"""Achievement extraction service."""

import json
import re

import httpx

from app.core.config import settings
from app.core.logging import get_logger
from app.core.prompts import ACHIEVEMENT_EXTRACTION_PROMPT

logger = get_logger(__name__)

TEXT_API_BASE = "https://generativelanguage.googleapis.com/v1beta/models"


async def extract_achievements(story_text: str) -> list[dict]:
    """Extract achievements from story text using LLM."""
    if not settings.text_api_key:
        logger.warning("achievement_extraction_skipped", reason="missing_text_api_key")
        return []

    model = settings.text_model or "gemini-2.0-flash"
    url = f"{TEXT_API_BASE}/{model}:generateContent"

    prompt = ACHIEVEMENT_EXTRACTION_PROMPT.format(story_text=story_text)
    payload = {
        "contents": [{"parts": [{"text": prompt}]}],
        "generationConfig": {
            "responseMimeType": "application/json",
            "temperature": 0.2,
            "topP": 0.9,
        },
    }

    async with httpx.AsyncClient(timeout=30) as client:
        response = await client.post(
            url,
            json=payload,
            headers={"x-goog-api-key": settings.text_api_key},
        )
        response.raise_for_status()
        result = response.json()

    candidates = result.get("candidates") or []
    if not candidates:
        logger.warning("achievement_extraction_empty")
        return []

    parts = candidates[0].get("content", {}).get("parts") or []
    if not parts or "text" not in parts[0]:
        logger.warning("achievement_extraction_missing_text")
        return []

    response_text = parts[0]["text"]
    clean_json = response_text
    if response_text.startswith("```json"):
        clean_json = re.sub(r"^```json\n|```$", "", response_text)

    try:
        parsed = json.loads(clean_json)
    except json.JSONDecodeError:
        logger.warning("achievement_extraction_parse_failed")
        return []

    achievements = parsed.get("achievements")
    if not isinstance(achievements, list):
        return []

    normalized: list[dict] = []
    for item in achievements:
        if not isinstance(item, dict):
            continue
        a_type = str(item.get("type", "")).strip()
        description = str(item.get("description", "")).strip()
        score = item.get("score", 0)
        if not a_type or not description:
            continue
        normalized.append({
            "type": a_type,
            "description": description,
            "score": score
        })

    return normalized