mirror of
https://github.com/langbot-app/LangBot.git
synced 2026-06-02 03:55:55 +00:00
feat: pipeline invoking
This commit is contained in:
Junyan Qin
@@ -57,6 +57,12 @@ class Query(pydantic.BaseModel):
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message_chain: platform_message.MessageChain
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"""消息链，platform收到的原始消息链"""
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pipeline_uuid: typing.Optional[str] = None
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"""流水线UUID。"""
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pipeline_config: typing.Optional[dict[str, typing.Any]] = None
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"""流水线配置，由 Pipeline 在运行开始时设置。"""
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adapter: msadapter.MessagePlatformAdapter
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"""消息平台适配器对象，单个app中可能启用了多个消息平台适配器，此对象表明发起此query的适配器"""
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@@ -50,14 +50,19 @@ class Controller:
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continue
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if selected_query:
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async def _process_query(selected_query):
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async def _process_query(selected_query: entities.Query):
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async with self.semaphore: # 总并发上限
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await self.process_query(selected_query)
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# find pipeline
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pipeline = await self.ap.pipeline_mgr.get_pipeline_by_uuid(selected_query.pipeline_uuid)
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if pipeline:
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await pipeline.run(selected_query)
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async with self.ap.query_pool:
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(await self.ap.sess_mgr.get_session(selected_query)).semaphore.release()
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# 通知其他协程，有新的请求可以处理了
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self.ap.query_pool.condition.notify_all()
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self.ap.task_mgr.create_task(
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_process_query(selected_query),
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kind="query",
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@@ -70,127 +75,6 @@ class Controller:
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self.ap.logger.error(f"控制器循环出错: {e}")
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self.ap.logger.error(f"Traceback: {traceback.format_exc()}")
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async def _check_output(self, query: entities.Query, result: pipeline_entities.StageProcessResult):
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"""检查输出
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"""
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if result.user_notice:
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# 处理str类型
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if isinstance(result.user_notice, str):
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result.user_notice = platform_message.MessageChain(
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platform_message.Plain(result.user_notice)
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)
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elif isinstance(result.user_notice, list):
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result.user_notice = platform_message.MessageChain(
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*result.user_notice
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)
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await self.ap.platform_mgr.send(
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query.message_event,
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result.user_notice,
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query.adapter
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)
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if result.debug_notice:
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self.ap.logger.debug(result.debug_notice)
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if result.console_notice:
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self.ap.logger.info(result.console_notice)
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if result.error_notice:
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self.ap.logger.error(result.error_notice)
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async def _execute_from_stage(
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self,
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stage_index: int,
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query: entities.Query,
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):
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"""从指定阶段开始执行，实现了责任链模式和基于生成器的阶段分叉功能。
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如何看懂这里为什么这么写？
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去问 GPT-4:
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Q1: 现在有一个责任链，其中有多个stage，query对象在其中传递，stage.process可能返回Result也有可能返回typing.AsyncGenerator[Result, None]，
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如果返回的是生成器，需要挨个生成result，检查是否result中是否要求继续，如果要求继续就进行下一个stage。如果此次生成器产生的result处理完了，就继续生成下一个result，
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调用后续的stage，直到该生成器全部生成完。责任链中可能有多个stage会返回生成器
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Q2: 不是这样的，你可能理解有误。如果我们责任链上有这些Stage：
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A B C D E F G
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如果所有的stage都返回Result，且所有Result都要求继续，那么执行顺序是：
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A B C D E F G
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现在假设C返回的是AsyncGenerator，那么执行顺序是：
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A B C D E F G C D E F G C D E F G ...
