fix: Add LanguageModel to field_typing module (#2410)

* feat: Add LanguageModel to field_typing module

* chore: Fix type annotations in model build methods

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>

src/backend/base/langflow/base/models/model.py

@@ -143,13 +143,13 @@ class LCModelComponent(Component):
                 messages.append(HumanMessage(content=input_value))
         inputs: Union[list, dict] = messages or {}
         try:
-            runnable = runnable.with_config(
+            runnable = runnable.with_config(  # type: ignore
-                {"run_name": self.display_name, "project_name": self._tracing_service.project_name}
+                {"run_name": self.display_name, "project_name": self._tracing_service.project_name}  # type: ignore
             )
             if stream:
-                return runnable.stream(inputs)
+                return runnable.stream(inputs)  # type: ignore
             else:
-                message = runnable.invoke(inputs)
+                message = runnable.invoke(inputs)  # type: ignore
                 result = message.content if hasattr(message, "content") else message
                 if isinstance(message, AIMessage):
                     status_message = self.build_status_message(message)

src/backend/base/langflow/components/deactivated/ChatLiteLLMModel.py

@@ -127,7 +127,7 @@ class ChatLiteLLMModelComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         try:
             import litellm  # type: ignore
 
@@ -176,5 +176,4 @@ class ChatLiteLLMModelComponent(LCModelComponent):
             openrouter_api_key=api_keys["openrouter_api_key"],
         )
 
-        return output
+        return output  # type: ignore
-        return output

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

@@ -69,7 +69,7 @@ class AmazonBedrockComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         model_id = self.model_id
         credentials_profile_name = self.credentials_profile_name
         region_name = self.region_name
@@ -89,4 +89,4 @@ class AmazonBedrockComponent(LCModelComponent):
             )
         except Exception as e:
             raise ValueError("Could not connect to AmazonBedrock API.") from e
-        return output
+        return output  # type: ignore

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

@@ -64,7 +64,7 @@ class AnthropicModelComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         model = self.model
         anthropic_api_key = self.anthropic_api_key
         max_tokens = self.max_tokens
@@ -83,7 +83,7 @@ class AnthropicModelComponent(LCModelComponent):
         except Exception as e:
             raise ValueError("Could not connect to Anthropic API.") from e
 
-        return output
+        return output  # type: ignore
 
     def _get_exception_message(self, exception: Exception) -> str | None:
         """

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

@@ -78,7 +78,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="model_response"),
     ]
 
-    def model_response(self) -> LanguageModel:
+    def model_response(self) -> LanguageModel:  # type: ignore[type-var]
         model = self.model
         azure_endpoint = self.azure_endpoint
         azure_deployment = self.azure_deployment
@@ -107,4 +107,4 @@ class AzureChatOpenAIComponent(LCModelComponent):
         except Exception as e:
             raise ValueError("Could not connect to AzureOpenAI API.") from e
 
-        return output
+        return output  # type: ignore

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

@@ -51,4 +51,4 @@ class CohereComponent(LCModelComponent):
             cohere_api_key=api_key,
         )
 
-        return output
+        return output  # type: ignore

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

@@ -3,15 +3,7 @@ from pydantic.v1 import SecretStr
 from langflow.base.constants import STREAM_INFO_TEXT
 from langflow.base.models.model import LCModelComponent
 from langflow.field_typing import LanguageModel
-from langflow.inputs import (
+from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
-    BoolInput,
-    DropdownInput,
-    FloatInput,
-    IntInput,
-    MessageInput,
-    SecretStrInput,
-    StrInput,
-)
 
 
 class GoogleGenerativeAIComponent(LCModelComponent):
@@ -66,7 +58,7 @@ class GoogleGenerativeAIComponent(LCModelComponent):
         ),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         try:
             from langchain_google_genai import ChatGoogleGenerativeAI
         except ImportError:
@@ -90,4 +82,4 @@ class GoogleGenerativeAIComponent(LCModelComponent):
             google_api_key=SecretStr(google_api_key),
         )
 
-        return output
+        return output  # type: ignore

src/backend/base/langflow/components/models/GroqModel.py

@@ -68,7 +68,7 @@ class GroqModel(LCModelComponent):
         ),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         groq_api_key = self.groq_api_key
         model_name = self.model_name
         max_tokens = self.max_tokens
@@ -87,4 +87,4 @@ class GroqModel(LCModelComponent):
             streaming=stream,
         )
 
-        return output
+        return output  # type: ignore

src/backend/base/langflow/components/models/HuggingFaceModel.py

@@ -36,7 +36,7 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         endpoint_url = self.endpoint_url
         task = self.task
         huggingfacehub_api_token = self.huggingfacehub_api_token
@@ -53,4 +53,4 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
             raise ValueError("Could not connect to HuggingFace Endpoints API.") from e
 
         output = ChatHuggingFace(llm=llm)
-        return output
+        return output  # type: ignore

src/backend/base/langflow/components/models/MistralModel.py

@@ -70,7 +70,7 @@ class MistralAIModelComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         mistral_api_key = self.mistral_api_key
         temperature = self.temperature
         model_name = self.model_name
@@ -102,4 +102,4 @@ class MistralAIModelComponent(LCModelComponent):
             safe_mode=safe_mode,
         )
 
-        return output
+        return output  # type: ignore

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

@@ -223,7 +223,7 @@ class ChatOllamaComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         # Mapping mirostat settings to their corresponding values
         mirostat_options = {"Mirostat": 1, "Mirostat 2.0": 2}
 
@@ -272,4 +272,4 @@ class ChatOllamaComponent(LCModelComponent):
         except Exception as e:
             raise ValueError("Could not initialize Ollama LLM.") from e
 
-        return output
+        return output  # type: ignore

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

@@ -80,8 +80,8 @@ class OpenAIModelComponent(LCModelComponent):
         ),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
-        # self.output_schea is a list of dictionaries
+        # self.output_schea is a list of dictionarie s
         # let's convert it to a dictionary
         output_schema_dict: dict[str, str] = reduce(operator.ior, self.output_schema or {}, {})
         openai_api_key = self.openai_api_key
@@ -112,7 +112,7 @@ class OpenAIModelComponent(LCModelComponent):
             else:
                 output = output.bind(response_format={"type": "json_object"})  # type: ignore
 
-        return output
+        return output  # type: ignore
 
     def _get_exception_message(self, e: Exception):
         """

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

@@ -52,7 +52,7 @@ class ChatVertexAIComponent(LCModelComponent):
         Output(display_name="Language Model", name="model_output", method="build_model"),
     ]
 
-    def build_model(self) -> LanguageModel:
+    def build_model(self) -> LanguageModel:  # type: ignore[type-var]
         credentials = self.credentials
         location = self.location
         max_output_tokens = self.max_output_tokens
@@ -75,4 +75,4 @@ class ChatVertexAIComponent(LCModelComponent):
             verbose=verbose,
         )
 
-        return output
+        return output  # type: ignore

src/backend/base/langflow/field_typing/__init__.py

@@ -26,6 +26,7 @@ from .constants import (
     TextSplitter,
     Tool,
     VectorStore,
+    LanguageModel,
 )
 from .range_spec import RangeSpec
 
@@ -84,4 +85,5 @@ __all__ = [
     "BaseChatModel",
     "Retriever",
     "Text",
+    "LanguageModel",
 ]