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https://github.com/langbot-app/LangBot.git
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阿里云百炼平台应用API支持
This commit is contained in:
Civic_Crab
@@ -6,7 +6,7 @@ from . import entities, requester
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from ...core import app
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from . import token
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from .requesters import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl, xaichatcmpl, zhipuaichatcmpl, lmstudiochatcmpl, siliconflowchatcmpl, dashscopecmpl, qwenchatcmpl
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from .requesters import chatcmpl, anthropicmsgs, moonshotchatcmpl, deepseekchatcmpl, ollamachat, giteeaichatcmpl, xaichatcmpl, zhipuaichatcmpl, lmstudiochatcmpl, siliconflowchatcmpl
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FETCH_MODEL_LIST_URL = "https://api.qchatgpt.rockchin.top/api/v2/fetch/model_list"
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@@ -1,167 +0,0 @@
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from __future__ import annotations
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import re
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import asyncio
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import typing
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import dashscope
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from .. import entities, errors, requester
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from ....core import entities as core_entities, app
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from ... import entities as llm_entities
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from ...tools import entities as tools_entities
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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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def replace_references(text, references_dict):
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# 修正正则表达式，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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ref_key = match.group(1) # 获取引用编号
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if ref_key in references_dict:
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return f"（参考资料来自：{references_dict[ref_key]}）"
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else:
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return match.group(0) # 如果没有对应的参考资料，保留原样
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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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@requester.requester_class("dashscope-chat-applications")
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class DashscopeChatApplication(requester.LLMAPIRequester):
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"""Dashscope ChatApplications API 请求器"""
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requester_cfg: dict
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def __init__(self, ap: app.Application):
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self.requester_cfg = ap.provider_cfg.data['requester']['dashscope-chat-applications']
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self.ap = ap
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async def initialize(self):
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dashscope.api_key = self.ap.provider_cfg.data['keys']['dashscope'][0]
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async def _req(self, args: dict):
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#print("args:", args)
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#局部变量
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chunk = None
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pending_content = ""
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output = {
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"role": "assistant",
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"content": "",
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"tool_calls": [],
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"tool_call_id": None # Dashscope暂时不支持工具调用
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} #由于Dashscope的content的键值是text，所以需要定义一个新格式的字典适配llm_entities.Message
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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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#调用API
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response = dashscope.Application.call(
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api_key=dashscope.api_key,
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app_id=args["model"],
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prompt=args["messages"],
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stream=True, # 设置流式输出
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tools=args.get("tools", None),
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incremental_output = True,
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)
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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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#print(chunk)
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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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#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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pending_content = replace_references(pending_content, references_dict)
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#将流式传输的内容整合到output中
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output["content"] = pending_content
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return output if chunk else None
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async def _make_msg(
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self,
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chat_completion: dict,
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) -> llm_entities.Message:
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chatcmpl_message = chat_completion
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# 确保 role 字段存在且不为 None
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if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
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chatcmpl_message['role'] = 'assistant'
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message = llm_entities.Message(**chatcmpl_message)
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#print("message:", message)
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return message
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async def _closure(
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self,
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query: core_entities.Query,
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req_messages: list[dict],
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use_model: entities.LLMModelInfo,
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use_funcs: list[tools_entities.LLMFunction] = None,
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) -> llm_entities.Message:
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args = self.requester_cfg['args'].copy()
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args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
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# 设置此次请求中的messages
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messages = req_messages.copy()
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# 检查vision
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for msg in messages:
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if 'content' in msg and isinstance(msg["content"], list):
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for me in msg["content"]:
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if me["type"] == "image_base64":
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me["image_url"] = {
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"url": me["image_base64"]
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}
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me["type"] = "image_url"
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del me["image_base64"]
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args["messages"] = messages
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# 发送请求
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resp = await self._req(args)
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# 处理请求结果
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message = await self._make_msg(resp)
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return message
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async def call(
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self,
