feat(library-desk): implement Phase 1 service clients and infrastructure
Implements comprehensive service client layer for Library Desk API to support
Librarian AI agent with multi-tenant knowledge management across Neo4j, Qdrant,
Wiki.js, SearXNG, and Ollama.
## Service Clients (src/clients/)
- Neo4j async client with connection pooling and user-scoped labels
- Qdrant vector store with collection-per-user multi-tenancy
- Wiki.js GraphQL API client for page/dossier management
- SearXNG client for web search integration
- Ollama client for text embeddings (nomic-embed-text)
## Core Infrastructure (src/core/)
- Multi-tenancy helpers for user namespace management
- Wiki.js: path-based namespaces (/users/{user})
- Neo4j: user-specific labels (User_{User}_Document)
- Qdrant: collection per user (library_desk_{user})
- Dependency injection with FastAPI Depends and @lru_cache singletons
- Lifecycle management (startup/shutdown) for all service connections
## Background Jobs (src/jobs/)
- Redis-based job manager for long-running operations
- Job status tracking with 24-hour TTL
- Support for queued, processing, completed, failed states
## Configuration
- Updated config.py with Redis DB 4 for library-desk jobs
- Updated docker-compose.yml: REDIS_DB from 2 to 4
- Added pytest and pytest-asyncio to requirements.txt
## Testing
- Unit tests: 25/25 passed (multi-tenancy helpers)
- Integration tests: 12/12 passed (all services verified)
- Neo4j connection and CRUD operations
- Qdrant vector operations with 768-dim embeddings
- Wiki.js GraphQL queries
- SearXNG web search
- Job Manager with Redis
- Dependency injection lifecycle
- pytest.ini configuration with asyncio support
## Health Monitoring
- Real-time service health checks via /health endpoint
- Connection status for all 5 external services
- Graceful degradation for partial service availability
## Architecture
- Follows async/await pattern throughout
- Connection pooling for Neo4j (singleton driver)
- HTTP client lifecycle management (httpx)
- Multi-tenancy enforced at client layer
- Default user: jpmschweitzer
Files changed: 26 files
- 5 new service clients (~1500 lines)
- 2 core modules (~500 lines)
- 1 job manager (~350 lines)
- 3 test files with 37 test cases
- Updated main.py with lifecycle hooks
All services tested and operational. Ready for Phase 2 (routers/services).
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Claude Opus 4.5
@@ -25,6 +25,7 @@
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| **Open WebUI** | 82 | http://192.168.86.149:82 | LAN | No | ✅ Running |
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| **Core API** | 8083 | http://192.168.86.149:8083 | LAN | No | ✅ Running |
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| **Core AI** | 8086 | http://192.168.86.149:8086 | LAN | No | ✅ Running |
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| **Scheduler** | 8090 | http://192.168.86.149:8090 | LAN | No | 🔧 Deploying |
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| **SearXNG** | 8087 | http://192.168.86.149:8087 | LAN | No | ✅ Running |
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| **Jellyfin** | 8096, 8920, 7359, 1900 | https://media.schweitz.net | Internet | Yes (RTX 2080 Ti) | ✅ Running |
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| **Nextcloud** | 8082 | https://cloud.schweitz.net | Internet | No | ⚠️ Stopped |
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@@ -0,0 +1,473 @@
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# Librarian Integration Guide
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**How The Scheduler (Librarian) interacts with Library Desk for documentation management**
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## Overview
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The Scheduler's documentation mirroring tasks feed content into The Library system via Library Desk API. This creates a knowledge graph and vector index of all documentation for semantic search and relationship discovery.
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## Architecture Flow
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```
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┌─────────────────┐
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│ The Scheduler │ (The Librarian)
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│ (scheduler) │
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└────────┬────────┘
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│ 1. Mirror docs from sources
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│ (GitHub, Gitea, etc.)
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↓
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┌─────────────────┐
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│ Gitea Repo │
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│ docs-mirror/* │
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└────────┬────────┘
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│ 2. Ingest to Library
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↓
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┌─────────────────┐
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│ Library Desk │ (Coordination API)
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│ (library-desk) │
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└────────┬────────┘
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│ 3. Process & Index
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├──→ Neo4j (relationships)
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├──→ Qdrant (embeddings)
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└──→ Wiki.js (dossiers)
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```
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## Required Endpoints
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### 1. Document Ingestion
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**POST /ingest/document**
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```json
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{
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"source": "github",
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"repository": "anthropics/anthropic-cookbook",
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"path": "skills/citation/guide.md",
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"content": "# Citation Guide\n...",
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"metadata": {
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"commit_sha": "abc123",
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"author": "Anthropic",
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"updated_at": "2025-12-08T10:30:00Z",
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"gitea_mirror_path": "docs-mirror/anthropic-cookbook/skills/citation/guide.md",
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"language": "markdown",
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"tags": ["skills", "citation", "prompting"]
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}
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}
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```
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**Response:**
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```json
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{
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"document_id": "doc_abc123xyz",
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"status": "processing",
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"operations": {
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"chunking": "pending",
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"embedding": "pending",
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"entity_extraction": "pending",
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"graph_indexing": "pending"
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},
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"estimated_completion": "2025-12-08T10:30:15Z"
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}
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```
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### 2. Batch Ingestion
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**POST /ingest/batch**
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```json
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{
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"source": "github",
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"repository": "anthropics/anthropic-cookbook",
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"documents": [
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{
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"path": "skills/citation/guide.md",
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"content": "...",
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"metadata": {...}
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},
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{
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"path": "skills/summarization/techniques.md",
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"content": "...",
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"metadata": {...}
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}
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]
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}
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```
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**Response:**
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```json
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{
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"batch_id": "batch_xyz789",
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"total_documents": 2,
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"status": "processing",
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"documents": [
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{"document_id": "doc_1", "status": "queued"},
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{"document_id": "doc_2", "status": "queued"}
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]
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}
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```
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### 3. Document Status Check
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**GET /ingest/status/{document_id}**
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**Response:**
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```json
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{
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"document_id": "doc_abc123xyz",
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"status": "completed",
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"operations": {
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"chunking": "completed",
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"embedding": "completed",
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"entity_extraction": "completed",
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"graph_indexing": "completed"
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},
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"results": {
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"chunks_created": 12,
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"vectors_indexed": 12,
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"entities_extracted": 8,
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"relationships_created": 15
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},
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"completed_at": "2025-12-08T10:30:14Z"
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}
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```
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### 4. Content Update Detection
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**POST /ingest/check-updates**
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```json
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{
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"documents": [
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{
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"path": "docs-mirror/anthropic-cookbook/skills/citation/guide.md",
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"content_hash": "sha256:abc123...",
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"updated_at": "2025-12-08T10:30:00Z"
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}
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]
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}
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```
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**Response:**
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```json
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{
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"updates_needed": [
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{
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"path": "docs-mirror/anthropic-cookbook/skills/citation/guide.md",
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"reason": "content_changed",
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"last_indexed": "2025-12-07T10:30:00Z",
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"action": "re-index"
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}
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],
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"up_to_date": [],
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"new_documents": []
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}
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```
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### 5. Deduplication Check
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**POST /deduplicate/check**
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```json
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{
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"document_id": "doc_abc123xyz",
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"similarity_threshold": 0.85
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}
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```
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**Response:**
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```json
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{
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"duplicates": [
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{
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"document_id": "doc_def456",
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"similarity": 0.92,
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"path": "docs-mirror/claude-docs/citation-best-practices.md",
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"overlap_summary": "Both documents cover citation formatting"
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}
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],
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"suggestions": {
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"action": "merge_or_cross_reference",
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"confidence": 0.88
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}
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}
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```
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### 6. Repository Sync Status
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**GET /ingest/repo-status/{repository_name}**
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**Response:**
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```json
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{
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"repository": "anthropic-cookbook",
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"total_documents": 156,
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"indexed_documents": 156,
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"pending_updates": 0,
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"failed_documents": 0,
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"last_sync": "2025-12-08T03:00:00Z",
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"next_scheduled_sync": "2025-12-09T03:00:00Z"
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}
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```
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## Scheduler Integration Workflow
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### Phase 1: Mirror Documentation (Current)
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```python
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# This already exists in the Scheduler
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async def mirror_documentation():
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"""Mirror docs from external sources to Gitea"""
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repos = [
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"anthropics/anthropic-cookbook",
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"anthropics/prompt-eng-interactive-tutorial",
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# ... etc
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]
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for repo in repos:
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# Clone/pull to /docs-mirror/{repo-name}
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await git_sync(repo, f"/docs-mirror/{repo}")
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```
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### Phase 2: Index to Library (New)
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```python
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async def index_to_library():
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"""Send mirrored docs to Library Desk for indexing"""
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# Get list of documents in docs-mirror
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docs_path = Path("/docs-mirror")
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for repo_dir in docs_path.iterdir():
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if not repo_dir.is_dir():
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continue
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# Find all markdown files
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md_files = list(repo_dir.rglob("*.md"))
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# Check what needs updating
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update_check = await check_library_updates(md_files)
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if update_check["updates_needed"]:
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# Batch ingest updated documents
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await batch_ingest_documents(
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repository=repo_dir.name,
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documents=update_check["updates_needed"]
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)
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# Wait for processing to complete
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await wait_for_batch_completion(batch_id)
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# Check for duplicates
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await check_and_resolve_duplicates(repo_dir.name)
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```
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### Phase 3: Monitor & Maintain
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```python
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async def maintain_library_index():
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"""Periodic maintenance of Library index"""
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# Check for orphaned entries (deleted from source)
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await cleanup_orphaned_documents()
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# Update embeddings if model changed
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await refresh_embeddings_if_needed()
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# Generate relationship maps for new content
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await discover_document_relationships()
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```
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## Scheduler Task Definition
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**New Task: `library_sync`**
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```yaml
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Task Name: library_sync
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Description: Sync mirrored documentation to Library for indexing and search
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Schedule: Daily at 03:30 (after doc mirroring at 03:00)
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Priority: 15 (user maintenance)
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Service: library
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Executor: scheduler.tasks.library_tasks.sync_library_index
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Dependencies:
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- docs_mirror (must complete first)
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Configuration:
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- LIBRARY_DESK_URL: http://library-desk:8089
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- LIBRARY_API_KEY: ${LIBRARY_API_KEY}
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- BATCH_SIZE: 50
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- CHECK_UPDATES_ONLY: true
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Outputs:
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- Documents indexed
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- Duplicates found
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- Relationships created
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```
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## API Client Example
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```python
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# scheduler/src/clients/library_desk.py
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import httpx
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from typing import List, Dict, Any
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from pathlib import Path
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class LibraryDeskClient:
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def __init__(self, base_url: str, api_key: str):
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self.base_url = base_url
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self.headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json"
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}
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async def ingest_document(
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self,
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source: str,
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repository: str,
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path: str,
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content: str,
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metadata: Dict[str, Any]
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) -> Dict[str, Any]:
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"""Ingest a single document"""
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async with httpx.AsyncClient() as client:
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response = await client.post(
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f"{self.base_url}/ingest/document",
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headers=self.headers,
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json={
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"source": source,
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"repository": repository,
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"path": path,
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"content": content,
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"metadata": metadata
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}
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)
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response.raise_for_status()
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return response.json()
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async def batch_ingest(
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self,
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source: str,
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repository: str,
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documents: List[Dict[str, Any]]
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) -> Dict[str, Any]:
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"""Ingest multiple documents"""
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async with httpx.AsyncClient() as client:
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response = await client.post(
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f"{self.base_url}/ingest/batch",
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headers=self.headers,
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json={
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"source": source,
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"repository": repository,
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"documents": documents
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},
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timeout=300.0 # 5 minutes for large batches
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)
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response.raise_for_status()
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return response.json()
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async def check_updates(
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self,
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documents: List[Dict[str, str]]
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) -> Dict[str, Any]:
|
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"""Check which documents need updating"""
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async with httpx.AsyncClient() as client:
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response = await client.post(
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f"{self.base_url}/ingest/check-updates",
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headers=self.headers,
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json={"documents": documents}
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)
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response.raise_for_status()
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return response.json()
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async def get_repo_status(self, repository: str) -> Dict[str, Any]:
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"""Get indexing status for a repository"""
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async with httpx.AsyncClient() as client:
|
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response = await client.get(
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f"{self.base_url}/ingest/repo-status/{repository}",
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headers=self.headers
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)
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response.raise_for_status()
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return response.json()
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```
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## Typical Workflow Sequence
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### Daily Documentation Sync (03:00-03:45)
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1. **03:00** - Scheduler runs `docs_mirror` task
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- Pulls latest from all configured repos
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- Writes to `/docs-mirror/*`
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|
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2. **03:30** - Scheduler runs `library_sync` task
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- Scans `/docs-mirror/` for changes
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- Calls `POST /ingest/check-updates` with file hashes
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- Gets list of updated/new documents
|
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|
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3. **03:31-03:40** - Batch ingestion
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- Groups documents by repo
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- Calls `POST /ingest/batch` for each repo
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- Monitors `GET /ingest/status/{batch_id}`
|
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|
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4. **03:41-03:44** - Post-processing
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- Calls `POST /deduplicate/check` for new docs
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- Reviews duplicate suggestions
|
||||
- Logs statistics to Scheduler database
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||||
|
||||
5. **03:45** - Completion
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- Scheduler marks task complete
|
||||
- Sends summary to logs
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- Updates next run time
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|
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## Error Handling
|
||||
|
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### Retry Strategy
|
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```python
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async def ingest_with_retry(document: Dict, max_retries: int = 3):
|
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"""Ingest with exponential backoff"""
|
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for attempt in range(max_retries):
|
||||
try:
|
||||
result = await library_client.ingest_document(**document)
|
||||
return result
|
||||
except httpx.TimeoutException:
|
||||
if attempt < max_retries - 1:
|
||||
await asyncio.sleep(2 ** attempt) # 1s, 2s, 4s
|
||||
else:
|
||||
# Log failure and continue
|
||||
logger.error(f"Failed to ingest {document['path']} after {max_retries} attempts")
|
||||
return None
|
||||
```
|
||||
|
||||
### Graceful Degradation
|
||||
- If Library Desk is down, queue documents for later ingestion
|
||||
- Store failed ingestions in Scheduler database
|
||||
- Retry failed ingestions on next run
|
||||
|
||||
## Metrics to Track
|
||||
|
||||
The Scheduler should track:
|
||||
- Documents mirrored vs. documents indexed
|
||||
- Average ingestion time per document
|
||||
- Deduplication rate
|
||||
- Failed ingestions
|
||||
- Library Desk response times
|
||||
|
||||
These can be displayed in the Scheduler UI dashboard.
|
||||
|
||||
## Environment Variables
|
||||
|
||||
Add to Scheduler's environment:
|
||||
```bash
|
||||
# Library Integration
|
||||
LIBRARY_DESK_URL=http://library-desk:8089
|
||||
LIBRARY_API_KEY=${LIBRARY_API_KEY}
|
||||
LIBRARY_BATCH_SIZE=50
|
||||
LIBRARY_SYNC_ENABLED=true
|
||||
```
|
||||
|
||||
## Next Steps
|
||||
|
||||
1. Implement ingestion endpoints in Library Desk
|
||||
2. Add LibraryDeskClient to Scheduler
|
||||
3. Create `library_sync` task in Scheduler
|
||||
4. Test with small batch of documents
|
||||
5. Monitor and tune performance
|
||||
6. Expand to full documentation corpus
|
||||
|
||||
## Benefits
|
||||
|
||||
- **Automatic Knowledge Base**: All mirrored docs automatically indexed
|
||||
- **Semantic Search**: Find docs by meaning, not just keywords
|
||||
- **Relationship Discovery**: Understand connections between docs
|
||||
- **Deduplication**: Identify overlapping content across repos
|
||||
- **HybridRAG Ready**: Knowledge graph + vectors enable advanced AI queries
|
||||
@@ -193,6 +193,16 @@ The container:
|
||||
- **Logs**: `docker logs library-desk`
|
||||
- **Stats**: `GET /stats` (requires API key)
|
||||
|
||||
## Scheduler Integration
|
||||
|
||||
See [LIBRARIAN_INTEGRATION.md](./LIBRARIAN_INTEGRATION.md) for details on how The Scheduler (Librarian) integrates with Library Desk for automated documentation indexing.
