Update component display names and descriptions

src/backend/base/langflow/components/embeddings/AmazonBedrockEmbeddings.py

@@ -7,12 +7,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class AmazonBedrockEmeddingsComponent(CustomComponent):
-    """
-    A custom component for implementing an Embeddings Model using Amazon Bedrock.
-    """
-
     display_name: str = "Amazon Bedrock Embeddings"
-    description: str = "Embeddings model from Amazon Bedrock."
+    description: str = "Generate embeddings using Amazon Bedrock models."
     documentation = "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/bedrock"
 
     def build_config(self):

src/backend/base/langflow/components/embeddings/AzureOpenAIEmbeddings.py

@@ -5,8 +5,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class AzureOpenAIEmbeddingsComponent(CustomComponent):
-    display_name: str = "AzureOpenAIEmbeddings"
-    description: str = "Embeddings model from Azure OpenAI."
+    display_name: str = "Azure OpenAI Embeddings"
+    description: str = "Generate embeddings using Azure OpenAI models."
     documentation: str = "https://python.langchain.com/docs/integrations/text_embedding/azureopenai"
     beta = False
     icon = "Azure"

src/backend/base/langflow/components/embeddings/CohereEmbeddings.py

@@ -6,8 +6,8 @@ from langflow.custom import CustomComponent
 
 
 class CohereEmbeddingsComponent(CustomComponent):
-    display_name = "CohereEmbeddings"
-    description = "Cohere embedding models."
+    display_name = "Cohere Embeddings"
+    description = "Generate embeddings using Cohere models."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/embeddings/HuggingFaceEmbeddings.py

@@ -6,8 +6,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class HuggingFaceEmbeddingsComponent(CustomComponent):
-    display_name = "HuggingFaceEmbeddings"
-    description = "HuggingFace sentence_transformers embedding models."
+    display_name = "Hugging Face Embeddings"
+    description = "Generate embeddings using HuggingFace models."
     documentation = (
         "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
     )

src/backend/base/langflow/components/embeddings/HuggingFaceInferenceAPIEmbeddings.py

@@ -7,8 +7,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class HuggingFaceInferenceAPIEmbeddingsComponent(CustomComponent):
-    display_name = "HuggingFaceInferenceAPIEmbeddings"
-    description = "HuggingFace sentence_transformers embedding models, API version."
+    display_name = "Hugging Face API Embeddings"
+    description = "Generate embeddings using Hugging Face Inference API models."
     documentation = "https://github.com/huggingface/text-embeddings-inference"
     icon = "HuggingFace"
 

src/backend/base/langflow/components/embeddings/OllamaEmbeddings.py

@@ -7,12 +7,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class OllamaEmbeddingsComponent(CustomComponent):
-    """
-    A custom component for implementing an Embeddings Model using Ollama.
-    """
-
     display_name: str = "Ollama Embeddings"
-    description: str = "Embeddings model from Ollama."
+    description: str = "Generate embeddings using Ollama models."
     documentation = "https://python.langchain.com/docs/integrations/text_embedding/ollama"
 
     def build_config(self):

src/backend/base/langflow/components/embeddings/OpenAIEmbeddings.py

@@ -7,8 +7,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class OpenAIEmbeddingsComponent(CustomComponent):
-    display_name = "OpenAIEmbeddings"
-    description = "OpenAI embedding models"
+    display_name = "OpenAI Embeddings"
+    description = "Generate embeddings using OpenAI models."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/embeddings/VertexAIEmbeddings.py

@@ -6,8 +6,8 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 
 class VertexAIEmbeddingsComponent(CustomComponent):
-    display_name = "VertexAIEmbeddings"
-    description = "Google Cloud VertexAI embedding models."
+    display_name = "VertexAI Embeddings"
+    description = "Generate embeddings using Google Cloud VertexAI models."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/inputs/Prompt.py

@@ -6,7 +6,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 class PromptComponent(CustomComponent):
     display_name: str = "Prompt"
-    description: str = "Create prompt templates with dynamic variables. Prompts can help guide the behavior of a Language Model."
+    description: str = "Create a prompt template with dynamic variables."
     icon = "terminal-square"
 
     def build_config(self):

src/backend/base/langflow/components/vectorsearch/ChromaSearch.py

@@ -9,10 +9,6 @@ from langflow.schema import Record
 
 
 class ChromaSearchComponent(LCVectorStoreComponent):
-    """
-    A custom component for implementing a Vector Store using Chroma.
-    """
-
     display_name: str = "Chroma Search"
     description: str = "Search a Chroma collection for similar documents."
     icon = "Chroma"

src/backend/base/langflow/components/vectorsearch/pgvectorSearch.py

@@ -9,10 +9,6 @@ from langflow.schema import Record
 
 
 class PGVectorSearchComponent(PGVectorComponent, LCVectorStoreComponent):
-    """
-    A custom component for implementing a Vector Store using PostgreSQL.
-    """
-
     display_name: str = "PGVector Search"
     description: str = "Search a PGVector Store for similar documents."
     documentation = "https://python.langchain.com/docs/integrations/vectorstores/pgvector"