Support streaming output for OpenAI o1-preview and o1-mini (#10890)

api/core/model_runtime/model_providers/openai/llm/llm.py

@@ -615,19 +615,11 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
         prompt_messages = self._clear_illegal_prompt_messages(model, prompt_messages)
 
         # o1 compatibility
-        block_as_stream = False
         if model.startswith("o1"):
             if "max_tokens" in model_parameters:
                 model_parameters["max_completion_tokens"] = model_parameters["max_tokens"]
                 del model_parameters["max_tokens"]
 
-            if stream:
-                block_as_stream = True
-                stream = False
-
-                if "stream_options" in extra_model_kwargs:
-                    del extra_model_kwargs["stream_options"]
-
             if "stop" in extra_model_kwargs:
                 del extra_model_kwargs["stop"]
 
@@ -644,47 +636,7 @@ class OpenAILargeLanguageModel(_CommonOpenAI, LargeLanguageModel):
         if stream:
             return self._handle_chat_generate_stream_response(model, credentials, response, prompt_messages, tools)
 
-        block_result = self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
-
-        if block_as_stream:
-            return self._handle_chat_block_as_stream_response(block_result, prompt_messages, stop)
-
-        return block_result
-
-    def _handle_chat_block_as_stream_response(
-        self,
-        block_result: LLMResult,
-        prompt_messages: list[PromptMessage],
-        stop: Optional[list[str]] = None,
-    ) -> Generator[LLMResultChunk, None, None]:
-        """
-        Handle llm chat response
-
-        :param model: model name
-        :param credentials: credentials
-        :param response: response
-        :param prompt_messages: prompt messages
-        :param tools: tools for tool calling
-        :param stop: stop words
-        :return: llm response chunk generator
-        """
-        text = block_result.message.content
-        text = cast(str, text)
-
-        if stop:
-            text = self.enforce_stop_tokens(text, stop)
-
-        yield LLMResultChunk(
-            model=block_result.model,
-            prompt_messages=prompt_messages,
-            system_fingerprint=block_result.system_fingerprint,
-            delta=LLMResultChunkDelta(
-                index=0,
-                message=AssistantPromptMessage(content=text),
-                finish_reason="stop",
-                usage=block_result.usage,
-            ),
-        )
+        return self._handle_chat_generate_response(model, credentials, response, prompt_messages, tools)
 
     def _handle_chat_generate_response(
         self,

api/core/model_runtime/model_providers/openrouter/llm/llm.py

@@ -45,19 +45,7 @@ class OpenRouterLargeLanguageModel(OAIAPICompatLargeLanguageModel):
         user: Optional[str] = None,
     ) -> Union[LLMResult, Generator]:
         self._update_credential(model, credentials)
-
-        block_as_stream = False
-        if model.startswith("openai/o1"):
-            block_as_stream = True
-            stop = None
-
-        # invoke block as stream
-        if stream and block_as_stream:
-            return self._generate_block_as_stream(
-                model, credentials, prompt_messages, model_parameters, tools, stop, user
-            )
-        else:
-            return super()._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user)
+        return super()._generate(model, credentials, prompt_messages, model_parameters, tools, stop, stream, user)
 
     def _generate_block_as_stream(
         self,
@@ -69,9 +57,7 @@ class OpenRouterLargeLanguageModel(OAIAPICompatLargeLanguageModel):
         stop: Optional[list[str]] = None,
         user: Optional[str] = None,
     ) -> Generator:
-        resp: LLMResult = super()._generate(
-            model, credentials, prompt_messages, model_parameters, tools, stop, False, user
-        )
+        resp = super()._generate(model, credentials, prompt_messages, model_parameters, tools, stop, False, user)
 
         yield LLMResultChunk(
             model=model,