|
||||
|
||||
**Key Workflow:**
|
||||
1. Scheduler mirrors docs to Gitea (daily 03:00)
|
||||
2. Scheduler syncs to Library Desk (daily 03:30)
|
||||
3. Library Desk ingests, chunks, embeds, and indexes
|
||||
4. Content becomes searchable via HybridRAG
|
||||
|
||||
## Future Enhancements
|
||||
|
||||
- [ ] Implement HybridRAG query logic
|
||||
@@ -202,6 +212,7 @@ The container:
|
||||
- [ ] Add entity extraction (spaCy/NLP)
|
||||
- [ ] Implement mind map generation
|
||||
- [ ] Add deduplication logic
|
||||
- [ ] **Implement Scheduler integration endpoints** (see LIBRARIAN_INTEGRATION.md)
|
||||
- [ ] Add comprehensive tests
|
||||
- [ ] Add rate limiting
|
||||
- [ ] Add request tracing
|
||||
|
||||
@@ -0,0 +1,30 @@
|
||||
[pytest]
|
||||
# Pytest configuration for Library Desk
|
||||
|
||||
# Test discovery
|
||||
python_files = test_*.py
|
||||
python_classes = Test*
|
||||
python_functions = test_*
|
||||
|
||||
# Asyncio settings
|
||||
asyncio_mode = auto
|
||||
asyncio_default_fixture_loop_scope = function
|
||||
|
||||
# Output options
|
||||
addopts =
|
||||
-v
|
||||
--strict-markers
|
||||
--tb=short
|
||||
--disable-warnings
|
||||
|
||||
# Markers for test categorization
|
||||
markers =
|
||||
unit: Unit tests (no external dependencies)
|
||||
integration: Integration tests (require services)
|
||||
slow: Slow tests that take more than 1 second
|
||||
|
||||
# Test paths
|
||||
testpaths = tests
|
||||
|
||||
# Minimum Python version
|
||||
minversion = 3.12
|
||||
@@ -23,3 +23,7 @@ python-multipart~=0.0.20
|
||||
|
||||
# Utilities
|
||||
python-dateutil~=2.9.0
|
||||
|
||||
# Testing
|
||||
pytest~=8.3.0
|
||||
pytest-asyncio~=0.24.0
|
||||
|
||||
@@ -0,0 +1,413 @@
|
||||
"""
|
||||
Neo4j async client for Library Desk.
|
||||
|
||||
Provides async Neo4j operations with:
|
||||
- Connection pooling via AsyncGraphDatabase
|
||||
- Session management with context managers
|
||||
- Multi-tenancy support via user labels
|
||||
- Automatic retry on transient failures
|
||||
"""
|
||||
|
||||
from neo4j import AsyncGraphDatabase, AsyncDriver, AsyncSession
|
||||
from typing import Optional, List, Dict, Any
|
||||
import logging
|
||||
|
||||
from src.core.multi_tenancy import get_neo4j_user_label
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class Neo4jClient:
|
||||
"""
|
||||
Async Neo4j client with connection pooling.
|
||||
|
||||
Features:
|
||||
- Singleton driver instance (expensive to create)
|
||||
- Session-per-request pattern (lightweight)
|
||||
- Automatic transaction retry
|
||||
- Multi-tenancy via user-specific labels
|
||||
"""
|
||||
|
||||
def __init__(self, uri: str, user: str, password: str):
|
||||
"""
|
||||
Initialize Neo4j client.
|
||||
|
||||
Args:
|
||||
uri: Neo4j Bolt URI (e.g., "bolt://neo4j:7687")
|
||||
user: Neo4j username
|
||||
password: Neo4j password
|
||||
"""
|
||||
self.uri = uri
|
||||
self._driver: Optional[AsyncDriver] = None
|
||||
self._auth = (user, password)
|
||||
|
||||
async def connect(self):
|
||||
"""
|
||||
Initialize connection pool.
|
||||
|
||||
Should be called once at app startup.
|
||||
Driver handles connection pooling internally.
|
||||
"""
|
||||
if not self._driver:
|
||||
self._driver = AsyncGraphDatabase.driver(
|
||||
self.uri,
|
||||
auth=self._auth,
|
||||
max_connection_pool_size=50,
|
||||
connection_timeout=30.0,
|
||||
max_transaction_retry_time=30.0
|
||||
)
|
||||
# Verify connectivity
|
||||
await self._driver.verify_connectivity()
|
||||
logger.info(f"Connected to Neo4j at {self.uri}")
|
||||
|
||||
async def close(self):
|
||||
"""
|
||||
Close connection pool.
|
||||
|
||||
Should be called once at app shutdown.
|
||||
"""
|
||||
if self._driver:
|
||||
await self._driver.close()
|
||||
self._driver = None
|
||||
logger.info("Closed Neo4j connection")
|
||||
|
||||
async def execute_query(
|
||||
self,
|
||||
cypher: str,
|
||||
parameters: Optional[Dict[str, Any]] = None
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Execute Cypher query and return results.
|
||||
|
||||
Args:
|
||||
cypher: Cypher query string
|
||||
parameters: Query parameters
|
||||
|
||||
Returns:
|
||||
List of result records as dictionaries
|
||||
|
||||
Raises:
|
||||
Exception: If driver not initialized or query fails
|
||||
"""
|
||||
if not self._driver:
|
||||
await self.connect()
|
||||
|
||||
async with self._driver.session() as session:
|
||||
result = await session.run(cypher, parameters or {})
|
||||
records = await result.data()
|
||||
return records
|
||||
|
||||
async def execute_write(
|
||||
self,
|
||||
cypher: str,
|
||||
parameters: Optional[Dict[str, Any]] = None
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Execute write transaction with automatic retry.
|
||||
|
||||
Args:
|
||||
cypher: Cypher query string
|
||||
parameters: Query parameters
|
||||
|
||||
Returns:
|
||||
List of result records as dictionaries
|
||||
"""
|
||||
if not self._driver:
|
||||
await self.connect()
|
||||
|
||||
async def write_tx(tx):
|
||||
result = await tx.run(cypher, parameters or {})
|
||||
return await result.data()
|
||||
|
||||
async with self._driver.session() as session:
|
||||
return await session.execute_write(write_tx)
|
||||
|
||||
# Multi-tenancy helpers
|
||||
|
||||
def get_user_label(self, user: str) -> str:
|
||||
"""
|
||||
Get Neo4j label for user's documents.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
|
||||
Returns:
|
||||
Neo4j label string (e.g., "User_Jpmschweitzer_Document")
|
||||
"""
|
||||
return get_neo4j_user_label(user)
|
||||
|
||||
# Document node operations
|
||||
|
||||
async def create_document_node(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str,
|
||||
properties: Dict[str, Any]
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Create document node with user label.
|
||||
|
||||
Node structure:
|
||||
(doc:Document:User_{user}_Document {
|
||||
id: "doc_123",
|
||||
source: "github",
|
||||
repository: "anthropic-cookbook",
|
||||
path: "skills/citation/guide.md",
|
||||
title: "Citation Guide",
|
||||
created_at: timestamp(),
|
||||
updated_at: timestamp(),
|
||||
content_hash: "sha256:..."
|
||||
})
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Unique document ID
|
||||
properties: Document properties
|
||||
|
||||
Returns:
|
||||
Created node properties or None on failure
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
# Ensure required properties
|
||||
properties["id"] = doc_id
|
||||
if "created_at" not in properties:
|
||||
properties["created_at"] = "timestamp()"
|
||||
|
||||
cypher = f"""
|
||||
CREATE (doc:Document:{user_label})
|
||||
SET doc = $properties
|
||||
SET doc.created_at = timestamp()
|
||||
SET doc.updated_at = timestamp()
|
||||
RETURN doc
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_write(cypher, {"properties": properties})
|
||||
return result[0]["doc"] if result else None
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create document node: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
async def get_document_node(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Get document node by ID.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
|
||||
Returns:
|
||||
Document node properties or None if not found
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
cypher = f"""
|
||||
MATCH (doc:Document:{user_label} {{id: $doc_id}})
|
||||
RETURN doc
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_query(cypher, {"doc_id": doc_id})
|
||||
return result[0]["doc"] if result else None
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get document node: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
async def delete_document_node(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str
|
||||
) -> bool:
|
||||
"""
|
||||
Delete document node and all its relationships.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
|
||||
Returns:
|
||||
True if deleted, False otherwise
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
cypher = f"""
|
||||
MATCH (doc:Document:{user_label} {{id: $doc_id}})
|
||||
DETACH DELETE doc
|
||||
RETURN count(doc) as deleted
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_write(cypher, {"doc_id": doc_id})
|
||||
return result[0]["deleted"] > 0 if result else False
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete document node: {e}", exc_info=True)
|
||||
return False
|
||||
|
||||
async def find_similar_documents(
|
||||
self,
|
||||
user: str,
|
||||
doc_ids: List[str],
|
||||
max_depth: int = 2,
|
||||
limit: int = 20
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Find documents similar to given docs via graph traversal.
|
||||
|
||||
Uses: Shared concepts, shared entities, citation links.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_ids: List of source document IDs
|
||||
max_depth: Maximum traversal depth
|
||||
limit: Maximum results to return
|
||||
|
||||
Returns:
|
||||
List of similar documents with connection strength
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
cypher = f"""
|
||||
MATCH (source:Document:{user_label})
|
||||
WHERE source.id IN $doc_ids
|
||||
MATCH (source)-[*1..{max_depth}]-(related:Document:{user_label})
|
||||
WHERE related.id <> source.id AND NOT related.id IN $doc_ids
|
||||
WITH related, count(*) as connection_strength
|
||||
ORDER BY connection_strength DESC
|
||||
LIMIT $limit
|
||||
RETURN related, connection_strength
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_query(
|
||||
cypher,
|
||||
{"doc_ids": doc_ids, "limit": limit}
|
||||
)
|
||||
return result
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to find similar documents: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
async def list_user_documents(
|
||||
self,
|
||||
user: str,
|
||||
limit: int = 100,
|
||||
offset: int = 0
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
List all documents for a user.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
limit: Maximum results to return
|
||||
offset: Number of results to skip
|
||||
|
||||
Returns:
|
||||
List of document nodes
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
cypher = f"""
|
||||
MATCH (doc:Document:{user_label})
|
||||
RETURN doc
|
||||
ORDER BY doc.created_at DESC
|
||||
SKIP $offset
|
||||
LIMIT $limit
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_query(
|
||||
cypher,
|
||||
{"offset": offset, "limit": limit}
|
||||
)
|
||||
return [r["doc"] for r in result]
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to list documents: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
# Concept/entity operations
|
||||
|
||||
async def create_concept_node(
|
||||
self,
|
||||
concept_name: str,
|
||||
concept_type: str,
|
||||
properties: Optional[Dict[str, Any]] = None
|
||||
) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Create or update concept node.
|
||||
|
||||
Args:
|
||||
concept_name: Concept name
|
||||
concept_type: Concept type (Technique, Tool, Pattern, etc.)
|
||||
properties: Additional properties
|
||||
|
||||
Returns:
|
||||
Concept node properties
|
||||
"""
|
||||
cypher = """
|
||||
MERGE (concept:Concept {name: $name})
|
||||
ON CREATE SET
|
||||
concept.type = $type,
|
||||
concept.first_seen = timestamp(),
|
||||
concept.mention_count = 1
|
||||
ON MATCH SET
|
||||
concept.mention_count = concept.mention_count + 1
|
||||
SET concept += $properties
|
||||
RETURN concept
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_write(
|
||||
cypher,
|
||||
{
|
||||
"name": concept_name,
|
||||
"type": concept_type,
|
||||
"properties": properties or {}
|
||||
}
|
||||
)
|
||||
return result[0]["concept"] if result else None
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to create concept node: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
async def link_document_to_concept(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str,
|
||||
concept_name: str
|
||||
) -> bool:
|
||||
"""
|
||||
Create MENTIONS relationship between document and concept.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
concept_name: Concept name
|
||||
|
||||
Returns:
|
||||
True if link created
|
||||
"""
|
||||
user_label = self.get_user_label(user)
|
||||
|
||||
cypher = f"""
|
||||
MATCH (doc:Document:{user_label} {{id: $doc_id}})
|
||||
MATCH (concept:Concept {{name: $concept_name}})
|
||||
MERGE (doc)-[r:MENTIONS]->(concept)
|
||||
ON CREATE SET r.count = 1
|
||||
ON MATCH SET r.count = r.count + 1
|
||||
RETURN r
|
||||
"""
|
||||
|
||||
try:
|
||||
result = await self.execute_write(
|
||||
cypher,
|
||||
{"doc_id": doc_id, "concept_name": concept_name}
|
||||
)
|
||||
return len(result) > 0
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to link document to concept: {e}", exc_info=True)
|
||||
return False
|
||||
@@ -0,0 +1,366 @@
|
||||
"""
|
||||
Ollama client for embeddings generation.
|
||||
|
||||
Provides async embedding operations via Ollama API:
|
||||
- Text embedding generation
|
||||
- Batch embedding support
|
||||
- Model management
|
||||
"""
|
||||
|
||||
import httpx
|
||||
from typing import List, Dict, Any, Optional
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class OllamaClient:
|
||||
"""
|
||||
Ollama API client for embeddings.
|
||||
|
||||
Documentation: https://github.com/ollama/ollama/blob/main/docs/api.md
|
||||
Default model: nomic-embed-text (768-dimensional embeddings)
|
||||
"""
|
||||
|
||||
def __init__(self, base_url: str, model: str = "nomic-embed-text"):
|
||||
"""
|
||||
Initialize Ollama client.
|
||||
|
||||
Args:
|
||||
base_url: Ollama server URL (e.g., "http://ollama:11434")
|
||||
model: Embedding model name (default: "nomic-embed-text")
|
||||
"""
|
||||
self.base_url = base_url.rstrip("/")
|
||||
self.model = model
|
||||
self.embeddings_url = f"{self.base_url}/api/embeddings"
|
||||
self.generate_url = f"{self.base_url}/api/generate"
|
||||
self.tags_url = f"{self.base_url}/api/tags"
|
||||
self.client = httpx.AsyncClient(timeout=120.0) # Embeddings can be slow
|
||||
logger.info(f"Initialized Ollama client: {base_url}, model: {model}")
|
||||
|
||||
async def close(self):
|
||||
"""Close HTTP client"""
|
||||
await self.client.aclose()
|
||||
|
||||
async def embed(self, text: str) -> Optional[List[float]]:
|
||||
"""
|
||||
Generate embedding for single text.
|
||||
|
||||
Args:
|
||||
text: Text to embed
|
||||
|
||||
Returns:
|
||||
Embedding vector (768-dimensional for nomic-embed-text) or None on failure
|
||||
|
||||
Example:
|
||||
>>> embedding = await client.embed("Hello world")
|
||||
>>> len(embedding)
|
||||
768
|
||||
"""
|
||||
try:
|
||||
payload = {
|
||||
"model": self.model,
|
||||
"prompt": text
|
||||
}
|
||||
|
||||
response = await self.client.post(
|
||||
self.embeddings_url,
|
||||
json=payload
|
||||
)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
embedding = data.get("embedding")
|
||||
if not embedding:
|
||||
logger.error(f"No embedding in response: {data}")
|
||||
return None
|
||||
|
||||
return embedding
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"HTTP error: {e.response.status_code} - {e.response.text}")
|
||||
return None
|
||||
except Exception as e:
|
||||
logger.error(f"Embedding failed: {e}", exc_info=True)
|
||||
return None
|
||||
|
||||
async def embed_batch(
|
||||
self,
|
||||
texts: List[str],
|
||||
show_progress: bool = False
|
||||
) -> List[Optional[List[float]]]:
|
||||
"""
|
||||
Generate embeddings for multiple texts.
|
||||
|
||||
Args:
|
||||
texts: List of texts to embed
|
||||
show_progress: Log progress for large batches
|
||||
|
||||
Returns:
|
||||
List of embedding vectors (same order as input)
|
||||
None entries for texts that failed to embed
|
||||
|
||||
Example:
|
||||
>>> texts = ["Hello", "World", "Test"]
|
||||
>>> embeddings = await client.embed_batch(texts)
|
||||
>>> len(embeddings)
|
||||
3
|
||||
"""
|
||||
embeddings = []
|
||||
|
||||
for i, text in enumerate(texts):
|
||||
if show_progress and i % 10 == 0:
|
||||
logger.info(f"Embedding progress: {i}/{len(texts)}")
|
||||
|
||||
embedding = await self.embed(text)
|
||||
embeddings.append(embedding)
|
||||
|
||||
if show_progress:
|
||||
logger.info(f"Embedding complete: {len(embeddings)}/{len(texts)}")
|
||||
|
||||
return embeddings
|
||||
|
||||
async def embed_batch_filtered(
|
||||
self,
|
||||
texts: List[str],
|
||||
show_progress: bool = False
|
||||
) -> List[List[float]]:
|
||||
"""
|
||||
Generate embeddings for multiple texts, filtering out failures.
