feat: add RAG search endpoint with content extraction
- Add /rag/search endpoint for web, news, and image search via SearXNG - Add /content/extract and /content/extract/batch endpoints - Add ContentExtractor client using Trafilatura for content extraction - Enhance HybridRAG web search with full content extraction - Add Redis caching for search results - Add new configuration options for search and extraction timeouts 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
@@ -5,6 +5,40 @@ All notable changes to Library Desk will be documented in this file.
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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [1.2.0] - 2025-12-15
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### Added
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- **RAG Search Endpoint** (`POST /rag/search`)
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- Web, news, and image search via SearXNG
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- Full content extraction using Trafilatura (F1 score 0.958)
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- Redis caching with configurable TTL
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- Markdown sources summary for LLM consumption
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- Returns both extracted content and original snippets
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- **Content Extraction Endpoints** (`/content/*`)
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- `POST /content/extract` - Extract content from a single URL
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- `POST /content/extract/batch` - Batch extraction (up to 20 URLs)
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- Reusable ContentExtractor client for use across the codebase
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- **HybridRAG Content Extraction Enhancement**
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- Web search results now include full extracted content via Trafilatura
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- Falls back to original snippets if extraction fails
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- Improves context quality for LLM re-ranking and consumption
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### Changed
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- Added new configuration options:
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- `SEARCH_CACHE_TTL` - Search cache TTL in seconds (default: 300)
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- `SEARCH_TIMEOUT` - SearXNG timeout (default: 10s)
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- `CONTENT_EXTRACTION_TIMEOUT` - Per-URL extraction timeout (default: 5s)
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- `CONTENT_MAX_LENGTH` - Max extracted content length (default: 2000)
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- `SEARCH_DEFAULT_LIMIT` - Default search results (default: 10)
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### Dependencies
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- Added `trafilatura~=1.12.0` for content extraction
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## [1.1.3] - 2025-12-14
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### Added
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+1
-1
@@ -1,6 +1,6 @@
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[project]
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name = "library-desk"
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version = "1.1.3"
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version = "1.2.0"
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description = "Coordination service for The Library system - HybridRAG queries, document ingestion, entity extraction, and knowledge consolidation"
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readme = "README.md"
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requires-python = ">=3.12"
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@@ -25,6 +25,9 @@ python-multipart~=0.0.20
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# Utilities
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python-dateutil~=2.9.0
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# Content Extraction
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trafilatura~=1.12.0
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# Testing
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pytest~=8.3.0
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pytest-asyncio~=0.24.0
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@@ -0,0 +1,310 @@
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"""
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Content extraction client for Library Desk.
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A reusable Trafilatura wrapper that can be used throughout library-desk:
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- RAG search service (extract content from search results)
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- Ingestion service (extract content from URLs)
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- Standalone endpoint (ad-hoc content extraction)
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"""
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import asyncio
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import logging
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from concurrent.futures import ThreadPoolExecutor
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from typing import List, Optional
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import trafilatura
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from src.models.content import ContentExtractionResult
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logger = logging.getLogger(__name__)
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class ContentExtractor:
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"""
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Generic content extraction client using Trafilatura.
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Provides async wrappers around Trafilatura's synchronous extraction,
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with support for parallel batch processing and configurable timeouts.
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"""
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def __init__(
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self,
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timeout: int = 5,
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max_length: int = 2000,
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max_workers: int = 10
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):
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"""
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Initialize ContentExtractor.
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Args:
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timeout: Per-URL timeout in seconds
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max_length: Maximum content length to return (truncated if longer)
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max_workers: Max concurrent extractions for batch operations
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"""
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self.timeout = timeout
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self.max_length = max_length
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self._executor = ThreadPoolExecutor(max_workers=max_workers)
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logger.info(
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f"Initialized ContentExtractor: timeout={timeout}s, "
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f"max_length={max_length}, max_workers={max_workers}"
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)
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def _extract_sync(
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self,
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url: str,
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include_metadata: bool = True,
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max_length: Optional[int] = None
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) -> ContentExtractionResult:
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"""
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Synchronous extraction (runs in thread pool).
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Args:
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url: URL to extract content from
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include_metadata: Whether to extract title, author, date
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max_length: Override default max length
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Returns:
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ContentExtractionResult with extracted content or error
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"""
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effective_max_length = max_length or self.max_length
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try:
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# Fetch the URL
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downloaded = trafilatura.fetch_url(url)
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if not downloaded:
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error="Failed to fetch URL"
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)
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# Extract content
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content = trafilatura.extract(
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downloaded,
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include_comments=False,
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include_tables=True,
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output_format='txt'
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)
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if not content:
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error="No content extracted"
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)
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# Truncate if needed
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if len(content) > effective_max_length:
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content = content[:effective_max_length] + "..."
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# Extract metadata if requested
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title = None
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author = None
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date = None
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language = None
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if include_metadata:
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metadata = trafilatura.extract(
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downloaded,
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output_format='xml',
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include_comments=False
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)
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# Parse metadata from XML if available
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# trafilatura.extract with output_format='xml' returns XML with metadata
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# For simplicity, we'll use bare_extraction which returns a dict
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try:
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meta_dict = trafilatura.bare_extraction(
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downloaded,
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include_comments=False
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)
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if meta_dict:
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title = meta_dict.get('title')
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author = meta_dict.get('author')
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date = meta_dict.get('date')
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language = meta_dict.get('language')
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except Exception as e:
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logger.debug(f"Metadata extraction failed for {url}: {e}")
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return ContentExtractionResult(
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url=url,
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title=title,
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content=content,
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author=author,
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date=date,
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language=language,
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success=True,
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error=None
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)
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except Exception as e:
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logger.error(f"Content extraction failed for {url}: {e}")
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error=str(e)
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)
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async def extract(
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self,
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url: str,
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include_metadata: bool = True,
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max_length: Optional[int] = None
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) -> ContentExtractionResult:
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"""
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Extract content from a single URL asynchronously.
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Args:
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url: URL to extract content from
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include_metadata: Whether to extract title, author, date
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max_length: Override default max length
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Returns:
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ContentExtractionResult with extracted content or error
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"""
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loop = asyncio.get_event_loop()
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try:
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result = await asyncio.wait_for(
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loop.run_in_executor(
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self._executor,
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self._extract_sync,
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url,
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include_metadata,
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max_length
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),
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timeout=self.timeout
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)
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return result
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except asyncio.TimeoutError:
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logger.warning(f"Content extraction timed out for {url}")
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error=f"Extraction timed out after {self.timeout}s"
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)
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except Exception as e:
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logger.error(f"Unexpected error extracting {url}: {e}")
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error=str(e)
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)
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async def extract_batch(
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self,
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urls: List[str],
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include_metadata: bool = True,
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max_length: Optional[int] = None
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) -> List[ContentExtractionResult]:
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"""
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Extract content from multiple URLs in parallel.
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Args:
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urls: List of URLs to extract content from
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include_metadata: Whether to extract title, author, date
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max_length: Override default max length
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Returns:
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List of ContentExtractionResult in same order as input URLs
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"""
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tasks = [
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self.extract(url, include_metadata, max_length)
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for url in urls
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]
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results = await asyncio.gather(*tasks)
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return list(results)
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async def extract_from_html(
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self,
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html: str,
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url: str = "",
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include_metadata: bool = True,
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max_length: Optional[int] = None
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) -> ContentExtractionResult:
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"""
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Extract content from raw HTML string.
