mirror of
https://github.com/langbot-app/LangBot.git
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279 lines
10 KiB
Python
279 lines
10 KiB
Python
from __future__ import annotations
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import typing
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import json
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import uuid
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from .. import runner
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from ...core import entities as core_entities
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from .. import entities as llm_entities
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from ...utils import image
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from libs.dify_service_api.v1 import client, errors
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@runner.runner_class("dify-service-api")
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class DifyServiceAPIRunner(runner.RequestRunner):
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"""Dify Service API 对话请求器"""
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dify_client: client.AsyncDifyServiceClient
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async def initialize(self):
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"""初始化"""
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valid_app_types = ["chat", "agent", "workflow"]
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if (
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self.ap.provider_cfg.data["dify-service-api"]["app-type"]
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not in valid_app_types
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):
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raise errors.DifyAPIError(
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f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}"
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)
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api_key = self.ap.provider_cfg.data["dify-service-api"][
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self.ap.provider_cfg.data["dify-service-api"]["app-type"]
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]["api-key"]
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self.dify_client = client.AsyncDifyServiceClient(
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api_key=api_key,
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base_url=self.ap.provider_cfg.data["dify-service-api"]["base-url"],
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)
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async def _preprocess_user_message(
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self, query: core_entities.Query
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) -> tuple[str, list[str]]:
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"""预处理用户消息，提取纯文本，并将图片上传到 Dify 服务
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Returns:
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tuple[str, list[str]]: 纯文本和图片的 Dify 服务图片 ID
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"""
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plain_text = ""
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image_ids = []
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if isinstance(query.user_message.content, list):
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for ce in query.user_message.content:
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if ce.type == "text":
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plain_text += ce.text
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elif ce.type == "image_url":
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file_bytes, image_format = await image.get_qq_image_bytes(
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ce.image_url.url
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)
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file = ("img.png", file_bytes, f"image/{image_format}")
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file_upload_resp = await self.dify_client.upload_file(
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file,
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f"{query.session.launcher_type.value}_{query.session.launcher_id}",
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)
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image_id = file_upload_resp["id"]
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image_ids.append(image_id)
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elif isinstance(query.user_message.content, str):
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plain_text = query.user_message.content
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return plain_text, image_ids
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async def _chat_messages(
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self, query: core_entities.Query
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) -> typing.AsyncGenerator[llm_entities.Message, None]:
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"""调用聊天助手"""
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cov_id = query.session.using_conversation.uuid or ""
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plain_text, image_ids = await self._preprocess_user_message(query)
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files = [
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{
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"type": "image",
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"transfer_method": "local_file",
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"upload_file_id": image_id,
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}
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for image_id in image_ids
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]
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mode = "basic" # 标记是基础编排还是工作流编排
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basic_mode_pending_chunk = ''
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async for chunk in self.dify_client.chat_messages(
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inputs={},
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query=plain_text,
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user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
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conversation_id=cov_id,
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files=files,
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timeout=self.ap.provider_cfg.data["dify-service-api"]["chat"]["timeout"],
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):
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self.ap.logger.debug("dify-chat-chunk: ", chunk)
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if chunk['event'] == 'workflow_started':
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mode = "workflow"
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if mode == "workflow":
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if chunk['event'] == 'node_finished':
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if chunk['data']['node_type'] == 'answer':
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yield llm_entities.Message(
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role="assistant",
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content=chunk['data']['outputs']['answer'],
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)
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elif mode == "basic":
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if chunk['event'] == 'message':
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basic_mode_pending_chunk += chunk['answer']
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elif chunk['event'] == 'message_end':
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yield llm_entities.Message(
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role="assistant",
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content=basic_mode_pending_chunk,
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)
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basic_mode_pending_chunk = ''
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query.session.using_conversation.uuid = chunk["conversation_id"]
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async def _agent_chat_messages(
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self, query: core_entities.Query
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) -> typing.AsyncGenerator[llm_entities.Message, None]:
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"""调用聊天助手"""
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cov_id = query.session.using_conversation.uuid or ""
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plain_text, image_ids = await self._preprocess_user_message(query)
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files = [
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{
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"type": "image",
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"transfer_method": "local_file",
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"upload_file_id": image_id,
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}
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for image_id in image_ids