|
||||
|
||||
Args:
|
||||
texts: List of texts to embed
|
||||
show_progress: Log progress for large batches
|
||||
|
||||
Returns:
|
||||
List of successful embedding vectors (may be shorter than input)
|
||||
|
||||
Example:
|
||||
>>> texts = ["Hello", "World", "Test"]
|
||||
>>> embeddings = await client.embed_batch_filtered(texts)
|
||||
>>> all(e is not None for e in embeddings)
|
||||
True
|
||||
"""
|
||||
all_embeddings = await self.embed_batch(texts, show_progress)
|
||||
return [e for e in all_embeddings if e is not None]
|
||||
|
||||
async def embed_documents(
|
||||
self,
|
||||
documents: List[Dict[str, Any]],
|
||||
content_field: str = "content",
|
||||
show_progress: bool = False
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Embed documents with metadata preservation.
|
||||
|
||||
Args:
|
||||
documents: List of document dictionaries
|
||||
content_field: Field name containing text to embed
|
||||
show_progress: Log progress for large batches
|
||||
|
||||
Returns:
|
||||
List of documents with added "embedding" field
|
||||
|
||||
Example:
|
||||
>>> docs = [
|
||||
... {"content": "Hello world", "id": 1},
|
||||
... {"content": "Test doc", "id": 2}
|
||||
... ]
|
||||
>>> embedded = await client.embed_documents(docs)
|
||||
>>> "embedding" in embedded[0]
|
||||
True
|
||||
"""
|
||||
texts = [doc.get(content_field, "") for doc in documents]
|
||||
embeddings = await self.embed_batch(texts, show_progress)
|
||||
|
||||
results = []
|
||||
for doc, embedding in zip(documents, embeddings):
|
||||
doc_copy = doc.copy()
|
||||
doc_copy["embedding"] = embedding
|
||||
results.append(doc_copy)
|
||||
|
||||
return results
|
||||
|
||||
async def get_embedding_dimension(self) -> Optional[int]:
|
||||
"""
|
||||
Get embedding dimension for current model.
|
||||
|
||||
Returns:
|
||||
Embedding dimension (e.g., 768 for nomic-embed-text) or None on failure
|
||||
|
||||
Example:
|
||||
>>> dim = await client.get_embedding_dimension()
|
||||
>>> dim
|
||||
768
|
||||
"""
|
||||
# Generate a test embedding to determine dimension
|
||||
test_embedding = await self.embed("test")
|
||||
if test_embedding:
|
||||
return len(test_embedding)
|
||||
return None
|
||||
|
||||
async def list_models(self) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
List available Ollama models.
|
||||
|
||||
Returns:
|
||||
List of model information dictionaries
|
||||
|
||||
Example:
|
||||
>>> models = await client.list_models()
|
||||
>>> any(m["name"] == "nomic-embed-text" for m in models)
|
||||
True
|
||||
"""
|
||||
try:
|
||||
response = await self.client.get(self.tags_url)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
return data.get("models", [])
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to list models: {e}")
|
||||
return []
|
||||
|
||||
async def check_model_available(self, model_name: Optional[str] = None) -> bool:
|
||||
"""
|
||||
Check if a model is available.
|
||||
|
||||
Args:
|
||||
model_name: Model name to check (defaults to self.model)
|
||||
|
||||
Returns:
|
||||
True if model is available, False otherwise
|
||||
"""
|
||||
check_model = model_name or self.model
|
||||
models = await self.list_models()
|
||||
return any(m.get("name") == check_model for m in models)
|
||||
|
||||
async def generate_text(
|
||||
self,
|
||||
prompt: str,
|
||||
model: Optional[str] = None,
|
||||
stream: bool = False
|
||||
) -> Optional[str]:
|
||||
"""
|
||||
Generate text completion (for non-embedding use cases).
|
||||
|
||||
Args:
|
||||
prompt: Input prompt
|
||||
model: Model name (defaults to self.model)
|
||||
stream: Enable streaming response
|
||||
|
||||
Returns:
|
||||
Generated text or None on failure
|
||||
|
||||
Note: This is primarily for debugging/testing. Use specialized
|
||||
LLM services for production text generation.
|
||||
"""
|
||||
try:
|
||||
payload = {
|
||||
"model": model or self.model,
|
||||
"prompt": prompt,
|
||||
"stream": stream
|
||||
}
|
||||
|
||||
response = await self.client.post(
|
||||
self.generate_url,
|
||||
json=payload
|
||||
)
|
||||
response.raise_for_status()
|
||||
|
||||
if stream:
|
||||
# For streaming, return first chunk
|
||||
# Full streaming implementation would need async generator
|
||||
return response.text
|
||||
else:
|
||||
data = response.json()
|
||||
return data.get("response")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Text generation failed: {e}")
|
||||
return None
|
||||
|
||||
async def health_check(self) -> bool:
|
||||
"""
|
||||
Check if Ollama server is reachable and model is available.
|
||||
|
||||
Returns:
|
||||
True if healthy, False otherwise
|
||||
"""
|
||||
try:
|
||||
# Check server is up
|
||||
response = await self.client.get(self.tags_url, timeout=5.0)
|
||||
response.raise_for_status()
|
||||
|
||||
# Check model is available
|
||||
models_available = await self.check_model_available()
|
||||
if not models_available:
|
||||
logger.warning(f"Model '{self.model}' not found in Ollama")
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Health check failed: {e}")
|
||||
return False
|
||||
|
||||
def estimate_tokens(self, text: str) -> int:
|
||||
"""
|
||||
Rough estimate of token count for text.
|
||||
|
||||
Uses simple heuristic: ~4 characters per token.
|
||||
|
||||
Args:
|
||||
text: Input text
|
||||
|
||||
Returns:
|
||||
Estimated token count
|
||||
"""
|
||||
return len(text) // 4
|
||||
|
||||
def chunk_text_for_embedding(
|
||||
self,
|
||||
text: str,
|
||||
max_tokens: int = 512,
|
||||
overlap: int = 50
|
||||
) -> List[str]:
|
||||
"""
|
||||
Chunk text into segments suitable for embedding.
|
||||
|
||||
Args:
|
||||
text: Input text
|
||||
max_tokens: Maximum tokens per chunk
|
||||
overlap: Token overlap between chunks
|
||||
|
||||
Returns:
|
||||
List of text chunks
|
||||
|
||||
Example:
|
||||
>>> chunks = client.chunk_text_for_embedding(long_text, max_tokens=512)
|
||||
>>> all(client.estimate_tokens(c) <= 512 for c in chunks)
|
||||
True
|
||||
"""
|
||||
# Convert tokens to approximate character count
|
||||
max_chars = max_tokens * 4
|
||||
overlap_chars = overlap * 4
|
||||
|
||||
if len(text) <= max_chars:
|
||||
return [text]
|
||||
|
||||
chunks = []
|
||||
start = 0
|
||||
|
||||
while start < len(text):
|
||||
end = start + max_chars
|
||||
chunk = text[start:end]
|
||||
|
||||
# Try to break at sentence boundary
|
||||
if end < len(text):
|
||||
last_period = chunk.rfind(". ")
|
||||
if last_period > max_chars * 0.5: # Only break if > 50% through chunk
|
||||
end = start + last_period + 1
|
||||
chunk = text[start:end]
|
||||
|
||||
chunks.append(chunk.strip())
|
||||
start = end - overlap_chars
|
||||
|
||||
return chunks
|
||||
@@ -0,0 +1,412 @@
|
||||
"""
|
||||
Qdrant client wrapper for Library Desk.
|
||||
|
||||
Provides async vector operations with:
|
||||
- Collection-per-user multi-tenancy
|
||||
- Document chunk storage with embeddings
|
||||
- Semantic search
|
||||
- Similarity queries
|
||||
"""
|
||||
|
||||
from qdrant_client import QdrantClient
|
||||
from qdrant_client.models import (
|
||||
Distance, VectorParams, PointStruct,
|
||||
Filter, FieldCondition, MatchValue
|
||||
)
|
||||
from typing import List, Dict, Any, Optional
|
||||
import uuid
|
||||
import logging
|
||||
|
||||
from src.core.multi_tenancy import get_qdrant_collection_name
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class QdrantClientWrapper:
|
||||
"""
|
||||
Qdrant client wrapper with multi-tenancy support.
|
||||
|
||||
Pattern: Collection per user (from qdrant_memory.py)
|
||||
Each user has isolated vector collection for their documents.
|
||||
"""
|
||||
|
||||
def __init__(self, url: str, embedding_dim: int = 768):
|
||||
"""
|
||||
Initialize Qdrant client.
|
||||
|
||||
Args:
|
||||
url: Qdrant server URL (e.g., "http://qdrant:6333")
|
||||
embedding_dim: Vector embedding dimension (default 768 for nomic-embed-text)
|
||||
"""
|
||||
self.client = QdrantClient(url=url)
|
||||
self.embedding_dim = embedding_dim
|
||||
logger.info(f"Initialized Qdrant client: {url}")
|
||||
|
||||
def get_collection_name(self, user: str) -> str:
|
||||
"""
|
||||
Get collection name for user.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
|
||||
Returns:
|
||||
Collection name (e.g., "library_desk_jpmschweitzer")
|
||||
"""
|
||||
return get_qdrant_collection_name(user)
|
||||
|
||||
async def ensure_collection(self, user: str):
|
||||
"""
|
||||
Create user's collection if it doesn't exist.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
collections = self.client.get_collections()
|
||||
existing = [c.name for c in collections.collections]
|
||||
|
||||
if collection_name not in existing:
|
||||
logger.info(f"Creating Qdrant collection: {collection_name}")
|
||||
self.client.create_collection(
|
||||
collection_name=collection_name,
|
||||
vectors_config=VectorParams(
|
||||
size=self.embedding_dim,
|
||||
distance=Distance.COSINE
|
||||
)
|
||||
)
|
||||
logger.info(f"Created collection: {collection_name}")
|
||||
except Exception as e:
|
||||
logger.error(f"Error ensuring collection: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def upsert_document_chunks(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str,
|
||||
chunks: List[Dict[str, Any]],
|
||||
embeddings: List[List[float]]
|
||||
) -> int:
|
||||
"""
|
||||
Upsert document chunks with embeddings.
|
||||
|
||||
Point structure:
|
||||
{
|
||||
id: "doc_123_chunk_0",
|
||||
vector: [...],
|
||||
payload: {
|
||||
doc_id: "doc_123",
|
||||
chunk_index: 0,
|
||||
content: "text content",
|
||||
metadata: {...}
|
||||
}
|
||||
}
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
chunks: List of chunk dictionaries with content
|
||||
embeddings: List of embedding vectors
|
||||
|
||||
Returns:
|
||||
Number of chunks upserted
|
||||
|
||||
Raises:
|
||||
ValueError: If chunks and embeddings length mismatch
|
||||
"""
|
||||
if len(chunks) != len(embeddings):
|
||||
raise ValueError(
|
||||
f"Chunks ({len(chunks)}) and embeddings ({len(embeddings)}) length mismatch"
|
||||
)
|
||||
|
||||
collection_name = self.get_collection_name(user)
|
||||
await self.ensure_collection(user)
|
||||
|
||||
points = []
|
||||
for i, (chunk, embedding) in enumerate(zip(chunks, embeddings)):
|
||||
# Generate deterministic point ID
|
||||
point_id = str(uuid.uuid5(
|
||||
uuid.NAMESPACE_DNS,
|
||||
f"{doc_id}_chunk_{i}"
|
||||
))
|
||||
|
||||
points.append(PointStruct(
|
||||
id=point_id,
|
||||
vector=embedding,
|
||||
payload={
|
||||
"doc_id": doc_id,
|
||||
"chunk_index": i,
|
||||
"content": chunk.get("content", ""),
|
||||
"metadata": chunk.get("metadata", {})
|
||||
}
|
||||
))
|
||||
|
||||
try:
|
||||
self.client.upsert(
|
||||
collection_name=collection_name,
|
||||
points=points
|
||||
)
|
||||
logger.info(f"Upserted {len(points)} chunks for {doc_id}")
|
||||
return len(points)
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to upsert chunks: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def search(
|
||||
self,
|
||||
user: str,
|
||||
query_vector: List[float],
|
||||
limit: int = 10,
|
||||
score_threshold: float = 0.7,
|
||||
filter_dict: Optional[Dict[str, Any]] = None
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Semantic search in user's collection.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
query_vector: Query embedding vector
|
||||
limit: Maximum results to return
|
||||
score_threshold: Minimum similarity score (0.0-1.0)
|
||||
filter_dict: Optional payload filters
|
||||
|
||||
Returns:
|
||||
List of matches with scores and payloads
|
||||
|
||||
Example:
|
||||
results = await client.search(
|
||||
user="jpmschweitzer",
|
||||
query_vector=[0.1, 0.2, ...],
|
||||
limit=5,
|
||||
filter_dict={"doc_id": "doc_123"}
|
||||
)
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
# Build filter if provided
|
||||
query_filter = None
|
||||
if filter_dict:
|
||||
conditions = []
|
||||
for key, value in filter_dict.items():
|
||||
conditions.append(
|
||||
FieldCondition(key=key, match=MatchValue(value=value))
|
||||
)
|
||||
query_filter = Filter(must=conditions)
|
||||
|
||||
try:
|
||||
results = self.client.search(
|
||||
collection_name=collection_name,
|
||||
query_vector=query_vector,
|
||||
limit=limit,
|
||||
score_threshold=score_threshold,
|
||||
query_filter=query_filter,
|
||||
with_payload=True
|
||||
)
|
||||
|
||||
return [
|
||||
{
|
||||
"id": str(result.id),
|
||||
"score": result.score,
|
||||
"doc_id": result.payload["doc_id"],
|
||||
"chunk_index": result.payload["chunk_index"],
|
||||
"content": result.payload["content"],
|
||||
"metadata": result.payload.get("metadata", {})
|
||||
}
|
||||
for result in results
|
||||
]
|
||||
except Exception as e:
|
||||
logger.error(f"Search failed: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
async def delete_document(self, user: str, doc_id: str) -> bool:
|
||||
"""
|
||||
Delete all chunks for a document.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
|
||||
Returns:
|
||||
True if deleted successfully
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
self.client.delete(
|
||||
collection_name=collection_name,
|
||||
points_selector=Filter(
|
||||
must=[
|
||||
FieldCondition(
|
||||
key="doc_id",
|
||||
match=MatchValue(value=doc_id)
|
||||
)
|
||||
]
|
||||
)
|
||||
)
|
||||
logger.info(f"Deleted chunks for {doc_id}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete document: {e}", exc_info=True)
|
||||
return False
|
||||
|
||||
async def get_document_chunks(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Get all chunks for a document.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Document ID
|
||||
|
||||
Returns:
|
||||
List of chunks with content and metadata
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
# Scroll through points with doc_id filter
|
||||
points, _ = self.client.scroll(
|
||||
collection_name=collection_name,
|
||||
scroll_filter=Filter(
|
||||
must=[
|
||||
FieldCondition(
|
||||
key="doc_id",
|
||||
match=MatchValue(value=doc_id)
|
||||
)
|
||||
]
|
||||
),
|
||||
limit=1000,
|
||||
with_payload=True,
|
||||
with_vectors=False
|
||||
)
|
||||
|
||||
return [
|
||||
{
|
||||
"id": str(point.id),
|
||||
"chunk_index": point.payload["chunk_index"],
|
||||
"content": point.payload["content"],
|
||||
"metadata": point.payload.get("metadata", {})
|
||||
}
|
||||
for point in points
|
||||
]
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get document chunks: {e}", exc_info=True)
|
||||
return []
|
||||
|
||||
async def count_documents(self, user: str) -> int:
|
||||
"""
|
||||
Count total number of unique documents in user's collection.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
|
||||
Returns:
|
||||
Number of unique documents
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
# Get collection info
|
||||
collection_info = self.client.get_collection(collection_name)
|
||||
# This gives total points, not unique docs
|
||||
# For unique docs, would need to aggregate by doc_id
|
||||
return collection_info.points_count
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to count documents: {e}", exc_info=True)
|
||||
return 0
|
||||
|
||||
async def delete_collection(self, user: str) -> bool:
|
||||
"""
|
||||
Delete user's entire collection.
|
||||
|
||||
Warning: This removes all data for the user!