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Args:
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html: Raw HTML content
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url: Optional URL for reference (not fetched)
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include_metadata: Whether to extract title, author, date
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max_length: Override default max length
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Returns:
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ContentExtractionResult with extracted content or error
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"""
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effective_max_length = max_length or self.max_length
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def _extract():
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try:
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content = trafilatura.extract(
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html,
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include_comments=False,
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include_tables=True,
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output_format='txt'
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)
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if not content:
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error="No content extracted from HTML"
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)
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# Truncate if needed
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if len(content) > effective_max_length:
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content = content[:effective_max_length] + "..."
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# Extract metadata
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title = None
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author = None
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date = None
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language = None
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if include_metadata:
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try:
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meta_dict = trafilatura.bare_extraction(
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html,
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include_comments=False
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)
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if meta_dict:
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title = meta_dict.get('title')
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author = meta_dict.get('author')
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date = meta_dict.get('date')
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language = meta_dict.get('language')
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except Exception as e:
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logger.debug(f"Metadata extraction failed: {e}")
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return ContentExtractionResult(
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url=url,
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title=title,
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content=content,
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author=author,
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date=date,
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language=language,
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success=True,
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error=None
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)
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except Exception as e:
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logger.error(f"HTML content extraction failed: {e}")
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return ContentExtractionResult(
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url=url,
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content="",
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success=False,
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error=str(e)
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)
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loop = asyncio.get_event_loop()
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return await loop.run_in_executor(self._executor, _extract)
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async def close(self):
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"""Shutdown the thread pool executor."""
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self._executor.shutdown(wait=False)
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logger.info("ContentExtractor closed")
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@@ -89,6 +89,15 @@ class Settings(BaseSettings):
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app_version: str = Field(default=__version__, description="Application version")
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debug: bool = Field(default=False, description="Debug mode")
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# RAG Search Configuration
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search_cache_ttl: int = Field(default=300, ge=0, le=3600, description="Search cache TTL in seconds")
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search_timeout: int = Field(default=10, ge=1, le=60, description="SearXNG timeout in seconds")
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search_default_limit: int = Field(default=10, ge=1, le=20, description="Default number of search results")
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# Content Extraction Configuration
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content_extraction_timeout: int = Field(default=5, ge=1, le=30, description="Trafilatura per-URL timeout in seconds")
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content_max_length: int = Field(default=2000, ge=500, le=10000, description="Max extracted content length per result")
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@property
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def qdrant_url(self) -> str:
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"""Computed Qdrant URL."""
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@@ -13,12 +13,15 @@ from typing import Annotated
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from fastapi import Depends
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import logging
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import redis.asyncio as aioredis
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from src.config import Settings, get_settings
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from src.clients.neo4j_client import Neo4jClient
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from src.clients.qdrant_client import QdrantClientWrapper
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from src.clients.wikijs_client import WikiJSClient
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from src.clients.searxng_client import SearXNGClient
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from src.clients.ollama_client import OllamaClient
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from src.clients.content_extractor import ContentExtractor
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logger = logging.getLogger(__name__)
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@@ -116,6 +119,43 @@ def get_ollama_client() -> OllamaClient:
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return client
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@lru_cache
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def get_redis_client() -> aioredis.Redis:
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"""
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Get Redis client singleton for caching.
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Returns:
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Async Redis client connected to the configured database
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Note: Uses Redis DB 4 (configured for library-desk)
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"""
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settings = get_settings()
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client = aioredis.from_url(
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settings.redis_url,
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encoding="utf-8",
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decode_responses=True
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)
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logger.debug(f"Created Redis client: {settings.redis_url}")
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return client
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@lru_cache
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def get_content_extractor() -> ContentExtractor:
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"""
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Get ContentExtractor singleton.
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Returns:
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Initialized content extraction client using Trafilatura
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"""
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settings = get_settings()
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extractor = ContentExtractor(
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timeout=settings.content_extraction_timeout,
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max_length=settings.content_max_length
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)
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logger.debug("Created ContentExtractor instance")
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return extractor
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# Type aliases for FastAPI endpoint dependencies
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# Usage: def my_endpoint(neo4j: Neo4jDep):
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Neo4jDep = Annotated[Neo4jClient, Depends(get_neo4j_client)]
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@@ -123,6 +163,8 @@ QdrantDep = Annotated[QdrantClientWrapper, Depends(get_qdrant_client)]
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WikiJSDep = Annotated[WikiJSClient, Depends(get_wikijs_client)]
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SearXNGDep = Annotated[SearXNGClient, Depends(get_searxng_client)]
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OllamaDep = Annotated[OllamaClient, Depends(get_ollama_client)]
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RedisDep = Annotated[aioredis.Redis, Depends(get_redis_client)]
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ContentExtractorDep = Annotated[ContentExtractor, Depends(get_content_extractor)]
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# Lifecycle management functions
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@@ -336,6 +378,19 @@ def get_hybrid_rag_service() -> "HybridRAGService":
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graph_service=get_graph_service(),
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searxng_client=get_searxng_client(),
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ollama_client=get_ollama_client(),
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content_extractor=get_content_extractor(),
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settings=get_settings()
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)
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@lru_cache
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def get_rag_search_service() -> "RAGSearchService":
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"""Get RAGSearchService singleton."""
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from src.services.rag_search_service import RAGSearchService
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return RAGSearchService(
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searxng_client=get_searxng_client(),
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content_extractor=get_content_extractor(),
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redis_client=get_redis_client(),
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settings=get_settings()
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)
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||||
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+6
-1
@@ -45,7 +45,10 @@ app.add_middleware(
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)
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|
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# Register routers
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||||
from src.routers import wiki, tools, graph, vector, hybrid_rag, consolidation, ingestion, entity_linking, webhooks
|
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from src.routers import (
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wiki, tools, graph, vector, hybrid_rag, consolidation,
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ingestion, entity_linking, webhooks, rag_search, content
|
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)
|
||||
|
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app.include_router(wiki.router)
|
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app.include_router(tools.router)
|
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@@ -56,6 +59,8 @@ app.include_router(consolidation.router)
|
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app.include_router(ingestion.router)
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app.include_router(entity_linking.router)
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app.include_router(webhooks.router)
|
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app.include_router(rag_search.router)
|
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app.include_router(content.router)
|
||||
|
||||
# Mount static files directory for Wiki.js integration scripts
|
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static_dir = Path(__file__).parent.parent / "static"
|
||||
|
||||
@@ -0,0 +1,69 @@
|
||||
"""
|
||||
Content extraction models for Library Desk.
|
||||
|
||||
Pydantic models for content extraction requests and responses.
|
||||
"""
|
||||
|
||||
from typing import Optional, List
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
|
||||
class ContentExtractionResult(BaseModel):
|
||||
"""Result of extracting content from a single URL."""
|
||||
|
||||
url: str = Field(..., description="The URL that was processed")
|
||||
title: Optional[str] = Field(None, description="Page title if extracted")
|
||||
content: str = Field("", description="Extracted main text content")
|
||||
author: Optional[str] = Field(None, description="Author if available")
|
||||
date: Optional[str] = Field(None, description="Publication date if available (ISO format)")
|
||||
language: Optional[str] = Field(None, description="Detected language code")
|
||||
success: bool = Field(..., description="Whether extraction succeeded")
|
||||
error: Optional[str] = Field(None, description="Error message if extraction failed")
|
||||
|
||||
|
||||
class ContentExtractionRequest(BaseModel):
|
||||
"""Request to extract content from a single URL."""
