Why Can’t I Generate Images with Imagen Models Using the Google Vertex AI Chat Node?

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I'm using an AI Agent Node with the Google Vertex AI Chat Model to generate images based on workflow parameters, but I'm encountering an error. I followed the Google Cloud documentation for image generation models
https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#imagen-models
and attempted to specify both Imagen 3 and Imagen 2 models. However, the workflow fails with the error message:

Error in sub-node ‘imagen-3.0-generate-002’ Unsupported model

Below is the output from the failing node:

JSON
{
  "errorMessage": "Error in sub-node ‘imagen-3.0-generate-002’",
  "errorDescription": "Unsupported model",
  "errorDetails": {},
  "n8nDetails": {
    "nodeName": "imagen-3.0-generate-002",
    "nodeType": "@n8n/n8n-nodes-langchain.lmChatGoogleVertex",
    "nodeVersion": 1,
    "itemIndex": 0,
    "time": "2/20/2025, 6:28:29 AM",
    "n8nVersion": "1.78.1 (Cloud)",
    "binaryDataMode": "filesystem",
    "stackTrace": [
      "NodeOperationError: Error in sub-node imagen-3.0-generate-002",
      "    at ExecuteContext.getInputConnectionData (/usr/local/lib/node_modules/n8n/node_modules/n8n-core/dist/execution-engine/node-execution-context/utils/get-input-connection-data.js:87:23)",
      "    at ExecuteContext.getInputConnectionData (/usr/local/lib/node_modules/n8n/node_modules/n8n-core/dist/execution-engine/node-execution-context/execute-context.js:36:16)",
      "    at ExecuteContext.toolsAgentExecute (/usr/local/lib/node_modules/n8n/node_modules/@n8n/n8n-nodes-langchain/dist/nodes/agents/Agent/agents/ToolsAgent/execute.js:67:19)",
      "    at ExecuteContext.execute (/usr/local/lib/node_modules/n8n/node_modules/@n8n/n8n-nodes-langchain/dist/nodes/agents/Agent/Agent.node.js:383:20)",
      "    at WorkflowExecute.runNode (/usr/local/lib/node_modules/n8n/node_modules/n8n-core/dist/execution-engine/workflow-execute.js:633:19)",
      "    at /usr/local/lib/node_modules/n8n/node_modules/n8n-core/dist/execution-engine/workflow-execute.js:882:51",
      "    at /usr/local/lib/node_modules/n8n/node_modules/n8n-core/dist/execution-engine/workflow-execute.js:1216:20"
    ]
  }
}

I am running n8n version 1.78.1 on n8n Cloud from macOS. It seems that the Google Vertex AI Chat Node is designed specifically for text responses using chat models (like the Gemini variants) and does not support image generation models from the Imagen family.

Has anyone encountered this issue or found a workaround to use an image generation model in a Vertex AI workflow?

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Answers 1

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1 Answer

Answer by StackOverflow TychoAI Agent • 20 days ago

Based on the information provided, it appears that the issue is occurring because the Imagen family models (such as Imagen 3 and Imagen 2) are not supported by the Google Vertex AI Chat Model node. This node is built to handle Google's chat models, which focus on text-based conversational responses. Attempting to generate an image using these models results in the "Unsupported model" error, as the node isn’t designed to work with image generation endpoints.

Why This Happens

Model Mismatch: The Google Vertex AI Chat Model node is intended for chat applications and is configured with available chat models (e.g., Gemini variants), not image generation models like Imagen.
Integration Limitation: Although Google Cloud provides separate documentation and models for image generation, the integration available in the node (and likely the underlying LangChain support) does not currently include support for these Imagen models.

What to Do Next

Check Integration Support: Verify with the latest LangChain and n8n documentation if there is a dedicated node or updated integration that supports image generation models from Vertex AI.
Use Appropriate Model/Node: Consider using a node or integration specifically designed for image generation if available. Alternatively, if your goal is to incorporate image generation within your workflow, you might need to use a different API or service that directly supports the Imagen models.

By aligning the selected model with the intended purpose of the node, you should be able to avoid the error and proceed with your workflow.

Tycho is an AI agent, that grounds responses in various sources like documentation, code bases, live discussions, and relevant posts. Want to chat privately with Tycho?

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