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
|
||||
Returns:
|
||||
True if deleted successfully
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
self.client.delete_collection(collection_name)
|
||||
logger.warning(f"Deleted collection: {collection_name}")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to delete collection: {e}", exc_info=True)
|
||||
return False
|
||||
|
||||
async def find_similar_chunks(
|
||||
self,
|
||||
user: str,
|
||||
doc_id: str,
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Find chunks similar to those in a given document.
|
||||
|
||||
Strategy: Get all chunks from doc, use their vectors to find similar chunks.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
doc_id: Source document ID
|
||||
limit: Maximum results per chunk
|
||||
|
||||
Returns:
|
||||
List of similar chunks from other documents
|
||||
"""
|
||||
collection_name = self.get_collection_name(user)
|
||||
|
||||
try:
|
||||
# Get source document chunks with vectors
|
||||
source_points, _ = self.client.scroll(
|
||||
collection_name=collection_name,
|
||||
scroll_filter=Filter(
|
||||
must=[
|
||||
FieldCondition(
|
||||
key="doc_id",
|
||||
match=MatchValue(value=doc_id)
|
||||
)
|
||||
]
|
||||
),
|
||||
limit=10, # Sample first 10 chunks
|
||||
with_payload=True,
|
||||
with_vectors=True
|
||||
)
|
||||
|
||||
if not source_points:
|
||||
return []
|
||||
|
||||
# Search using first chunk's vector
|
||||
# (could aggregate multiple chunks for better results)
|
||||
first_vector = source_points[0].vector
|
||||
|
||||
results = self.client.search(
|
||||
collection_name=collection_name,
|
||||
query_vector=first_vector,
|
||||
limit=limit * 2, # Get more to filter out same doc
|
||||
with_payload=True
|
||||
)
|
||||
|
||||
# Filter out chunks from same document
|
||||
similar = [
|
||||
{
|
||||
"id": str(r.id),
|
||||
"score": r.score,
|
||||
"doc_id": r.payload["doc_id"],
|
||||
"content": r.payload["content"]
|
||||
}
|
||||
for r in results
|
||||
if r.payload["doc_id"] != doc_id
|
||||
]
|
||||
|
||||
return similar[:limit]
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to find similar chunks: {e}", exc_info=True)
|
||||
return []
|
||||
@@ -0,0 +1,332 @@
|
||||
"""
|
||||
SearXNG search client for Library Desk.
|
||||
|
||||
Provides async web search via SearXNG instance:
|
||||
- General web search
|
||||
- Category-specific search
|
||||
- Language filtering
|
||||
- Result formatting
|
||||
"""
|
||||
|
||||
import httpx
|
||||
from typing import Optional, List, Dict, Any
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class SearXNGClient:
|
||||
"""
|
||||
SearXNG search API client.
|
||||
|
||||
Documentation: https://docs.searxng.org/dev/search_api.html
|
||||
API Format: JSON (?format=json)
|
||||
"""
|
||||
|
||||
def __init__(self, base_url: str):
|
||||
"""
|
||||
Initialize SearXNG client.
|
||||
|
||||
Args:
|
||||
base_url: SearXNG base URL (e.g., "http://searxng:8080")
|
||||
"""
|
||||
self.base_url = base_url.rstrip("/")
|
||||
self.search_url = f"{self.base_url}/search"
|
||||
self.client = httpx.AsyncClient(timeout=30.0)
|
||||
logger.info(f"Initialized SearXNG client: {base_url}")
|
||||
|
||||
async def close(self):
|
||||
"""Close HTTP client"""
|
||||
await self.client.aclose()
|
||||
|
||||
async def search(
|
||||
self,
|
||||
query: str,
|
||||
categories: Optional[List[str]] = None,
|
||||
language: str = "en",
|
||||
time_range: Optional[str] = None,
|
||||
safesearch: int = 0,
|
||||
pageno: int = 1,
|
||||
limit: int = 10
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Search via SearXNG.
|
||||
|
||||
Args:
|
||||
query: Search query string
|
||||
categories: List of categories (e.g., ["general", "images", "news"])
|
||||
language: Language code (e.g., "en", "fr", "auto")
|
||||
time_range: Time range filter ("day", "week", "month", "year", None for all)
|
||||
safesearch: Safe search level (0=off, 1=moderate, 2=strict)
|
||||
pageno: Page number (starts at 1)
|
||||
limit: Maximum results to return
|
||||
|
||||
Returns:
|
||||
Search results dictionary with:
|
||||
- query: Original query
|
||||
- results: List of result items
|
||||
- number_of_results: Total results found
|
||||
- suggestions: Query suggestions
|
||||
|
||||
Raises:
|
||||
Exception: If search fails
|
||||
"""
|
||||
params = {
|
||||
"q": query,
|
||||
"format": "json",
|
||||
"language": language,
|
||||
"safesearch": safesearch,
|
||||
"pageno": pageno
|
||||
}
|
||||
|
||||
# Add optional parameters
|
||||
if categories:
|
||||
params["categories"] = ",".join(categories)
|
||||
if time_range:
|
||||
params["time_range"] = time_range
|
||||
|
||||
try:
|
||||
response = await self.client.get(self.search_url, params=params)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
# Limit results if requested
|
||||
results = data.get("results", [])
|
||||
if limit:
|
||||
results = results[:limit]
|
||||
|
||||
return {
|
||||
"query": data.get("query", query),
|
||||
"results": results,
|
||||
"number_of_results": data.get("number_of_results", 0),
|
||||
"suggestions": data.get("suggestions", []),
|
||||
"answers": data.get("answers", []),
|
||||
"infoboxes": data.get("infoboxes", [])
|
||||
}
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"HTTP error: {e.response.status_code} - {e.response.text}")
|
||||
raise Exception(f"SearXNG search failed: {e.response.status_code}")
|
||||
except Exception as e:
|
||||
logger.error(f"Search failed: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def search_general(
|
||||
self,
|
||||
query: str,
|
||||
language: str = "en",
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Simplified general web search.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
language: Language code
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of search results with:
|
||||
- title: Page title
|
||||
- url: Page URL
|
||||
- content: Page description/snippet
|
||||
- engine: Search engine that provided result
|
||||
- score: Relevance score (if available)
|
||||
"""
|
||||
try:
|
||||
result = await self.search(
|
||||
query=query,
|
||||
categories=["general"],
|
||||
language=language,
|
||||
limit=limit
|
||||
)
|
||||
return result.get("results", [])
|
||||
except Exception as e:
|
||||
logger.error(f"General search failed: {e}")
|
||||
return []
|
||||
|
||||
async def search_with_context(
|
||||
self,
|
||||
query: str,
|
||||
context: Optional[str] = None,
|
||||
language: str = "en",
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search with additional context appended to query.
|
||||
|
||||
Useful for RAG queries where you want to enhance search with context.
|
||||
|
||||
Args:
|
||||
query: Primary search query
|
||||
context: Additional context to append
|
||||
language: Language code
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of search results
|
||||
"""
|
||||
enhanced_query = f"{query} {context}" if context else query
|
||||
return await self.search_general(enhanced_query, language, limit)
|
||||
|
||||
async def search_documentation(
|
||||
self,
|
||||
query: str,
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search for technical documentation.
|
||||
|
||||
Enhances query with "documentation" and filters for technical content.
|
||||
|
||||
Args:
|
||||
query: Search query (e.g., "FastAPI")
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of documentation search results
|
||||
"""
|
||||
enhanced_query = f"{query} documentation"
|
||||
return await self.search_general(enhanced_query, limit=limit)
|
||||
|
||||
async def search_recent(
|
||||
self,
|
||||
query: str,
|
||||
time_range: str = "month",
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search for recent content only.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
time_range: Time range ("day", "week", "month", "year")
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of recent search results
|
||||
"""
|
||||
try:
|
||||
result = await self.search(
|
||||
query=query,
|
||||
categories=["general"],
|
||||
time_range=time_range,
|
||||
limit=limit
|
||||
)
|
||||
return result.get("results", [])
|
||||
except Exception as e:
|
||||
logger.error(f"Recent search failed: {e}")
|
||||
return []
|
||||
|
||||
async def get_suggestions(self, query: str) -> List[str]:
|
||||
"""
|
||||
Get search query suggestions.
|
||||
|
||||
Args:
|
||||
query: Partial query
|
||||
|
||||
Returns:
|
||||
List of suggested queries
|
||||
"""
|
||||
try:
|
||||
result = await self.search(query=query, limit=1)
|
||||
return result.get("suggestions", [])
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get suggestions: {e}")
|
||||
return []
|
||||
|
||||
async def search_images(
|
||||
self,
|
||||
query: str,
|
||||
safesearch: int = 1,
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search for images.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
safesearch: Safe search level (0=off, 1=moderate, 2=strict)
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of image results with:
|
||||
- title: Image title
|
||||
- url: Image URL
|
||||
- thumbnail_src: Thumbnail URL
|
||||
- img_src: Full image URL
|
||||
- content: Description
|
||||
"""
|
||||
try:
|
||||
result = await self.search(
|
||||
query=query,
|
||||
categories=["images"],
|
||||
safesearch=safesearch,
|
||||
limit=limit
|
||||
)
|
||||
return result.get("results", [])
|
||||
except Exception as e:
|
||||
logger.error(f"Image search failed: {e}")
|
||||
return []
|
||||
|
||||
async def search_news(
|
||||
self,
|
||||
query: str,
|
||||
time_range: str = "week",
|
||||
limit: int = 10
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search for news articles.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
time_range: Time range ("day", "week", "month")
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of news results
|
||||
"""
|
||||
try:
|
||||
result = await self.search(
|
||||
query=query,
|
||||
categories=["news"],
|
||||
time_range=time_range,
|
||||
limit=limit
|
||||
)
|
||||
return result.get("results", [])
|
||||
except Exception as e:
|
||||
logger.error(f"News search failed: {e}")
|
||||
return []
|
||||
|
||||
async def format_results_for_rag(
|
||||
self,
|
||||
results: List[Dict[str, Any]],
|
||||
max_snippet_length: int = 500
|
||||
) -> List[Dict[str, str]]:
|
||||
"""
|
||||
Format search results for RAG context.
|
||||
|
||||
Extracts relevant fields and truncates content.
|
||||
|
||||
Args:
|
||||
results: Raw search results
|
||||
max_snippet_length: Maximum length of content snippet
|
||||
|
||||
Returns:
|
||||
Formatted results with title, url, snippet
|
||||
"""
|
||||
formatted = []
|
||||
for result in results:
|
||||
content = result.get("content", "")
|
||||
if len(content) > max_snippet_length:
|
||||
content = content[:max_snippet_length] + "..."
|
||||
|
||||
formatted.append({
|
||||
"title": result.get("title", ""),
|
||||
"url": result.get("url", ""),
|
||||
"snippet": content,
|
||||
"engine": result.get("engine", ""),
|
||||
"score": result.get("score", 0.0)
|
||||
})
|
||||
|
||||
return formatted
|
||||
@@ -0,0 +1,502 @@
|
||||
"""
|
||||
Wiki.js GraphQL client for Library Desk.
|
||||
|
||||
Provides async Wiki.js operations via GraphQL API:
|
||||
- Page CRUD (create, read, update, delete)
|
||||
- Search and listing
|
||||
- Tag management
|
||||
- Multi-tenancy via path namespaces
|
||||
"""
|
||||
|
||||
import httpx
|
||||
from typing import Optional, List, Dict, Any
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class WikiJSClient:
|
||||
"""
|
||||
Wiki.js GraphQL API client.
|
||||
|
||||
Documentation: https://docs.requarks.io/dev/api
|
||||
Authentication: Bearer token in Authorization header
|
||||
"""
|
||||
|
||||
def __init__(self, base_url: str, api_key: str):
|
||||
"""
|
||||
Initialize Wiki.js client.
|
||||
|
||||
Args:
|
||||
base_url: Wiki.js base URL (e.g., "http://wiki:3000")
|
||||
api_key: Wiki.js API key (from Admin → API Access)
|
||||
"""
|
||||
self.base_url = base_url.rstrip("/")
|
||||
self.graphql_url = f"{self.base_url}/graphql"
|
||||
self.headers = {
|
||||
"Authorization": f"Bearer {api_key}",
|
||||
"Content-Type": "application/json"
|
||||
}
|
||||
self.client = httpx.AsyncClient(timeout=30.0)
|
||||
logger.info(f"Initialized Wiki.js client: {base_url}")
|
||||
|
||||
async def close(self):
|
||||
"""Close HTTP client"""
|
||||
await self.client.aclose()
|
||||
|
||||
async def _execute_query(
|
||||
self,
|
||||
query: str,
|
||||
variables: Optional[Dict] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Execute GraphQL query.
|
||||
|
||||
Args:
|
||||
query: GraphQL query string
|
||||
variables: Query variables
|
||||
|
||||
Returns:
|
||||
Query result data
|
||||
|
||||
Raises:
|
||||
Exception: If query fails or returns errors
|
||||
"""
|
||||
payload = {
|
||||
"query": query,
|
||||
"variables": variables or {}
|
||||
}
|
||||
|
||||
try:
|
||||
response = await self.client.post(
|
||||
self.graphql_url,
|
||||
headers=self.headers,
|
||||
json=payload
|
||||
)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
|
||||
if "errors" in result:
|
||||
logger.error(f"GraphQL errors: {result['errors']}")
|
||||
raise Exception(f"GraphQL errors: {result['errors']}")
|
||||
|
||||
return result.get("data", {})
|
||||
|
||||
except httpx.HTTPStatusError as e:
|
||||
logger.error(f"HTTP error: {e.response.status_code} - {e.response.text}")
|
||||
raise
|
||||
except Exception as e:
|
||||
logger.error(f"GraphQL query failed: {e}", exc_info=True)
|
||||
raise
|
||||
|
||||
async def list_pages(
|
||||
self,
|
||||
path_prefix: str = "",
|
||||
tags: Optional[List[str]] = None,
|
||||
limit: int = 50
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
List pages with optional filtering.
|
||||
|
||||
Multi-tenancy: Use path_prefix to filter by user namespace.
|
||||
|
||||
Args:
|
||||
path_prefix: Filter by path prefix (e.g., "/users/jpmschweitzer")
|
||||
tags: Filter by tags (e.g., ["projects"])
|
||||
limit: Maximum results
|
||||
|
||||
Returns:
|
||||
List of page objects
|
||||
"""
|
||||
query = """
|
||||
query ListPages($limit: Int, $orderBy: PageOrderBy) {
|
||||
pages {
|
||||
list(limit: $limit, orderBy: $orderBy) {
|
||||
id
|
||||
path
|
||||
title
|
||||
description
|
||||
tags
|
||||
createdAt
|
||||
updatedAt
|
||||
isPublished
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
variables = {
|
||||
"limit": limit,
|
||||
"orderBy": "TITLE"
|
||||
}
|
||||
|
||||
data = await self._execute_query(query, variables)
|
||||
pages = data.get("pages", {}).get("list", [])
|
||||
|
||||
# Filter by path prefix (client-side if API doesn't support)
|
||||
if path_prefix:
|
||||
pages = [p for p in pages if p["path"].startswith(path_prefix)]
|
||||
|
||||
# Filter by tags (dossiers)
|
||||
if tags:
|
||||
pages = [
|
||||
p for p in pages
|
||||
if any(tag in (p.get("tags") or []) for tag in tags)
|
||||
]
|
||||
|
||||
return pages
|
||||
|
||||
async def get_page(self, page_id: int) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Get single page by ID.
|
||||
|
||||
Args:
|
||||
page_id: Page ID
|
||||
|
||||
Returns:
|
||||
Page object or None if not found
|
||||
"""
|
||||
query = """
|
||||
query GetPage($id: Int!) {
|
||||
pages {
|
||||
single(id: $id) {
|
||||
id
|
||||
path
|
||||
title
|
||||
description
|
||||
content
|
||||
tags
|
||||
createdAt
|
||||
updatedAt
|
||||
isPublished
|
||||
editor
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
try:
|
||||
data = await self._execute_query(query, {"id": page_id})
|
||||
return data.get("pages", {}).get("single")
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get page {page_id}: {e}")
|
||||
return None
|
||||
|
||||
async def create_page(
|
||||
self,
|
||||
path: str,
|
||||
title: str,
|
||||
content: str,
|
||||
description: str = "",
|
||||
tags: Optional[List[str]] = None,
|
||||
is_published: bool = True,
|
||||
editor: str = "markdown"
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Create new page.