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Q3: 但是如果不止一个stage会返回生成器呢？
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"""
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i = stage_index
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while i < len(self.ap.stage_mgr.stage_containers):
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stage_container = self.ap.stage_mgr.stage_containers[i]
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query.current_stage = stage_container # 标记到 Query 对象里
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result = stage_container.inst.process(query, stage_container.inst_name)
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if isinstance(result, typing.Coroutine):
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result = await result
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if isinstance(result, pipeline_entities.StageProcessResult): # 直接返回结果
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} res {result}")
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await self._check_output(query, result)
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if result.result_type == pipeline_entities.ResultType.INTERRUPT:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} interrupted query {query}")
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break
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elif result.result_type == pipeline_entities.ResultType.CONTINUE:
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query = result.new_query
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elif isinstance(result, typing.AsyncGenerator): # 生成器
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} gen")
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async for sub_result in result:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} res {sub_result}")
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await self._check_output(query, sub_result)
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if sub_result.result_type == pipeline_entities.ResultType.INTERRUPT:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} interrupted query {query}")
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break
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elif sub_result.result_type == pipeline_entities.ResultType.CONTINUE:
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query = sub_result.new_query
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await self._execute_from_stage(i + 1, query)
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break
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i += 1
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async def process_query(self, query: entities.Query):
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"""处理请求
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"""
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try:
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# ======== 触发 MessageReceived 事件 ========
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event_type = events.PersonMessageReceived if query.launcher_type == entities.LauncherTypes.PERSON else events.GroupMessageReceived
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event_ctx = await self.ap.plugin_mgr.emit_event(
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event=event_type(
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launcher_type=query.launcher_type.value,
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launcher_id=query.launcher_id,
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sender_id=query.sender_id,
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message_chain=query.message_chain,
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query=query
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)
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)
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if event_ctx.is_prevented_default():
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return
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self.ap.logger.debug(f"Processing query {query}")
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await self._execute_from_stage(0, query)
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except Exception as e:
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inst_name = query.current_stage.inst_name if query.current_stage else 'unknown'
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self.ap.logger.error(f"处理请求时出错 query_id={query.query_id} stage={inst_name} : {e}")
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self.ap.logger.debug(f"Traceback: {traceback.format_exc()}")
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finally:
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self.ap.logger.debug(f"Query {query} processed")
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async def run(self):
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"""运行控制器
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"""
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@@ -1,13 +1,16 @@
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from __future__ import annotations
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import typing
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import traceback
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import sqlalchemy
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from ..core import app, entities
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from . import entities as pipeline_entities
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from ..entity.persistence import pipeline as persistence_pipeline
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from . import stagemgr, stage
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from ..platform.types import message as platform_message, events as platform_events
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from ..plugin import events
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class RuntimePipeline:
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"""运行时流水线"""
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@@ -25,8 +28,130 @@ class RuntimePipeline:
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self.pipeline_entity = pipeline_entity
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self.stage_containers = stage_containers
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async def run(self):
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pass
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async def run(self, query: entities.Query):
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query.pipeline_config = self.pipeline_entity.config
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await self.process_query(query)
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async def _check_output(self, query: entities.Query, result: pipeline_entities.StageProcessResult):
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"""检查输出
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"""
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if result.user_notice:
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# 处理str类型
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if isinstance(result.user_notice, str):
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result.user_notice = platform_message.MessageChain(
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platform_message.Plain(result.user_notice)
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)
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elif isinstance(result.user_notice, list):
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result.user_notice = platform_message.MessageChain(
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*result.user_notice
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)
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await self.ap.platform_mgr.send(
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query.message_event,
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result.user_notice,
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query.adapter
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)
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if result.debug_notice:
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self.ap.logger.debug(result.debug_notice)
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if result.console_notice:
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self.ap.logger.info(result.console_notice)
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if result.error_notice:
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self.ap.logger.error(result.error_notice)
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async def _execute_from_stage(
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self,
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stage_index: int,
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query: entities.Query,
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):
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"""从指定阶段开始执行，实现了责任链模式和基于生成器的阶段分叉功能。
|
||||
|
||||
如何看懂这里为什么这么写？
|
||||
去问 GPT-4:
|
||||
Q1: 现在有一个责任链，其中有多个stage，query对象在其中传递，stage.process可能返回Result也有可能返回typing.AsyncGenerator[Result, None]，
|
||||
如果返回的是生成器，需要挨个生成result，检查是否result中是否要求继续，如果要求继续就进行下一个stage。如果此次生成器产生的result处理完了，就继续生成下一个result，
|
||||
调用后续的stage，直到该生成器全部生成完。责任链中可能有多个stage会返回生成器
|
||||
Q2: 不是这样的，你可能理解有误。如果我们责任链上有这些Stage：
|
||||
|
||||
A B C D E F G
|
||||
|
||||
如果所有的stage都返回Result，且所有Result都要求继续，那么执行顺序是：
|
||||
|
||||
A B C D E F G
|
||||
|
||||
现在假设C返回的是AsyncGenerator，那么执行顺序是：
|
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|
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A B C D E F G C D E F G C D E F G ...
