This commit is contained in:
parent
9e0c58743a
commit
5b5f41be49
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@ -279,10 +279,10 @@ class ConversationState(rx.State):
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conversation.is_running = True
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# 将等待流式输出设置为是
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conversation.awaiting_stream = True
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yield # 通知前端更新渲染
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# 获取数据库状态
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db_state = await self.get_db_state()
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# 先创建消息记录再添加消息实例
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conversation.messages.update(
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await db_state.create_message_record(
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@ -350,6 +350,7 @@ class ConversationState(rx.State):
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conversation.messages[message.id] = message
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# 将消息实例唯一标识与片段索引映射
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index_map_to_message_id[index] = message.id
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yield # 通知前端更新渲染
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# 文本分片开始事件
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case TextPart(content=content):
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@ -360,6 +361,7 @@ class ConversationState(rx.State):
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conversation.messages[message.id] = message
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# 将消息实例唯一标识与片段索引映射
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index_map_to_message_id[index] = message.id
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yield # 通知前端更新渲染
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# ========== 增量事件 ==========
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case PartDeltaEvent(index=index, delta=delta):
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@ -373,6 +375,7 @@ class ConversationState(rx.State):
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conversation.messages[
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index_map_to_message_id[index]
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].content += content_delta
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yield # 通知前端更新渲染
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# 文本分片增量事件
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case TextPartDelta(
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@ -382,6 +385,7 @@ class ConversationState(rx.State):
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conversation.messages[
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index_map_to_message_id[index]
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].content += content_delta
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yield # 通知前端更新渲染
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# ========== 结束事件 ==========
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case PartEndEvent(
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@ -397,6 +401,7 @@ class ConversationState(rx.State):
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]
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message.is_running = False
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message.title = "思考完成"
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yield # 通知前端更新渲染
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messages.append(message)
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case TextPart(content=content):
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@ -404,7 +409,6 @@ class ConversationState(rx.State):
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message = conversation.messages[
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index_map_to_message_id[index]
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]
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message.content = content
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messages.append(message)
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# ========== 智能体运行结果事件 ==========
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@ -419,10 +423,6 @@ class ConversationState(rx.State):
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new_messages=result.new_messages(),
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)
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# 强制更新会话并推送前端
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self.conversations[self.actived_conversation_id] = conversation
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yield
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except Exception as e:
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...
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finally:
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@ -2,29 +2,52 @@
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"""
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预定航班（范式）
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"""
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import asyncio
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import datetime
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from typing import AsyncGenerator, Literal
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from typing import AsyncGenerator
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from pydantic import BaseModel, Field
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from pydantic_ai import Agent, ModelMessage, ModelRetry, RunContext, UsageLimits, RunUsage, DeferredToolRequests
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from pydantic_ai.run import AgentRunResultEvent
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from application.states.models import (
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WorkFlow,
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WorkFlowType,
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from logfire_api.variables import ValueDoesNotEqual
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from pydantic import BaseModel, Field, field_validator
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from pydantic_ai import (
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Agent,
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ApprovalRequired,
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DeferredToolRequests,
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DeferredToolResults,
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ModelMessage,
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ModelRetry,
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ModelSettings,
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RunContext,
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RunUsage,
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UsageLimits,
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)
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from application.workshop.models import DEEPSEEK_V4_FLASH_MODEL, MODEL_SETTINGS_DISABLED_THINKING
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from pydantic_ai.models.openai import OpenAIChatModel
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from pydantic_ai.providers.openai import OpenAIProvider
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from sqlalchemy.sql.dml import ReturningDelete
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class Dependences(BaseModel):
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DEEPSEEK_V4_FLASH_MODEL = OpenAIChatModel(
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model_name="deepseek-v4-flash",
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provider=OpenAIProvider(
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base_url="https://tokenhub.tencentmaas.com/v1",
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api_key="sk-D9Y1mCe8VlvNqLuSC4mAjqEwxJ2nW4C0h8a7EPn8kg9RLsHq",
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),
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)
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MODEL_SETTINGS = ModelSettings(
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temperature=0, extra_body={"thinking": {"type": "disabled"}} # 温度控制
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) # 禁用思考模式
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class Deps(BaseModel):
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"""
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依赖类
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"""
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date: datetime.date = Field(..., description="航班日期")
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origin: str = Field(..., description="航班出发机场")
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destination: str = Field(..., description="航班到达机场")
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source_material: str = Field(..., description="航班来源资料")
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date: datetime.date = Field(..., description="日期")
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origin_airport_code: str = Field(..., description="出发机场代码")
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destination_airport_code: str = Field(..., description="到达机场代码")
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source_material: str = Field(..., description="来源资料")
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class Flight(BaseModel):
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"""
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@ -32,10 +55,22 @@ class Flight(BaseModel):
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"""