|
||||
|
||||
url: str = Field(..., min_length=1, description="URL to extract content from")
|
||||
include_metadata: bool = Field(default=True, description="Include title, author, date metadata")
|
||||
max_length: Optional[int] = Field(
|
||||
None,
|
||||
ge=100,
|
||||
le=50000,
|
||||
description="Override default max content length"
|
||||
)
|
||||
|
||||
|
||||
class ContentExtractionResponse(BaseModel):
|
||||
"""Response for single URL extraction."""
|
||||
|
||||
result: ContentExtractionResult
|
||||
extraction_time_ms: int = Field(..., ge=0, description="Time taken to extract content")
|
||||
|
||||
|
||||
class BatchContentExtractionRequest(BaseModel):
|
||||
"""Request to extract content from multiple URLs."""
|
||||
|
||||
urls: List[str] = Field(
|
||||
...,
|
||||
min_length=1,
|
||||
max_length=20,
|
||||
description="URLs to extract content from (max 20)"
|
||||
)
|
||||
include_metadata: bool = Field(default=True, description="Include title, author, date metadata")
|
||||
max_length: Optional[int] = Field(
|
||||
None,
|
||||
ge=100,
|
||||
le=50000,
|
||||
description="Override default max content length"
|
||||
)
|
||||
|
||||
|
||||
class BatchContentExtractionResponse(BaseModel):
|
||||
"""Response for batch URL extraction."""
|
||||
|
||||
results: List[ContentExtractionResult]
|
||||
total_urls: int = Field(..., ge=0, description="Total number of URLs processed")
|
||||
successful: int = Field(..., ge=0, description="Number of successful extractions")
|
||||
failed: int = Field(..., ge=0, description="Number of failed extractions")
|
||||
extraction_time_ms: int = Field(..., ge=0, description="Total time for batch extraction")
|
||||
@@ -0,0 +1,88 @@
|
||||
"""
|
||||
RAG search models for Library Desk.
|
||||
|
||||
Pydantic models for web/news/image search requests and responses.
|
||||
"""
|
||||
|
||||
from enum import Enum
|
||||
from typing import Optional, List
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
from src.core.multi_tenancy import DEFAULT_USER
|
||||
|
||||
|
||||
class SearchType(str, Enum):
|
||||
"""Supported search types."""
|
||||
WEB = "web"
|
||||
NEWS = "news"
|
||||
IMAGES = "images"
|
||||
|
||||
|
||||
class RAGSearchRequest(BaseModel):
|
||||
"""Request for RAG search endpoint."""
|
||||
|
||||
query: str = Field(
|
||||
...,
|
||||
min_length=1,
|
||||
max_length=500,
|
||||
description="The search query"
|
||||
)
|
||||
search_type: SearchType = Field(
|
||||
default=SearchType.WEB,
|
||||
description="Type of search: web, news, or images"
|
||||
)
|
||||
limit: int = Field(
|
||||
default=10,
|
||||
ge=1,
|
||||
le=20,
|
||||
description="Maximum number of results (1-20)"
|
||||
)
|
||||
user: str = Field(
|
||||
default=DEFAULT_USER,
|
||||
description="User identifier for rate limiting/personalization"
|
||||
)
|
||||
|
||||
|
||||
class RAGSearchResult(BaseModel):
|
||||
"""A single search result with extracted content."""
|
||||
|
||||
title: str = Field(..., description="Title of the result")
|
||||
url: str = Field(..., description="URL of the source")
|
||||
content: str = Field(
|
||||
"",
|
||||
description="Full extracted text via Trafilatura (max ~2000 chars)"
|
||||
)
|
||||
snippet: str = Field(
|
||||
"",
|
||||
description="Original search engine snippet (150-300 chars)"
|
||||
)
|
||||
source: str = Field(..., description="Domain name of the source")
|
||||
published_date: Optional[str] = Field(
|
||||
None,
|
||||
description="Publication date in ISO format if available"
|
||||
)
|
||||
|
||||
|
||||
class RAGSearchResponse(BaseModel):
|
||||
"""Response from RAG search endpoint."""
|
||||
|
||||
query: str = Field(..., description="Echo of the original query")
|
||||
search_type: SearchType = Field(..., description="Type of search performed")
|
||||
results: List[RAGSearchResult] = Field(
|
||||
default_factory=list,
|
||||
description="List of search results with extracted content"
|
||||
)
|
||||
total_results: int = Field(
|
||||
...,
|
||||
ge=0,
|
||||
description="Number of results returned"
|
||||
)
|
||||
search_time_ms: int = Field(
|
||||
...,
|
||||
ge=0,
|
||||
description="Total time for search and content extraction"
|
||||
)
|
||||
sources_summary: str = Field(
|
||||
"",
|
||||
description="Markdown-formatted list of all source URLs"
|
||||
)
|
||||
@@ -0,0 +1,132 @@
|
||||
"""
|
||||
Content extraction router for Library Desk API.
|
||||
|
||||
Endpoints for extracting main content from web URLs using Trafilatura.
|
||||
"""
|
||||
|
||||
import time
|
||||
from fastapi import APIRouter, HTTPException, Depends
|
||||
import logging
|
||||
|
||||
from src.models.content import (
|
||||
ContentExtractionRequest,
|
||||
ContentExtractionResponse,
|
||||
BatchContentExtractionRequest,
|
||||
BatchContentExtractionResponse,
|
||||
)
|
||||
from src.clients.content_extractor import ContentExtractor
|
||||
from src.core.dependencies import verify_api_key
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/content", tags=["Content Extraction"])
|
||||
|
||||
|
||||
# Lazy import to avoid circular dependency
|
||||
def get_content_extractor() -> ContentExtractor:
|
||||
"""Get content extractor instance."""
|
||||
from src.core.dependencies import get_content_extractor as _get_extractor
|
||||
return _get_extractor()
|
||||
|
||||
|
||||
@router.post("/extract", response_model=ContentExtractionResponse)
|
||||
async def extract_content(
|
||||
request: ContentExtractionRequest,
|
||||
api_key: str = Depends(verify_api_key)
|
||||
):
|
||||
"""
|
||||
Extract main content from a single URL.
|
||||
|
||||
Uses Trafilatura to fetch the URL and extract the main text content,
|
||||
removing navigation, ads, and other boilerplate.
|
||||
|
||||
**Example Request:**
|
||||
```json
|
||||
{
|
||||
"url": "https://example.com/article",
|
||||
"include_metadata": true,
|
||||
"max_length": 2000
|
||||
}
|
||||
```
|
||||
|
||||
**Returns:** Extracted content with optional metadata (title, author, date)
|
||||
"""
|
||||
start_time = time.time()
|
||||
|
||||
try:
|
||||
extractor = get_content_extractor()
|
||||
result = await extractor.extract(
|
||||
url=request.url,
|
||||
include_metadata=request.include_metadata,
|
||||
max_length=request.max_length
|
||||
)
|
||||
|
||||
extraction_time_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
return ContentExtractionResponse(
|
||||
result=result,
|
||||
extraction_time_ms=extraction_time_ms
|
||||
)
|
||||
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.error(f"Content extraction failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail="Content extraction failed")
|
||||
|
||||
|
||||
@router.post("/extract/batch", response_model=BatchContentExtractionResponse)
|
||||
async def extract_content_batch(
|
||||
request: BatchContentExtractionRequest,
|
||||
api_key: str = Depends(verify_api_key)
|
||||
):
|
||||
"""
|
||||
Extract content from multiple URLs in parallel.
|
||||
|
||||
Processes up to 20 URLs concurrently with per-URL timeouts.
