import uuid
import logging
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel
from langchain.schema import HumanMessage, SystemMessage

from ..core.llm import get_llm, COMPLIANCE_CHECK_PROMPT
from ..services.rag import hybrid_search

logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api/compliance", tags=["合规审查"])


class ComplianceCheckRequest(BaseModel):
    query: str
    regulation_domains: list[str] = ["vehicle_safety"]
    top_k: int = 5


class ComplianceCheckResponse(BaseModel):
    risk_level: str
    risk_score: float
    findings: list[dict]
    recommendations: list[str]
    sources: list[dict]


@router.post("/check", response_model=ComplianceCheckResponse)
async def check_compliance(req: ComplianceCheckRequest):
    """
    对输入内容进行合规性检查，与法规库比对后给出风险评估。
    """
    # 检索相关法规（从多个域检索）
    all_chunks = []
    for domain in req.regulation_domains:
        chunks = await hybrid_search(
            req.query,
            collection_name="regulation_chunks",
            top_k=req.top_k,
        )
        all_chunks.extend(chunks)

    # 去重 + 按分数排序
    seen = set()
    unique_chunks = []
    for c in sorted(all_chunks, key=lambda x: x["score"], reverse=True):
        if c["id"] not in seen:
            seen.add(c["id"])
            unique_chunks.append(c)
    top_chunks = unique_chunks[:req.top_k]

    if not top_chunks:
        return ComplianceCheckResponse(
            risk_level="unknown",
            risk_score=0,
            findings=[{"issue": "未找到相关法规，请先上传法规文档"}],
            recommendations=["上传相关法规文档到知识库后重试"],
            sources=[],
        )

    # 构建法规上下文
    regulations_text = "\n\n".join(
        f"[{i+1}] {c['content'][:500]}" for i, c in enumerate(top_chunks)
    )

    prompt = COMPLIANCE_CHECK_PROMPT.format(
        content=req.query,
        regulations=regulations_text,
    )

    llm = get_llm(temperature=0.0)
    try:
        response = await llm.ainvoke([HumanMessage(content=prompt)])
        analysis = response.content
    except Exception as e:
        logger.error(f"LLM 合规分析失败：{e}")
        analysis = f"LLM 分析失败：{e}"

    # 简单解析 LLM 输出（生产可用结构化输出）
    risk_level = "medium"
    risk_score = 50.0
    if "critical" in analysis.lower() or "严重" in analysis:
        risk_level, risk_score = "critical", 90.0
    elif "high" in analysis.lower() or "高风险" in analysis:
        risk_level, risk_score = "high", 70.0
    elif "low" in analysis.lower() or "低风险" in analysis:
        risk_level, risk_score = "low", 20.0

    return ComplianceCheckResponse(
        risk_level=risk_level,
        risk_score=risk_score,
        findings=[{"analysis": analysis}],
        recommendations=["请参考上述分析进行整改"],
        sources=[{"content": c["content"][:200], "score": c["score"]} for c in top_chunks],
    )