Update input variable names in build functions

src/backend/langflow/components/chains/ConversationChain.py

@@ -23,7 +23,7 @@ class ConversationChainComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         llm: BaseLanguageModel,
         memory: Optional[BaseMemory] = None,
     ) -> Text:

src/backend/langflow/components/chains/LLMCheckerChain.py

@@ -18,7 +18,7 @@ class LLMCheckerChainComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         llm: BaseLanguageModel,
     ) -> Text:
 

src/backend/langflow/components/chains/LLMMathChain.py

@@ -24,7 +24,7 @@ class LLMMathChainComponent(CustomComponent):
 
     def build(
         self,
-        inputs: Text,
+        input_value: Text,
         llm: BaseLanguageModel,
         llm_chain: LLMChain,
         input_key: str = "question",

src/backend/langflow/components/chains/RetrievalQA.py

@@ -27,7 +27,7 @@ class RetrievalQAComponent(CustomComponent):
         self,
         combine_documents_chain: BaseCombineDocumentsChain,
         retriever: BaseRetriever,
-        inputs: str = "",
+        input_value: str = "",
         memory: Optional[BaseMemory] = None,
         input_key: str = "query",
         output_key: str = "result",

src/backend/langflow/components/chains/RetrievalQAWithSourcesChain.py

@@ -26,7 +26,7 @@ class RetrievalQAWithSourcesChainComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         retriever: BaseRetriever,
         llm: BaseLanguageModel,
         chain_type: str,

src/backend/langflow/components/chains/SQLGenerator.py

@@ -28,7 +28,7 @@ class SQLGeneratorComponent(CustomComponent):
 
     def build(
         self,
-        inputs: Text,
+        input_value: Text,
         db: SQLDatabase,
         llm: BaseLanguageModel,
         top_k: int = 5,

src/backend/langflow/components/io/ChatInput.py

@@ -11,7 +11,7 @@ class ChatInput(CustomComponent):
 
     def build_config(self):
         return {
-            "message": {
+            "input_value": {
                 "input_types": ["Text"],
                 "display_name": "Message",
                 "multiline": True,
@@ -35,26 +35,26 @@ class ChatInput(CustomComponent):
         self,
         sender: Optional[str] = "User",
         sender_name: Optional[str] = "User",
-        message: Optional[str] = None,
+        input_value: Optional[str] = None,
         session_id: Optional[str] = None,
         return_record: Optional[bool] = False,
     ) -> Union[Text, Record]:
         if return_record:
-            if isinstance(message, Record):
+            if isinstance(input_value, Record):
                 # Update the data of the record
-                message.data["sender"] = sender
-                message.data["sender_name"] = sender_name
-                message.data["session_id"] = session_id
+                input_value.data["sender"] = sender
+                input_value.data["sender_name"] = sender_name
+                input_value.data["session_id"] = session_id
             else:
-                message = Record(
-                    text=message,
+                input_value = Record(
+                    text=input_value,
                     data={
                         "sender": sender,
                         "sender_name": sender_name,
                         "session_id": session_id,
                     },
                 )
-        if not message:
-            message = ""
-        self.status = message
-        return message
+        if not input_value:
+            input_value = ""
+        self.status = input_value
+        return input_value

src/backend/langflow/components/io/ChatOutput.py

@@ -17,7 +17,7 @@ class ChatOutput(CustomComponent):
 
     def build_config(self):
         return {
-            "message": {"input_types": ["Text"], "display_name": "Message"},
+            "input_value": {"input_types": ["Text"], "display_name": "Message"},
             "sender": {
                 "options": ["Machine", "User"],
                 "display_name": "Sender Type",
@@ -39,25 +39,25 @@ class ChatOutput(CustomComponent):
         sender: Optional[str] = "Machine",
         sender_name: Optional[str] = "AI",
         session_id: Optional[str] = None,
-        message: Optional[str] = None,
+        input_value: Optional[str] = None,
         return_record: Optional[bool] = False,
     ) -> Union[Text, Record]:
         if return_record:
-            if isinstance(message, Record):
+            if isinstance(input_value, Record):
                 # Update the data of the record
-                message.data["sender"] = sender
-                message.data["sender_name"] = sender_name
-                message.data["session_id"] = session_id
+                input_value.data["sender"] = sender
+                input_value.data["sender_name"] = sender_name
+                input_value.data["session_id"] = session_id
             else:
-                message = Record(
-                    text=message,
+                input_value = Record(
+                    text=input_value,
                     data={
                         "sender": sender,
                         "sender_name": sender_name,
                         "session_id": session_id,
                     },
                 )
-        if not message:
-            message = ""
-        self.status = message
-        return message
+        if not input_value:
+            input_value = ""
+        self.status = input_value
+        return input_value

