mirror of
https://github.com/langbot-app/LangBot.git
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style: introduce ruff as linter and formatter (#1356)
* style: remove necessary imports * style: fix F841 * style: fix F401 * style: fix F811 * style: fix E402 * style: fix E721 * style: fix E722 * style: fix E722 * style: fix F541 * style: ruff format * style: all passed * style: add ruff in deps * style: more ignores in ruff.toml * style: add pre-commit
This commit is contained in:
Junyan Qin (Chin)
committed by
GitHub
GitHub
parent
09e70d70e9
commit
209f16af76
@@ -1,8 +1,6 @@
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from __future__ import annotations
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import typing
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import json
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import base64
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import re
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import dashscope
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@@ -10,7 +8,7 @@ import dashscope
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from .. import runner
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from ...core import app, 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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class DashscopeAPIError(Exception):
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"""Dashscope API 请求失败"""
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@@ -20,49 +18,49 @@ class DashscopeAPIError(Exception):
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super().__init__(self.message)
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@runner.runner_class("dashscope-app-api")
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@runner.runner_class('dashscope-app-api')
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class DashScopeAPIRunner(runner.RequestRunner):
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"阿里云百炼DashsscopeAPI对话请求器"
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# 运行器内部使用的配置
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app_type: str # 应用类型
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app_id: str # 应用ID
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api_key: str # API Key
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references_quote: str # 引用资料提示（当展示回答来源功能开启时，这个变量会作为引用资料名前的提示，可在provider.json中配置）
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app_type: str # 应用类型
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app_id: str # 应用ID
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api_key: str # API Key
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references_quote: str # 引用资料提示（当展示回答来源功能开启时，这个变量会作为引用资料名前的提示，可在provider.json中配置）
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def __init__(self, ap: app.Application, pipeline_config: dict):
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"""初始化"""
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self.ap = ap
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self.pipeline_config = pipeline_config
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valid_app_types = ["agent", "workflow"]
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self.app_type = self.pipeline_config["ai"]["dashscope-app-api"]["app-type"]
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#检查配置文件中使用的应用类型是否支持
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if (self.app_type not in valid_app_types):
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raise DashscopeAPIError(
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f"不支持的 Dashscope 应用类型: {self.app_type}"
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)
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#初始化Dashscope 参数配置
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self.app_id = self.pipeline_config["ai"]["dashscope-app-api"]["app-id"]
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self.api_key = self.pipeline_config["ai"]["dashscope-app-api"]["api-key"]
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self.references_quote = self.pipeline_config["ai"]["dashscope-app-api"]["references_quote"]
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valid_app_types = ['agent', 'workflow']
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self.app_type = self.pipeline_config['ai']['dashscope-app-api']['app-type']
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# 检查配置文件中使用的应用类型是否支持
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if self.app_type not in valid_app_types:
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raise DashscopeAPIError(f'不支持的 Dashscope 应用类型: {self.app_type}')
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# 初始化Dashscope 参数配置
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self.app_id = self.pipeline_config['ai']['dashscope-app-api']['app-id']
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self.api_key = self.pipeline_config['ai']['dashscope-app-api']['api-key']
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self.references_quote = self.pipeline_config['ai']['dashscope-app-api'][
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'references_quote'
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]
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def _replace_references(self, text, references_dict):
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"""阿里云百炼平台的自定义应用支持资料引用，此函数可以将引用标签替换为参考资料"""
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# 匹配 <ref>[index_id]</ref> 形式的字符串
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pattern = re.compile(r'<ref>\[(.*?)\]</ref>')
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def replacement(match):
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# 获取引用编号
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ref_key = match.group(1)
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ref_key = match.group(1)
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if ref_key in references_dict:
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# 如果有对应的参考资料按照provider.json中的reference_quote返回提示，来自哪个参考资料文件
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return f"({self.references_quote} {references_dict[ref_key]})"
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return f'({self.references_quote} {references_dict[ref_key]})'
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else:
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# 如果没有对应的参考资料，保留原样
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return match.group(0)
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return match.group(0)
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# 使用 re.sub() 进行替换
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return pattern.sub(replacement, text)
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@@ -71,14 +69,14 @@ class DashScopeAPIRunner(runner.RequestRunner):
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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，阿里云提供的上传文件方法过于复杂，暂不支持上传文件（包括图片）"""
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plain_text = ""
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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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if ce.type == 'text':
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plain_text += ce.text
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# 暂时不支持上传图片，保留代码以便后续扩展
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# elif ce.type == "image_base64":
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# elif ce.type == "image_base64":