|
||||
|
||||
Multi-tenancy: Ensure path starts with user namespace.
|
||||
|
||||
Args:
|
||||
path: Page path (e.g., "/users/jpmschweitzer/projects/library-desk")
|
||||
title: Page title
|
||||
content: Page content (markdown)
|
||||
description: Short description
|
||||
tags: List of tags (for dossier organization)
|
||||
is_published: Whether page is published
|
||||
editor: Editor type (markdown, wysiwyg, etc.)
|
||||
|
||||
Returns:
|
||||
Created page object
|
||||
|
||||
Raises:
|
||||
Exception: If creation fails
|
||||
"""
|
||||
mutation = """
|
||||
mutation CreatePage(
|
||||
$content: String!,
|
||||
$description: String!,
|
||||
$editor: String!,
|
||||
$isPublished: Boolean!,
|
||||
$locale: String!,
|
||||
$path: String!,
|
||||
$tags: [String]!,
|
||||
$title: String!
|
||||
) {
|
||||
pages {
|
||||
create(
|
||||
content: $content,
|
||||
description: $description,
|
||||
editor: $editor,
|
||||
isPublished: $isPublished,
|
||||
locale: $locale,
|
||||
path: $path,
|
||||
tags: $tags,
|
||||
title: $title
|
||||
) {
|
||||
responseResult {
|
||||
succeeded
|
||||
errorCode
|
||||
message
|
||||
}
|
||||
page {
|
||||
id
|
||||
path
|
||||
title
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
variables = {
|
||||
"path": path,
|
||||
"title": title,
|
||||
"content": content,
|
||||
"description": description,
|
||||
"tags": tags or [],
|
||||
"isPublished": is_published,
|
||||
"editor": editor,
|
||||
"locale": "en"
|
||||
}
|
||||
|
||||
data = await self._execute_query(mutation, variables)
|
||||
result = data.get("pages", {}).get("create", {})
|
||||
|
||||
if not result.get("responseResult", {}).get("succeeded"):
|
||||
error = result.get("responseResult", {})
|
||||
raise Exception(f"Failed to create page: {error}")
|
||||
|
||||
logger.info(f"Created page: {path}")
|
||||
return result.get("page")
|
||||
|
||||
async def update_page(
|
||||
self,
|
||||
page_id: int,
|
||||
content: Optional[str] = None,
|
||||
title: Optional[str] = None,
|
||||
description: Optional[str] = None,
|
||||
tags: Optional[List[str]] = None
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Update existing page.
|
||||
|
||||
Args:
|
||||
page_id: Page ID
|
||||
content: New content (optional)
|
||||
title: New title (optional)
|
||||
description: New description (optional)
|
||||
tags: New tags (optional)
|
||||
|
||||
Returns:
|
||||
Updated page object
|
||||
|
||||
Raises:
|
||||
Exception: If update fails
|
||||
"""
|
||||
mutation = """
|
||||
mutation UpdatePage(
|
||||
$id: Int!,
|
||||
$content: String,
|
||||
$title: String,
|
||||
$description: String,
|
||||
$tags: [String]
|
||||
) {
|
||||
pages {
|
||||
update(
|
||||
id: $id,
|
||||
content: $content,
|
||||
title: $title,
|
||||
description: $description,
|
||||
tags: $tags
|
||||
) {
|
||||
responseResult {
|
||||
succeeded
|
||||
errorCode
|
||||
message
|
||||
}
|
||||
page {
|
||||
id
|
||||
updatedAt
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
variables = {"id": page_id}
|
||||
if content is not None:
|
||||
variables["content"] = content
|
||||
if title is not None:
|
||||
variables["title"] = title
|
||||
if description is not None:
|
||||
variables["description"] = description
|
||||
if tags is not None:
|
||||
variables["tags"] = tags
|
||||
|
||||
data = await self._execute_query(mutation, variables)
|
||||
result = data.get("pages", {}).get("update", {})
|
||||
|
||||
if not result.get("responseResult", {}).get("succeeded"):
|
||||
error = result.get("responseResult", {})
|
||||
raise Exception(f"Failed to update page: {error}")
|
||||
|
||||
logger.info(f"Updated page: {page_id}")
|
||||
return result.get("page")
|
||||
|
||||
async def delete_page(self, page_id: int):
|
||||
"""
|
||||
Delete page.
|
||||
|
||||
Args:
|
||||
page_id: Page ID
|
||||
|
||||
Raises:
|
||||
Exception: If deletion fails
|
||||
"""
|
||||
mutation = """
|
||||
mutation DeletePage($id: Int!) {
|
||||
pages {
|
||||
delete(id: $id) {
|
||||
responseResult {
|
||||
succeeded
|
||||
errorCode
|
||||
message
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
data = await self._execute_query(mutation, {"id": page_id})
|
||||
result = data.get("pages", {}).get("delete", {})
|
||||
|
||||
if not result.get("responseResult", {}).get("succeeded"):
|
||||
error = result.get("responseResult", {})
|
||||
raise Exception(f"Failed to delete page: {error}")
|
||||
|
||||
logger.info(f"Deleted page: {page_id}")
|
||||
|
||||
async def search_pages(
|
||||
self,
|
||||
query: str,
|
||||
path_prefix: Optional[str] = None
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Search pages by content.
|
||||
|
||||
Args:
|
||||
query: Search query
|
||||
path_prefix: Optional path prefix filter
|
||||
|
||||
Returns:
|
||||
List of matching pages
|
||||
"""
|
||||
gql_query = """
|
||||
query SearchPages($query: String!) {
|
||||
pages {
|
||||
search(query: $query) {
|
||||
results {
|
||||
id
|
||||
path
|
||||
title
|
||||
description
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
data = await self._execute_query(gql_query, {"query": query})
|
||||
results = data.get("pages", {}).get("search", {}).get("results", [])
|
||||
|
||||
# Filter by path prefix if provided
|
||||
if path_prefix:
|
||||
results = [r for r in results if r["path"].startswith(path_prefix)]
|
||||
|
||||
return results
|
||||
|
||||
async def get_page_tree(self, path: str = "/") -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Get page tree structure.
|
||||
|
||||
Args:
|
||||
path: Root path
|
||||
|
||||
Returns:
|
||||
Tree structure of pages
|
||||
"""
|
||||
query = """
|
||||
query GetPageTree($parent: Int, $mode: String!) {
|
||||
pages {
|
||||
tree(parent: $parent, mode: $mode) {
|
||||
id
|
||||
path
|
||||
title
|
||||
isFolder
|
||||
pageId
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
try:
|
||||
data = await self._execute_query(
|
||||
query,
|
||||
{"parent": 0, "mode": "all"}
|
||||
)
|
||||
return data.get("pages", {}).get("tree", [])
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to get page tree: {e}")
|
||||
return []
|
||||
|
||||
async def move_page(
|
||||
self,
|
||||
page_id: int,
|
||||
new_path: str,
|
||||
locale: str = "en"
|
||||
) -> bool:
|
||||
"""
|
||||
Move/rename page.
|
||||
|
||||
Args:
|
||||
page_id: Page ID
|
||||
new_path: New page path
|
||||
locale: Page locale
|
||||
|
||||
Returns:
|
||||
True if successful
|
||||
"""
|
||||
mutation = """
|
||||
mutation MovePage($id: Int!, $destinationPath: String!, $destinationLocale: String!) {
|
||||
pages {
|
||||
move(id: $id, destinationPath: $destinationPath, destinationLocale: $destinationLocale) {
|
||||
responseResult {
|
||||
succeeded
|
||||
errorCode
|
||||
message
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
"""
|
||||
|
||||
try:
|
||||
data = await self._execute_query(
|
||||
mutation,
|
||||
{
|
||||
"id": page_id,
|
||||
"destinationPath": new_path,
|
||||
"destinationLocale": locale
|
||||
}
|
||||
)
|
||||
result = data.get("pages", {}).get("move", {})
|
||||
success = result.get("responseResult", {}).get("succeeded", False)
|
||||
|
||||
if success:
|
||||
logger.info(f"Moved page {page_id} to {new_path}")
|
||||
return success
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"Failed to move page: {e}")
|
||||
return False
|
||||
@@ -41,10 +41,10 @@ class Settings(BaseSettings):
|
||||
ollama_url: str = Field(default="http://ollama:11434", description="Ollama URL")
|
||||
ollama_model: str = Field(default="nomic-embed-text", description="Ollama embedding model")
|
||||
|
||||
# Redis Configuration
|
||||
# Redis Configuration (for job tracking - separate DB from wiki)
|
||||
redis_host: str = Field(default="redis-shared", description="Redis host")
|
||||
redis_port: int = Field(default=6379, description="Redis port")
|
||||
redis_db: int = Field(default=2, description="Redis database number")
|
||||
redis_db: int = Field(default=4, description="Redis database number (4 for library-desk jobs)")
|
||||
|
||||
# Application
|
||||
app_name: str = Field(default="Library Desk", description="Application name")
|
||||
|
||||
@@ -0,0 +1,286 @@
|
||||
"""
|
||||
Dependency injection for Library Desk.
|
||||
|
||||
Provides FastAPI dependencies for service clients with:
|
||||
- Singleton pattern via @lru_cache
|
||||
- Lazy initialization
|
||||
- Proper lifecycle management
|
||||
- Type aliases for clean endpoint signatures
|
||||
"""
|
||||
|
||||
from functools import lru_cache
|
||||
from typing import Annotated
|
||||
from fastapi import Depends
|
||||
import logging
|
||||
|
||||
from src.config import Settings, get_settings
|
||||
from src.clients.neo4j_client import Neo4jClient
|
||||
from src.clients.qdrant_client import QdrantClientWrapper
|
||||
from src.clients.wikijs_client import WikiJSClient
|
||||
from src.clients.searxng_client import SearXNGClient
|
||||
from src.clients.ollama_client import OllamaClient
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
# Settings dependency
|
||||
SettingsDep = Annotated[Settings, Depends(get_settings)]
|
||||
|
||||
|
||||
# Client factory functions with @lru_cache for singletons
|
||||
@lru_cache
|
||||
def get_neo4j_client() -> Neo4jClient:
|
||||
"""
|
||||
Get Neo4j client singleton.
|
||||
|
||||
Returns:
|
||||
Initialized Neo4j client (not yet connected)
|
||||
|
||||
Note: Call client.connect() during app startup
|
||||
"""
|
||||
settings = get_settings()
|
||||
client = Neo4jClient(
|
||||
uri=settings.neo4j_uri,
|
||||
user=settings.neo4j_user,
|
||||
password=settings.neo4j_password
|
||||
)
|
||||
logger.debug("Created Neo4j client instance")
|
||||
return client
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_qdrant_client() -> QdrantClientWrapper:
|
||||
"""
|
||||
Get Qdrant client singleton.
|
||||
|
||||
Returns:
|
||||
Initialized Qdrant client
|
||||
|
||||
Note: Collections are created lazily per-user
|
||||
"""
|
||||
settings = get_settings()
|
||||
client = QdrantClientWrapper(
|
||||
url=settings.qdrant_url,
|
||||
embedding_dim=768 # nomic-embed-text default
|
||||
)
|
||||
logger.debug("Created Qdrant client instance")
|
||||
return client
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_wikijs_client() -> WikiJSClient:
|
||||
"""
|
||||
Get Wiki.js client singleton.
|
||||
|
||||
Returns:
|
||||
Initialized Wiki.js GraphQL client
|
||||
"""
|
||||
settings = get_settings()
|
||||
client = WikiJSClient(
|
||||
base_url=settings.wikijs_url,
|
||||
api_key=settings.wikijs_api_key
|
||||
)
|
||||
logger.debug("Created Wiki.js client instance")
|
||||
return client
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_searxng_client() -> SearXNGClient:
|
||||
"""
|
||||
Get SearXNG client singleton.
|
||||
|
||||
Returns:
|
||||
Initialized SearXNG search client
|
||||
"""
|
||||
settings = get_settings()
|
||||
client = SearXNGClient(base_url=settings.searxng_url)
|
||||
logger.debug("Created SearXNG client instance")
|
||||
return client
|
||||
|
||||
|
||||
@lru_cache
|
||||
def get_ollama_client() -> OllamaClient:
|
||||
"""
|
||||
Get Ollama client singleton.
|
||||
|
||||
Returns:
|
||||
Initialized Ollama embeddings client
|
||||
"""
|
||||
settings = get_settings()
|
||||
client = OllamaClient(
|
||||
base_url=settings.ollama_url,
|
||||
model=settings.ollama_model
|
||||
)
|
||||
logger.debug("Created Ollama client instance")
|
||||
return client
|
||||
|
||||
|
||||
# Type aliases for FastAPI endpoint dependencies
|
||||
# Usage: def my_endpoint(neo4j: Neo4jDep):
|
||||
Neo4jDep = Annotated[Neo4jClient, Depends(get_neo4j_client)]
|
||||
QdrantDep = Annotated[QdrantClientWrapper, Depends(get_qdrant_client)]
|
||||
WikiJSDep = Annotated[WikiJSClient, Depends(get_wikijs_client)]
|
||||
SearXNGDep = Annotated[SearXNGClient, Depends(get_searxng_client)]
|
||||
OllamaDep = Annotated[OllamaClient, Depends(get_ollama_client)]
|
||||
|
||||
|
||||
# Lifecycle management functions
|
||||
async def startup_clients():
|
||||
"""
|
||||
Initialize all service clients at application startup.
|
||||
|
||||
Should be called in FastAPI lifespan or startup event.
|
||||
|
||||
Performs:
|
||||
- Neo4j connection pool initialization
|
||||
- Neo4j connectivity verification
|
||||
- Ollama model availability check
|
||||
"""
|
||||
logger.info("Starting up service clients...")
|
||||
|
||||
# Initialize Neo4j connection pool
|
||||
neo4j = get_neo4j_client()
|
||||
try:
|
||||
await neo4j.connect()
|
||||
logger.info("✓ Neo4j connected")
|
||||
except Exception as e:
|
||||
logger.error(f"✗ Neo4j connection failed: {e}")
|
||||
# Don't fail startup - allow degraded operation
|
||||
pass
|
||||
|
||||
# Check Ollama availability
|
||||
ollama = get_ollama_client()
|
||||
try:
|
||||
is_healthy = await ollama.health_check()
|
||||
if is_healthy:
|
||||
logger.info(f"✓ Ollama ready (model: {ollama.model})")
|
||||
else:
|
||||
logger.warning(f"✗ Ollama model '{ollama.model}' not available")
|
||||
except Exception as e:
|
||||
logger.error(f"✗ Ollama health check failed: {e}")
|
||||
pass
|
||||
|
||||
# Qdrant, Wiki.js, SearXNG are lazy-initialized
|
||||
logger.info("Service clients startup complete")
|
||||
|
||||
|
||||
async def shutdown_clients():
|
||||
"""
|
||||
Cleanup all service clients at application shutdown.
|
||||
|
||||
Should be called in FastAPI lifespan or shutdown event.
|
||||
|
||||
Performs:
|
||||
- Close Neo4j connection pool
|
||||
- Close HTTP clients
|
||||
"""
|
||||
logger.info("Shutting down service clients...")
|
||||
|
||||
# Close Neo4j driver
|
||||
neo4j = get_neo4j_client()
|
||||
try:
|
||||
await neo4j.close()
|
||||
logger.info("✓ Neo4j closed")
|
||||
except Exception as e:
|
||||
logger.error(f"Error closing Neo4j: {e}")
|
||||
|
||||
# Close HTTP clients
|
||||
clients_to_close = [
|
||||
("Wiki.js", get_wikijs_client()),
|
||||
("SearXNG", get_searxng_client()),
|
||||
("Ollama", get_ollama_client())
|
||||
]
|
||||
|
||||
for name, client in clients_to_close:
|
||||
try:
|
||||
await client.close()
|
||||
logger.info(f"✓ {name} client closed")
|
||||
except Exception as e:
|
||||
logger.error(f"Error closing {name} client: {e}")
|
||||
|
||||
logger.info("Service clients shutdown complete")
|
||||
|
||||
|
||||
async def check_service_health() -> dict:
|
||||
"""
|
||||
Check health of all service clients.
