✨ feat: 完善流式处理

astrbot/core/provider/sources/dashscope_source.py

@@ -7,6 +7,7 @@ from ..entites import LLMResponse
 from ..func_tool_manager import FuncCall
 from astrbot.core.db import BaseDatabase
 from ..register import register_provider_adapter
+from astrbot.core.message.message_event_result import MessageChain
 from .openai_source import ProviderOpenAIOfficial
 from astrbot.core import logger, sp
 from dashscope import Application
@@ -132,7 +133,9 @@ class ProviderDashscope(ProviderOpenAIOfficial):
             )
             return LLMResponse(
                 role="err",
-                completion_text=f"阿里云百炼请求失败: message={response.message} code={response.status_code}",
+                result_chain=MessageChain().message(
+                    f"阿里云百炼请求失败: message={response.message} code={response.status_code}"
+                ),
             )
 
         output_text = response.output.get("text", "")
@@ -149,7 +152,10 @@ class ProviderDashscope(ProviderOpenAIOfficial):
                 ref_str += f"{ref['index_id']}. {ref_title}\n"
             output_text += f"\n\n回答来源:\n{ref_str}"
 
-        return LLMResponse(role="assistant", completion_text=output_text)
+        llm_response = LLMResponse("assistant")
+        llm_response.result_chain = MessageChain().message(output_text)
+
+        return llm_response
 
     async def text_chat_stream(
         self,
@@ -162,7 +168,21 @@ class ProviderDashscope(ProviderOpenAIOfficial):
         tool_calls_result=None,
         **kwargs,
     ):
-        raise NotImplementedError("This method is not implemented yet.")
+        # raise NotImplementedError("This method is not implemented yet.")
+        # 调用 text_chat 模拟流式
+        llm_response = await self.text_chat(
+            prompt=prompt,
+            session_id=session_id,
+            image_urls=image_urls,
+            func_tool=func_tool,
+            contexts=contexts,
+            system_prompt=system_prompt,
+            tool_calls_result=tool_calls_result,
+        )
+        llm_response.is_chunk = True
+        yield llm_response
+        llm_response.is_chunk = False
+        yield llm_response
 
     async def forget(self, session_id):
         return True