Refactor model components to support streaming

src/backend/langflow/components/models/AmazonBedrockModel.py

@@ -35,6 +35,10 @@ class AmazonBedrockComponent(CustomComponent):
             "cache": {"display_name": "Cache"},
             "code": {"advanced": True},
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -47,6 +51,7 @@ class AmazonBedrockComponent(CustomComponent):
         endpoint_url: Optional[str] = None,
         streaming: bool = False,
         cache: Optional[bool] = None,
+        stream: bool = False,
     ) -> Text:
         try:
             output = BedrockChat(
@@ -60,7 +65,10 @@ class AmazonBedrockComponent(CustomComponent):
             )  # type: ignore
         except Exception as e:
             raise ValueError("Could not connect to AmazonBedrock API.") from e
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/AnthropicModel.py

@@ -50,6 +50,10 @@ class AnthropicLLM(CustomComponent):
             },
             "code": {"show": False},
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -60,6 +64,7 @@ class AnthropicLLM(CustomComponent):
         max_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
         api_endpoint: Optional[str] = None,
+        stream: bool = False,
     ) -> Text:
         # Set default API endpoint if not provided
         if not api_endpoint:
@@ -77,7 +82,10 @@ class AnthropicLLM(CustomComponent):
             )
         except Exception as e:
             raise ValueError("Could not connect to Anthropic API.") from e
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/AzureOpenAIModel.py

@@ -74,6 +74,10 @@ class AzureChatOpenAIComponent(CustomComponent):
             },
             "code": {"show": False},
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -86,6 +90,7 @@ class AzureChatOpenAIComponent(CustomComponent):
         api_version: str,
         temperature: float = 0.7,
         max_tokens: Optional[int] = 1000,
+        stream: bool = False,
     ) -> BaseLanguageModel:
         try:
             output = AzureChatOpenAI(
@@ -99,7 +104,10 @@ class AzureChatOpenAIComponent(CustomComponent):
             )
         except Exception as e:
             raise ValueError("Could not connect to AzureOpenAI API.") from e
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/BaiduQianfanChatModel.py

@@ -69,6 +69,10 @@ class QianfanChatEndpointComponent(CustomComponent):
             },
             "code": {"show": False},
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -81,6 +85,7 @@ class QianfanChatEndpointComponent(CustomComponent):
         temperature: Optional[float] = None,
         penalty_score: Optional[float] = None,
         endpoint: Optional[str] = None,
+        stream: bool = False,
     ) -> Text:
         try:
             output = QianfanChatEndpoint(  # type: ignore
@@ -94,7 +99,10 @@ class QianfanChatEndpointComponent(CustomComponent):
             )
         except Exception as e:
             raise ValueError("Could not connect to Baidu Qianfan API.") from e
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/CTransformersModel.py

@@ -29,6 +29,10 @@ class CTransformersComponent(CustomComponent):
                 "value": '{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}',
             },
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -38,11 +42,15 @@ class CTransformersComponent(CustomComponent):
         input_value: str,
         model_type: str,
         config: Optional[Dict] = None,
+        stream: Optional[bool] = False,
     ) -> Text:
         output = CTransformers(
             model=model, model_file=model_file, model_type=model_type, config=config
         )
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/CohereModel.py

@@ -43,8 +43,10 @@ class CohereComponent(CustomComponent):
             max_tokens=max_tokens,
             temperature=temperature,
         )
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
-        return result
+            message = output.invoke(input_value)
-        return result
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
+        return result        return result

src/backend/langflow/components/models/GoogleGenerativeAIModel.py

@@ -70,7 +70,10 @@ class GoogleGenerativeAIComponent(CustomComponent):
             n=n or 1,
             google_api_key=SecretStr(google_api_key),
         )
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/LlamaCppModel.py

@@ -57,6 +57,10 @@ class LlamaCppComponent(CustomComponent):
             "verbose": {"display_name": "Verbose", "advanced": True},
             "vocab_only": {"display_name": "Vocab Only", "advanced": True},
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -97,6 +101,7 @@ class LlamaCppComponent(CustomComponent):
         use_mmap: Optional[bool] = True,
         verbose: bool = True,
         vocab_only: bool = False,
+        stream: bool = False,
     ) -> Text:
         output = LlamaCpp(
             model_path=model_path,
@@ -135,9 +140,10 @@ class LlamaCppComponent(CustomComponent):
             verbose=verbose,
             vocab_only=vocab_only,
         )
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
-        return result
+            message = output.invoke(input_value)
-        self.status = result
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/OllamaModel.py

@@ -165,6 +165,10 @@ class ChatOllamaComponent(CustomComponent):
                 "advanced": True,
             },
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -197,6 +201,7 @@ class ChatOllamaComponent(CustomComponent):
         timeout: Optional[int] = None,
         top_k: Optional[int] = None,
         top_p: Optional[int] = None,
+        stream: Optional[bool] = False,
     ) -> Text:
         if not base_url:
             base_url = "http://localhost:11434"
@@ -250,7 +255,10 @@ class ChatOllamaComponent(CustomComponent):
             output = ChatOllama(**llm_params)  # type: ignore
         except Exception as e:
             raise ValueError("Could not initialize Ollama LLM.") from e
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/OpenAIModel.py

@@ -57,6 +57,10 @@ class OpenAIModelComponent(CustomComponent):
                 "required": False,
                 "value": 0.7,
             },
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -68,10 +72,11 @@ class OpenAIModelComponent(CustomComponent):
         openai_api_base: Optional[str] = None,
         openai_api_key: Optional[str] = None,
         temperature: float = 0.7,
+        stream: Optional[bool] = False,
     ) -> Text:
         if not openai_api_base:
             openai_api_base = "https://api.openai.com/v1"
-        model = ChatOpenAI(
+        output = ChatOpenAI(
             max_tokens=max_tokens,
             model_kwargs=model_kwargs,
             model=model_name,
@@ -79,8 +84,10 @@ class OpenAIModelComponent(CustomComponent):
             api_key=openai_api_key,
             temperature=temperature,
         )
-
+        if stream:
-        message = model.invoke(input_value)
+            result = output.stream(input_value)
-        result = message.content if hasattr(message, "content") else message
+        else:
-        self.status = result
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result

src/backend/langflow/components/models/VertexAiModel.py

@@ -58,6 +58,10 @@ class ChatVertexAIComponent(CustomComponent):
                 "advanced": True,
             },
             "input_value": {"display_name": "Input"},
+            "stream": {
+                "display_name": "Stream",
+                "info": "Stream the response from the model.",
+            },
         }
 
     def build(
@@ -73,6 +77,7 @@ class ChatVertexAIComponent(CustomComponent):
         top_k: int = 40,
         top_p: float = 0.95,
         verbose: bool = False,
+        stream: bool = False,
     ) -> Text:
         try:
             from langchain_google_vertexai import ChatVertexAI
@@ -92,7 +97,10 @@ class ChatVertexAIComponent(CustomComponent):
             top_p=top_p,
             verbose=verbose,
         )
-        message = output.invoke(input_value)
+        if stream:
-        result = message.content if hasattr(message, "content") else message
+            result = output.stream(input_value)
-        self.status = result
+        else:
+            message = output.invoke(input_value)
+            result = message.content if hasattr(message, "content") else message
+            self.status = result
         return result