|
||||
Failed extractions are included in results with success=false.
|
||||
|
||||
**Example Request:**
|
||||
```json
|
||||
{
|
||||
"urls": [
|
||||
"https://example.com/article1",
|
||||
"https://example.com/article2"
|
||||
],
|
||||
"include_metadata": true,
|
||||
"max_length": 2000
|
||||
}
|
||||
```
|
||||
|
||||
**Returns:** List of extraction results with success/failure counts
|
||||
"""
|
||||
start_time = time.time()
|
||||
|
||||
if not request.urls:
|
||||
raise HTTPException(status_code=400, detail="URLs list cannot be empty")
|
||||
|
||||
try:
|
||||
extractor = get_content_extractor()
|
||||
results = await extractor.extract_batch(
|
||||
urls=request.urls,
|
||||
include_metadata=request.include_metadata,
|
||||
max_length=request.max_length
|
||||
)
|
||||
|
||||
extraction_time_ms = int((time.time() - start_time) * 1000)
|
||||
successful = sum(1 for r in results if r.success)
|
||||
failed = len(results) - successful
|
||||
|
||||
return BatchContentExtractionResponse(
|
||||
results=results,
|
||||
total_urls=len(request.urls),
|
||||
successful=successful,
|
||||
failed=failed,
|
||||
extraction_time_ms=extraction_time_ms
|
||||
)
|
||||
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
except Exception as e:
|
||||
logger.error(f"Batch content extraction failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail="Batch extraction failed")
|
||||
@@ -0,0 +1,87 @@
|
||||
"""
|
||||
RAG search router for Library Desk API.
|
||||
|
||||
Endpoints for web, news, and image search with content extraction.
|
||||
"""
|
||||
|
||||
import httpx
|
||||
from fastapi import APIRouter, HTTPException, Depends
|
||||
import logging
|
||||
|
||||
from src.models.rag_search import RAGSearchRequest, RAGSearchResponse
|
||||
from src.services.rag_search_service import RAGSearchService
|
||||
from src.core.dependencies import verify_api_key
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
router = APIRouter(prefix="/rag", tags=["RAG Search"])
|
||||
|
||||
|
||||
# Lazy import to avoid circular dependency
|
||||
def get_rag_search_service() -> RAGSearchService:
|
||||
"""Get RAG search service instance."""
|
||||
from src.core.dependencies import get_rag_search_service as _get_service
|
||||
return _get_service()
|
||||
|
||||
|
||||
@router.post("/search", response_model=RAGSearchResponse)
|
||||
async def search(
|
||||
request: RAGSearchRequest,
|
||||
api_key: str = Depends(verify_api_key)
|
||||
):
|
||||
"""
|
||||
Execute RAG-optimized web search with content extraction.
|
||||
|
||||
Searches via SearXNG and extracts full content from results using
|
||||
Trafilatura. Results are cached in Redis for efficiency.
|
||||
|
||||
**Search Types:**
|
||||
- `web`: General web search (default)
|
||||
- `news`: News articles with recency filtering
|
||||
- `images`: Image search results
|
||||
|
||||
**Example Request:**
|
||||
```json
|
||||
{
|
||||
"query": "Python async programming best practices",
|
||||
"search_type": "web",
|
||||
"limit": 10,
|
||||
"user": "default"
|
||||
}
|
||||
```
|
||||
|
||||
**Response includes:**
|
||||
- Full extracted text content per result
|
||||
- Original search snippets
|
||||
- Source domain names
|
||||
- Markdown sources summary for LLM consumption
|
||||
|
||||
**Error Codes:**
|
||||
- 400: Invalid query (empty or too long)
|
||||
- 502: Search provider (SearXNG) error
|
||||
- 504: Search timeout
|
||||
"""
|
||||
try:
|
||||
service = get_rag_search_service()
|
||||
response = await service.search(
|
||||
query=request.query,
|
||||
search_type=request.search_type,
|
||||
limit=request.limit,
|
||||
user=request.user
|
||||
)
|
||||
return response
|
||||
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
|
||||
except httpx.TimeoutException:
|
||||
logger.error(f"Search timed out for query: {request.query}")
|
||||
raise HTTPException(status_code=504, detail="Search timed out")
|
||||
|
||||
except httpx.HTTPError as e:
|
||||
logger.error(f"Search provider error: {e}")
|
||||
raise HTTPException(status_code=502, detail="Search provider error")
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"RAG search failed: {e}", exc_info=True)
|
||||
raise HTTPException(status_code=500, detail="Search failed")
|
||||
@@ -22,6 +22,7 @@ from src.services.vector_service import VectorService
|
||||
from src.services.graph_service import GraphService
|
||||
from src.clients.searxng_client import SearXNGClient
|
||||
from src.clients.ollama_client import OllamaClient
|
||||
from src.clients.content_extractor import ContentExtractor
|
||||
from src.config import Settings
|
||||
from src.models.hybrid_rag import (
|
||||
HybridRAGConfig, HybridRAGRequest, HybridRAGResponse,
|
||||
@@ -44,6 +45,7 @@ class HybridRAGService:
|
||||
graph_service: GraphService,
|
||||
searxng_client: SearXNGClient,
|
||||
ollama_client: OllamaClient,
|
||||
content_extractor: ContentExtractor,
|
||||
settings: Settings
|
||||
):
|
||||
"""
|
||||
@@ -54,12 +56,14 @@ class HybridRAGService:
|
||||
graph_service: Service for Neo4j graph search
|
||||
searxng_client: Client for web search
|
||||
ollama_client: Client for LLM (keyword extraction, re-ranking)
|
||||
content_extractor: Client for extracting full content from URLs
|
||||
settings: Application settings
|
||||
"""
|
||||
self.vector = vector_service
|
||||
self.graph = graph_service
|
||||
self.searxng = searxng_client
|
||||
self.ollama = ollama_client
|
||||
self.content_extractor = content_extractor
|
||||
self.settings = settings
|
||||
self.reranker_model = settings.reranker_model
|
||||
|
||||
@@ -334,7 +338,7 @@ JSON:"""
|
||||
|
||||
tasks["graph"] = graph_search()
|
||||
|
||||
# Web search
|
||||
# Web search with content extraction
|
||||
if config.enable_web:
|
||||
async def web_search():
|
||||
start = time.time()
|
||||
@@ -343,11 +347,24 @@ JSON:"""
|
||||
query=query,
|
||||
limit=config.web_limit
|
||||
)
|
||||
|
||||
# Extract full content from URLs using Trafilatura
|
||||
urls = [r.get("url") for r in results if r.get("url")]
|
||||
extraction_results = await self.content_extractor.extract_batch(urls)
|
||||
|
||||
# Map extracted content back to results by URL
|
||||
url_to_content = {
|
||||
ext.url: ext.content
|
||||
for ext in extraction_results
|
||||
if ext.success and ext.content
|
||||
}
|
||||
|
||||
formatted = [
|
||||
{
|
||||
"url": r.get("url"),
|
||||
"title": r.get("title", ""),
|
||||
"content": r.get("content", ""),
|
||||
"content": url_to_content.get(r.get("url"), r.get("content", "")),
|
||||
"snippet": r.get("content", ""), # Keep original snippet
|
||||
"engine": r.get("engine", ""),
|
||||
"source": "web"
|
||||
}
|
||||
|
||||
@@ -0,0 +1,265 @@
|
||||
"""
|
||||
RAG Search service for Library Desk.
