init

backend/app/services/diagnosis.py

@@ -0,0 +1,379 @@
+from __future__ import annotations
+
+import json
+import logging
+import time
+from dataclasses import dataclass, field
+from typing import Any, Literal
+from uuid import uuid4
+
+import httpx
+
+from app.core.schemas import DiagnosisDraft, DiagnosisQuestion, DiagnosisQuestionAnswer, DiagnosisResponse
+from app.core.settings import DEEPSEEK_API_KEY, DEEPSEEK_BASE_URL, DEEPSEEK_MODEL, DEEPSEEK_TIMEOUT
+
+logger = logging.getLogger(__name__)
+SESSION_TTL = 3600  # 1 hour
+
+CLASSIFY_SYSTEM_PROMPT = """你是宿舍维修故障诊断助手。根据学生故障描述，输出 JSON 对象。
+
+分类规则:
+- 电路照明: 灯、电、跳闸、插座、焦味、漏电、火花
+- 给排水: 漏水、水龙头、下水、厕所、马桶、管道、洗手池
+- 门窗锁具: 门、锁、窗、把手、柜门
+- 空调设备: 空调、制冷、制热
+- 网络设备: 网络、wifi、网速、断网、网口
+- 家具设施: 床、桌椅、衣柜、抽屉、护栏
+- 其他: 不属于以上类别
+
+紧急度规则(urgency):
+- 紧急: 火花、漏电、冒烟、大面积漏水、安全威胁
+- 高: 影响基本生活(照明/用水/用电/门禁)
+- 中: 普通故障影响使用
+- 低: 无立即影响
+
+safety_risk: 火花、漏电、冒烟、焦味 设为 true
+suggested_worker: 电工(电路照明)、水暖维修(给排水)、门窗维修(门窗锁具)、空调维修(空调设备)、
+  网络维护(网络设备)、综合维修(其他)
+questions: 2-3个有针对性、非模板化的追问，每个含 id(q1/q2/q3) 和 prompt 字段
+
+输出格式:
+{"category":"...","urgency":"...","safety_risk":false,"suggested_worker":"...","notes":["..."],"questions":[{"id":"q1","prompt":"..."}]}"""
+
+SUMMARY_SYSTEM_PROMPT = """根据学生原始描述和补充回答，生成维修工单摘要。
+格式:"[category]问题，建议[suggested_worker]处理。[现象]；[位置]；[影响范围]"
+不超过200字，使用中文标点。"""
+
+
+@dataclass
+class DiagnosisSession:
+    session_id: str
+    category: str
+    urgency: Literal["低", "中", "高", "紧急"]
+    suggested_worker: str
+    safety_risk: bool
+    initial_message: str
+    suggested_categories: list[str]
+    questions: list[DiagnosisQuestion]
+    notes: list[str] = field(default_factory=list)
+    created_at: float = field(default_factory=time.time)
+
+
+class AIDiagnosisProvider:
+    def __init__(
+        self,
+        *,
+        base_url: str = DEEPSEEK_BASE_URL,
+        api_key: str = DEEPSEEK_API_KEY,
+        model: str = DEEPSEEK_MODEL,
+        timeout: float = DEEPSEEK_TIMEOUT,
+    ) -> None:
+        self._api_key = api_key
+        self._client = httpx.AsyncClient(
+            base_url=base_url.rstrip("/"),
+            headers={
+                "Authorization": f"Bearer {api_key}",
+                "Content-Type": "application/json",
+            },
+            timeout=httpx.Timeout(timeout),
+        )
+        self._model = model
+        self._sessions: dict[str, DiagnosisSession] = {}
+        self._last_sweep = time.time()
+
+    def _sweep_expired_sessions(self) -> None:
+        now = time.time()
+        if now - self._last_sweep < 300:  # sweep every 5 minutes
+            return
+        self._last_sweep = now
+        expired = [sid for sid, s in self._sessions.items() if now - s.created_at > SESSION_TTL]
+        for sid in expired:
+            del self._sessions[sid]
+        if expired:
+            logger.info("Swept %d expired diagnosis sessions", len(expired))
+
+    async def start(self, message: str) -> DiagnosisResponse:
+        self._sweep_expired_sessions()
+        if not self._api_key:
+            return self._start_local(message)
+        try:
+            result = await self._call_classify(message)
+            category = result["category"]
+            urgency = result["urgency"]
+            worker = result["suggested_worker"]
+            safety_risk = result["safety_risk"]
+            ai_notes = result.get("notes", [])
+            questions = [DiagnosisQuestion(id=q["id"], prompt=q["prompt"]) for q in result.get("questions", [])]
+            if not questions:
+                questions = [
+                    DiagnosisQuestion(id="location", prompt="问题具体出现在宿舍的什么位置或设备上？"),
+                    DiagnosisQuestion(id="symptom", prompt="请补充最明显的故障现象，方便维修人员带对工具。"),
+                ]
+        except (httpx.HTTPError, json.JSONDecodeError, KeyError):
+            return self._start_local(message)
+
+        session_id = uuid4().hex
+        suggested_categories = [category]
+        if category != "其他":
+            suggested_categories.append("其他")
+        session = DiagnosisSession(
+            session_id=session_id,
+            category=category,
+            urgency=urgency,
+            suggested_worker=worker,
+            safety_risk=safety_risk,
+            initial_message=message,
+            suggested_categories=suggested_categories,
+            questions=questions,
+            notes=ai_notes,
+        )
+        self._sessions[session_id] = session
+        return DiagnosisResponse(
+            session_id=session_id,
+            stage="questions",
+            initial_message=message,
