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liubiren 2026-08-12 20:14:26 +08:00
parent 9e0c58743a
commit 5b5f41be49
4 changed files with 206 additions and 121 deletions
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12
agent/application/states/conversation.py
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@ -279,10 +279,10 @@ class ConversationState(rx.State):
conversation.is_running = True
# 将等待流式输出设置为是
conversation.awaiting_stream = True
yield # 通知前端更新渲染
# 获取数据库状态
db_state = await self.get_db_state()
# 先创建消息记录再添加消息实例
conversation.messages.update(
await db_state.create_message_record(
@ -350,6 +350,7 @@ class ConversationState(rx.State):
conversation.messages[message.id] = message
# 将消息实例唯一标识与片段索引映射
index_map_to_message_id[index] = message.id
yield # 通知前端更新渲染
# 文本分片开始事件
case TextPart(content=content):
@ -360,6 +361,7 @@ class ConversationState(rx.State):
conversation.messages[message.id] = message
# 将消息实例唯一标识与片段索引映射
index_map_to_message_id[index] = message.id
yield # 通知前端更新渲染
# ========== 增量事件 ==========
case PartDeltaEvent(index=index, delta=delta):
@ -373,6 +375,7 @@ class ConversationState(rx.State):
conversation.messages[
index_map_to_message_id[index]
].content += content_delta
yield # 通知前端更新渲染
# 文本分片增量事件
case TextPartDelta(
@ -382,6 +385,7 @@ class ConversationState(rx.State):
conversation.messages[
index_map_to_message_id[index]
].content += content_delta
yield # 通知前端更新渲染
# ========== 结束事件 ==========
case PartEndEvent(
@ -397,6 +401,7 @@ class ConversationState(rx.State):
]
message.is_running = False
message.title = "思考完成"
yield # 通知前端更新渲染
messages.append(message)
case TextPart(content=content):
@ -404,7 +409,6 @@ class ConversationState(rx.State):
message = conversation.messages[
index_map_to_message_id[index]
]
message.content = content
messages.append(message)
# ========== 智能体运行结果事件 ==========
@ -419,10 +423,6 @@ class ConversationState(rx.State):
new_messages=result.new_messages(),
)
# 强制更新会话并推送前端
self.conversations[self.actived_conversation_id] = conversation
yield
except Exception as e:
...
finally:

