Update moss_llm.py

models/moss_llm.py

@@ -58,6 +58,11 @@ class MOSSLLM(BaseAnswer, LLM, ABC):
                          history: List[List[str]] = [],
                          streaming: bool = False,
                          generate_with_callback: AnswerResultStream = None) -> None:
+        # Create the StoppingCriteriaList with the stopping strings
+        stopping_criteria_list = transformers.StoppingCriteriaList()
+        # 定义模型stopping_criteria 队列，在每次响应时将 torch.LongTensor, torch.FloatTensor同步到AnswerResult
+        listenerQueue = AnswerResultQueueSentinelTokenListenerQueue()
+        stopping_criteria_list.append(listenerQueue)
         if len(history) > 0:
             history = history[-self.history_len:-1] if self.history_len > 0 else []
             prompt_w_history = str(history)
@@ -83,6 +88,12 @@ class MOSSLLM(BaseAnswer, LLM, ABC):
             response = self.tokenizer.decode(outputs[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
             self.checkPoint.clear_torch_cache()
             history += [[prompt, response]]
-            yield response, history
+            answer_result = AnswerResult()
+            answer_result.history = history
+            answer_result.llm_output = {"answer": response}
+            if listenerQueue.listenerQueue.__len__() > 0:
+                answer_result.listenerToken = listenerQueue.listenerQueue.pop()
+
+            generate_with_callback(answer_result)