|
||||
|
||||
Provides web, news, and image search with content extraction:
|
||||
- Uses SearXNG for search queries
|
||||
- Uses Trafilatura for content extraction
|
||||
- Caches results in Redis
|
||||
"""
|
||||
|
||||
import hashlib
|
||||
import json
|
||||
import logging
|
||||
import time
|
||||
from typing import List, Optional
|
||||
from urllib.parse import urlparse
|
||||
|
||||
import redis.asyncio as aioredis
|
||||
|
||||
from src.clients.searxng_client import SearXNGClient
|
||||
from src.clients.content_extractor import ContentExtractor
|
||||
from src.config import Settings
|
||||
from src.models.rag_search import (
|
||||
SearchType,
|
||||
RAGSearchRequest,
|
||||
RAGSearchResult,
|
||||
RAGSearchResponse,
|
||||
)
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
def extract_domain(url: str) -> str:
|
||||
"""Extract domain name from URL, removing 'www.' prefix."""
|
||||
try:
|
||||
parsed = urlparse(url)
|
||||
domain = parsed.netloc
|
||||
return domain.removeprefix("www.")
|
||||
except Exception:
|
||||
return url
|
||||
|
||||
|
||||
class RAGSearchService:
|
||||
"""
|
||||
Service for RAG-optimized web search with content extraction.
|
||||
|
||||
Combines SearXNG search with Trafilatura content extraction
|
||||
and Redis caching for efficient RAG pipeline integration.
|
||||
"""
|
||||
|
||||
def __init__(
|
||||
self,
|
||||
searxng_client: SearXNGClient,
|
||||
content_extractor: ContentExtractor,
|
||||
redis_client: aioredis.Redis,
|
||||
settings: Settings
|
||||
):
|
||||
"""
|
||||
Initialize RAG search service.
|
||||
|
||||
Args:
|
||||
searxng_client: SearXNG search client
|
||||
content_extractor: Trafilatura content extractor
|
||||
redis_client: Async Redis client for caching
|
||||
settings: Application settings
|
||||
"""
|
||||
self.searxng = searxng_client
|
||||
self.extractor = content_extractor
|
||||
self.redis = redis_client
|
||||
self.settings = settings
|
||||
|
||||
self.cache_ttl = settings.search_cache_ttl
|
||||
self.default_limit = settings.search_default_limit
|
||||
|
||||
logger.info(
|
||||
f"Initialized RAGSearchService: cache_ttl={self.cache_ttl}s, "
|
||||
f"default_limit={self.default_limit}"
|
||||
)
|
||||
|
||||
def _cache_key(self, query: str, search_type: str, limit: int) -> str:
|
||||
"""Generate cache key from search parameters."""
|
||||
key_data = f"{query}:{search_type}:{limit}"
|
||||
key_hash = hashlib.md5(key_data.encode()).hexdigest()
|
||||
return f"rag_search:{key_hash}"
|
||||
|
||||
async def _get_cached_result(self, cache_key: str) -> Optional[RAGSearchResponse]:
|
||||
"""Try to get cached search result."""
|
||||
try:
|
||||
cached = await self.redis.get(cache_key)
|
||||
if cached:
|
||||
data = json.loads(cached)
|
||||
logger.debug(f"Cache hit: {cache_key}")
|
||||
return RAGSearchResponse(**data)
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache read failed: {e}")
|
||||
return None
|
||||
|
||||
async def _set_cached_result(self, cache_key: str, result: RAGSearchResponse):
|
||||
"""Cache search result."""
|
||||
try:
|
||||
await self.redis.setex(
|
||||
cache_key,
|
||||
self.cache_ttl,
|
||||
result.model_dump_json()
|
||||
)
|
||||
logger.debug(f"Cached result: {cache_key} (TTL={self.cache_ttl}s)")
|
||||
except Exception as e:
|
||||
logger.warning(f"Cache write failed: {e}")
|
||||
|
||||
async def _search_searxng(
|
||||
self,
|
||||
query: str,
|
||||
search_type: SearchType,
|
||||
limit: int
|
||||
) -> List[dict]:
|
||||
"""Execute search via SearXNG based on search type."""
|
||||
try:
|
||||
if search_type == SearchType.WEB:
|
||||
results = await self.searxng.search_general(
|
||||
query=query,
|
||||
limit=limit
|
||||
)
|
||||
elif search_type == SearchType.NEWS:
|
||||
results = await self.searxng.search_news(
|
||||
query=query,
|
||||
limit=limit
|
||||
)
|
||||
elif search_type == SearchType.IMAGES:
|
||||
results = await self.searxng.search_images(
|
||||
query=query,
|
||||
limit=limit
|
||||
)
|
||||
else:
|
||||
results = await self.searxng.search_general(
|
||||
query=query,
|
||||
limit=limit
|
||||
)
|
||||
|
||||
return results
|
||||
except Exception as e:
|
||||
logger.error(f"SearXNG search failed: {e}")
|
||||
raise
|
||||
|
||||
async def _extract_content_for_results(
|
||||
self,
|
||||
results: List[dict]
|
||||
) -> List[RAGSearchResult]:
|
||||
"""Extract full content from search result URLs."""
|
||||
# Get URLs for extraction
|
||||
urls = [r.get("url", "") for r in results if r.get("url")]
|
||||
|
||||
# Extract content in parallel
|
||||
extraction_results = await self.extractor.extract_batch(urls)
|
||||
|
||||
# Build result objects
|
||||
search_results = []
|
||||
for i, raw_result in enumerate(results):
|
||||
url = raw_result.get("url", "")
|
||||
|
||||
# Find matching extraction result
|
||||
extracted_content = ""
|
||||
for ext_result in extraction_results:
|
||||
if ext_result.url == url and ext_result.success:
|
||||
extracted_content = ext_result.content
|
||||
break
|
||||
|
||||
# Get original snippet
|
||||
snippet = raw_result.get("content", "")
|
||||
if len(snippet) > 300:
|
||||
snippet = snippet[:300] + "..."
|
||||
|
||||
# Build result
|
||||
search_results.append(RAGSearchResult(
|
||||
title=raw_result.get("title", ""),
|
||||
url=url,
|
||||
content=extracted_content,
|
||||
snippet=snippet,
|
||||
source=extract_domain(url),
|
||||
published_date=raw_result.get("publishedDate")
|
||||
))
|
||||
|
||||
return search_results
|
||||
|
||||
def _generate_sources_summary(self, results: List[RAGSearchResult]) -> str:
|
||||
"""Generate markdown list of source URLs."""
|
||||
if not results:
|
||||
return ""
|
||||
|
||||
lines = ["## Sources"]
|
||||
for i, r in enumerate(results, 1):
|
||||
lines.append(f"{i}. [{r.title}]({r.url})")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
async def search(
|
||||
self,
|
||||
query: str,
|
||||
search_type: SearchType = SearchType.WEB,
|
||||
limit: Optional[int] = None,
|
||||
user: str = "default"
|
||||
) -> RAGSearchResponse:
|
||||
"""
|
||||
Execute RAG-optimized search.