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Q3: 但是如果不止一个stage会返回生成器呢？
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"""
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i = stage_index
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while i < len(self.stage_containers):
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stage_container = self.stage_containers[i]
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query.current_stage = stage_container # 标记到 Query 对象里
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result = stage_container.inst.process(query, stage_container.inst_name)
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if isinstance(result, typing.Coroutine):
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result = await result
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if isinstance(result, pipeline_entities.StageProcessResult): # 直接返回结果
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} res {result}")
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await self._check_output(query, result)
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if result.result_type == pipeline_entities.ResultType.INTERRUPT:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} interrupted query {query}")
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break
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elif result.result_type == pipeline_entities.ResultType.CONTINUE:
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query = result.new_query
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elif isinstance(result, typing.AsyncGenerator): # 生成器
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} gen")
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async for sub_result in result:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} processed query {query} res {sub_result}")
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await self._check_output(query, sub_result)
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if sub_result.result_type == pipeline_entities.ResultType.INTERRUPT:
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self.ap.logger.debug(f"Stage {stage_container.inst_name} interrupted query {query}")
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break
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elif sub_result.result_type == pipeline_entities.ResultType.CONTINUE:
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query = sub_result.new_query
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await self._execute_from_stage(i + 1, query)
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break
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i += 1
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async def process_query(self, query: entities.Query):
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"""处理请求
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"""
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try:
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# ======== 触发 MessageReceived 事件 ========
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event_type = events.PersonMessageReceived if query.launcher_type == entities.LauncherTypes.PERSON else events.GroupMessageReceived
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event_ctx = await self.ap.plugin_mgr.emit_event(
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event=event_type(
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launcher_type=query.launcher_type.value,
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launcher_id=query.launcher_id,
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sender_id=query.sender_id,
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message_chain=query.message_chain,
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query=query
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)
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)
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if event_ctx.is_prevented_default():
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return
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self.ap.logger.debug(f"Processing query {query}")
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await self._execute_from_stage(0, query)
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except Exception as e:
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inst_name = query.current_stage.inst_name if query.current_stage else 'unknown'
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self.ap.logger.error(f"处理请求时出错 query_id={query.query_id} stage={inst_name} : {e}")
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self.ap.logger.debug(f"Traceback: {traceback.format_exc()}")
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finally:
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self.ap.logger.debug(f"Query {query} processed")
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class PipelineManager:
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@@ -33,7 +33,8 @@ class QueryPool:
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sender_id: typing.Union[int, str],
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message_event: platform_events.MessageEvent,
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message_chain: platform_message.MessageChain,
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adapter: msadapter.MessagePlatformAdapter
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adapter: msadapter.MessagePlatformAdapter,
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pipeline_uuid: str
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) -> entities.Query:
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async with self.condition:
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query = entities.Query(
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@@ -43,6 +44,7 @@ class QueryPool:
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sender_id=sender_id,
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message_event=message_event,
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message_chain=message_chain,
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pipeline_uuid=pipeline_uuid,
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resp_messages=[],
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resp_message_chain=[],
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adapter=adapter
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@@ -50,6 +50,41 @@ class RuntimeBot:
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self.adapter = adapter
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self.task_context = taskmgr.TaskContext()
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async def initialize(self):