313
agent/application/workshop/book_flight.py
View File

@ -2,29 +2,52 @@
"""
预定航班（范式）
"""
import asyncio
import datetime
from typing import AsyncGenerator, Literal
from typing import AsyncGenerator
from pydantic import BaseModel, Field
from pydantic_ai import Agent, ModelMessage, ModelRetry, RunContext, UsageLimits, RunUsage, DeferredToolRequests
from pydantic_ai.run import AgentRunResultEvent
from application.states.models import (
WorkFlow,
WorkFlowType,
from logfire_api.variables import ValueDoesNotEqual
from pydantic import BaseModel, Field, field_validator
from pydantic_ai import (
Agent,
ApprovalRequired,
DeferredToolRequests,
DeferredToolResults,
ModelMessage,
ModelRetry,
ModelSettings,
RunContext,
RunUsage,
UsageLimits,
)
from application.workshop.models import DEEPSEEK_V4_FLASH_MODEL, MODEL_SETTINGS_DISABLED_THINKING
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider
from sqlalchemy.sql.dml import ReturningDelete
class Dependences(BaseModel):
DEEPSEEK_V4_FLASH_MODEL = OpenAIChatModel(
model_name="deepseek-v4-flash",
provider=OpenAIProvider(
base_url="https://tokenhub.tencentmaas.com/v1",
api_key="sk-D9Y1mCe8VlvNqLuSC4mAjqEwxJ2nW4C0h8a7EPn8kg9RLsHq",
),
)
MODEL_SETTINGS = ModelSettings(
temperature=0, extra_body={"thinking": {"type": "disabled"}} # 温度控制
) # 禁用思考模式
class Deps(BaseModel):
"""
依赖类
"""
date: datetime.date = Field(..., description="航班日期")
origin: str = Field(..., description="航班出发机场")
destination: str = Field(..., description="航班到达机场")
source_material: str = Field(..., description="航班来源资料")
date: datetime.date = Field(..., description="日期")
origin_airport_code: str = Field(..., description="出发机场代码")
destination_airport_code: str = Field(..., description="到达机场代码")
source_material: str = Field(..., description="来源资料")
class Flight(BaseModel):
"""
@ -32,10 +55,22 @@ class Flight(BaseModel):
"""
number: str = Field(..., description="航班号")
date: datetime.date = Field(..., description="航班日期")
origin: str = Field(..., description="航班出发机场")
destination: str = Field(..., description="航班到达机场")
airfare: int = Field(..., description="航班机票价格")
date: datetime.date = Field(..., description="日期")
origin_airport_code: str = Field(..., description="出发机场代码")
destination_airport_code: str = Field(..., description="到达机场代码")
airfare: int = Field(..., description="机票价格")
@field_validator("origin_airport_code", "destination_airport_code")
@classmethod
def validate_airport_code(cls, airport_code: str) -> str:
"""校验机场代码"""
if (
not airport_code.isalpha()
or not airport_code.isupper()
or len(airport_code) != 3
):
raise ValueError(f"机场代码须为英文、大写、3位字符串")
return airport_code
class FlightNoFound(BaseModel):
@ -43,85 +78,104 @@ class FlightNoFound(BaseModel):
未查询到航班类
"""
class SeatPreference(BaseModel):
"""
座位偏好类
"""
row: int = Field(ge=1, le=30, description="座位行")
column: Literal["A", "B", "C", "D", "E", "F"] = Field(description="座位列")
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。
1. 使用 extract_flights 从来源资料提取所有航班信息；
2. 使用 select_flight 从所有航班信息中选择匹配航班；
"""
class SeatPreferenceNoExtracted(BaseModel):
"""
未提取到座位偏好类
"""
# 航班查询智能体
flight_inquiry_agent = Agent[Dependences, Flight | FlightNoFound | DeferredToolRequests](
# 主智能体
agent = Agent[Deps, Flight | FlightNoFound](
model=DEEPSEEK_V4_FLASH_MODEL,
model_settings=MODEL_SETTINGS_DISABLED_THINKING,
deps_type=Dependences,
output_type=Flight | FlightNoFound | DeferredToolRequests,
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。",
model_settings=MODEL_SETTINGS,
deps_type=Deps,
output_type=Flight | FlightNoFound,
system_prompt=system_prompt,
)
# 航班信息提取智能体
flights_extraction_agent = Agent(
extraction_agent = Agent(
model=DEEPSEEK_V4_FLASH_MODEL,
model_settings=MODEL_SETTINGS_DISABLED_THINKING,
model_settings=MODEL_SETTINGS,
output_type=list[Flight],
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。")
system_prompt=(
"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。",
"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。",
"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。",
"禁止编造。",
),
) # 通过提示词约束输出
# 航班选择智能体
selection_agent = Agent(
model=DEEPSEEK_V4_FLASH_MODEL,
model_settings=MODEL_SETTINGS,
output_type=Flight | FlightNoFound,
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。",
)
@flight_inquiry_agent.tool
async def extract_flight_details(ctx: RunContext[Dependences]) -> list[Flight]:
"""
如何提高提取准确率
1. 系统提示词规则约束
2. 降低模型温度
3. 输出类型约定和输出模型校验
4. 业务规则约束（例如，输出不可为空列表）
"""
@agent.tool
async def extract_flights(ctx: RunContext[Deps]) -> list[Flight]:
"""
提取所有航班信息
"""
result = await flights_extraction_agent.run(
ctx.deps.source_material, usage=ctx.usage
result = await extraction_agent.run(
ctx.deps.source_material,
usage_limits=UsageLimits(request_limit=3),
usage=ctx.usage,
)
if len(output := result.output) != 8:
raise ModelRetry("提取到的所有航班信息应为 8 条")
return output
@agent.tool
async def select_flight(ctx: RunContext[Deps]) -> Flight | FlightNoFound:
"""
选择航班
"""
result = await selection_agent.run(ctx.deps.source_material, usage=ctx.usage)