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number: str = Field(..., description="航班号")
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date: datetime.date = Field(..., description="航班日期")
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origin: str = Field(..., description="航班出发机场")
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destination: str = Field(..., description="航班到达机场")
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airfare: int = Field(..., description="航班机票价格")
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date: datetime.date = Field(..., description="日期")
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origin_airport_code: str = Field(..., description="出发机场代码")
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destination_airport_code: str = Field(..., description="到达机场代码")
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airfare: int = Field(..., description="机票价格")
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@field_validator("origin_airport_code", "destination_airport_code")
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@classmethod
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def validate_airport_code(cls, airport_code: str) -> str:
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"""校验机场代码"""
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if (
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not airport_code.isalpha()
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or not airport_code.isupper()
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or len(airport_code) != 3
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):
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raise ValueError(f"机场代码须为英文、大写、3位字符串")
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return airport_code
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class FlightNoFound(BaseModel):
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@ -43,85 +78,104 @@ class FlightNoFound(BaseModel):
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未查询到航班类
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"""
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class SeatPreference(BaseModel):
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"""
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座位偏好类
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system_prompt = """你的任务是根据用户提供的日期、出发机场和到达机场选择航班。
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1. 使用 extract_flights 从来源资料提取所有航班信息；
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2. 使用 select_flight 从所有航班信息中选择匹配航班；
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"""
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row: int = Field(ge=1, le=30, description="座位行")
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column: Literal["A", "B", "C", "D", "E", "F"] = Field(description="座位列")
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class SeatPreferenceNoExtracted(BaseModel):
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"""
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未提取到座位偏好类
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"""
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# 航班查询智能体
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flight_inquiry_agent = Agent[Dependences, Flight | FlightNoFound | DeferredToolRequests](
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# 主智能体
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agent = Agent[Deps, Flight | FlightNoFound](
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model=DEEPSEEK_V4_FLASH_MODEL,
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model_settings=MODEL_SETTINGS_DISABLED_THINKING,
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deps_type=Dependences,
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output_type=Flight | FlightNoFound | DeferredToolRequests,
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system_prompt="你的任务是根据给定的日期、出发机场和到达机场帮助用户找到最便宜的航班。",
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model_settings=MODEL_SETTINGS,
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deps_type=Deps,
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output_type=Flight | FlightNoFound,
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system_prompt=system_prompt,
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)
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# 航班信息提取智能体
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flights_extraction_agent = Agent(
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extraction_agent = Agent(
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model=DEEPSEEK_V4_FLASH_MODEL,
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model_settings=MODEL_SETTINGS_DISABLED_THINKING,
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model_settings=MODEL_SETTINGS,
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output_type=list[Flight],
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system_prompt="你的任务是根据给定的航班来源资料提取出所有航班信息，包括航班号、航班日期、航班出发机场、航班到达机场和航班机票价格。禁止编造。")
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system_prompt=(
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"你的任务是根据给定的来源资料提取出所有航班信息，包括航班号、日期、出发机场代码、到达机场代码和机票价格。",
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"其中，出发机场代码和到达机场代码须为英文、大写、3位字符串，例如 San Francisco International Airport (SFO) 的机场代码为 SFO。",
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"若某航班信息不全则跳过该航班，若没有任何航班信息则返回空列表。",
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"禁止编造。",
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),
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) # 通过提示词约束输出
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# 航班选择智能体
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selection_agent = Agent(
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model=DEEPSEEK_V4_FLASH_MODEL,
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model_settings=MODEL_SETTINGS,
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output_type=Flight | FlightNoFound,
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system_prompt="你的任务是从所有航班信息中选择匹配用户提供的日期、出发机场和到达机场的航班：若有多个航班则选择最便宜的航班，选择完成需用户确认是否预定；若没有则返回 FlightNoFound。",
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)
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@flight_inquiry_agent.tool
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async def extract_flight_details(ctx: RunContext[Dependences]) -> list[Flight]:
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"""
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如何提高提取准确率
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1. 系统提示词规则约束
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2. 降低模型温度
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3. 输出类型约定和输出模型校验
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4. 业务规则约束（例如，输出不可为空列表）
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"""
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@agent.tool
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async def extract_flights(ctx: RunContext[Deps]) -> list[Flight]:
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"""
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提取所有航班信息
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"""
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result = await flights_extraction_agent.run(
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ctx.deps.source_material, usage=ctx.usage
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result = await extraction_agent.run(
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ctx.deps.source_material,
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usage_limits=UsageLimits(request_limit=3),
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usage=ctx.usage,
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)
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if len(output := result.output) != 8:
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raise ModelRetry("提取到的所有航班信息应为 8 条")
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return output
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@agent.tool
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async def select_flight(ctx: RunContext[Deps]) -> Flight | FlightNoFound:
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"""
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选择航班
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"""
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result = await selection_agent.run(ctx.deps.source_material, usage=ctx.usage)
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if isinstance(result.output, Flight):
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if not ctx.tool_call_approved:
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raise ApprovalRequired(metadata={"reason": "protected"})
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return result.output
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@flight_inquiry_agent.output_validator
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@agent.output_validator
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async def validate_output(
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ctx: RunContext[Dependences], output: Flight | FlightNoFound | DeferredToolRequests
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) -> Flight | FlightNoFound | DeferredToolRequests:
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ctx: RunContext[Deps], output: Flight | FlightNoFound
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) -> Flight | FlightNoFound:
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"""
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输出校验：航班信息
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输出校验
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"""
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# 不校验未查询到航班