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# image_b64, image_format = await image.extract_b64_and_format(ce.image_base64)
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# file_bytes = base64.b64decode(image_b64)
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# file = ("img.png", file_bytes, f"image/{image_format}")
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@@ -92,147 +90,141 @@ class DashScopeAPIRunner(runner.RequestRunner):
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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 _agent_messages(
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self, query: core_entities.Query
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) -> typing.AsyncGenerator[llm_entities.Message, None]:
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"""Dashscope 智能体对话请求"""
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#局部变量
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chunk = None # 流式传输的块
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pending_content = "" # 待处理的Agent输出内容
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references_dict = {} # 用于存储引用编号和对应的参考资料
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plain_text = "" # 用户输入的纯文本信息
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image_ids = [] # 用户输入的图片ID列表 （暂不支持）
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# 局部变量
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chunk = None # 流式传输的块
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pending_content = '' # 待处理的Agent输出内容
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references_dict = {} # 用于存储引用编号和对应的参考资料
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plain_text = '' # 用户输入的纯文本信息
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image_ids = [] # 用户输入的图片ID列表 （暂不支持）
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plain_text, image_ids = await self._preprocess_user_message(query)
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#发送对话请求
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# 发送对话请求
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response = dashscope.Application.call(
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api_key=self.api_key, # 智能体应用的API Key
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app_id=self.app_id, # 智能体应用的ID
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prompt=plain_text, # 用户输入的文本信息
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stream=True, # 流式输出
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incremental_output=True, # 增量输出，使用流式输出需要开启增量输出
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session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话
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api_key=self.api_key, # 智能体应用的API Key
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app_id=self.app_id, # 智能体应用的ID
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prompt=plain_text, # 用户输入的文本信息
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stream=True, # 流式输出
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incremental_output=True, # 增量输出，使用流式输出需要开启增量输出
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session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话
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# rag_options={ # 主要用于文件交互，暂不支持
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# "session_file_ids": ["FILE_ID1"], # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个
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# }
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)
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for chunk in response:
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if chunk.get("status_code") != 200:
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if chunk.get('status_code') != 200:
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raise DashscopeAPIError(
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f"Dashscope API 请求失败: status_code={chunk.get('status_code')} message={chunk.get('message')} request_id={chunk.get('request_id')} "
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f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} '
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)
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if not chunk:
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continue
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#获取流式传输的output
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stream_output = chunk.get("output", {})
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if stream_output.get("text") is not None:
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pending_content += stream_output.get("text")
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#保存当前会话的session_id用于下次对话的语境
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query.session.using_conversation.uuid = stream_output.get("session_id")
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#获取模型传出的参考资料列表
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references_dict_list = stream_output.get("doc_references", [])
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#从模型传出的参考资料信息中提取用于替换的字典
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# 获取流式传输的output
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stream_output = chunk.get('output', {})
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if stream_output.get('text') is not None:
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pending_content += stream_output.get('text')
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# 保存当前会话的session_id用于下次对话的语境
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query.session.using_conversation.uuid = stream_output.get('session_id')
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# 获取模型传出的参考资料列表
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references_dict_list = stream_output.get('doc_references', [])
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# 从模型传出的参考资料信息中提取用于替换的字典
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if references_dict_list is not None:
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for doc in references_dict_list:
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if doc.get("index_id") is not None:
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references_dict[doc.get("index_id")] = doc.get("doc_name")
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#将参考资料替换到文本中
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if doc.get('index_id') is not None:
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references_dict[doc.get('index_id')] = doc.get('doc_name')
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# 将参考资料替换到文本中
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pending_content = self._replace_references(pending_content, references_dict)
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yield llm_entities.Message(
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role="assistant",
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role='assistant',
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content=pending_content,
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)
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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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"""Dashscope 工作流对话请求"""
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#局部变量
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chunk = None # 流式传输的块
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pending_content = "" # 待处理的Agent输出内容
