Node Details
- Name: googlevertexaiEmbeddings
- Type: GoogleVertexAIEmbeddings
- Version: 2.0
- Category: Embeddings
Base Classes
- GoogleVertexAIEmbeddings
- (Additional base classes from GoogleVertexAIEmbeddings)
Parameters
Credential (Optional)
- Type: googleVertexAuth
- Description: Google Vertex AI credential. Not required if using a GCP service like Cloud Run or if default credentials are installed on the local machine.
Inputs
- Model Name:
- Type: Asynchronous options
- Default: “textembedding-gecko@001”
- Load Method: listModels (retrieves available embedding models)
Initialization
The node initializes a GoogleVertexAIEmbeddings instance with the following potential configurations:- Google Application Credential File Path
- Google Application Credential JSON
- Project ID
- Model Name
Usage
This node is typically used in workflows that require text embeddings, such as:- Semantic search
- Text classification
- Clustering
- Recommendation systems
Implementation Details
- The node first retrieves credential data and input parameters.
- It then configures authentication options based on the provided credentials.
- A GoogleVertexAIEmbeddings instance is created with the specified model and authentication options.
- The initialized model is returned, ready to generate embeddings for input text.
Error Handling
The node includes error checks for:- Missing Google Application Credential
- Conflicting credential inputs
Integration
This node is designed to work within a larger system, likely a workflow or pipeline for natural language processing tasks. It can be connected to other nodes that require text embeddings as input.Notes
- The node uses the @langchain/community library for the GoogleVertexAIEmbeddings implementation.
- It supports dynamic loading of available embedding models.
- The node is flexible in terms of authentication, supporting both file-based and JSON-based credentials.