fix: Restore all files lost during destructive rebase
A previous `git pull --rebase origin main` dropped 177 local commits,
losing 3400+ files across admin-v2, backend, studio-v2, website,
klausur-service, and many other services. The partial restore attempt
(660295e2) only recovered some files.
This commit restores all missing files from pre-rebase ref 98933f5e
while preserving post-rebase additions (night-scheduler, night-mode UI,
NightModeWidget dashboard integration).
Restored features include:
- AI Module Sidebar (FAB), OCR Labeling, OCR Compare
- GPU Dashboard, RAG Pipeline, Magic Help
- Klausur-Korrektur (8 files), Abitur-Archiv (5+ files)
- Companion, Zeugnisse-Crawler, Screen Flow
- Full backend, studio-v2, website, klausur-service
- All compliance SDKs, agent-core, voice-service
- CI/CD configs, documentation, scripts
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
285
backend/llm_gateway/services/tool_gateway.py
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285
backend/llm_gateway/services/tool_gateway.py
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"""
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Tool Gateway Service.
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Bietet sichere Schnittstelle zu externen Tools wie Tavily Web Search.
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Alle Anfragen werden vor dem Versand auf PII geprüft und redaktiert.
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"""
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import os
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import httpx
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import logging
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from dataclasses import dataclass, field
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from typing import Optional, Any
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from enum import Enum
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from .pii_detector import PIIDetector, get_pii_detector, RedactionResult
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logger = logging.getLogger(__name__)
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class SearchDepth(str, Enum):
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"""Suchtiefe für Tavily."""
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BASIC = "basic"
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ADVANCED = "advanced"
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@dataclass
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class SearchResult:
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"""Ein einzelnes Suchergebnis."""
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title: str
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url: str
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content: str
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score: float = 0.0
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published_date: Optional[str] = None
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@dataclass
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class SearchResponse:
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"""Antwort einer Suche."""
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query: str
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redacted_query: Optional[str] = None
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results: list[SearchResult] = field(default_factory=list)
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answer: Optional[str] = None
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pii_detected: bool = False
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pii_types: list[str] = field(default_factory=list)
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response_time_ms: int = 0
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@dataclass
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class ToolGatewayConfig:
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"""Konfiguration für den Tool Gateway."""
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tavily_api_key: Optional[str] = None
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tavily_base_url: str = "https://api.tavily.com"
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timeout: int = 30
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max_results: int = 5
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search_depth: SearchDepth = SearchDepth.BASIC
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include_answer: bool = True
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include_images: bool = False
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pii_redaction_enabled: bool = True
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@classmethod
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def from_env(cls) -> "ToolGatewayConfig":
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"""Erstellt Config aus Umgebungsvariablen."""
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return cls(
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tavily_api_key=os.getenv("TAVILY_API_KEY"),
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tavily_base_url=os.getenv("TAVILY_BASE_URL", "https://api.tavily.com"),
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timeout=int(os.getenv("TAVILY_TIMEOUT", "30")),
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max_results=int(os.getenv("TAVILY_MAX_RESULTS", "5")),
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search_depth=SearchDepth(os.getenv("TAVILY_SEARCH_DEPTH", "basic")),
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include_answer=os.getenv("TAVILY_INCLUDE_ANSWER", "true").lower() == "true",
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include_images=os.getenv("TAVILY_INCLUDE_IMAGES", "false").lower() == "true",
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pii_redaction_enabled=os.getenv("PII_REDACTION_ENABLED", "true").lower() == "true",
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)
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class ToolGatewayError(Exception):
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"""Fehler im Tool Gateway."""
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pass
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class TavilyError(ToolGatewayError):
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"""Fehler bei Tavily API."""
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pass
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class ToolGateway:
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"""
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Gateway für externe Tools mit PII-Schutz.
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Alle Anfragen werden vor dem Versand auf personenbezogene Daten
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geprüft und diese redaktiert. Dies gewährleistet DSGVO-Konformität.
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"""
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def __init__(
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self,
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config: Optional[ToolGatewayConfig] = None,
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pii_detector: Optional[PIIDetector] = None,
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):
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"""
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Initialisiert den Tool Gateway.
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Args:
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config: Konfiguration. None = aus Umgebungsvariablen.
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pii_detector: PII Detector. None = Standard-Detector.
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"""
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self.config = config or ToolGatewayConfig.from_env()
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self.pii_detector = pii_detector or get_pii_detector()
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self._client: Optional[httpx.AsyncClient] = None
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@property
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def tavily_available(self) -> bool:
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"""Prüft ob Tavily konfiguriert ist."""
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return bool(self.config.tavily_api_key)
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async def _get_client(self) -> httpx.AsyncClient:
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"""Lazy-init HTTP Client."""