|
||||
|
||||
Args:
|
||||
query: Search query string
|
||||
search_type: Type of search (web, news, images)
|
||||
limit: Maximum results to return (default from settings)
|
||||
user: User identifier for logging/rate limiting
|
||||
|
||||
Returns:
|
||||
RAGSearchResponse with extracted content and sources
|
||||
|
||||
Raises:
|
||||
ValueError: If query is empty
|
||||
Exception: If search fails
|
||||
"""
|
||||
start_time = time.time()
|
||||
|
||||
if not query or not query.strip():
|
||||
raise ValueError("Query cannot be empty")
|
||||
|
||||
effective_limit = limit or self.default_limit
|
||||
|
||||
# Check cache
|
||||
cache_key = self._cache_key(query, search_type.value, effective_limit)
|
||||
cached = await self._get_cached_result(cache_key)
|
||||
if cached:
|
||||
return cached
|
||||
|
||||
logger.info(
|
||||
f"RAG search: '{query}' type={search_type.value} "
|
||||
f"limit={effective_limit} user={user}"
|
||||
)
|
||||
|
||||
# Execute search
|
||||
raw_results = await self._search_searxng(query, search_type, effective_limit)
|
||||
|
||||
# Extract content from results
|
||||
search_results = await self._extract_content_for_results(raw_results)
|
||||
|
||||
# Generate sources summary
|
||||
sources_summary = self._generate_sources_summary(search_results)
|
||||
|
||||
# Calculate timing
|
||||
search_time_ms = int((time.time() - start_time) * 1000)
|
||||
|
||||
# Build response
|
||||
response = RAGSearchResponse(
|
||||
query=query,
|
||||
search_type=search_type,
|
||||
results=search_results,
|
||||
total_results=len(search_results),
|
||||
search_time_ms=search_time_ms,
|
||||
sources_summary=sources_summary
|
||||
)
|
||||
|
||||
# Cache result
|
||||
await self._set_cached_result(cache_key, response)
|
||||
|
||||
logger.info(
|
||||
f"RAG search completed: {len(search_results)} results "
|
||||
f"in {search_time_ms}ms"
|
||||
)
|
||||
|
||||
return response
|
||||
@@ -0,0 +1,183 @@
|
||||
"""Tests for ContentExtractor client."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
from src.clients.content_extractor import ContentExtractor
|
||||
from src.models.content import ContentExtractionResult
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def content_extractor():
|
||||
"""Create ContentExtractor with test configuration."""
|
||||
return ContentExtractor(timeout=5, max_length=2000)
|
||||
|
||||
|
||||
class TestContentExtractor:
|
||||
"""Tests for ContentExtractor client."""
|
||||
|
||||
def test_init(self, content_extractor):
|
||||
"""Test ContentExtractor initialization."""
|
||||
assert content_extractor.timeout == 5
|
||||
assert content_extractor.max_length == 2000
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_success(self, content_extractor):
|
||||
"""Test successful content extraction."""
|
||||
test_url = "https://example.com/article"
|
||||
test_content = "This is the extracted article content."
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url.return_value = "<html><body>Test</body></html>"
|
||||
mock_traf.extract.return_value = test_content
|
||||
mock_traf.bare_extraction.return_value = {
|
||||
"title": "Test Article",
|
||||
"author": "John Doe",
|
||||
"date": "2024-01-15",
|
||||
"language": "en"
|
||||
}
|
||||
|
||||
result = await content_extractor.extract(test_url)
|
||||
|
||||
assert result.success is True
|
||||
assert result.url == test_url
|
||||
assert result.content == test_content
|
||||
assert result.error is None
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_fetch_failure(self, content_extractor):
|
||||
"""Test extraction when URL fetch fails."""
|
||||
test_url = "https://example.com/nonexistent"
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url.return_value = None
|
||||
|
||||
result = await content_extractor.extract(test_url)
|
||||
|
||||
assert result.success is False
|
||||
assert result.url == test_url
|
||||
assert result.content == ""
|
||||
assert "Failed to fetch URL" in result.error
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_no_content(self, content_extractor):
|
||||
"""Test extraction when page has no extractable content."""
|
||||
test_url = "https://example.com/empty"
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url.return_value = "<html><body></body></html>"
|
||||
mock_traf.extract.return_value = None
|
||||
|
||||
result = await content_extractor.extract(test_url)
|
||||
|
||||
assert result.success is False
|
||||
assert "No content extracted" in result.error
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_max_length_truncation(self, content_extractor):
|
||||
"""Test that content is truncated to max length."""
|
||||
test_url = "https://example.com/long-article"
|
||||
# Content longer than max_length (2000)
|
||||
long_content = "x" * 3000
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url.return_value = "<html><body>Test</body></html>"
|
||||
mock_traf.extract.return_value = long_content
|
||||
mock_traf.bare_extraction.return_value = {}
|
||||
|
||||
result = await content_extractor.extract(test_url)
|
||||
|
||||
assert result.success is True
|
||||
assert len(result.content) <= content_extractor.max_length + 3 # +3 for "..."
|
||||
assert result.content.endswith("...")
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_batch(self, content_extractor):
|
||||
"""Test batch extraction of multiple URLs."""
|
||||
test_urls = [
|
||||
"https://example.com/article1",
|
||||
"https://example.com/article2",
|
||||
"https://example.com/article3"
|
||||
]
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url.return_value = "<html><body>Test</body></html>"
|
||||
mock_traf.extract.return_value = "Extracted content"
|
||||
mock_traf.bare_extraction.return_value = {}
|
||||
|
||||
results = await content_extractor.extract_batch(test_urls)
|
||||
|
||||
assert len(results) == 3
|
||||
for i, result in enumerate(results):
|
||||
assert result.url == test_urls[i]
|
||||
assert result.success is True
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_timeout(self):
|
||||
"""Test extraction timeout handling."""
|
||||
import time
|
||||
|
||||
test_url = "https://example.com/slow"
|
||||
|
||||
# Create an extractor with very short timeout
|
||||
fast_extractor = ContentExtractor(timeout=0.001, max_length=2000)
|
||||
|
||||
def slow_fetch(url):
|
||||
time.sleep(1) # Sleep synchronously (this runs in thread pool)
|
||||
return "<html></html>"
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.fetch_url = slow_fetch
|
||||
|
||||
result = await fast_extractor.extract(test_url)
|
||||
|
||||
assert result.success is False
|
||||
assert "timed out" in result.error.lower()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_extract_from_html(self, content_extractor):
|
||||
"""Test extraction from raw HTML."""
|
||||
test_html = "<html><body><article>Article content here.</article></body></html>"
|
||||
|
||||
with patch('src.clients.content_extractor.trafilatura') as mock_traf:
|
||||
mock_traf.extract.return_value = "Article content here."
|
||||
mock_traf.bare_extraction.return_value = {"title": "Test"}
|
||||
|
||||
result = await content_extractor.extract_from_html(test_html, url="https://example.com")
|
||||
|
||||
assert result.success is True
|
||||
assert result.content == "Article content here."
|
||||
|
||||
|
||||
class TestContentExtractionResult:
|
||||
"""Tests for ContentExtractionResult model."""
|
||||
|
||||
def test_success_result(self):
|
||||
"""Test creating a successful result."""
|
||||
result = ContentExtractionResult(
|
||||
url="https://example.com",
|
||||
title="Test Article",
|
||||
content="Article content",
|
||||
author="John Doe",
|
||||
date="2024-01-15",
|
||||
language="en",
|
||||
success=True,
|
||||
error=None
|
||||
)
|
||||
|
||||
assert result.url == "https://example.com"
|
||||
assert result.success is True
|
||||
assert result.error is None
|
||||
|
||||
def test_failure_result(self):
|
||||
"""Test creating a failure result."""