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

@@ -39,7 +39,7 @@ class AmazonBedrockComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         model_id: str = "anthropic.claude-instant-v1",
         credentials_profile_name: Optional[str] = None,
         region_name: Optional[str] = None,

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

@@ -9,7 +9,9 @@ from langflow.field_typing import Text
 
 class AnthropicLLM(CustomComponent):
     display_name: str = "AnthropicModel"
-    description: str = "Generate text using Anthropic Chat&Completion large language models."
+    description: str = (
+        "Generate text using Anthropic Chat&Completion large language models."
+    )
 
     def build_config(self):
         return {
@@ -53,7 +55,7 @@ class AnthropicLLM(CustomComponent):
     def build(
         self,
         model: str,
-        inputs: str,
+        input_value: str,
         anthropic_api_key: Optional[str] = None,
         max_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
@@ -66,7 +68,9 @@ class AnthropicLLM(CustomComponent):
         try:
             output = ChatAnthropic(
                 model_name=model,
-                anthropic_api_key=(SecretStr(anthropic_api_key) if anthropic_api_key else None),
+                anthropic_api_key=(
+                    SecretStr(anthropic_api_key) if anthropic_api_key else None
+                ),
                 max_tokens_to_sample=max_tokens,  # type: ignore
                 temperature=temperature,
                 anthropic_api_url=api_endpoint,

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

@@ -9,7 +9,9 @@ from langflow import CustomComponent
 class AzureChatOpenAIComponent(CustomComponent):
     display_name: str = "AzureOpenAI Model"
     description: str = "Generate text using LLM model from Azure OpenAI."
-    documentation: str = "https://python.langchain.com/docs/integrations/llms/azure_openai"
+    documentation: str = (
+        "https://python.langchain.com/docs/integrations/llms/azure_openai"
+    )
     beta = False
 
     AZURE_OPENAI_MODELS = [
@@ -78,7 +80,7 @@ class AzureChatOpenAIComponent(CustomComponent):
         self,
         model: str,
         azure_endpoint: str,
-        inputs: str,
+        input_value: str,
         azure_deployment: str,
         api_key: str,
         api_version: str,

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

@@ -73,7 +73,7 @@ class QianfanChatEndpointComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         model: str = "ERNIE-Bot-turbo",
         qianfan_ak: Optional[str] = None,
         qianfan_sk: Optional[str] = None,

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

@@ -35,11 +35,13 @@ class CTransformersComponent(CustomComponent):
         self,
         model: str,
         model_file: str,
-        inputs: str,
+        input_value: str,
         model_type: str,
         config: Optional[Dict] = None,
     ) -> Text:
-        output = CTransformers(model=model, model_file=model_file, model_type=model_type, config=config)
+        output = CTransformers(
+            model=model, model_file=model_file, model_type=model_type, config=config
+        )
         message = output.invoke(inputs)
         result = message.content if hasattr(message, "content") else message
         self.status = result

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

@@ -34,7 +34,7 @@ class CohereComponent(CustomComponent):
     def build(
         self,
         cohere_api_key: str,
-        inputs: str,
+        input_value: str,
         max_tokens: int = 256,
         temperature: float = 0.75,
     ) -> Text:

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

@@ -57,7 +57,7 @@ class GoogleGenerativeAIComponent(CustomComponent):
         self,
         google_api_key: str,
         model: str,
-        inputs: str,
+        input_value: str,
         max_output_tokens: Optional[int] = None,
         temperature: float = 0.1,
         top_k: Optional[int] = None,