|
||||
|
||||
Returns:
|
||||
Dictionary with health status of each service:
|
||||
{
|
||||
"neo4j": bool,
|
||||
"qdrant": bool,
|
||||
"wikijs": bool,
|
||||
"searxng": bool,
|
||||
"ollama": bool
|
||||
}
|
||||
|
||||
Usage:
|
||||
>>> health = await check_service_health()
|
||||
>>> health["neo4j"]
|
||||
True
|
||||
"""
|
||||
health = {}
|
||||
|
||||
# Neo4j
|
||||
try:
|
||||
neo4j = get_neo4j_client()
|
||||
# Simple query to check connectivity
|
||||
await neo4j.execute_query("RETURN 1 as test", {})
|
||||
health["neo4j"] = True
|
||||
except Exception as e:
|
||||
logger.error(f"Neo4j health check failed: {e}")
|
||||
health["neo4j"] = False
|
||||
|
||||
# Qdrant
|
||||
try:
|
||||
qdrant = get_qdrant_client()
|
||||
# Check if we can list collections
|
||||
collections = qdrant.client.get_collections()
|
||||
health["qdrant"] = True
|
||||
except Exception as e:
|
||||
logger.error(f"Qdrant health check failed: {e}")
|
||||
health["qdrant"] = False
|
||||
|
||||
# Wiki.js
|
||||
try:
|
||||
wikijs = get_wikijs_client()
|
||||
# Try a simple query (list pages with limit 1)
|
||||
await wikijs.list_pages(limit=1)
|
||||
health["wikijs"] = True
|
||||
except Exception as e:
|
||||
logger.error(f"Wiki.js health check failed: {e}")
|
||||
health["wikijs"] = False
|
||||
|
||||
# SearXNG
|
||||
try:
|
||||
searxng = get_searxng_client()
|
||||
# Try a simple search
|
||||
await searxng.search_general("test", limit=1)
|
||||
health["searxng"] = True
|
||||
except Exception as e:
|
||||
logger.error(f"SearXNG health check failed: {e}")
|
||||
health["searxng"] = False
|
||||
|
||||
# Ollama
|
||||
try:
|
||||
ollama = get_ollama_client()
|
||||
is_healthy = await ollama.health_check()
|
||||
health["ollama"] = is_healthy
|
||||
except Exception as e:
|
||||
logger.error(f"Ollama health check failed: {e}")
|
||||
health["ollama"] = False
|
||||
|
||||
return health
|
||||
|
||||
|
||||
# Utility: Get default user from settings or multi_tenancy
|
||||
def get_default_user() -> str:
|
||||
"""
|
||||
Get default user for operations.
|
||||
|
||||
Returns:
|
||||
Default user identifier
|
||||
"""
|
||||
from src.core.multi_tenancy import DEFAULT_USER
|
||||
return DEFAULT_USER
|
||||
@@ -0,0 +1,182 @@
|
||||
"""
|
||||
Multi-tenancy helpers for Library Desk.
|
||||
|
||||
Provides utilities for user namespace management across:
|
||||
- Wiki.js (path-based namespaces)
|
||||
- Neo4j (user-specific labels)
|
||||
- Qdrant (collection per user)
|
||||
"""
|
||||
|
||||
import re
|
||||
|
||||
# Default user for all operations
|
||||
DEFAULT_USER = "jpmschweitzer"
|
||||
|
||||
|
||||
def sanitize_user_id(user_id: str) -> str:
|
||||
"""
|
||||
Sanitize user ID for use in collection names, labels, and paths.
|
||||
|
||||
Converts special characters to underscores and ensures alphanumeric safety.
|
||||
|
||||
Args:
|
||||
user_id: Raw user identifier (email, username, etc.)
|
||||
|
||||
Returns:
|
||||
Sanitized user ID safe for use in identifiers
|
||||
|
||||
Examples:
|
||||
>>> sanitize_user_id("john@example.com")
|
||||
'john_at_example_com'
|
||||
>>> sanitize_user_id("user.name")
|
||||
'user_name'
|
||||
>>> sanitize_user_id("User Name")
|
||||
'user_name'
|
||||
"""
|
||||
sanitized = user_id.lower()
|
||||
|
||||
# Convert @ to _at_
|
||||
sanitized = sanitized.replace("@", "_at_")
|
||||
|
||||
# Convert dots to underscores
|
||||
sanitized = sanitized.replace(".", "_")
|
||||
|
||||
# Replace any non-alphanumeric characters with underscores
|
||||
sanitized = re.sub(r'[^a-z0-9_]', '_', sanitized)
|
||||
|
||||
# Remove consecutive underscores
|
||||
sanitized = re.sub(r'_+', '_', sanitized)
|
||||
|
||||
# Remove leading/trailing underscores
|
||||
sanitized = sanitized.strip('_')
|
||||
|
||||
return sanitized
|
||||
|
||||
|
||||
def get_qdrant_collection_name(user_id: str) -> str:
|
||||
"""
|
||||
Get Qdrant collection name for user.
|
||||
|
||||
Pattern: library_desk_{sanitized_user_id}
|
||||
|
||||
Args:
|
||||
user_id: User identifier
|
||||
|
||||
Returns:
|
||||
Qdrant collection name
|
||||
|
||||
Examples:
|
||||
>>> get_qdrant_collection_name("jpmschweitzer")
|
||||
'library_desk_jpmschweitzer'
|
||||
>>> get_qdrant_collection_name("john@example.com")
|
||||
'library_desk_john_at_example_com'
|
||||
"""
|
||||
sanitized = sanitize_user_id(user_id)
|
||||
return f"library_desk_{sanitized}"
|
||||
|
||||
|
||||
def get_wikijs_namespace(user_id: str) -> str:
|
||||
"""
|
||||
Get Wiki.js namespace (path prefix) for user.
|
||||
|
||||
Pattern: /users/{sanitized_user_id}
|
||||
|
||||
All wiki pages for a user will be under this namespace.
|
||||
|
||||
Args:
|
||||
user_id: User identifier
|
||||
|
||||
Returns:
|
||||
Wiki.js path prefix
|
||||
|
||||
Examples:
|
||||
>>> get_wikijs_namespace("jpmschweitzer")
|
||||
'/users/jpmschweitzer'
|
||||
>>> get_wikijs_namespace("john@example.com")
|
||||
'/users/john_at_example_com'
|
||||
"""
|
||||
sanitized = sanitize_user_id(user_id)
|
||||
return f"/users/{sanitized}"
|
||||
|
||||
|
||||
def get_neo4j_user_label(user_id: str) -> str:
|
||||
"""
|
||||
Get Neo4j label for user's documents.
|
||||
|
||||
Pattern: User_{Sanitized}_Document
|
||||
|
||||
Uses title case for Neo4j label convention.
|
||||
|
||||
Args:
|
||||
user_id: User identifier
|
||||
|
||||
Returns:
|
||||
Neo4j label for user's document nodes
|
||||
|
||||
Examples:
|
||||
>>> get_neo4j_user_label("jpmschweitzer")
|
||||
'User_Jpmschweitzer_Document'
|
||||
>>> get_neo4j_user_label("john@example.com")
|
||||
'User_John_At_Example_Com_Document'
|
||||
"""
|
||||
sanitized = sanitize_user_id(user_id)
|
||||
# Title case each segment for Neo4j label convention
|
||||
parts = sanitized.split('_')
|
||||
titled = '_'.join(part.capitalize() for part in parts if part)
|
||||
return f"User_{titled}_Document"
|
||||
|
||||
|
||||
def validate_user_id(user_id: str) -> bool:
|
||||
"""
|
||||
Validate that a user ID is acceptable.
|
||||
|
||||
Checks:
|
||||
- Not empty
|
||||
- Not too long (max 100 chars)
|
||||
- Contains some alphanumeric characters
|
||||
|
||||
Args:
|
||||
user_id: User identifier to validate
|
||||
|
||||
Returns:
|
||||
True if valid, False otherwise
|
||||
|
||||
Examples:
|
||||
>>> validate_user_id("jpmschweitzer")
|
||||
True
|
||||
>>> validate_user_id("")
|
||||
False
|
||||
>>> validate_user_id("a" * 101)
|
||||
False
|
||||
"""
|
||||
if not user_id or len(user_id) > 100:
|
||||
return False
|
||||
|
||||
# Must contain at least one alphanumeric character
|
||||
if not re.search(r'[a-zA-Z0-9]', user_id):
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
|
||||
def is_path_in_user_namespace(path: str, user_id: str) -> bool:
|
||||
"""
|
||||
Check if a Wiki.js path belongs to user's namespace.
|
||||
|
||||
Args:
|
||||
path: Wiki.js page path
|
||||
user_id: User identifier
|
||||
|
||||
Returns:
|
||||
True if path is in user's namespace
|
||||
|
||||
Examples:
|
||||
>>> is_path_in_user_namespace("/users/jpmschweitzer/projects", "jpmschweitzer")
|
||||
True
|
||||
>>> is_path_in_user_namespace("/users/other/projects", "jpmschweitzer")
|
||||
False
|
||||
>>> is_path_in_user_namespace("/public/docs", "jpmschweitzer")
|
||||
False
|
||||
"""
|
||||
namespace = get_wikijs_namespace(user_id)
|
||||
return path.startswith(namespace)
|
||||
@@ -0,0 +1,426 @@
|
||||
"""
|
||||
Redis-based job tracking for Library Desk.
|
||||
|
||||
Provides background job management with:
|
||||
- Job creation and status tracking
|
||||
- Progress updates
|
||||
- Result storage
|
||||
- Auto-expiration after 24 hours
|
||||
- User-scoped job queries
|
||||
"""
|
||||
|
||||
import redis.asyncio as redis
|
||||
import json
|
||||
import uuid
|
||||
from datetime import datetime, timezone
|
||||
from typing import Optional, Dict, Any, List
|
||||
from enum import Enum
|
||||
import logging
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
class JobStatus(str, Enum):
|
||||
"""Job status enumeration."""
|
||||
QUEUED = "queued"
|
||||
PROCESSING = "processing"
|
||||
COMPLETED = "completed"
|
||||
FAILED = "failed"
|
||||
CANCELLED = "cancelled"
|
||||
|
||||
|
||||
class JobType(str, Enum):
|
||||
"""Job type enumeration."""
|
||||
DOCUMENT_INGESTION = "document_ingestion"
|
||||
BATCH_INGESTION = "batch_ingestion"
|
||||
GRAPH_UPDATE = "graph_update"
|
||||
VECTOR_UPDATE = "vector_update"
|
||||
EMBEDDINGS_GENERATION = "embeddings_generation"
|
||||
|
||||
|
||||
class JobManager:
|
||||
"""
|
||||
Redis-based job tracking manager.
|
||||
|
||||
Key structure:
|
||||
- library:job:{job_id} - Job data (JSON, TTL 24h)
|
||||
- library:user_jobs:{user} - Set of job IDs for user
|
||||
- library:active_jobs - Set of active (non-completed) job IDs
|
||||
|
||||
Job data format:
|
||||
{
|
||||
"job_id": "uuid",
|
||||
"job_type": "document_ingestion",
|
||||
"status": "processing",
|
||||
"user": "jpmschweitzer",
|
||||
"parameters": {...},
|
||||
"result": {...},
|
||||
"error": "error message",
|
||||
"progress": 50,
|
||||
"created_at": "2024-01-15T10:30:00Z",
|
||||
"started_at": "2024-01-15T10:30:05Z",
|
||||
"completed_at": "2024-01-15T10:35:00Z"
|
||||
}
|
||||
"""
|
||||
|
||||
def __init__(self, redis_url: str):
|
||||
"""
|
||||
Initialize job manager.
|
||||
|
||||
Args:
|
||||
redis_url: Redis connection URL (e.g., "redis://redis-shared:6379/4")
|
||||
"""
|
||||
self.redis_url = redis_url
|
||||
self._redis: Optional[redis.Redis] = None
|
||||
self.ttl = 86400 # 24 hours
|
||||
logger.info(f"Initialized JobManager: {redis_url}")
|
||||
|
||||
async def connect(self):
|
||||
"""Initialize Redis connection."""
|
||||
if not self._redis:
|
||||
self._redis = await redis.from_url(
|
||||
self.redis_url,
|
||||
encoding="utf-8",
|
||||
decode_responses=True
|
||||
)
|
||||
logger.info("Connected to Redis for job tracking")
|
||||
|
||||
async def close(self):
|
||||
"""Close Redis connection."""
|
||||
if self._redis:
|
||||
await self._redis.close()
|
||||
self._redis = None
|
||||
logger.info("Closed Redis connection")
|
||||
|
||||
def _job_key(self, job_id: str) -> str:
|
||||
"""Get Redis key for job."""
|
||||
return f"library:job:{job_id}"
|
||||
|
||||
def _user_jobs_key(self, user: str) -> str:
|
||||
"""Get Redis key for user's jobs."""
|
||||
return f"library:user_jobs:{user}"
|
||||
|
||||
def _active_jobs_key(self) -> str:
|
||||
"""Get Redis key for active jobs."""
|
||||
return "library:active_jobs"
|
||||
|
||||
async def create_job(
|
||||
self,
|
||||
job_type: JobType,
|
||||
user: str,
|
||||
parameters: Dict[str, Any]
|
||||
) -> str:
|
||||
"""
|
||||
Create new job.
|
||||
|
||||
Args:
|
||||
job_type: Type of job
|
||||
user: User identifier
|
||||
parameters: Job parameters
|
||||
|
||||
Returns:
|
||||
Job ID (UUID)
|
||||
|
||||
Example:
|
||||
>>> job_id = await manager.create_job(
|
||||
... JobType.DOCUMENT_INGESTION,
|
||||
... "jpmschweitzer",
|
||||
... {"doc_url": "https://example.com/doc.pdf"}
|
||||
... )
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
job_id = str(uuid.uuid4())
|
||||
job_data = {
|
||||
"job_id": job_id,
|
||||
"job_type": job_type.value,
|
||||
"status": JobStatus.QUEUED.value,
|
||||
"user": user,
|
||||
"parameters": parameters,
|
||||
"result": None,
|
||||
"error": None,
|
||||
"progress": 0,
|
||||
"created_at": datetime.now(timezone.utc).isoformat()
|
||||
}
|
||||
|
||||
# Store job data
|
||||
await self._redis.setex(
|
||||
self._job_key(job_id),
|
||||
self.ttl,
|
||||
json.dumps(job_data)
|
||||
)
|
||||
|
||||
# Add to user's job set
|
||||
await self._redis.sadd(self._user_jobs_key(user), job_id)
|
||||
await self._redis.expire(self._user_jobs_key(user), self.ttl)
|
||||
|
||||
# Add to active jobs set
|
||||
await self._redis.sadd(self._active_jobs_key(), job_id)
|
||||
|
||||
logger.info(f"Created job {job_id}: {job_type.value} for user {user}")
|
||||
return job_id
|
||||
|
||||
async def get_job(self, job_id: str) -> Optional[Dict[str, Any]]:
|
||||
"""
|
||||
Get job by ID.
|
||||
|
||||
Args:
|
||||
job_id: Job ID
|
||||
|
||||
Returns:
|
||||
Job data dictionary or None if not found
|
||||
|
||||
Example:
|
||||
>>> job = await manager.get_job(job_id)
|
||||
>>> job["status"]
|
||||
'processing'
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
job_json = await self._redis.get(self._job_key(job_id))
|
||||
if not job_json:
|
||||
return None
|
||||
|
||||
return json.loads(job_json)
|
||||
|
||||
async def update_job_status(
|
||||
self,
|
||||
job_id: str,
|
||||
status: JobStatus,
|
||||
progress: Optional[int] = None,
|
||||
result: Optional[Dict[str, Any]] = None,
|
||||
error: Optional[str] = None
|
||||
):
|
||||
"""
|
||||
Update job status.
|
||||
|
||||
Args:
|
||||
job_id: Job ID
|
||||
status: New status
|
||||
progress: Progress percentage (0-100)
|
||||
result: Result data (for completed jobs)
|
||||
error: Error message (for failed jobs)
|
||||
|
||||
Example:
|
||||
>>> await manager.update_job_status(
|
||||
... job_id,
|
||||
... JobStatus.PROCESSING,
|
||||
... progress=50
|
||||
... )
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
job = await self.get_job(job_id)
|
||||
if not job:
|
||||
logger.error(f"Job {job_id} not found")
|
||||
return
|
||||
|
||||
# Update fields
|
||||
job["status"] = status.value
|
||||
if progress is not None:
|
||||
job["progress"] = progress
|
||||
if result is not None:
|
||||
job["result"] = result
|
||||
if error is not None:
|
||||
job["error"] = error
|
||||
|
||||
# Update timestamps
|
||||
now = datetime.now(timezone.utc).isoformat()
|
||||
if status == JobStatus.PROCESSING and not job.get("started_at"):
|
||||
job["started_at"] = now
|
||||
if status in (JobStatus.COMPLETED, JobStatus.FAILED, JobStatus.CANCELLED):
|
||||
job["completed_at"] = now
|
||||
|
||||
# Save updated job
|
||||
await self._redis.setex(
|
||||
self._job_key(job_id),
|
||||
self.ttl,
|
||||
json.dumps(job)
|
||||
)
|
||||
|
||||
# Remove from active jobs if completed
|
||||
if status in (JobStatus.COMPLETED, JobStatus.FAILED, JobStatus.CANCELLED):
|
||||
await self._redis.srem(self._active_jobs_key(), job_id)
|
||||
|
||||
logger.info(f"Updated job {job_id}: status={status.value}, progress={progress}")
|
||||
|
||||
async def get_user_jobs(
|
||||
self,
|
||||
user: str,
|
||||
limit: int = 50
|
||||
) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Get all jobs for a user.