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if self._client is None:
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self._client = httpx.AsyncClient(
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timeout=self.config.timeout,
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headers={"Content-Type": "application/json"},
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)
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return self._client
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async def close(self):
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"""Schließt HTTP Client."""
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if self._client:
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await self._client.aclose()
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self._client = None
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def _redact_query(self, query: str) -> RedactionResult:
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"""
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Redaktiert PII aus einer Suchanfrage.
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Args:
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query: Die originale Suchanfrage.
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Returns:
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RedactionResult mit redaktiertem Text.
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"""
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if not self.config.pii_redaction_enabled:
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return RedactionResult(
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original_text=query,
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redacted_text=query,
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matches=[],
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pii_found=False,
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)
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return self.pii_detector.redact(query)
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async def search(
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self,
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query: str,
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search_depth: Optional[SearchDepth] = None,
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max_results: Optional[int] = None,
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include_domains: Optional[list[str]] = None,
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exclude_domains: Optional[list[str]] = None,
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) -> SearchResponse:
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"""
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Führt eine Web-Suche mit Tavily durch.
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PII wird automatisch aus der Anfrage entfernt bevor sie
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an Tavily gesendet wird.
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Args:
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query: Die Suchanfrage.
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search_depth: Suchtiefe (basic/advanced).
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max_results: Maximale Anzahl Ergebnisse.
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include_domains: Nur diese Domains durchsuchen.
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exclude_domains: Diese Domains ausschließen.
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Returns:
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SearchResponse mit Ergebnissen.
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Raises:
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TavilyError: Bei API-Fehlern.
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ToolGatewayError: Bei Konfigurationsfehlern.
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"""
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import time
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start_time = time.time()
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if not self.tavily_available:
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raise ToolGatewayError("Tavily API key not configured")
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# PII redaktieren
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redaction = self._redact_query(query)
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if redaction.pii_found:
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logger.warning(
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f"PII detected in search query. Types: {[m.type.value for m in redaction.matches]}"
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)
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# Request an Tavily
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client = await self._get_client()
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payload: dict[str, Any] = {
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"api_key": self.config.tavily_api_key,
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"query": redaction.redacted_text,
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"search_depth": (search_depth or self.config.search_depth).value,
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"max_results": max_results or self.config.max_results,
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"include_answer": self.config.include_answer,
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"include_images": self.config.include_images,
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}
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if include_domains:
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payload["include_domains"] = include_domains
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if exclude_domains:
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payload["exclude_domains"] = exclude_domains
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try:
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response = await client.post(
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f"{self.config.tavily_base_url}/search",
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json=payload,
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)
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response.raise_for_status()
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data = response.json()
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except httpx.HTTPStatusError as e:
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logger.error(f"Tavily API error: {e.response.status_code} - {e.response.text}")
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raise TavilyError(f"Tavily API error: {e.response.status_code}")
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except httpx.RequestError as e:
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logger.error(f"Tavily request error: {e}")
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raise TavilyError(f"Failed to connect to Tavily: {e}")
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# Response parsen
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results = [
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SearchResult(
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title=r.get("title", ""),
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url=r.get("url", ""),
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content=r.get("content", ""),
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score=r.get("score", 0.0),
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published_date=r.get("published_date"),
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)
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for r in data.get("results", [])
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]
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elapsed_ms = int((time.time() - start_time) * 1000)
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return SearchResponse(
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query=query,
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redacted_query=redaction.redacted_text if redaction.pii_found else None,
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results=results,
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answer=data.get("answer"),
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pii_detected=redaction.pii_found,
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pii_types=[m.type.value for m in redaction.matches],
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response_time_ms=elapsed_ms,
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)
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async def health_check(self) -> dict[str, Any]:
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"""
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Prüft Verfügbarkeit der Tools.
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Returns:
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Dict mit Status der einzelnen Tools.
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"""
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status = {
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"tavily": {
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"configured": self.tavily_available,
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"healthy": False,
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},
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"pii_redaction": {
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"enabled": self.config.pii_redaction_enabled,
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},
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}
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# Tavily Health Check (einfache Suche)
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if self.tavily_available:
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try:
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result = await self.search("test", max_results=1)
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status["tavily"]["healthy"] = True
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status["tavily"]["response_time_ms"] = result.response_time_ms
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except Exception as e:
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status["tavily"]["error"] = str(e)
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return status
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# Singleton Instance
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_tool_gateway: Optional[ToolGateway] = None
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def get_tool_gateway() -> ToolGateway:
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"""Gibt Singleton-Instanz des Tool Gateways zurück."""
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global _tool_gateway
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if _tool_gateway is None:
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_tool_gateway = ToolGateway()
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return _tool_gateway
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