if isinstance(result.output, Flight):
if not ctx.tool_call_approved:
raise ApprovalRequired(metadata={"reason": "protected"})
return result.output
@flight_inquiry_agent.output_validator
@agent.output_validator
async def validate_output(
ctx: RunContext[Dependences], output: Flight | FlightNoFound | DeferredToolRequests
) -> Flight | FlightNoFound | DeferredToolRequests:
ctx: RunContext[Deps], output: Flight | FlightNoFound
) -> Flight | FlightNoFound:
"""
输出校验：航班信息
输出校验
"""
# 不校验未查询到航班
if isinstance(output, FlightNoFound):
return output
# 不校验延迟工具请求
if isinstance(output, DeferredToolRequests):
return output
errors = []
if output.date != ctx.deps.date:
errors.append(f"航班日期应为 {ctx.deps.date}, 不是 {output.date}")
if output.origin != ctx.deps.origin:
errors.append(f"航班出发机场应为 {ctx.deps.origin}, 不是 {output.origin}")
if output.destination != ctx.deps.destination:
errors.append(f"航班到达机场应为 {ctx.deps.destination}, 不是 {output.destination}")
errors.append(
f"航班到达机场应为 {ctx.deps.destination}, 不是 {output.destination}"
)
if errors:
raise ModelRetry("\n".join(errors))
return output
# 座位偏好提取智能体
seat_preference_extraction_agent = Agent[object, SeatPreference | SeatPreferenceNoExtracted](
model=DEEPSEEK_V4_FLASH_MODEL,
model_settings=MODEL_SETTINGS_DISABLED_THINKING,
output_type=SeatPreference | SeatPreferenceNoExtracted,
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",
)
source_material = """
1. Flight SFO-AK123
- Price: $350
@ -166,62 +220,72 @@ source_material = """
"""
def init_work_flow() -> WorkFlow:
return WorkFlow(
type=WorkFlowType.BOOK_FLIGHT,
deps=Deps_(
flight_info=flight_info,
date=datetime.date(2025, 1, 10),
origin="SFO",
destination="ANC",
),
usage_limits={},
)
async def run_stream_events(
usage: RunUsage,
user_prompt: str,
deps: Deps,
message_history: list[ModelMessage],
usage: RunUsage,
deferred_tool_results: DeferredToolResults | None = None,
) -> AsyncGenerator:
result = None
while True:
if not task:
return
async with agent.run_stream_events(
user_prompt=user_prompt,
deps=deps,
message_history=message_history,
usage=usage,
deferred_tool_results=deferred_tool_results,
) as events:
async for event in events:
yield event
match task.node:
# 航班查询
case "flight_search":
async with flight_search_agent.run_stream_events(
user_prompt=user_prompt,
deps=task.deps,
message_history=message_history,
usage=usage,
) as events:
async for event in events:
if not isinstance(event, AgentRunResultEvent):
yield event
else:
result = event.result
# 更新任务使用量
task.usage = usage_to_dict(result.usage)
if isinstance(result.output, FlightDetail):
content = "\n---\n已查询到航班，请回复 buy 购票 或 search 重新查询\n"
# 更新任务节点为提取座位偏好
task.node = "seat_preference_extraction"
else:
content = (
"\n---\n未查询到满足您需求的航班，流程结束！\n"
)
# 更新任务为空
task = None
# 返回任务节点结果事件
yield TaskNodeResultEvent(
task=task,
content=content,
)
yield event
return
async def main():
deps = Deps(
source_material=source_material,
date=datetime.date(2025, 1, 10),
origin="SFO",
destination="ANC",
)
# message_history 传空列表，不要传 None
msg_history: list[ModelMessage] = []
prompt = f"Find me a flight from {deps.origin} to {deps.destination} on {deps.date}"
gen = run_stream_events(
user_prompt=prompt,
deps=deps,
message_history=msg_history,
usage=RunUsage(),
)
# 消费异步生成器
async for ev in gen:
print(ev)
asyncio.run(main())
"""
if not isinstance(event, AgentRunResultEvent):
yield event
else:
result = event.result
# 更新任务使用量
task.usage = usage_to_dict(result.usage)
if isinstance(result.output, FlightDetail):
content = "\n---\n已查询到航班，请回复 buy 购票 或 search 重新查询\n"
# 更新任务节点为提取座位偏好
task.node = "seat_preference_extraction"
else:
content = (
"\n---\n未查询到满足您需求的航班，流程结束！\n"
)
# 更新任务为空
task = None
# 返回任务节点结果事件
yield TaskNodeResultEvent(
task=task,
content=content,
)
yield event
return
# 提取座位偏好
case "seat_preference_extraction":
if user_prompt == "buy":
@ -237,7 +301,7 @@ async def run_stream_events(
task.node = "flight_search"
else:
async with seat_preference_extraction_agent.run_stream_events(
async with seat_preference_extraction_agent.run_stream_events(
user_prompt=user_prompt,
message_history=message_history,
usage=usage_to_object(dict(task.usage)),
@ -328,4 +392,25 @@ async def run_stream_events(
dialog.thoughts[index].content = f"已调用 {content}"
case _:
continue
continue
def init_work_flow() -> WorkFlow:
return WorkFlow(
type=WorkFlowType.BOOK_FLIGHT,
deps=Dependences(
source_material=source_material,
date=datetime.date(2025, 1, 10),
origin="SFO",
destination="ANC",
),
)
from application.states.models import (
WorkFlow,
WorkFlowType,
)
from application.workshop.models import (
DEEPSEEK_V4_FLASH_MODEL,
MODEL_SETTINGS_DISABLED_THINKING,
)
"""

2
agent/application/workshop/models.py
View File

@ -3,7 +3,7 @@
智能体相关模块
"""
from pydantic_ai import ModelSettings
from pydantic_ai.models.openai import OpenAIChatModel, OpenAIChatModelSettings
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider
DEEPSEEK_V4_FLASH_MODEL = OpenAIChatModel(

BIN
agent/database.db
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