e9d7f8832a
- Backend: FastAPI + SQLAlchemy + Celery (Python 3.11+) - Frontend: Vue 3 + TypeScript + Pinia + Tailwind - Admin Frontend: separate Vue 3 app for management - Docker Compose: 9 services orchestration - Specs: design prototypes, memory system PRD, product roadmap Cleanup performed: - Removed temporary debug scripts from backend root - Removed deprecated admin_app.py (embedded UI) - Removed duplicate docs from admin-frontend - Updated .gitignore for Vite cache and egg-info
86 lines
2.5 KiB
Python
86 lines
2.5 KiB
Python
"""Achievement extraction service."""
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import json
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import re
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import httpx
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from app.core.config import settings
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from app.core.logging import get_logger
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from app.core.prompts import ACHIEVEMENT_EXTRACTION_PROMPT
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logger = get_logger(__name__)
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TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"
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async def extract_achievements(story_text: str) -> list[dict]:
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"""Extract achievements from story text using LLM."""
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if not settings.text_api_key:
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logger.warning("achievement_extraction_skipped", reason="missing_text_api_key")
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return []
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model = settings.text_model or "gemini-2.0-flash"
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url = f"{TEXT_API_BASE}/{model}:generateContent"
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prompt = ACHIEVEMENT_EXTRACTION_PROMPT.format(story_text=story_text)
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payload = {
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"contents": [{"parts": [{"text": prompt}]}],
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"generationConfig": {
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"responseMimeType": "application/json",
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"temperature": 0.2,
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"topP": 0.9,
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},
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}
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async with httpx.AsyncClient(timeout=30) as client:
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response = await client.post(
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url,
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json=payload,
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headers={"x-goog-api-key": settings.text_api_key},
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)
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response.raise_for_status()
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result = response.json()
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candidates = result.get("candidates") or []
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if not candidates:
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logger.warning("achievement_extraction_empty")
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return []
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parts = candidates[0].get("content", {}).get("parts") or []
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if not parts or "text" not in parts[0]:
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logger.warning("achievement_extraction_missing_text")
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return []
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response_text = parts[0]["text"]
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clean_json = response_text
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if response_text.startswith("```json"):
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clean_json = re.sub(r"^```json\n|```$", "", response_text)
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try:
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parsed = json.loads(clean_json)
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except json.JSONDecodeError:
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logger.warning("achievement_extraction_parse_failed")
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return []
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achievements = parsed.get("achievements")
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if not isinstance(achievements, list):
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return []
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normalized: list[dict] = []
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for item in achievements:
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if not isinstance(item, dict):
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continue
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a_type = str(item.get("type", "")).strip()
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description = str(item.get("description", "")).strip()
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score = item.get("score", 0)
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if not a_type or not description:
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continue
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normalized.append({
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"type": a_type,
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"description": description,
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"score": score
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})
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return normalized
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