支持阿里云百炼的通用模型和自定义大模型应用

pkg/provider/modelmgr/requesters/dashscopecmpl.py

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+from __future__ import annotations
+
+import re
+import asyncio
+import typing
+import dashscope
+
+from .. import entities, errors, requester
+from ....core import entities as core_entities, app
+from ... import entities as llm_entities
+from ...tools import entities as tools_entities
+
+#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
+def replace_references(text, references_dict):
+    # 修正正则表达式，匹配 <ref>[index_id]</ref> 形式的字符串
+    pattern = re.compile(r'<ref>\[(.*?)\]</ref>')
+
+    def replacement(match):
+        ref_key = match.group(1)  # 获取引用编号
+        if ref_key in references_dict:
+            return f"（参考资料来自：{references_dict[ref_key]}）"
+        else:
+            return match.group(0)  # 如果没有对应的参考资料，保留原样
+
+    # 使用 re.sub() 进行替换
+    return pattern.sub(replacement, text)
+
+
+@requester.requester_class("dashscope-chat-applications")
+class DashscopeChatApplication(requester.LLMAPIRequester):
+    """Dashscope ChatApplications API 请求器"""
+    
+    requester_cfg: dict
+
+    def __init__(self, ap: app.Application):
+        self.requester_cfg = ap.provider_cfg.data['requester']['dashscope-chat-applications']
+        self.ap = ap
+
+    async def initialize(self):
+        dashscope.api_key = self.ap.provider_cfg.data['keys']['dashscope'][0]
+
+    async def _req(self, args: dict):
+        
+        #print("args:", args)
+        
+        #局部变量
+        chunk = None
+        pending_content = ""
+        output = {
+            "role": "assistant",
+            "content": "",
+            "tool_calls": [], 
+            "tool_call_id": None  # Dashscope暂时不支持工具调用
+        }   #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
+        
+        references_dict = {}  # 用于存储引用编号和对应的参考资料
+        
+        #调用API
+        response = dashscope.Application.call(
+            api_key=dashscope.api_key,
+            app_id=args["model"],
+            prompt=args["messages"],
+            stream=True,  # 设置流式输出
+            tools=args.get("tools", None),
+            incremental_output = True,
+        )
+
+        #处理API返回的流式输出
+        for chunk in response:
+            #print(chunk)
+            if not chunk:
+                continue
+            
+            #获取流式传输的output
+            stream_output = chunk.get("output", {})
+            if stream_output.get("text") is not None:
+                pending_content += stream_output.get("text")
+        
+
+        #获取模型传出的参考资料列表
+        references_dict_list = stream_output.get("doc_references", [])
+        
+        #从模型传出的参考资料信息中提取用于替换的字典
+        if references_dict_list is not None:
+            for doc in references_dict_list:
+                if doc.get("index_id") is not None:
+                    references_dict[doc.get("index_id")] = doc.get("doc_name")
+
+            #将参考资料替换到文本中
+            pending_content = replace_references(pending_content, references_dict)
+        
+        #将流式传输的内容整合到output中
+        output["content"] = pending_content
+        
+        return output if chunk else None
+
+    async def _make_msg(
+        self,
+        chat_completion: dict,
+    ) -> llm_entities.Message:
+        chatcmpl_message = chat_completion
+
+        # 确保 role 字段存在且不为 None
+        if 'role' not in chatcmpl_message or chatcmpl_message['role'] is None:
+            chatcmpl_message['role'] = 'assistant'
+
+        message = llm_entities.Message(**chatcmpl_message)
+        #print("message:", message)
+        return message
+
+    async def _closure(
+        self,
+        query: core_entities.Query,
+        req_messages: list[dict],
+        use_model: entities.LLMModelInfo,
+        use_funcs: list[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+
+        args = self.requester_cfg['args'].copy()
+        args["model"] = use_model.name if use_model.model_name is None else use_model.model_name
+
+        # 设置此次请求中的messages
+        messages = req_messages.copy()
+        
+        # 检查vision
+        for msg in messages:
+            if 'content' in msg and isinstance(msg["content"], list):
+                for me in msg["content"]:
+                    if me["type"] == "image_base64":
+                        me["image_url"] = {
+                            "url": me["image_base64"]
+                        }
+                        me["type"] = "image_url"
+                        del me["image_base64"]
+
+        args["messages"] = messages
+
+        # 发送请求
+        resp = await self._req(args)
+
+        # 处理请求结果
+        message = await self._make_msg(resp)
+
+        return message
+    
+    async def call(
+        self,
+        query: core_entities.Query,
+        model: entities.LLMModelInfo,
+        messages: typing.List[llm_entities.Message],
+        funcs: typing.List[tools_entities.LLMFunction] = None,
+    ) -> llm_entities.Message:
+        req_messages = []  # req_messages 仅用于类内，外部同步由 query.messages 进行
+        for m in messages:
+            msg_dict = m.dict(exclude_none=True)
+            content = msg_dict.get("content")
+            if isinstance(content, list):
+                # 检查 content 列表中是否每个部分都是文本
+                if all(isinstance(part, dict) and part.get("type") == "text" for part in content):
+                    # 将所有文本部分合并为一个字符串
+                    msg_dict["content"] = "\n".join(part["text"] for part in content)
+            req_messages.append(msg_dict)
+
+        try:
+            return await self._closure(query=query, req_messages=req_messages, use_model=model, use_funcs=funcs)
+        except asyncio.TimeoutError:
+            raise errors.RequesterError('请求超时')

pkg/provider/modelmgr/requesters/qwenchatcmpl.py

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+from __future__ import annotations
+
+import openai
+
+from . import chatcmpl
+from .. import requester
+from ....core import app
+
+
+@requester.requester_class("siliconflow-chat-completions")
+class QwenChatCompletions(chatcmpl.OpenAIChatCompletions):
+    """Qwen ChatCompletion API 请求器"""
+
+    client: openai.AsyncClient
+
+    requester_cfg: dict
+
+    def __init__(self, ap: app.Application):
+        self.ap = ap
+
+        self.requester_cfg = self.ap.provider_cfg.data['requester']['qwen-chat-completions']