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async def on_friend_message(event: platform_events.FriendMessage, adapter: msadapter.MessagePlatformAdapter):
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await self.ap.query_pool.add_query(
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launcher_type=core_entities.LauncherTypes.PERSON,
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launcher_id=event.sender.id,
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sender_id=event.sender.id,
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message_event=event,
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message_chain=event.message_chain,
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adapter=adapter,
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pipeline_uuid=self.bot_entity.use_pipeline_uuid
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)
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async def on_group_message(event: platform_events.GroupMessage, adapter: msadapter.MessagePlatformAdapter):
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await self.ap.query_pool.add_query(
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launcher_type=core_entities.LauncherTypes.GROUP,
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launcher_id=event.group.id,
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sender_id=event.sender.id,
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message_event=event,
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message_chain=event.message_chain,
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adapter=adapter,
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pipeline_uuid=self.bot_entity.use_pipeline_uuid
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)
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self.adapter.register_listener(
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platform_events.FriendMessage,
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on_friend_message
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)
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self.adapter.register_listener(
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platform_events.GroupMessage,
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on_group_message
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)
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async def run(self):
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async def exception_wrapper():
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@@ -135,49 +170,20 @@ class PlatformManager:
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bot_entity = persistence_bot.Bot(**bot_entity._mapping)
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elif isinstance(bot_entity, dict):
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bot_entity = persistence_bot.Bot(**bot_entity)
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async def on_friend_message(event: platform_events.FriendMessage, adapter: msadapter.MessagePlatformAdapter):
|
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|
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await self.ap.query_pool.add_query(
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launcher_type=core_entities.LauncherTypes.PERSON,
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launcher_id=event.sender.id,
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sender_id=event.sender.id,
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message_event=event,
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message_chain=event.message_chain,
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adapter=adapter
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)
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async def on_group_message(event: platform_events.GroupMessage, adapter: msadapter.MessagePlatformAdapter):
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await self.ap.query_pool.add_query(
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launcher_type=core_entities.LauncherTypes.GROUP,
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launcher_id=event.group.id,
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sender_id=event.sender.id,
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message_event=event,
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message_chain=event.message_chain,
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adapter=adapter
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)
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adapter_inst = self.adapter_dict[bot_entity.adapter](
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bot_entity.adapter_config,
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self.ap
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)
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adapter_inst.register_listener(
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platform_events.FriendMessage,
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on_friend_message
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)
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adapter_inst.register_listener(
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platform_events.GroupMessage,
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on_group_message
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||||
)
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runtime_bot = RuntimeBot(
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ap=self.ap,
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bot_entity=bot_entity,
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adapter=adapter_inst
|
||||
)
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await runtime_bot.initialize()
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self.bots.append(runtime_bot)
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return runtime_bot
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@@ -42,7 +42,7 @@ stages:
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||||
zh_CN: 模型
|
||||
type: select
|
||||
required: true
|
||||
scope: llm-model
|
||||
scope: /provider/models/llm
|
||||
- name: max-round
|
||||
label:
|
||||
en_US: Max Round
|
||||
@@ -54,11 +54,9 @@ stages:
|
||||
label:
|
||||
en_US: Prompt
|
||||
zh_CN: 提示词
|
||||
type: array
|
||||
type: string
|
||||
required: true
|
||||
default: []
|
||||
items:
|
||||
type: string
|
||||
default: "You are a helpful assistant."
|
||||
- name: dify-service-api
|
||||
label:
|
||||
en_US: Dify Service API
|
||||
|
||||
@@ -46,7 +46,7 @@ stages:
|
||||
zh_CN: 窗口长度（秒）
|
||||
type: integer
|
||||
required: true
|
||||
default: 10
|
||||
default: 60
|
||||
- name: limitation
|
||||
label:
|
||||
en_US: Limitation
|
||||
|
||||
Reference in New Issue
Block a user