+            suggested_categories=suggested_categories,
+            questions=questions,
+            draft=None,
+        )
+
+    async def answer(self, session_id: str, answers: list[DiagnosisQuestionAnswer]) -> DiagnosisResponse:
+        session = self._sessions.get(session_id)
+        if session is None:
+            raise KeyError("session_not_found")
+
+        if time.time() - session.created_at > SESSION_TTL:
+            del self._sessions[session_id]
+            raise KeyError("session_not_found")
+
+        session.created_at = time.time()
+
+        if not self._api_key:
+            return self._answer_local(session, answers)
+        try:
+            summary = await self._call_summary(session, answers)
+        except (httpx.HTTPError, json.JSONDecodeError):
+            return self._answer_local(session, answers)
+
+        notes = list(session.notes)
+        if session.safety_risk:
+            notes.append("建议尽快断电或停止继续使用相关设备。")
+        answer_map = {item.question_id: item.answer.strip() for item in answers}
+        for question in session.questions:
+            value = answer_map.get(question.id)
+            if value:
+                notes.append(f"{question.prompt}：{value}")
+
+        draft = DiagnosisDraft(
+            category=session.category,
+            urgency=session.urgency,
+            summary=summary,
+            safety_risk=session.safety_risk,
+            suggested_worker=session.suggested_worker,
+            notes=notes,
+        )
+        return DiagnosisResponse(
+            session_id=session.session_id,
+            stage="draft",
+            initial_message=session.initial_message,
+            suggested_categories=session.suggested_categories,
+            questions=[],
+            draft=draft,
+        )
+
+    def _start_local(self, message: str) -> DiagnosisResponse:
+        category, urgency, worker, safety_risk, questions = self._local_classify(message)
+        session_id = uuid4().hex
+        suggested_categories = [category]
+        if category != "其他":
+            suggested_categories.append("其他")
+        session = DiagnosisSession(
+            session_id=session_id,
+            category=category,
+            urgency=urgency,
+            suggested_worker=worker,
+            safety_risk=safety_risk,
+            initial_message=message,
+            suggested_categories=suggested_categories,
+            questions=questions,
+        )
+        self._sessions[session_id] = session
+        return DiagnosisResponse(
+            session_id=session_id,
+            stage="questions",
+            initial_message=message,
+            suggested_categories=suggested_categories,
+            questions=questions,
+            draft=None,
+        )
+
+    def _answer_local(self, session: DiagnosisSession, answers: list[DiagnosisQuestionAnswer]) -> DiagnosisResponse:
+        answer_map = {item.question_id: item.answer.strip() for item in answers}
+        notes = []
+        if session.safety_risk:
+            notes.append("建议尽快断电或停止继续使用相关设备。")
+        if "location" in answer_map:
+            notes.append(f"具体位置：{answer_map['location']}")
+        if "impact" in answer_map:
+            notes.append(f"影响范围：{answer_map['impact']}")
+        if "symptom" in answer_map:
+            notes.append(f"补充现象：{answer_map['symptom']}")
+
+        summary = self._local_build_summary(session, answer_map)
+        draft = DiagnosisDraft(
+            category=session.category,
+            urgency=session.urgency,
+            summary=summary,
+            safety_risk=session.safety_risk,
+            suggested_worker=session.suggested_worker,
+            notes=notes,
+        )
+        return DiagnosisResponse(
+            session_id=session.session_id,
+            stage="draft",
+            initial_message=session.initial_message,
+            suggested_categories=session.suggested_categories,
+            questions=[],
+            draft=draft,
+        )
+
+    def _local_classify(
+        self, message: str
+    ) -> tuple[str, Literal["低", "中", "高", "紧急"], str, bool, list[DiagnosisQuestion]]:
+        text = message.lower()
+        category = "其他"
+        urgency: Literal["低", "中", "高", "紧急"] = "中"
+        worker = "综合维修"
+        safety_risk = False
+
+        if any(keyword in text for keyword in ["灯", "电", "跳闸", "插座", "焦味"]):
+            category = "电路照明"
+            worker = "电工"
+            urgency = "高"
+        if any(keyword in text for keyword in ["漏水", "水龙头", "下水", "厕所", "马桶"]):
+            category = "给排水"