|
||||
|
||||
Args:
|
||||
user: User identifier
|
||||
limit: Maximum jobs to return
|
||||
|
||||
Returns:
|
||||
List of job dictionaries (most recent first)
|
||||
|
||||
Example:
|
||||
>>> jobs = await manager.get_user_jobs("jpmschweitzer", limit=10)
|
||||
>>> len(jobs)
|
||||
10
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
# Get job IDs for user
|
||||
job_ids = await self._redis.smembers(self._user_jobs_key(user))
|
||||
if not job_ids:
|
||||
return []
|
||||
|
||||
# Fetch job data
|
||||
jobs = []
|
||||
for job_id in job_ids:
|
||||
job = await self.get_job(job_id)
|
||||
if job:
|
||||
jobs.append(job)
|
||||
|
||||
# Sort by created_at descending
|
||||
jobs.sort(key=lambda j: j.get("created_at", ""), reverse=True)
|
||||
|
||||
return jobs[:limit]
|
||||
|
||||
async def get_active_jobs(self, limit: int = 100) -> List[Dict[str, Any]]:
|
||||
"""
|
||||
Get all active (non-completed) jobs.
|
||||
|
||||
Args:
|
||||
limit: Maximum jobs to return
|
||||
|
||||
Returns:
|
||||
List of active job dictionaries
|
||||
|
||||
Example:
|
||||
>>> active = await manager.get_active_jobs()
|
||||
>>> all(j["status"] in ["queued", "processing"] for j in active)
|
||||
True
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
job_ids = await self._redis.smembers(self._active_jobs_key())
|
||||
if not job_ids:
|
||||
return []
|
||||
|
||||
jobs = []
|
||||
for job_id in job_ids:
|
||||
job = await self.get_job(job_id)
|
||||
if job:
|
||||
jobs.append(job)
|
||||
|
||||
return jobs[:limit]
|
||||
|
||||
async def cancel_job(self, job_id: str):
|
||||
"""
|
||||
Cancel a job.
|
||||
|
||||
Args:
|
||||
job_id: Job ID
|
||||
|
||||
Note: This only marks the job as cancelled. The actual job
|
||||
worker must check status and stop processing.
|
||||
"""
|
||||
await self.update_job_status(
|
||||
job_id,
|
||||
JobStatus.CANCELLED
|
||||
)
|
||||
logger.info(f"Cancelled job {job_id}")
|
||||
|
||||
async def delete_job(self, job_id: str, user: str):
|
||||
"""
|
||||
Delete a job.
|
||||
|
||||
Args:
|
||||
job_id: Job ID
|
||||
user: User identifier (for authorization)
|
||||
|
||||
Returns:
|
||||
True if deleted, False if not found or unauthorized
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
job = await self.get_job(job_id)
|
||||
if not job:
|
||||
return False
|
||||
|
||||
# Check user authorization
|
||||
if job.get("user") != user:
|
||||
logger.warning(f"User {user} attempted to delete job {job_id} owned by {job.get('user')}")
|
||||
return False
|
||||
|
||||
# Delete job data
|
||||
await self._redis.delete(self._job_key(job_id))
|
||||
|
||||
# Remove from user's jobs
|
||||
await self._redis.srem(self._user_jobs_key(user), job_id)
|
||||
|
||||
# Remove from active jobs
|
||||
await self._redis.srem(self._active_jobs_key(), job_id)
|
||||
|
||||
logger.info(f"Deleted job {job_id}")
|
||||
return True
|
||||
|
||||
async def cleanup_expired_jobs(self):
|
||||
"""
|
||||
Clean up expired jobs from sets.
|
||||
|
||||
Redis will auto-expire job data, but set memberships need manual cleanup.
|
||||
Should be called periodically (e.g., hourly).
|
||||
"""
|
||||
if not self._redis:
|
||||
await self.connect()
|
||||
|
||||
# Cleanup active jobs set
|
||||
job_ids = await self._redis.smembers(self._active_jobs_key())
|
||||
for job_id in job_ids:
|
||||
exists = await self._redis.exists(self._job_key(job_id))
|
||||
if not exists:
|
||||
await self._redis.srem(self._active_jobs_key(), job_id)
|
||||
|
||||
logger.info("Cleaned up expired jobs")
|
||||
|
||||
async def get_job_stats(self, user: Optional[str] = None) -> Dict[str, int]:
|
||||
"""
|
||||
Get job statistics.
|
||||
|
||||
Args:
|
||||
user: Optional user filter
|
||||
|
||||
Returns:
|
||||
Statistics dictionary:
|
||||
{
|
||||
"total": 100,
|
||||
"queued": 5,
|
||||
"processing": 10,
|
||||
"completed": 80,
|
||||
"failed": 5
|
||||
}
|
||||
"""
|
||||
if user:
|
||||
jobs = await self.get_user_jobs(user, limit=1000)
|
||||
else:
|
||||
jobs = await self.get_active_jobs(limit=1000)
|
||||
|
||||
stats = {
|
||||
"total": len(jobs),
|
||||
"queued": 0,
|
||||
"processing": 0,
|
||||
"completed": 0,
|
||||
"failed": 0,
|
||||
"cancelled": 0
|
||||
}
|
||||
|
||||
for job in jobs:
|
||||
status = job.get("status", "")
|
||||
if status in stats:
|
||||
stats[status] += 1
|
||||
|
||||
return stats
|
||||
@@ -69,9 +69,7 @@ class HealthResponse(BaseModel):
|
||||
status: str
|
||||
app_name: str
|
||||
version: str
|
||||
neo4j: str
|
||||
qdrant: str
|
||||
wiki: str
|
||||
services: Dict[str, Any]
|
||||
|
||||
|
||||
class StatsResponse(BaseModel):
|
||||
@@ -98,13 +96,42 @@ async def health(settings: Settings = Depends(get_settings)) -> HealthResponse:
|
||||
Health check endpoint.
|
||||
Returns status of all connected services.
|
||||
"""
|
||||
from src.core.dependencies import check_service_health
|
||||
|
||||
# Check service connectivity
|
||||
service_health = await check_service_health()
|
||||
|
||||
# Overall status is healthy if at least Neo4j and Qdrant are up
|
||||
all_healthy = service_health.get("neo4j", False) and service_health.get("qdrant", False)
|
||||
overall_status = "healthy" if all_healthy else "degraded"
|
||||
|
||||
return HealthResponse(
|
||||
status="healthy",
|
||||
status=overall_status,
|
||||
app_name=settings.app_name,
|
||||
version=settings.app_version,
|
||||
neo4j=settings.neo4j_uri,
|
||||
qdrant=settings.qdrant_url,
|
||||
wiki=settings.wikijs_url
|
||||
services={
|
||||
"neo4j": {
|
||||
"url": settings.neo4j_uri,
|
||||
"healthy": service_health.get("neo4j", False)
|
||||
},
|
||||
"qdrant": {
|
||||
"url": settings.qdrant_url,
|
||||
"healthy": service_health.get("qdrant", False)
|
||||
},
|
||||
"wikijs": {
|
||||
"url": settings.wikijs_url,
|
||||
"healthy": service_health.get("wikijs", False)
|
||||
},
|
||||
"searxng": {
|
||||
"url": settings.searxng_url,
|
||||
"healthy": service_health.get("searxng", False)
|
||||
},
|
||||
"ollama": {
|
||||
"url": settings.ollama_url,
|
||||
"model": settings.ollama_model,
|
||||
"healthy": service_health.get("ollama", False)
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
|
||||
@@ -128,6 +155,114 @@ async def stats(
|
||||
)
|
||||
|
||||
|
||||
# Ingestion endpoints (for Scheduler integration)
|
||||
@app.post("/ingest/document", tags=["Ingestion"])
|
||||
async def ingest_document(
|
||||
document: Dict[str, Any],
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Ingest a single document for indexing.
|
||||
Used by The Scheduler to add mirrored documentation to the knowledge base.
|
||||
|
||||
Expected fields:
|
||||
- source: str (e.g., "github", "gitea")
|
||||
- repository: str (e.g., "anthropic-cookbook")
|
||||
- path: str (file path)
|
||||
- content: str (document content)
|
||||
- metadata: dict (commit, author, tags, etc.)
|
||||
|
||||
TODO: Implement document ingestion pipeline:
|
||||
1. Chunk content
|
||||
2. Generate embeddings (Ollama)
|
||||
3. Extract entities (NLP)
|
||||
4. Index in Qdrant
|
||||
5. Create graph nodes/relationships in Neo4j
|
||||
"""
|
||||
return {
|
||||
"message": "Document ingestion not yet implemented",
|
||||
"document_id": f"doc_{document.get('path', 'unknown')}",
|
||||
"status": "stub"
|
||||
}
|
||||
|
||||
|
||||
@app.post("/ingest/batch", tags=["Ingestion"])
|
||||
async def batch_ingest(
|
||||
batch: Dict[str, Any],
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Ingest multiple documents in a batch.
|
||||
More efficient than individual ingestion for large syncs.
|
||||
|
||||
TODO: Implement batch processing with task queue
|
||||
"""
|
||||
document_count = len(batch.get("documents", []))
|
||||
return {
|
||||
"message": "Batch ingestion not yet implemented",
|
||||
"batch_id": "batch_stub",
|
||||
"total_documents": document_count,
|
||||
"status": "stub"
|
||||
}
|
||||
|
||||
|
||||
@app.post("/ingest/check-updates", tags=["Ingestion"])
|
||||
async def check_updates(
|
||||
documents: Dict[str, Any],
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Check which documents need updating based on content hashes.
|
||||
Used by Scheduler to determine what changed since last sync.
|
||||
|
||||
TODO: Implement update detection:
|
||||
1. Query existing documents by path
|
||||
2. Compare content hashes
|
||||
3. Return list of updates needed
|
||||
"""
|
||||
return {
|
||||
"message": "Update checking not yet implemented",
|
||||
"updates_needed": [],
|
||||
"up_to_date": [],
|
||||
"new_documents": []
|
||||
}
|
||||
|
||||
|
||||
@app.get("/ingest/status/{document_id}", tags=["Ingestion"])
|
||||
async def get_ingestion_status(
|
||||
document_id: str,
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Get processing status for a document.
|
||||
|
||||
TODO: Implement status tracking
|
||||
"""
|
||||
return {
|
||||
"message": "Status tracking not yet implemented",
|
||||
"document_id": document_id,
|
||||
"status": "unknown"
|
||||
}
|
||||
|
||||
|
||||
@app.get("/ingest/repo-status/{repository}", tags=["Ingestion"])
|
||||
async def get_repo_status(
|
||||
repository: str,
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Get indexing status for an entire repository.
|
||||
|
||||
TODO: Implement repository-level statistics
|
||||
"""
|
||||
return {
|
||||
"message": "Repository status not yet implemented",
|
||||
"repository": repository,
|
||||
"total_documents": 0,
|
||||
"indexed_documents": 0
|
||||
}
|
||||
|
||||
|
||||
# Query endpoints (stubs for future implementation)
|
||||
@app.post("/query/hybrid", tags=["Query"])
|
||||
async def hybrid_query(
|
||||
@@ -180,20 +315,62 @@ async def graph_query(
|
||||
}
|
||||
|
||||
|
||||
# Deduplication endpoints
|
||||
@app.post("/deduplicate/check", tags=["Deduplication"])
|
||||
async def check_duplicates(
|
||||
request: Dict[str, Any],
|
||||
api_key: str = Depends(verify_api_key)
|
||||
) -> Dict[str, Any]:
|
||||
"""
|
||||
Check for duplicate or highly similar documents.
|
||||
Uses vector similarity and graph analysis.
|
||||
|
||||
Expected fields:
|
||||
- document_id: str
|
||||
- similarity_threshold: float (default 0.85)
|
||||
|
||||
TODO: Implement deduplication:
|
||||
1. Get document embedding from Qdrant
|
||||
2. Find similar vectors above threshold
|
||||
3. Check graph relationships
|
||||
4. Return candidates with similarity scores
|
||||
"""
|
||||
document_id = request.get("document_id")
|
||||
threshold = request.get("similarity_threshold", 0.85)
|
||||
|
||||
return {
|
||||
"message": "Deduplication not yet implemented",
|
||||
"document_id": document_id,
|
||||
"threshold": threshold,
|
||||
"duplicates": [],
|
||||
"suggestions": None
|
||||
}
|
||||
|
||||
|
||||
# Application lifecycle
|
||||
@app.on_event("startup")
|
||||
async def startup_event():
|
||||
"""Initialize connections and resources on startup."""
|
||||
from src.core.dependencies import startup_clients
|
||||
|
||||
settings = get_settings()
|
||||
logger.info(f"Starting {settings.app_name} v{settings.app_version}")
|
||||
logger.info(f"Neo4j: {settings.neo4j_uri}")
|
||||
logger.info(f"Qdrant: {settings.qdrant_url}")
|
||||
logger.info(f"Wiki.js: {settings.wikijs_url}")
|
||||
# TODO: Initialize database connections
|
||||
logger.info(f"SearXNG: {settings.searxng_url}")
|
||||
logger.info(f"Ollama: {settings.ollama_url}")
|
||||
|
||||
# Initialize all service clients
|
||||
await startup_clients()
|
||||
|
||||
|
||||
@app.on_event("shutdown")
|
||||
async def shutdown_event():
|
||||
"""Clean up resources on shutdown."""
|
||||
from src.core.dependencies import shutdown_clients
|
||||
|
||||
logger.info("Shutting down Library Desk API")
|
||||
# TODO: Close database connections
|
||||
|
||||
# Close all service clients
|
||||
await shutdown_clients()
|
||||
|
||||
@@ -0,0 +1 @@
|
||||
"""Tests for Library Desk service."""
|
||||
@@ -0,0 +1,109 @@
|
||||
"""Pytest configuration and shared fixtures for Library Desk tests."""
|
||||
|
||||
import pytest
|
||||
import pytest_asyncio
|
||||
from typing import AsyncGenerator
|
||||
|
||||
# Test configuration
|
||||
pytest_plugins = ("pytest_asyncio",)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def test_user() -> str:
|
||||
"""Default test user."""
|
||||
return "test_user"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def neo4j_test_uri() -> str:
|
||||
"""Test Neo4j URI."""
|
||||
return "bolt://neo4j:7687"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def neo4j_test_auth() -> tuple:
|
||||
"""Test Neo4j authentication."""
|
||||
return ("neo4j", "test_password")
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def qdrant_test_url() -> str:
|
||||
"""Test Qdrant URL."""
|
||||
return "http://qdrant:6333"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def wikijs_test_config() -> dict:
|
||||
"""Test Wiki.js configuration."""
|
||||
return {
|
||||
"base_url": "http://wiki:3000",
|
||||
"api_key": "test_api_key"
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def searxng_test_url() -> str:
|
||||
"""Test SearXNG URL."""
|
||||
return "http://searxng:8080"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def ollama_test_config() -> dict:
|
||||
"""Test Ollama configuration."""
|
||||
return {
|
||||
"base_url": "http://ollama:11434",
|
||||
"model": "nomic-embed-text"
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def redis_test_url() -> str:
|
||||
"""Test Redis URL."""
|
||||
return "redis://redis-shared:6379/4"
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_document() -> dict:
|
||||
"""Sample document for testing."""
|
||||
return {
|
||||
"id": "test_doc_1",
|
||||
"title": "Test Document",
|
||||
"content": "This is a test document for unit testing.",
|
||||
"metadata": {
|
||||
"source": "test",
|
||||
"author": "test_user"
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_chunks() -> list:
|
||||
"""Sample document chunks for testing."""
