"""
ExtractionAgent：从用户消息中提取 5-stage 状态与 slots。
对应现有逻辑：get_state_extraction_prompt + JSON 解析
"""
from __future__ import annotations

import json
from dataclasses import dataclass
from typing import Any, Dict

from app.core.logging import get_logger
from app.features.memoir.memoir_images.json_payload import extract_json_payload

from app.agents.memoir.prompts import get_state_extraction_prompt

logger = get_logger(__name__)


@dataclass
class ExtractionResult:
    """状态提取结果"""
    detected_stage: str
    slots: Dict[str, str]


class ExtractionAgent:
    """从用户消息中提取 detected_stage 和 slots"""

    def extract(
        self,
        user_message: str,
        current_stage: str,
        stage_slots: Dict[str, Any],
        llm: Any,
    ) -> ExtractionResult:
        """
        提取结构化信息并判断阶段。
        llm 需支持 .invoke(prompt) 同步调用（Celery 任务内使用）。
        """
        detected_stage = current_stage
        extracted_slots: Dict[str, str] = {}

        if not llm:
            return ExtractionResult(detected_stage=detected_stage, slots=extracted_slots)

        try:
            prompt = get_state_extraction_prompt(
                user_message=user_message,
                current_stage=current_stage,
                stage_slots={
                    k: v.model_dump() if hasattr(v, "model_dump") else v
                    for k, v in (stage_slots or {}).items()
                },
            )
            json_llm = llm.bind(
                model_kwargs={"response_format": {"type": "json_object"}},
                max_tokens=1024,
            )
            response = json_llm.invoke(prompt)
            parsed = json.loads(extract_json_payload(response.content))
            detected_stage = parsed.get("detected_stage", detected_stage)
            raw_slots = parsed.get("slots", {}) or {}
            extracted_slots = {
                k: v if isinstance(v, str) else str(v)
                for k, v in raw_slots.items()
            }
        except (json.JSONDecodeError, Exception) as e:
            logger.warning("ExtractionAgent LLM 解析失败: %s", e)

        return ExtractionResult(detected_stage=detected_stage, slots=extracted_slots)