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

@@ -4,7 +4,6 @@ from langchain_community.chat_models.huggingface import ChatHuggingFace
 from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 
 from langflow import CustomComponent
-
 from langflow.field_typing import Text
 
 
@@ -30,7 +29,7 @@ class HuggingFaceEndpointsComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         endpoint_url: str,
         task: str = "text2text-generation",
         huggingfacehub_api_token: Optional[str] = None,

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

@@ -62,7 +62,7 @@ class LlamaCppComponent(CustomComponent):
     def build(
         self,
         model_path: str,
-        inputs: str,
+        input_value: str,
         grammar: Optional[str] = None,
         cache: Optional[bool] = None,
         client: Optional[Any] = None,

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

@@ -171,7 +171,7 @@ class ChatOllamaComponent(CustomComponent):
         self,
         base_url: Optional[str],
         model: str,
-        inputs: str,
+        input_value: str,
         mirostat: Optional[str],
         mirostat_eta: Optional[float] = None,
         mirostat_tau: Optional[float] = None,

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

@@ -1,6 +1,7 @@
 from typing import Optional
 
 from langchain_openai import ChatOpenAI
+
 from langflow import CustomComponent
 from langflow.field_typing import NestedDict, Text
 
@@ -60,7 +61,7 @@ class OpenAIModelComponent(CustomComponent):
 
     def build(
         self,
-        inputs: Text,
+        input_value: Text,
         max_tokens: Optional[int] = 256,
         model_kwargs: NestedDict = {},
         model_name: str = "gpt-4-1106-preview",

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

@@ -62,7 +62,7 @@ class ChatVertexAIComponent(CustomComponent):
 
     def build(
         self,
-        inputs: str,
+        input_value: str,
         credentials: Optional[str],
         project: str,
         examples: Optional[List[BaseMessage]] = [],

src/backend/langflow/components/utilities/RunnableExecutor.py

@@ -32,7 +32,7 @@ class RunnableExecComponent(CustomComponent):
     def build(
         self,
         input_key: str,
-        inputs: str,
+        input_value: str,
         runnable: Runnable,
         output_key: str = "output",
     ) -> Text:

src/backend/langflow/components/vectorstores/ChromaSearch.py

@@ -2,6 +2,7 @@ from typing import List, Optional
 
 import chromadb  # type: ignore
 from langchain_community.vectorstores.chroma import Chroma
+
 from langflow import CustomComponent
 from langflow.field_typing import Embeddings, Text
 from langflow.schema import Record, docs_to_records
@@ -57,7 +58,7 @@ class ChromaSearchComponent(CustomComponent):
 
     def build(
         self,
-        inputs: Text,
+        input_value: Text,
         search_type: str,
         collection_name: str,
         embedding: Embeddings,
@@ -92,7 +93,8 @@ class ChromaSearchComponent(CustomComponent):
 
         if chroma_server_host is not None:
             chroma_settings = chromadb.config.Settings(
-                chroma_server_cors_allow_origins=chroma_server_cors_allow_origins or None,
+                chroma_server_cors_allow_origins=chroma_server_cors_allow_origins
+                or None,
                 chroma_server_host=chroma_server_host,
                 chroma_server_port=chroma_server_port or None,
                 chroma_server_grpc_port=chroma_server_grpc_port or None,

src/backend/langflow/interface/custom/custom_component/custom_component.py

@@ -47,10 +47,10 @@ class CustomComponent(Component):
     """The icon of the component. It should be an emoji. Defaults to None."""
     is_input: Optional[bool] = None
     """The input state of the component. Defaults to None.
-    If True, the component must have a field named 'message'."""
+    If True, the component must have a field named 'input_value'."""
     is_output: Optional[bool] = None
     """The output state of the component. Defaults to None.
-    If True, the component must have a field named 'message'."""
+    If True, the component must have a field named 'input_value'."""
     code: Optional[str] = None
     """The code of the component. Defaults to None."""
     field_config: dict = {}