Merge branch 'dev-web' of https://git.97id.com/ly/zjdataai-app into dev-web

backend/app/engine/model/xinfeng.py

@@ -22,9 +22,12 @@ from llama_index.llms.xinference.utils import (
 class XinfengModel(Xinference):
     @llm_chat_callback()
     def chat(self, messages: Sequence[ChatMessage], **kwargs: Any) -> ChatResponse:
+        msgs = []
         assert self._generator is not None
+        for message in messages:
+            msgs.append(message.dict())
         response_text = self._generator.chat(
-            messages=messages,
+            messages=msgs,
             generate_config={
                 "stream": False,
                 "temperature": self.temperature,
@@ -69,4 +72,52 @@ class XinfengModel(Xinference):
                     delta=delta,
                 )
 
+        return gen()
+    
+    @llm_completion_callback()
+    def complete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponse:
+        assert self._generator is not None
+        message = ChatMessage.from_str(prompt,MessageRole.SYSTEM)
+        msgs = [message.dict()]
+        response_text = self._generator.chat(
+            messages=msgs,
+            generate_config={
+                "stream": False,
+                "temperature": self.temperature,
+                "max_tokens": self.max_tokens,
+            },
+        )["choices"][0]["message"]["content"]
+        return CompletionResponse(
+            delta=None,
+            text=response_text,
+        )
+
+    @llm_completion_callback()
+    def stream_complete(
+        self, prompt: str, formatted: bool = False, **kwargs: Any
+    ) -> CompletionResponseGen:
+        assert self._generator is not None
+        message = ChatMessage.from_str(prompt,MessageRole.SYSTEM)
+        msgs = [message.dict()]
+        response_iter = self._generator.chat(
+            messages=msgs,
+            generate_config={
+                "stream": True,
+                "temperature": self.temperature,
+                "max_tokens": self.max_tokens,
+            },
+        )
+
+        def gen() -> CompletionResponseGen:
+            text = ""
+            for c in response_iter:
+                delta = c["choices"][0]["delta"].get("content", "")
+                text += delta
+                yield CompletionResponse(
+                    delta=delta,
+                    text=text,
+                )
+
         return gen()