|
||||
return [
|
||||
{
|
||||
"content": "First chunk of text.",
|
||||
"metadata": {"chunk_index": 0}
|
||||
},
|
||||
{
|
||||
"content": "Second chunk of text.",
|
||||
"metadata": {"chunk_index": 1}
|
||||
},
|
||||
{
|
||||
"content": "Third chunk of text.",
|
||||
"metadata": {"chunk_index": 2}
|
||||
}
|
||||
]
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def sample_embeddings() -> list:
|
||||
"""Sample embeddings for testing (768-dimensional for nomic-embed-text)."""
|
||||
import random
|
||||
random.seed(42) # Reproducible embeddings
|
||||
|
||||
# Generate 3 sample 768-dimensional embeddings
|
||||
return [
|
||||
[random.random() for _ in range(768)],
|
||||
[random.random() for _ in range(768)],
|
||||
[random.random() for _ in range(768)]
|
||||
]
|
||||
@@ -0,0 +1,313 @@
|
||||
"""Integration tests for Library Desk service clients.
|
||||
|
||||
These tests require actual service connectivity:
|
||||
- Neo4j running at bolt://neo4j:7687
|
||||
- Qdrant running at http://qdrant:6333
|
||||
- Wiki.js running at http://wiki:3000
|
||||
- SearXNG running at http://searxng:8080
|
||||
- Ollama running at http://ollama:11434
|
||||
|
||||
Run with: pytest tests/test_integration.py -v
|
||||
"""
|
||||
|
||||
import pytest
|
||||
import pytest_asyncio
|
||||
from typing import AsyncGenerator
|
||||
|
||||
from src.clients.neo4j_client import Neo4jClient
|
||||
from src.clients.qdrant_client import QdrantClientWrapper
|
||||
from src.clients.wikijs_client import WikiJSClient
|
||||
from src.clients.searxng_client import SearXNGClient
|
||||
from src.clients.ollama_client import OllamaClient
|
||||
from src.jobs.job_manager import JobManager, JobType, JobStatus
|
||||
from src.config import get_settings
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def settings():
|
||||
"""Get application settings."""
|
||||
return get_settings()
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def neo4j_client(settings) -> AsyncGenerator[Neo4jClient, None]:
|
||||
"""Get connected Neo4j client."""
|
||||
client = Neo4jClient(
|
||||
uri=settings.neo4j_uri,
|
||||
user=settings.neo4j_user,
|
||||
password=settings.neo4j_password
|
||||
)
|
||||
await client.connect()
|
||||
yield client
|
||||
await client.close()
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def qdrant_client(settings) -> QdrantClientWrapper:
|
||||
"""Get Qdrant client."""
|
||||
return QdrantClientWrapper(url=settings.qdrant_url)
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def wikijs_client(settings) -> AsyncGenerator[WikiJSClient, None]:
|
||||
"""Get Wiki.js client."""
|
||||
client = WikiJSClient(
|
||||
base_url=settings.wikijs_url,
|
||||
api_key=settings.wikijs_api_key
|
||||
)
|
||||
yield client
|
||||
await client.close()
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def searxng_client(settings) -> AsyncGenerator[SearXNGClient, None]:
|
||||
"""Get SearXNG client."""
|
||||
client = SearXNGClient(base_url=settings.searxng_url)
|
||||
yield client
|
||||
await client.close()
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def ollama_client(settings) -> AsyncGenerator[OllamaClient, None]:
|
||||
"""Get Ollama client."""
|
||||
client = OllamaClient(
|
||||
base_url=settings.ollama_url,
|
||||
model=settings.ollama_model
|
||||
)
|
||||
yield client
|
||||
await client.close()
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def job_manager(settings) -> AsyncGenerator[JobManager, None]:
|
||||
"""Get job manager."""
|
||||
manager = JobManager(redis_url=settings.redis_url)
|
||||
await manager.connect()
|
||||
yield manager
|
||||
await manager.close()
|
||||
|
||||
|
||||
class TestNeo4jIntegration:
|
||||
"""Test Neo4j connectivity and basic operations."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_connection(self, neo4j_client):
|
||||
"""Test Neo4j connection."""
|
||||
result = await neo4j_client.execute_query("RETURN 1 as test", {})
|
||||
assert result
|
||||
assert result[0]["test"] == 1
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_and_get_document(self, neo4j_client, test_user):
|
||||
"""Test creating and retrieving a document node."""
|
||||
doc_id = "test_doc_integration"
|
||||
|
||||
# Create document
|
||||
doc = await neo4j_client.create_document_node(
|
||||
user=test_user,
|
||||
doc_id=doc_id,
|
||||
properties={
|
||||
"title": "Integration Test Document",
|
||||
"source": "test"
|
||||
}
|
||||
)
|
||||
assert doc is not None
|
||||
assert doc["id"] == doc_id
|
||||
|
||||
# Retrieve document
|
||||
retrieved = await neo4j_client.get_document_node(test_user, doc_id)
|
||||
assert retrieved is not None
|
||||
assert retrieved["id"] == doc_id
|
||||
assert retrieved["title"] == "Integration Test Document"
|
||||
|
||||
# Cleanup
|
||||
deleted = await neo4j_client.delete_document_node(test_user, doc_id)
|
||||
assert deleted is True
|
||||
|
||||
|
||||
class TestQdrantIntegration:
|
||||
"""Test Qdrant connectivity and basic operations."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_collection_creation(self, qdrant_client, test_user):
|
||||
"""Test creating a collection."""
|
||||
await qdrant_client.ensure_collection(test_user)
|
||||
|
||||
collection_name = qdrant_client.get_collection_name(test_user)
|
||||
collections = qdrant_client.client.get_collections()
|
||||
collection_names = [c.name for c in collections.collections]
|
||||
|
||||
assert collection_name in collection_names
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_upsert_and_search(self, qdrant_client, test_user):
|
||||
"""Test upserting and searching chunks."""
|
||||
await qdrant_client.ensure_collection(test_user)
|
||||
|
||||
# Create test chunks with 768-dimensional embeddings
|
||||
chunks = [
|
||||
{"content": "Test chunk 1", "metadata": {}},
|
||||
{"content": "Test chunk 2", "metadata": {}}
|
||||
]
|
||||
embeddings = [
|
||||
[0.1] * 768,
|
||||
[0.2] * 768
|
||||
]
|
||||
|
||||
# Upsert
|
||||
count = await qdrant_client.upsert_document_chunks(
|
||||
user=test_user,
|
||||
doc_id="test_doc_qdrant",
|
||||
chunks=chunks,
|
||||
embeddings=embeddings
|
||||
)
|
||||
assert count == 2
|
||||
|
||||
# Search
|
||||
results = await qdrant_client.search(
|
||||
user=test_user,
|
||||
query_vector=[0.1] * 768,
|
||||
limit=5,
|
||||
score_threshold=0.0
|
||||
)
|
||||
assert len(results) > 0
|
||||
|
||||
# Cleanup
|
||||
deleted = await qdrant_client.delete_document(test_user, "test_doc_qdrant")
|
||||
assert deleted is True
|
||||
|
||||
|
||||
class TestWikiJSIntegration:
|
||||
"""Test Wiki.js connectivity and basic operations."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_pages(self, wikijs_client):
|
||||
"""Test listing pages."""
|
||||
pages = await wikijs_client.list_pages(limit=10)
|
||||
assert isinstance(pages, list)
|
||||
# May be empty if wiki is new
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_pages(self, wikijs_client):
|
||||
"""Test searching pages."""
|
||||
results = await wikijs_client.search_pages("test")
|
||||
assert isinstance(results, list)
|
||||
|
||||
|
||||
class TestSearXNGIntegration:
|
||||
"""Test SearXNG connectivity and search."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_general_search(self, searxng_client):
|
||||
"""Test general web search."""
|
||||
results = await searxng_client.search_general("python programming", limit=5)
|
||||
assert isinstance(results, list)
|
||||
if results:
|
||||
assert "title" in results[0]
|
||||
assert "url" in results[0]
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_with_suggestions(self, searxng_client):
|
||||
"""Test getting search suggestions."""
|
||||
suggestions = await searxng_client.get_suggestions("pytho")
|
||||
assert isinstance(suggestions, list)
|
||||
|
||||
|
||||
class TestOllamaIntegration:
|
||||
"""Test Ollama connectivity and embeddings."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_health_check(self, ollama_client):
|
||||
"""Test Ollama health check."""
|
||||
is_healthy = await ollama_client.health_check()
|
||||
# May be False if model not pulled
|
||||
assert isinstance(is_healthy, bool)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_list_models(self, ollama_client):
|
||||
"""Test listing available models."""
|
||||
models = await ollama_client.list_models()
|
||||
assert isinstance(models, list)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
@pytest.mark.skipif(
|
||||
True, # Skip by default as embeddings can be slow
|
||||
reason="Embedding generation is slow - enable manually if needed"
|
||||
)
|
||||
async def test_generate_embedding(self, ollama_client):
|
||||
"""Test generating a single embedding."""
|
||||
embedding = await ollama_client.embed("test text")
|
||||
if embedding:
|
||||
assert isinstance(embedding, list)
|
||||
assert len(embedding) > 0
|
||||
|
||||
|
||||
class TestJobManagerIntegration:
|
||||
"""Test Job Manager with Redis."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_create_and_get_job(self, job_manager, test_user):
|
||||
"""Test creating and retrieving a job."""
|
||||
# Create job
|
||||
job_id = await job_manager.create_job(
|
||||
job_type=JobType.DOCUMENT_INGESTION,
|
||||
user=test_user,
|
||||
parameters={"doc_url": "https://example.com/doc.pdf"}
|
||||
)
|
||||
assert job_id
|
||||
|
||||
# Get job
|
||||
job = await job_manager.get_job(job_id)
|
||||
assert job is not None
|
||||
assert job["job_id"] == job_id
|
||||
assert job["user"] == test_user
|
||||
assert job["status"] == JobStatus.QUEUED.value
|
||||
|
||||
# Update job
|
||||
await job_manager.update_job_status(
|
||||
job_id,
|
||||
JobStatus.PROCESSING,
|
||||
progress=50
|
||||
)
|
||||
|
||||
updated_job = await job_manager.get_job(job_id)
|
||||
assert updated_job["status"] == JobStatus.PROCESSING.value
|
||||
assert updated_job["progress"] == 50
|
||||
|
||||
# Cleanup
|
||||
deleted = await job_manager.delete_job(job_id, test_user)
|
||||
assert deleted is True
|
||||
|
||||
|
||||
class TestDependencyInjection:
|
||||
"""Test dependency injection and lifecycle management."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_startup_clients(self):
|
||||
"""Test client startup."""
|
||||
from src.core.dependencies import startup_clients
|
||||
|
||||
# Should not raise exceptions
|
||||
await startup_clients()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_check_service_health(self):
|
||||
"""Test health check for all services."""
|
||||
from src.core.dependencies import check_service_health
|
||||
|
||||
health = await check_service_health()
|
||||
|
||||
assert isinstance(health, dict)
|
||||
assert "neo4j" in health
|
||||
assert "qdrant" in health
|
||||
assert "wikijs" in health
|
||||
assert "searxng" in health
|
||||
assert "ollama" in health
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_shutdown_clients(self):
|
||||
"""Test client shutdown."""
|
||||
from src.core.dependencies import shutdown_clients
|
||||
|
||||
# Should not raise exceptions
|
||||
await shutdown_clients()
|
||||
@@ -0,0 +1,115 @@
|
||||
"""Tests for multi-tenancy helpers."""
|
||||
|
||||
import pytest
|
||||
from src.core.multi_tenancy import (
|
||||
sanitize_user_id,
|
||||
get_qdrant_collection_name,
|
||||
get_wikijs_namespace,
|
||||
get_neo4j_user_label,
|
||||
validate_user_id,
|
||||
is_path_in_user_namespace,
|
||||
DEFAULT_USER
|
||||
)
|
||||
|
||||
|
||||
class TestSanitizeUserId:
|
||||
"""Test user ID sanitization."""
|
||||
|
||||
def test_lowercase_conversion(self):
|
||||
assert sanitize_user_id("JohnDoe") == "johndoe"
|
||||
|
||||
def test_email_conversion(self):
|
||||
assert sanitize_user_id("john@example.com") == "john_at_example_com"
|
||||
|
||||
def test_dot_conversion(self):
|
||||
assert sanitize_user_id("john.doe") == "john_doe"
|
||||
|
||||
def test_space_conversion(self):
|
||||
assert sanitize_user_id("John Doe") == "john_doe"
|
||||
|
||||
def test_special_chars_removal(self):
|
||||
assert sanitize_user_id("john-doe!") == "john_doe"
|
||||
|
||||
def test_consecutive_underscores(self):
|
||||
assert sanitize_user_id("john__doe") == "john_doe"
|
||||
|
||||
def test_leading_trailing_underscores(self):
|
||||
assert sanitize_user_id("_john_") == "john"
|
||||
|
||||
|
||||
class TestQdrantCollectionName:
|
||||
"""Test Qdrant collection name generation."""
|
||||
|
||||
def test_simple_user(self):
|
||||
assert get_qdrant_collection_name("jpmschweitzer") == "library_desk_jpmschweitzer"
|
||||
|
||||
def test_email_user(self):
|
||||
assert get_qdrant_collection_name("john@example.com") == "library_desk_john_at_example_com"
|
||||
|
||||
def test_default_user(self):
|
||||
assert get_qdrant_collection_name(DEFAULT_USER) == f"library_desk_{DEFAULT_USER}"
|
||||
|
||||
|
||||
class TestWikijsNamespace:
|
||||
"""Test Wiki.js namespace generation."""
|
||||
|
||||
def test_simple_user(self):
|
||||
assert get_wikijs_namespace("jpmschweitzer") == "/users/jpmschweitzer"
|
||||
|
||||
def test_email_user(self):
|
||||
assert get_wikijs_namespace("john@example.com") == "/users/john_at_example_com"
|
||||
|
||||
def test_starts_with_slash(self):
|
||||
namespace = get_wikijs_namespace("testuser")
|
||||
assert namespace.startswith("/")
|
||||
|
||||
|
||||
class TestNeo4jUserLabel:
|
||||
"""Test Neo4j user label generation."""
|
||||
|
||||
def test_simple_user(self):
|
||||
assert get_neo4j_user_label("jpmschweitzer") == "User_Jpmschweitzer_Document"
|
||||
|
||||
def test_email_user(self):
|
||||
result = get_neo4j_user_label("john@example.com")
|
||||
# Should be title case
|
||||
assert result == "User_John_At_Example_Com_Document"
|
||||
|
||||
def test_title_case(self):
|
||||
result = get_neo4j_user_label("john_doe")
|
||||
assert result == "User_John_Doe_Document"
|
||||
|
||||
|
||||
class TestValidateUserId:
|
||||
"""Test user ID validation."""
|
||||
|
||||
def test_valid_simple(self):
|
||||
assert validate_user_id("jpmschweitzer") is True
|
||||
|
||||
def test_valid_email(self):
|
||||
assert validate_user_id("john@example.com") is True
|
||||
|
||||
def test_empty_invalid(self):
|
||||
assert validate_user_id("") is False
|
||||
|
||||
def test_too_long_invalid(self):
|
||||
assert validate_user_id("a" * 101) is False
|
||||
|
||||
def test_no_alphanumeric_invalid(self):
|
||||
assert validate_user_id("___") is False
|
||||
|
||||
|
||||
class TestPathInNamespace:
|
||||
"""Test path namespace checking."""
|
||||
|
||||
def test_path_in_namespace(self):
|
||||
assert is_path_in_user_namespace("/users/jpmschweitzer/projects", "jpmschweitzer") is True
|
||||
|
||||
def test_path_not_in_namespace(self):
|
||||
assert is_path_in_user_namespace("/users/other/projects", "jpmschweitzer") is False
|
||||
|
||||
def test_public_path_not_in_namespace(self):
|
||||
assert is_path_in_user_namespace("/public/docs", "jpmschweitzer") is False
|
||||
|
||||
def test_root_path(self):
|
||||
assert is_path_in_user_namespace("/users/test", "test") is True
|
||||
@@ -66,7 +66,7 @@ services:
|
||||
# Redis Configuration
|
||||
- REDIS_HOST=redis-shared
|
||||
- REDIS_PORT=6379
|
||||
- REDIS_DB=2
|
||||
- REDIS_DB=4
|
||||
|
||||
# Python Configuration
|
||||
- PYTHONUNBUFFERED=1
|
||||
|
||||
Reference in New Issue
Block a user