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]
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ignored_events = ["agent_message"]
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async for chunk in self.dify_client.chat_messages(
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inputs={},
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query=plain_text,
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user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
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response_mode="streaming",
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conversation_id=cov_id,
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files=files,
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timeout=self.ap.provider_cfg.data["dify-service-api"]["chat"]["timeout"],
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):
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self.ap.logger.debug("dify-agent-chunk: ", chunk)
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if chunk["event"] in ignored_events:
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continue
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if chunk["event"] == "agent_thought":
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if chunk['tool'] != '' and chunk['observation'] != '': # 工具调用结果，跳过
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continue
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if chunk['thought'].strip() != '': # 文字回复内容
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msg = llm_entities.Message(
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role="assistant",
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content=chunk["thought"],
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)
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yield msg
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if chunk['tool']:
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msg = llm_entities.Message(
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role="assistant",
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tool_calls=[
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llm_entities.ToolCall(
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id=chunk['id'],
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type="function",
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function=llm_entities.FunctionCall(
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name=chunk["tool"],
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arguments=json.dumps({}),
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),
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)
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],
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)
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yield msg
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query.session.using_conversation.uuid = chunk["conversation_id"]
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async def _workflow_messages(
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self, query: core_entities.Query
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) -> typing.AsyncGenerator[llm_entities.Message, None]:
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"""调用工作流"""
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if not query.session.using_conversation.uuid:
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query.session.using_conversation.uuid = str(uuid.uuid4())
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cov_id = query.session.using_conversation.uuid
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plain_text, image_ids = await self._preprocess_user_message(query)
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files = [
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{
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"type": "image",
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"transfer_method": "local_file",
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"upload_file_id": image_id,
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}
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for image_id in image_ids
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]
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ignored_events = ["text_chunk", "workflow_started"]
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async for chunk in self.dify_client.workflow_run(
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inputs={
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"langbot_user_message_text": plain_text,
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"langbot_session_id": f"{query.session.launcher_type.value}_{query.session.launcher_id}",
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"langbot_conversation_id": cov_id,
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},
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user=f"{query.session.launcher_type.value}_{query.session.launcher_id}",
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files=files,
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timeout=self.ap.provider_cfg.data["dify-service-api"]["workflow"]["timeout"],
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):
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self.ap.logger.debug("dify-workflow-chunk: ", chunk)
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if chunk["event"] in ignored_events:
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continue
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if chunk["event"] == "node_started":
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if (
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chunk["data"]["node_type"] == "start"
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or chunk["data"]["node_type"] == "end"
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):
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continue
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msg = llm_entities.Message(
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role="assistant",
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content=None,
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tool_calls=[
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llm_entities.ToolCall(
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id=chunk["data"]["node_id"],
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type="function",
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function=llm_entities.FunctionCall(
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name=chunk["data"]["title"],
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arguments=json.dumps({}),
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),
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)
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],
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)
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yield msg
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elif chunk["event"] == "workflow_finished":
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if chunk['data']['error']:
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raise errors.DifyAPIError(chunk['data']['error'])
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msg = llm_entities.Message(
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role="assistant",
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content=chunk["data"]["outputs"][
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self.ap.provider_cfg.data["dify-service-api"]["workflow"][
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"output-key"
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]
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],
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)
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yield msg
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async def run(
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self, query: core_entities.Query
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) -> typing.AsyncGenerator[llm_entities.Message, None]:
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"""运行请求"""
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if self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "chat":
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async for msg in self._chat_messages(query):
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yield msg
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elif self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "agent":
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async for msg in self._agent_chat_messages(query):
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yield msg
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elif self.ap.provider_cfg.data["dify-service-api"]["app-type"] == "workflow":
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async for msg in self._workflow_messages(query):
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yield msg
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else:
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raise errors.DifyAPIError(
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f"不支持的 Dify 应用类型: {self.ap.provider_cfg.data['dify-service-api']['app-type']}"
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)
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