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query: core_entities.Query,
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model: entities.LLMModelInfo,
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messages: typing.List[llm_entities.Message],
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funcs: typing.List[tools_entities.LLMFunction] = None,
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) -> llm_entities.Message:
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req_messages = [] # req_messages 仅用于类内，外部同步由 query.messages 进行
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for m in messages:
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msg_dict = m.dict(exclude_none=True)
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content = msg_dict.get("content")
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if isinstance(content, list):
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# 检查 content 列表中是否每个部分都是文本
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if all(isinstance(part, dict) and part.get("type") == "text" for part in content):
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# 将所有文本部分合并为一个字符串
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msg_dict["content"] = "\n".join(part["text"] for part in content)
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req_messages.append(msg_dict)
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try:
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return await self._closure(query=query, req_messages=req_messages, use_model=model, use_funcs=funcs)
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except asyncio.TimeoutError:
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raise errors.RequesterError('请求超时')
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@@ -5,6 +5,7 @@ from ..core import app
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from .runners import localagent
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from .runners import difysvapi
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from .runners import dashscopeapi
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class RunnerManager:
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236
pkg/provider/runners/dashscopeapi.py
Normal file
236
pkg/provider/runners/dashscopeapi.py
Normal file
@@ -0,0 +1,236 @@
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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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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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class DashscopeAPIError(Exception):
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"""Dashscope API 请求失败"""
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def __init__(self, message: str):
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self.message = message
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super().__init__(self.message)
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@runner.runner_class("dashscope-service-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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biz_params: dict = {} # 工作流应用参数（仅在工作流应用中生效）
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async def initialize(self):
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"""初始化"""
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valid_app_types = ["agent", "workflow"]
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self.app_type = self.ap.provider_cfg.data["dashscope-service-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.ap.provider_cfg.data["dashscope-service-api"][self.app_type]["app-id"]
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self.api_key = self.ap.provider_cfg.data["dashscope-service-api"][self.app_type]["api-key"]
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self.references_quote = self.ap.provider_cfg.data["dashscope-service-api"][self.app_type]["references_quote"]
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self.biz_params = self.ap.provider_cfg.data["dashscope-service-api"]["workflow"]["biz_params"]
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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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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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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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# 使用 re.sub() 进行替换
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return pattern.sub(replacement, text)
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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，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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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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# 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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# 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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# 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 _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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plain_text, image_ids = await self._preprocess_user_message(query)
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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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# 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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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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)
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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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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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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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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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plain_text, image_ids = await self._preprocess_user_message(query)
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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=self.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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for chunk in response:
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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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)
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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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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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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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content=pending_content,
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||||
)
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||||
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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]:
|
||||
"""运行"""
|
||||
if self.ap.provider_cfg.data["dashscope-service-api"]["app-type"] == "agent":
|
||||
async for msg in self._agent_messages(query):
|
||||
yield msg
|
||||
elif self.ap.provider_cfg.data["dashscope-service-api"]["app-type"] == "workflow":
|
||||
async for msg in self._workflow_messages(query):
|
||||
yield msg
|
||||
else:
|
||||
raise DashscopeAPIError(
|
||||
f"不支持的 Dashscope 应用类型: {self.ap.provider_cfg.data['dashscope-service-api']['app-type']}"
|
||||
)
|
||||
|
||||
|
||||
@@ -25,12 +25,6 @@
|
||||
],
|
||||
"siliconflow": [
|
||||
"xxxxxxx"
|
||||
],
|
||||
"dashscope": [
|
||||
"sk-1234567890"
|
||||
],
|
||||
"qwen": [
|
||||
"sk-1234567890",
|
||||
]
|
||||
},
|
||||
"requester": {
|
||||
@@ -46,16 +40,6 @@
|
||||
},
|
||||
"timeout": 120
|
||||
},
|
||||
"dashscope-chat-applications": {
|
||||
"args": {},
|
||||
"base-url": "https://dashscope.aliyuncs.com/api/v1",
|
||||
"timeout": 120
|
||||
},
|
||||
"qwen-chat-completions": {
|
||||
"base-url": "https://dashscope.aliyuncs.com/compatible-mode/v1",
|
||||
"args": {},
|
||||
"timeout": 120
|
||||
},
|
||||
"moonshot-chat-completions": {
|
||||
"base-url": "https://api.moonshot.cn/v1",
|
||||
"args": {},
|
||||
@@ -119,5 +103,22 @@
|
||||
"output-key": "summary",
|
||||
"timeout": 120
|
||||
}
|
||||
},
|
||||
"dashscope-service-api": {
|
||||
"agent": {
|
||||
"api-key": "sk-1234567890",
|
||||
"app-id": "Your_app_id",
|
||||
"references_quote": "参考资料来自:"
|
||||
},
|
||||
"app-type": "agent",
|
||||
"workflow": {
|
||||
"api-key": "sk-1234567890",
|
||||
"app-id": "Your_app_id",
|
||||
"references_quote": "参考资料来自:",
|
||||
"biz_params": {
|
||||
"city": "北京",
|
||||
"date": "2023-08-10"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user