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if isinstance(output, FlightNoFound):
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return output
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# 不校验延迟工具请求
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if isinstance(output, DeferredToolRequests):
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return output
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errors = []
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if output.date != ctx.deps.date:
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errors.append(f"航班日期应为 {ctx.deps.date}, 不是 {output.date}")
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if output.origin != ctx.deps.origin:
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errors.append(f"航班出发机场应为 {ctx.deps.origin}, 不是 {output.origin}")
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if output.destination != ctx.deps.destination:
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errors.append(f"航班到达机场应为 {ctx.deps.destination}, 不是 {output.destination}")
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errors.append(
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f"航班到达机场应为 {ctx.deps.destination}, 不是 {output.destination}"
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)
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if errors:
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raise ModelRetry("\n".join(errors))
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return output
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# 座位偏好提取智能体
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seat_preference_extraction_agent = Agent[object, SeatPreference | SeatPreferenceNoExtracted](
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model=DEEPSEEK_V4_FLASH_MODEL,
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model_settings=MODEL_SETTINGS_DISABLED_THINKING,
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output_type=SeatPreference | SeatPreferenceNoExtracted,
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system_prompt="你的任务是根据用户回答提取座位偏好。座位规则说明：A 座、F 座为靠窗座位；第 1 排是前排座位，腿部空间更大；14 排、20 排同样拥有加宽腿部空间",
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)
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source_material = """
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1. Flight SFO-AK123
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- Price: $350
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@ -166,39 +220,49 @@ source_material = """
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"""
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def init_work_flow() -> WorkFlow:
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return WorkFlow(
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type=WorkFlowType.BOOK_FLIGHT,
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deps=Deps_(
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flight_info=flight_info,
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async def run_stream_events(
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user_prompt: str,
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deps: Deps,
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message_history: list[ModelMessage],
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usage: RunUsage,
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deferred_tool_results: DeferredToolResults | None = None,
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) -> AsyncGenerator:
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async with agent.run_stream_events(
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user_prompt=user_prompt,
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deps=deps,
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message_history=message_history,
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usage=usage,
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deferred_tool_results=deferred_tool_results,
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) as events:
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async for event in events:
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yield event
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async def main():
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deps = Deps(
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source_material=source_material,
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date=datetime.date(2025, 1, 10),
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origin="SFO",
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destination="ANC",
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),
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usage_limits={},
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)
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# message_history 传空列表，不要传 None
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msg_history: list[ModelMessage] = []
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prompt = f"Find me a flight from {deps.origin} to {deps.destination} on {deps.date}"
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gen = run_stream_events(
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user_prompt=prompt,
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deps=deps,
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message_history=msg_history,
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usage=RunUsage(),
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)
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# 消费异步生成器
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async for ev in gen:
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print(ev)
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async def run_stream_events(
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usage: RunUsage,
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user_prompt: str,
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message_history: list[ModelMessage],
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) -> AsyncGenerator:
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result = None
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while True:
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if not task:
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return
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asyncio.run(main())
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match task.node:
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# 航班查询
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case "flight_search":
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async with flight_search_agent.run_stream_events(
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user_prompt=user_prompt,
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deps=task.deps,
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message_history=message_history,
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usage=usage,
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) as events:
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async for event in events:
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"""
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if not isinstance(event, AgentRunResultEvent):
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yield event
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else:
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@ -329,3 +393,24 @@ async def run_stream_events(
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case _:
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continue
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def init_work_flow() -> WorkFlow:
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return WorkFlow(
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type=WorkFlowType.BOOK_FLIGHT,
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deps=Dependences(
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source_material=source_material,
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date=datetime.date(2025, 1, 10),
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origin="SFO",
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destination="ANC",
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),
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)
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from application.states.models import (
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WorkFlow,
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WorkFlowType,
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)
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from application.workshop.models import (
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DEEPSEEK_V4_FLASH_MODEL,
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MODEL_SETTINGS_DISABLED_THINKING,
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)
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"""
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|
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@ -3,7 +3,7 @@
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智能体相关模块
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"""
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from pydantic_ai import ModelSettings
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from pydantic_ai.models.openai import OpenAIChatModel, OpenAIChatModelSettings
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from pydantic_ai.models.openai import OpenAIChatModel
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from pydantic_ai.providers.openai import OpenAIProvider
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DEEPSEEK_V4_FLASH_MODEL = OpenAIChatModel(
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|
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