_operation_duration_seconds{db="sqlite",operation="insert"}` - Operation latency

## Dashboard Impact

**Panels Now Populated** (7/34 panels):
- ✅ Processing Queue Depth
- ✅ Nextcloud Health
- ✅ Qdrant Health
- ✅ Health Check Duration
- ✅ Database Operation Latency (partial)
- ✅ Vector sync panels (already working from PR #292)

**Panels Still Empty** (remaining work):
- ⏳ OAuth panels (4): Token validations, exchanges, cache hit rate, refresh ops
- ⏳ MCP tool panels (3): Call volume, error rates, execution duration
- ⏳ Database panel: Needs more SQLite operations instrumented (~29 remaining)

## Testing

Verified metric definitions exist and will be recorded on next deployment.

## Next Steps

Phase 4: OAuth token metrics (unified_verifier.py, context_helper.py, storage.py)
Phase 5: MCP tool metrics (all server/*.py files with @mcp.tool())
Phase 3 completion: Remaining 29 database operations in storage.py

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-13 16:14:38 +01:00
Chris Coutinho 1bced88c97 refactor: consolidate database storage for webhooks and OAuth tokens 
Refactored the storage system to use a unified SQLite database for both
webhook tracking and OAuth token storage, available in both BasicAuth
and OAuth modes.

Changes:
- Renamed refresh_token_storage.py → storage.py
- Made TOKEN_ENCRYPTION_KEY optional (only required for OAuth token ops)
- Added registered_webhooks table with schema versioning
- Added webhook storage methods (store, get, delete, list, clear)
- Initialize storage in both BasicAuth and OAuth modes
- Updated webhook routes to persist registrations in database
- Database-first pattern for webhook status checks (performance)
- Updated all imports across codebase

Storage Behavior:
- Database created automatically at startup if needed
- Existing databases detected and reused
- Server fails fast if database initialization fails
- No migrations needed (OAuth feature is experimental)

Testing:
- Added 13 comprehensive unit tests for webhook storage
- All 118 unit tests pass
- All 5 smoke tests pass
- Verified fail-fast behavior on initialization errors

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
 2025-11-11 20:01:49 +01:00