|
||||
result = ContentExtractionResult(
|
||||
url="https://example.com/error",
|
||||
content="",
|
||||
success=False,
|
||||
error="Failed to fetch URL"
|
||||
)
|
||||
|
||||
assert result.url == "https://example.com/error"
|
||||
assert result.success is False
|
||||
assert result.error == "Failed to fetch URL"
|
||||
@@ -25,6 +25,7 @@ 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.clients.content_extractor import ContentExtractor
|
||||
from src.services.hybrid_rag_service import HybridRAGService
|
||||
from src.services.vector_service import VectorService
|
||||
from src.services.graph_service import GraphService
|
||||
@@ -83,6 +84,15 @@ def ollama_client(settings) -> OllamaClient:
|
||||
return OllamaClient(base_url=settings.ollama_url)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def content_extractor(settings) -> ContentExtractor:
|
||||
"""Get ContentExtractor client."""
|
||||
return ContentExtractor(
|
||||
timeout=settings.content_extraction_timeout,
|
||||
max_length=settings.content_max_length
|
||||
)
|
||||
|
||||
|
||||
@pytest_asyncio.fixture
|
||||
async def vector_service(qdrant_client, wiki_client, ollama_client):
|
||||
"""Get VectorService instance."""
|
||||
@@ -101,6 +111,7 @@ async def hybrid_rag_service(
|
||||
graph_service,
|
||||
searxng_client,
|
||||
ollama_client,
|
||||
content_extractor,
|
||||
settings
|
||||
):
|
||||
"""Get HybridRAGService instance."""
|
||||
@@ -109,6 +120,7 @@ async def hybrid_rag_service(
|
||||
graph_service=graph_service,
|
||||
searxng_client=searxng_client,
|
||||
ollama_client=ollama_client,
|
||||
content_extractor=content_extractor,
|
||||
settings=settings
|
||||
)
|
||||
|
||||
|
||||
@@ -0,0 +1,369 @@
|
||||
"""Tests for RAG search service and endpoints."""
|
||||
|
||||
import pytest
|
||||
from unittest.mock import AsyncMock, MagicMock, patch
|
||||
|
||||
from src.models.rag_search import (
|
||||
SearchType,
|
||||
RAGSearchRequest,
|
||||
RAGSearchResult,
|
||||
RAGSearchResponse,
|
||||
)
|
||||
from src.services.rag_search_service import RAGSearchService, extract_domain
|
||||
|
||||
|
||||
class TestExtractDomain:
|
||||
"""Tests for domain extraction utility."""
|
||||
|
||||
def test_extract_simple_domain(self):
|
||||
"""Test extracting domain from simple URL."""
|
||||
assert extract_domain("https://example.com/page") == "example.com"
|
||||
|
||||
def test_extract_domain_with_www(self):
|
||||
"""Test extracting domain removes www prefix."""
|
||||
assert extract_domain("https://www.example.com/page") == "example.com"
|
||||
|
||||
def test_extract_domain_with_subdomain(self):
|
||||
"""Test extracting domain preserves subdomains."""
|
||||
assert extract_domain("https://blog.example.com/post") == "blog.example.com"
|
||||
|
||||
def test_extract_domain_invalid_url(self):
|
||||
"""Test extracting domain from invalid URL returns empty string."""
|
||||
# urlparse returns empty netloc for invalid URLs
|
||||
assert extract_domain("not-a-url") == ""
|
||||
|
||||
|
||||
class TestRAGSearchModels:
|
||||
"""Tests for RAG search Pydantic models."""
|
||||
|
||||
def test_search_request_defaults(self):
|
||||
"""Test RAGSearchRequest with default values."""
|
||||
request = RAGSearchRequest(query="test query")
|
||||
|
||||
assert request.query == "test query"
|
||||
assert request.search_type == SearchType.WEB
|
||||
assert request.limit == 10
|
||||
|
||||
def test_search_request_custom_values(self):
|
||||
"""Test RAGSearchRequest with custom values."""
|
||||
request = RAGSearchRequest(
|
||||
query="news about AI",
|
||||
search_type=SearchType.NEWS,
|
||||
limit=5,
|
||||
user="custom_user"
|
||||
)
|
||||
|
||||
assert request.query == "news about AI"
|
||||
assert request.search_type == SearchType.NEWS
|
||||
assert request.limit == 5
|
||||
assert request.user == "custom_user"
|
||||
|
||||
def test_search_result(self):
|
||||
"""Test RAGSearchResult model."""
|
||||
result = RAGSearchResult(
|
||||
title="Test Article",
|
||||
url="https://example.com/article",
|
||||
content="Full article content",
|
||||
snippet="Article snippet...",
|
||||
source="example.com",
|
||||
published_date="2024-01-15"
|
||||
)
|
||||
|
||||
assert result.title == "Test Article"
|
||||
assert result.source == "example.com"
|
||||
assert result.published_date == "2024-01-15"
|
||||
|
||||
def test_search_response(self):
|
||||
"""Test RAGSearchResponse model."""
|
||||
response = RAGSearchResponse(
|
||||
query="test",
|
||||
search_type=SearchType.WEB,
|
||||
results=[],
|
||||
total_results=0,
|
||||
search_time_ms=100,
|
||||
sources_summary=""
|
||||
)
|
||||
|
||||
assert response.query == "test"
|
||||
assert response.total_results == 0
|
||||
assert response.search_time_ms == 100
|
||||
|
||||
|
||||
class TestRAGSearchService:
|
||||
"""Tests for RAGSearchService."""
|
||||
|
||||
@pytest.fixture
|
||||
def mock_searxng_client(self):
|
||||
"""Create mock SearXNG client."""
|
||||
client = MagicMock()
|
||||
client.search_general = AsyncMock(return_value=[
|
||||
{
|
||||
"title": "Test Result 1",
|
||||
"url": "https://example.com/1",
|
||||
"content": "Snippet 1",
|
||||
"publishedDate": "2024-01-15"
|
||||
},
|
||||
{
|
||||
"title": "Test Result 2",
|
||||
"url": "https://example.com/2",
|
||||
"content": "Snippet 2",
|
||||
"publishedDate": None
|
||||
}
|
||||
])
|
||||
client.search_news = AsyncMock(return_value=[])
|
||||
client.search_images = AsyncMock(return_value=[])
|
||||
return client
|
||||
|
||||
@pytest.fixture
|
||||
def mock_content_extractor(self):
|
||||
"""Create mock ContentExtractor."""
|
||||
from src.models.content import ContentExtractionResult
|
||||
|
||||
extractor = MagicMock()
|
||||
extractor.extract_batch = AsyncMock(return_value=[
|
||||
ContentExtractionResult(
|
||||
url="https://example.com/1",
|
||||
content="Full extracted content 1",
|
||||
success=True
|
||||
),
|
||||
ContentExtractionResult(
|
||||
url="https://example.com/2",
|
||||
content="Full extracted content 2",
|
||||
success=True
|
||||
)
|
||||
])
|
||||
return extractor
|
||||
|
||||
@pytest.fixture
|
||||
def mock_redis_client(self):
|
||||
"""Create mock Redis client."""
|
||||
redis = MagicMock()
|
||||
redis.get = AsyncMock(return_value=None) # No cache hit
|
||||
redis.setex = AsyncMock()
|
||||
return redis
|
||||
|
||||
@pytest.fixture
|
||||
def mock_settings(self):
|
||||
"""Create mock settings."""
|
||||
settings = MagicMock()
|
||||
settings.search_cache_ttl = 300
|
||||
settings.search_default_limit = 10
|
||||
return settings
|
||||
|
||||
@pytest.fixture
|
||||
def rag_search_service(
|
||||
self,
|
||||
mock_searxng_client,
|
||||
mock_content_extractor,
|
||||
mock_redis_client,
|
||||
mock_settings
|
||||
):
|
||||
"""Create RAGSearchService with mocked dependencies."""