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references_dict = {} # 用于存储引用编号和对应的参考资料
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plain_text = "" # 用户输入的纯文本信息
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image_ids = [] # 用户输入的图片ID列表 （暂不支持）
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# 局部变量
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chunk = None # 流式传输的块
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pending_content = '' # 待处理的Agent输出内容
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references_dict = {} # 用于存储引用编号和对应的参考资料
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plain_text = '' # 用户输入的纯文本信息
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image_ids = [] # 用户输入的图片ID列表 （暂不支持）
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plain_text, image_ids = await self._preprocess_user_message(query)
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biz_params = {}
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biz_params.update(query.variables)
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#发送对话请求
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# 发送对话请求
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response = dashscope.Application.call(
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api_key=self.api_key, # 智能体应用的API Key
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app_id=self.app_id, # 智能体应用的ID
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prompt=plain_text, # 用户输入的文本信息
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stream=True, # 流式输出
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incremental_output=True, # 增量输出，使用流式输出需要开启增量输出
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session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话
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biz_params=biz_params, # 工作流应用的自定义输入参数传递
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api_key=self.api_key, # 智能体应用的API Key
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app_id=self.app_id, # 智能体应用的ID
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prompt=plain_text, # 用户输入的文本信息
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stream=True, # 流式输出
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incremental_output=True, # 增量输出，使用流式输出需要开启增量输出
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session_id=query.session.using_conversation.uuid, # 会话ID用于，多轮对话
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biz_params=biz_params, # 工作流应用的自定义输入参数传递
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# rag_options={ # 主要用于文件交互，暂不支持
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# "session_file_ids": ["FILE_ID1"], # FILE_ID1 替换为实际的临时文件ID,逗号隔开多个
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# }
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)
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#处理API返回的流式输出
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# 处理API返回的流式输出
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for chunk in response:
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if chunk.get("status_code") != 200:
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if chunk.get('status_code') != 200:
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raise DashscopeAPIError(
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f"Dashscope API 请求失败: status_code={chunk.get('status_code')} message={chunk.get('message')} request_id={chunk.get('request_id')} "
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f'Dashscope API 请求失败: status_code={chunk.get("status_code")} message={chunk.get("message")} request_id={chunk.get("request_id")} '
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)
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if not chunk:
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continue
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#获取流式传输的output
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stream_output = chunk.get("output", {})
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if stream_output.get("text") is not None:
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pending_content += stream_output.get("text")
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#保存当前会话的session_id用于下次对话的语境
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query.session.using_conversation.uuid = stream_output.get("session_id")
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#获取模型传出的参考资料列表
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references_dict_list = stream_output.get("doc_references", [])
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#从模型传出的参考资料信息中提取用于替换的字典
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# 获取流式传输的output
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stream_output = chunk.get('output', {})
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if stream_output.get('text') is not None:
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pending_content += stream_output.get('text')
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# 保存当前会话的session_id用于下次对话的语境
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query.session.using_conversation.uuid = stream_output.get('session_id')
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# 获取模型传出的参考资料列表
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references_dict_list = stream_output.get('doc_references', [])
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# 从模型传出的参考资料信息中提取用于替换的字典
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if references_dict_list is not None:
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for doc in references_dict_list:
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if doc.get("index_id") is not None:
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references_dict[doc.get("index_id")] = doc.get("doc_name")
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#将参考资料替换到文本中
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if doc.get('index_id') is not None:
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references_dict[doc.get('index_id')] = doc.get('doc_name')
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# 将参考资料替换到文本中
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pending_content = self._replace_references(pending_content, references_dict)
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yield llm_entities.Message(
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role="assistant",
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role='assistant',
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content=pending_content,
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)
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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"""
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if self.app_type == "agent":
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if self.app_type == 'agent':
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async for msg in self._agent_messages(query):
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yield msg
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elif self.app_type == "workflow":
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elif self.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 DashscopeAPIError(
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f"不支持的 Dashscope 应用类型: {self.app_type}"
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)
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raise DashscopeAPIError(f'不支持的 Dashscope 应用类型: {self.app_type}')
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