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Generator Node in Giselle

The Generator Node is the central component for AI-driven content creation in Giselle. It allows you to harness the power of various advanced AI models to generate text and images based on your instructions. By configuring prompts, selecting models, and providing tools, you can create highly customized outputs for any flow.

The Generator Node is configured through three main tabs in its settings panel: Prompt, Model, and Tools.

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Prompt Tab

This is where you provide the instructions for the AI model. Write a clear and detailed prompt describing the task you want the AI to perform. The output generated by the model will appear at the bottom of this panel, allowing you to quickly see the results.

You can also test the node individually by clicking the Generate button, which runs only this node without executing the entire flow.

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Model Tab

In the Model tab, you can select the specific AI model you want to use for the generation task. Giselle provides access to a wide range of models from leading providers.

  • Select a Model: Choose from a list of available models, such as OpenAI’s gpt-4o, Anthropic’s claude-4-opus, or Google’s gemini-2.5-pro.
  • Configure Parameters: Depending on the selected model, you can adjust various AI Parameters like Temperature or Max Tokens to fine-tune the output.

For more details on the available models from each provider, see our documentation:

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Tools Tab

The Tools tab allows you to grant the AI model access to external services, enabling it to perform actions or retrieve data from outside Giselle. This is useful for creating more dynamic and powerful flows.

Currently, the following tools are supported:

  • GitHub
  • PostgreSQL

We are continuously working to add support for more tools in the future.

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Output of the Generator Node

The primary output of a Generator Node is the content it creates (e.g., a block of text or an image). This output can be connected to the input of other nodes, allowing you to chain AI tasks together. For example, the text generated by one node can be used as the input for another node that summarizes or translates it.

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Generator Node in Giselle

The Generator Node is the central component for AI-driven content creation in Giselle. It allows you to harness the power of various advanced AI models to generate text and images based on your instructions. By configuring prompts, selecting models, and providing tools, you can create highly customized outputs for any flow.

The Generator Node is configured through three main tabs in its settings panel: Prompt, Model, and Tools.

​
Prompt Tab

This is where you provide the instructions for the AI model. Write a clear and detailed prompt describing the task you want the AI to perform. The output generated by the model will appear at the bottom of this panel, allowing you to quickly see the results.

You can also test the node individually by clicking the Generate button, which runs only this node without executing the entire flow.

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Model Tab

In the Model tab, you can select the specific AI model you want to use for the generation task. Giselle provides access to a wide range of models from leading providers.

  • Select a Model: Choose from a list of available models, such as OpenAI’s gpt-4o, Anthropic’s claude-4-opus, or Google’s gemini-2.5-pro.
  • Configure Parameters: Depending on the selected model, you can adjust various AI Parameters like Temperature or Max Tokens to fine-tune the output.

For more details on the available models from each provider, see our documentation:

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Tools Tab

The Tools tab allows you to grant the AI model access to external services, enabling it to perform actions or retrieve data from outside Giselle. This is useful for creating more dynamic and powerful flows.

Currently, the following tools are supported:

  • GitHub
  • PostgreSQL

We are continuously working to add support for more tools in the future.

​
Output of the Generator Node

The primary output of a Generator Node is the content it creates (e.g., a block of text or an image). This output can be connected to the input of other nodes, allowing you to chain AI tasks together. For example, the text generated by one node can be used as the input for another node that summarizes or translates it.