99 lines
2.8 KiB
Python
99 lines
2.8 KiB
Python
"""
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FILE: app/services/feedback_service.py
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DESCRIPTION: Schreibt Search- und Feedback-Logs in JSONL-Dateien.
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VERSION: 1.1
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STATUS: Active
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DEPENDENCIES: app.models.dto
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LAST_ANALYSIS: 2025-12-15
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"""
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import json
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import os
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import time
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import logging
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from pathlib import Path
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from typing import Dict, Any, List, Union
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from app.models.dto import QueryRequest, QueryResponse, FeedbackRequest, QueryHit
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logger = logging.getLogger(__name__)
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# Pfad für Logs (lokal auf dem Beelink/PC)
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LOG_DIR = Path("data/logs")
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SEARCH_LOG_FILE = LOG_DIR / "search_history.jsonl"
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FEEDBACK_LOG_FILE = LOG_DIR / "feedback.jsonl"
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def _ensure_log_dir():
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if not LOG_DIR.exists():
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os.makedirs(LOG_DIR, exist_ok=True)
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def _append_jsonl(file_path: Path, data: dict):
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try:
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with open(file_path, "a", encoding="utf-8") as f:
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f.write(json.dumps(data, ensure_ascii=False) + "\n")
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except Exception as e:
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logger.error(f"Failed to write log: {e}")
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def log_search(
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query_id: str,
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query_text: str,
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results: List[QueryHit],
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mode: str = "unknown",
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metadata: Dict[str, Any] = None
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):
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"""
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Generische Logging-Funktion für Suche UND Chat.
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Args:
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query_id: UUID der Anfrage.
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query_text: User-Eingabe.
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results: Liste der Treffer (QueryHit Objekte).
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mode: z.B. "semantic", "hybrid", "chat_rag".
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metadata: Zusätzliche Infos (z.B. generierte Antwort, Intent).
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"""
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_ensure_log_dir()
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hits_summary = []
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for hit in results:
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# Pydantic Model Dump für saubere Serialisierung
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breakdown = None
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if hit.explanation and hit.explanation.breakdown:
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breakdown = hit.explanation.breakdown.model_dump()
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hits_summary.append({
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"node_id": hit.node_id,
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"note_id": hit.note_id,
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"total_score": hit.total_score,
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"breakdown": breakdown,
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"rank_semantic": hit.semantic_score,
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"rank_edge": hit.edge_bonus,
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"type": hit.source.get("type") if hit.source else "unknown"
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})
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entry = {
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"timestamp": time.time(),
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"query_id": query_id,
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"query_text": query_text,
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"mode": mode,
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"hits_count": len(hits_summary),
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"hits": hits_summary,
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"metadata": metadata or {}
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}
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_append_jsonl(SEARCH_LOG_FILE, entry)
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logger.info(f"Logged search/chat interaction {query_id}")
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def log_feedback(fb: FeedbackRequest):
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"""
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Speichert das User-Feedback.
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"""
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_ensure_log_dir()
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entry = {
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"timestamp": time.time(),
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"query_id": fb.query_id,
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"node_id": fb.node_id,
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"score": fb.score,
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"comment": fb.comment
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}
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_append_jsonl(FEEDBACK_LOG_FILE, entry)
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logger.info(f"Logged feedback for {fb.query_id}") |