Overview
This n8n node allows you to run a prompt against a local GPT4All instance. It is designed for scenarios where you want to leverage a locally hosted large language model (LLM) for text generation, completion, or conversational AI tasks directly within your n8n workflows—without relying on external cloud-based APIs.
Common use cases:
- Automating content generation or summarization.
- Building chatbots or virtual assistants that operate entirely offline.
- Integrating AI-powered responses into data processing pipelines.
Example:
You could use this node to generate product descriptions from a list of features, summarize customer support tickets, or create automated replies in a workflow—all powered by your own local GPT4All model.
Properties
| Name | Type | Meaning |
|---|---|---|
| Prompt | String | The input text or question you want the GPT4All model to process and respond to. |
| Thread Count | Number | The number of threads to allocate for running GPT4All, which can affect performance and speed. Minimum value is 1. |
Output
The node outputs an object with at least the following structure in the json field:
| Field | Meaning |
|---|---|
| output | The generated response from the GPT4All model, as a string. Any terminal color codes are removed from the output. |
If an error occurs and "Continue On Fail" is enabled, the output may also include:
| Field | Meaning |
|---|---|
| error | Error information if the prompt execution failed for a particular item. |
| pairedItem | Index reference to the original input item. |
Dependencies
- External Service: Requires a local installation of the GPT4All model (
gpt4all-lora-quantized). - Node.js Package: Depends on the
gpt4allnpm package. - System Resources: Sufficient CPU resources to run multiple threads as specified by "Thread Count".
- n8n Configuration: No special environment variables required, but the local GPT4All model must be accessible.
Troubleshooting
Common Issues:
- Model Initialization Failure: If the GPT4All model files are missing or corrupted, initialization will fail.
- Insufficient Resources: Setting a high thread count without enough CPU cores may cause slowdowns or errors.
- Prompt Errors: If the prompt is empty or malformed, the model may return unexpected results or errors.
Error Messages:
"Cannot open gpt model": Indicates issues accessing the model file. Ensure the model is correctly installed and the path is correct."Execute prompt <prompt>": If followed by an error, check the prompt content and system resource usage.- If "Continue On Fail" is enabled, errors are included in the output under the
errorfield; otherwise, the workflow will stop and display the error.
Resolution Steps:
- Verify the GPT4All model is properly installed and accessible.
- Adjust the "Thread Count" according to your machine's capabilities.
- Check the prompt input for correctness.