forked from zhouruizhe/gmTouringMiniApp
204 lines
7.6 KiB
Python
204 lines
7.6 KiB
Python
from __future__ import annotations
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import json
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import os
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from datetime import datetime, timedelta
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from typing import Any, Optional
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from pydantic import ValidationError
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from .knowledge import KnowledgeBase
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from .prompts import SYSTEM_PROMPT
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from .schemas import GeneratedItinerary, Pace, TravelPreferences
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class LLMError(RuntimeError):
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pass
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class LLMTimeout(LLMError):
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pass
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class LLMService:
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def __init__(self, knowledge: KnowledgeBase) -> None:
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self.knowledge = knowledge
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self.mode = os.getenv("LLM_MODE", "mock").lower()
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self.timeout = float(os.getenv("LLM_TIMEOUT_SECONDS", "45"))
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@property
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def configured(self) -> bool:
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if self.mode == "mock":
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return True
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return bool(os.getenv("OPENAI_API_KEY") and os.getenv("OPENAI_MODEL"))
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async def generate(
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self,
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preferences: TravelPreferences,
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candidates: list[dict[str, Any]],
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previous: Optional[GeneratedItinerary] = None,
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user_message: Optional[str] = None,
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) -> GeneratedItinerary:
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if self.mode == "mock":
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return self._mock_generate(preferences, candidates, previous, user_message)
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return await self._real_generate(preferences, candidates, previous, user_message)
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async def _real_generate(
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self,
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preferences: TravelPreferences,
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candidates: list[dict[str, Any]],
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previous: Optional[GeneratedItinerary],
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user_message: Optional[str],
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) -> GeneratedItinerary:
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if not self.configured:
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raise LLMError("真实模型尚未配置")
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try:
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from openai import APITimeoutError, AsyncOpenAI
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except ImportError as exc:
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raise LLMError("缺少 openai 依赖") from exc
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client = AsyncOpenAI(
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api_key=os.environ["OPENAI_API_KEY"],
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base_url=os.getenv("OPENAI_BASE_URL") or None,
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timeout=self.timeout,
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)
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payload = {
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"preferences": preferences.model_dump(by_alias=True),
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"candidates": candidates,
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"travelTimes": self.knowledge.travel_context(
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candidates, preferences.transport.value
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),
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"previousItinerary": (
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previous.model_dump(by_alias=True) if previous else None
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),
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"adjustmentRequest": user_message,
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}
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feedback = ""
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allowed_ids = {place["id"] for place in candidates}
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for attempt in range(2):
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try:
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response = await client.chat.completions.create(
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model=os.environ["OPENAI_MODEL"],
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temperature=0.2,
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response_format={"type": "json_object"},
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messages=[
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{"role": "system", "content": SYSTEM_PROMPT},
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{
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"role": "user",
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"content": json.dumps(payload, ensure_ascii=False)
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+ feedback,
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},
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],
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)
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except APITimeoutError as exc:
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raise LLMTimeout("模型调用超时") from exc
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except Exception as exc:
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raise LLMError(f"模型调用失败：{exc}") from exc
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try:
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content = response.choices[0].message.content or "{}"
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itinerary = GeneratedItinerary.model_validate_json(content)
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unknown = {
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item.place_id for item in itinerary.items
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} - allowed_ids
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if unknown:
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raise ValueError(f"包含未知地点ID：{sorted(unknown)}")
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return itinerary
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except (ValidationError, ValueError, json.JSONDecodeError) as exc:
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if attempt == 1:
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raise LLMError(f"模型输出无法通过结构校验：{exc}") from exc
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feedback = f"\n上次输出校验失败：{exc}。请重新输出完整合法 JSON。"
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raise LLMError("模型未返回有效结果")
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def _mock_generate(
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self,
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preferences: TravelPreferences,
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candidates: list[dict[str, Any]],
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previous: Optional[GeneratedItinerary],
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user_message: Optional[str],
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) -> GeneratedItinerary:
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if not candidates:
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raise LLMError("没有符合条件的候选地点")
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max_items = {
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Pace.RELAXED: 3,
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Pace.MODERATE: 4,
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Pace.COMPACT: 5,
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}[preferences.pace]
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target = 240 if preferences.duration.value == "half_day" else 480
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start = datetime(2026, 1, 1, 9, 0)
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elapsed = 0
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items = []
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previous_place: Optional[dict[str, Any]] = None
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for place in candidates:
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if len(items) >= max_items:
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break
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transfer_value: Optional[int] = 0
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if previous_place:
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transfer_value = self.knowledge.travel_minutes(
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previous_place["id"],
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place["id"],
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preferences.transport.value,
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)
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transfer_for_math = transfer_value or 0
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duration = int(place.get("recommendedMinutes", 75))
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if elapsed + transfer_for_math + duration > target + 30 and items:
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continue
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item_start = start + timedelta(minutes=transfer_for_math)
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end = item_start + timedelta(minutes=duration)
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items.append(
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{
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"startTime": item_start.strftime("%H:%M"),
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"endTime": end.strftime("%H:%M"),
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"placeId": place["id"],
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"placeName": place["name"],
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"activity": place["summary"],
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"reason": self._reason(preferences, place),
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"transferFromPreviousMinutes": (
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transfer_value if previous_place else 0
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),
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"tips": place.get("tips", [])[:2],
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}
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)
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elapsed += transfer_for_math + duration
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start = end
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previous_place = place
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themes = "、".join(preferences.themes or preferences.interests[:1])
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adjustment = f"；已响应“{user_message}”" if user_message else ""
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pace_label = {
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Pace.RELAXED: "轻松",
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Pace.MODERATE: "适中",
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Pace.COMPACT: "紧凑",
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}[preferences.pace]
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return GeneratedItinerary.model_validate(
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{
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"title": f"光明区{themes or '精选'}{'半日' if preferences.duration.value == 'half_day' else '一日'}游",
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"summary": f"以科学、人文与都市自然为线索，按{pace_label}节奏安排{adjustment}。",
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"totalMinutes": max(elapsed, 1),
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"estimatedCostText": "费用以场馆、景区及实际交通信息为准",
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"items": items,
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"notes": [
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"开放时间、预约和票价请在出行前通过官方渠道再次确认。",
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"交通耗时为POC估算，请以出发时的实际导航为准。",
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],
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}
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)
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@staticmethod
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def _reason(
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preferences: TravelPreferences, place: dict[str, Any]
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) -> str:
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matches = list(
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(set(preferences.themes) & set(place.get("themes", [])))
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| (set(preferences.interests) & set(place.get("interests", [])))
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)
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return (
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f"符合你的{'、'.join(sorted(matches))}偏好"
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if matches
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else "作为光明区同路线备选，便于控制整体节奏"
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)
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