+            worker = "水暖维修"
+            urgency = "高"
+        if any(keyword in text for keyword in ["门", "锁", "窗", "把手"]):
+            category = "门窗锁具"
+            worker = "门窗维修"
+            urgency = "中"
+        if any(keyword in text for keyword in ["空调", "制冷", "制热"]):
+            category = "空调设备"
+            worker = "空调维修"
+            urgency = "中"
+        if any(keyword in text for keyword in ["网络", "wifi", "网速", "断网"]):
+            category = "网络设备"
+            worker = "网络维护"
+            urgency = "中"
+        if any(keyword in text for keyword in ["烟", "火花", "焦味", "漏电"]):
+            urgency = "紧急"
+            safety_risk = True
+
+        questions = [
+            DiagnosisQuestion(id="location", prompt="问题具体出现在宿舍的什么位置或设备上？"),
+            DiagnosisQuestion(id="impact", prompt="这个问题目前影响范围有多大？比如是否影响整间宿舍使用。"),
+            DiagnosisQuestion(id="symptom", prompt="请补充最明显的故障现象，方便维修人员带对工具。"),
+        ]
+        return category, urgency, worker, safety_risk, questions
+
+    def _local_build_summary(self, session: DiagnosisSession, answers: dict[str, str]) -> str:
+        parts = [session.initial_message.strip()]
+        for key in ("location", "impact", "symptom"):
+            value = answers.get(key)
+            if value:
+                parts.append(value)
+        joined = "；".join(parts)
+        return f"{session.category}问题，建议{session.suggested_worker}处理。{joined}"
+
+    async def _call_classify(self, message: str) -> dict[str, Any]:
+        response = await self._client.post(
+            "/v1/chat/completions",
+            json={
+                "model": self._model,
+                "messages": [
+                    {"role": "system", "content": CLASSIFY_SYSTEM_PROMPT},
+                    {"role": "user", "content": message},
+                ],
+                "response_format": {"type": "json_object"},
+                "temperature": 0.1,
+            },
+        )
+        response.raise_for_status()
+        body = response.json()
+        content = body["choices"][0]["message"]["content"]
+        result = json.loads(content)
+        _validate_classify_result(result)
+        return result
+
+    async def _call_summary(self, session: DiagnosisSession, answers: list[DiagnosisQuestionAnswer]) -> str:
+        answer_texts = "\n".join(f"- {item.question_id}: {item.answer.strip()}" for item in answers)
+        response = await self._client.post(
+            "/v1/chat/completions",
+            json={
+                "model": self._model,
+                "messages": [
+                    {"role": "system", "content": SUMMARY_SYSTEM_PROMPT},
+                    {
+                        "role": "user",
+                        "content": (
+                            f"原始描述：{session.initial_message}\n"
+                            f"故障类别：{session.category}\n"
+                            f"负责工种：{session.suggested_worker}\n"
+                            f"补充回答：\n{answer_texts}"
+                        ),
+                    },
+                ],
+                "temperature": 0.1,
+            },
+        )
+        response.raise_for_status()
+        body = response.json()
+        return body["choices"][0]["message"]["content"].strip()
+
+
+def _validate_classify_result(result: dict[str, Any]) -> None:
+    valid_categories = {"电路照明", "给排水", "门窗锁具", "空调设备", "网络设备", "家具设施", "其他"}
+    valid_urgencies = {"低", "中", "高", "紧急"}
+
+    category = result.get("category", "")
+    if category not in valid_categories:
+        result["category"] = "其他"
+
+    urgency = result.get("urgency", "")
+    if urgency not in valid_urgencies:
+        result["urgency"] = "中"
+
+    if not isinstance(result.get("safety_risk"), bool):
+        result["safety_risk"] = False
+
+    worker = result.get("suggested_worker", "")
+    if not worker:
+        result["suggested_worker"] = "综合维修"
+
+    questions = result.get("questions")
+    if not isinstance(questions, list):
+        result["questions"] = []
+    else:
+        result["questions"] = [q for q in questions if isinstance(q, dict) and "id" in q and "prompt" in q]
+
+    notes = result.get("notes")
+    if not isinstance(notes, list):
+        result["notes"] = []
+
+
+_dp: AIDiagnosisProvider | None = None
+
+
+def get_diagnosis_provider() -> AIDiagnosisProvider:
+    global _dp
+    if _dp is None:
+        _dp = AIDiagnosisProvider()
+    return _dp
+
+
+async def close_diagnosis_provider() -> None:
+    global _dp
+    if _dp is not None:
+        await _dp._client.aclose()
+        _dp = None