Google Vertex AI Embeddings

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Node Details

• Name: googlevertexaiEmbeddings
• Type: GoogleVertexAIEmbeddings
• Version: 2.0
• Category: Embeddings

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Base Classes

• GoogleVertexAIEmbeddings
• (Additional base classes from GoogleVertexAIEmbeddings)

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Parameters

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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.

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Inputs

• Model Name:
  • Type: Asynchronous options
  • Default: “textembedding-gecko@001”
  • Load Method: listModels (retrieves available embedding models)

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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

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Usage

This node is typically used in workflows that require text embeddings, such as:

• Semantic search
• Text classification
• Clustering
• Recommendation systems

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Implementation Details

1. The node first retrieves credential data and input parameters.
2. It then configures authentication options based on the provided credentials.
3. A GoogleVertexAIEmbeddings instance is created with the specified model and authentication options.
4. The initialized model is returned, ready to generate embeddings for input text.

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Error Handling

The node includes error checks for:

• Missing Google Application Credential
• Conflicting credential inputs

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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.

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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.