|
||||
return RAGSearchService(
|
||||
searxng_client=mock_searxng_client,
|
||||
content_extractor=mock_content_extractor,
|
||||
redis_client=mock_redis_client,
|
||||
settings=mock_settings
|
||||
)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_basic(self, rag_search_service, mock_searxng_client):
|
||||
"""Test basic web search."""
|
||||
response = await rag_search_service.search(
|
||||
query="test query",
|
||||
search_type=SearchType.WEB,
|
||||
limit=10
|
||||
)
|
||||
|
||||
assert response.query == "test query"
|
||||
assert response.search_type == SearchType.WEB
|
||||
assert len(response.results) == 2
|
||||
assert response.total_results == 2
|
||||
assert response.search_time_ms >= 0
|
||||
|
||||
mock_searxng_client.search_general.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_news(self, rag_search_service, mock_searxng_client):
|
||||
"""Test news search type."""
|
||||
mock_searxng_client.search_news.return_value = [
|
||||
{"title": "News", "url": "https://news.com/1", "content": "News content"}
|
||||
]
|
||||
|
||||
response = await rag_search_service.search(
|
||||
query="latest news",
|
||||
search_type=SearchType.NEWS
|
||||
)
|
||||
|
||||
assert response.search_type == SearchType.NEWS
|
||||
mock_searxng_client.search_news.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_images(self, rag_search_service, mock_searxng_client):
|
||||
"""Test image search type."""
|
||||
mock_searxng_client.search_images.return_value = [
|
||||
{"title": "Image", "url": "https://images.com/1.jpg", "content": ""}
|
||||
]
|
||||
|
||||
response = await rag_search_service.search(
|
||||
query="cat photos",
|
||||
search_type=SearchType.IMAGES
|
||||
)
|
||||
|
||||
assert response.search_type == SearchType.IMAGES
|
||||
mock_searxng_client.search_images.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_empty_query(self, rag_search_service):
|
||||
"""Test search with empty query raises ValueError."""
|
||||
with pytest.raises(ValueError, match="Query cannot be empty"):
|
||||
await rag_search_service.search(query="", search_type=SearchType.WEB)
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_caching_miss(
|
||||
self,
|
||||
rag_search_service,
|
||||
mock_redis_client,
|
||||
mock_searxng_client
|
||||
):
|
||||
"""Test search caches results on cache miss."""
|
||||
mock_redis_client.get.return_value = None # Cache miss
|
||||
|
||||
await rag_search_service.search(query="test", search_type=SearchType.WEB)
|
||||
|
||||
# Should call SearXNG (cache miss)
|
||||
mock_searxng_client.search_general.assert_called_once()
|
||||
# Should cache result
|
||||
mock_redis_client.setex.assert_called_once()
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_caching_hit(
|
||||
self,
|
||||
rag_search_service,
|
||||
mock_redis_client,
|
||||
mock_searxng_client
|
||||
):
|
||||
"""Test search returns cached results on cache hit."""
|
||||
# Simulate cache hit
|
||||
cached_response = RAGSearchResponse(
|
||||
query="test",
|
||||
search_type=SearchType.WEB,
|
||||
results=[],
|
||||
total_results=0,
|
||||
search_time_ms=50,
|
||||
sources_summary=""
|
||||
)
|
||||
mock_redis_client.get.return_value = cached_response.model_dump_json()
|
||||
|
||||
response = await rag_search_service.search(query="test", search_type=SearchType.WEB)
|
||||
|
||||
# Should NOT call SearXNG (cache hit)
|
||||
mock_searxng_client.search_general.assert_not_called()
|
||||
assert response.query == "test"
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_content_extraction(
|
||||
self,
|
||||
rag_search_service,
|
||||
mock_content_extractor
|
||||
):
|
||||
"""Test search extracts content from result URLs."""
|
||||
response = await rag_search_service.search(
|
||||
query="test",
|
||||
search_type=SearchType.WEB
|
||||
)
|
||||
|
||||
# Should have called content extractor
|
||||
mock_content_extractor.extract_batch.assert_called_once()
|
||||
|
||||
# Results should have extracted content
|
||||
for result in response.results:
|
||||
assert result.content # Content should be populated
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_sources_summary(self, rag_search_service):
|
||||
"""Test search generates sources summary."""
|
||||
response = await rag_search_service.search(
|
||||
query="test",
|
||||
search_type=SearchType.WEB
|
||||
)
|
||||
|
||||
assert response.sources_summary
|
||||
assert "## Sources" in response.sources_summary
|
||||
assert "[Test Result 1]" in response.sources_summary
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_search_limit(self, rag_search_service, mock_searxng_client):
|
||||
"""Test search respects limit parameter."""
|
||||
await rag_search_service.search(
|
||||
query="test",
|
||||
search_type=SearchType.WEB,
|
||||
limit=5
|
||||
)
|
||||
|
||||
# Check limit was passed to SearXNG
|
||||
mock_searxng_client.search_general.assert_called_once_with(
|
||||
query="test",
|
||||
limit=5
|
||||
)
|
||||
|
||||
|
||||
class TestRAGSearchServiceIntegration:
|
||||
"""Integration-style tests (still mocked but test more of the flow)."""
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_full_search_flow(self):
|
||||
"""Test full search flow with all components mocked."""
|
||||
from src.models.content import ContentExtractionResult
|
||||
|
||||
# Setup mocks
|
||||
mock_searxng = MagicMock()
|
||||
mock_searxng.search_general = AsyncMock(return_value=[
|
||||
{
|
||||
"title": "Python Tutorial",
|
||||
"url": "https://python.org/tutorial",
|
||||
"content": "Learn Python programming",
|
||||
"publishedDate": "2024-01-10"
|
||||
}
|
||||
])
|
||||
|
||||
mock_extractor = MagicMock()
|
||||
mock_extractor.extract_batch = AsyncMock(return_value=[
|
||||
ContentExtractionResult(
|
||||
url="https://python.org/tutorial",
|
||||
title="Python Tutorial",
|
||||
content="This is a comprehensive Python tutorial covering basics to advanced topics.",
|
||||
success=True
|
||||
)
|
||||
])
|
||||
|
||||
mock_redis = MagicMock()
|
||||
mock_redis.get = AsyncMock(return_value=None)
|
||||
mock_redis.setex = AsyncMock()
|
||||
|
||||
mock_settings = MagicMock()
|
||||
mock_settings.search_cache_ttl = 300
|
||||
mock_settings.search_default_limit = 10
|
||||
|
||||
# Create service and execute search
|
||||
service = RAGSearchService(
|
||||
searxng_client=mock_searxng,
|
||||
content_extractor=mock_extractor,
|
||||
redis_client=mock_redis,
|
||||
settings=mock_settings
|
||||
)
|
||||
|
||||
response = await service.search(
|
||||
query="python tutorial",
|
||||
search_type=SearchType.WEB,
|
||||
limit=10,
|
||||
user="test_user"
|
||||
)
|
||||
|
||||
# Verify response
|
||||
assert response.query == "python tutorial"
|
||||
assert len(response.results) == 1
|
||||
assert response.results[0].title == "Python Tutorial"
|
||||
assert response.results[0].source == "python.org"
|
||||
assert "comprehensive Python tutorial" in response.results[0].content
|
||||
assert response.results[0].snippet == "Learn Python programming"
|
||||
Reference in New Issue
Block a user