ComfyUI Node: ⛔ Generate Negative Prompt

⛔ Generate Negative Prompt:

The ⛔ Generate Negative Prompt node is designed to assist AI artists in generating negative prompts for their creative projects. This node leverages a pre-trained GPT-2 model to produce text that can be used to guide AI models away from certain concepts or styles, effectively helping to refine and control the output of generative models. By providing an initial input prompt, the node generates a corresponding negative prompt that can be used to suppress unwanted elements in the generated content. This is particularly useful for fine-tuning the behavior of AI models in creative applications, ensuring that the output aligns more closely with the artist's vision by avoiding specific words or phrases.

⛔ Generate Negative Prompt Input Parameters:

input_prompt

The input_prompt parameter is a string that serves as the initial text input for generating the negative prompt. This is the starting point from which the model will generate text that aims to counteract or negate the concepts presented in the input. This parameter is required and must be provided by the user.

max_length

The max_length parameter specifies the maximum length of the generated negative prompt. It determines how many tokens the model will generate beyond the length of the input prompt. The value must be an integer between 1 and 1024, with a default value of 100. Adjusting this parameter allows you to control the verbosity of the generated text.

num_beams

The num_beams parameter controls the number of beams used in beam search, a technique for generating text. Higher values can improve the quality of the generated text by exploring more potential sequences, but they also increase computational complexity. The value must be an integer between 1 and 10, with a default value of 1.

temperature

The temperature parameter affects the randomness of the generated text. Lower values make the output more deterministic, while higher values increase diversity. The value must be a float between 0.1 and 2.0, with a default value of 1.0. Adjusting this parameter can help balance creativity and coherence in the generated text.

top_k

The top_k parameter limits the sampling pool to the top k tokens, reducing the likelihood of less probable tokens being selected. This can help in generating more focused and relevant text. The value must be an integer between 0 and 100, with a default value of 50.

top_p

The top_p parameter, also known as nucleus sampling, restricts the sampling pool to a subset of tokens whose cumulative probability is at least p. This helps in generating more coherent and contextually appropriate text. The value must be a float between 0.0 and 1.0, with a default value of 0.92.

blocked_words

The blocked_words parameter is a multiline string where you can list words or phrases that should be removed from the generated negative prompt. Each word or phrase should be on a new line. This helps in refining the output by excluding unwanted terms, ensuring the generated text aligns more closely with your requirements.

⛔ Generate Negative Prompt Output Parameters:

negative_prompt

The negative_prompt output parameter is a string that contains the generated negative prompt. This text is designed to counteract or negate the concepts presented in the input prompt, helping to guide the AI model away from certain styles or elements. The generated negative prompt can be used in various creative applications to refine and control the output of generative models.

⛔ Generate Negative Prompt Usage Tips:

• Experiment with different temperature values to find the right balance between creativity and coherence in the generated negative prompt.
• Use the blocked_words parameter to exclude specific terms that you do not want to appear in the negative prompt, ensuring the output aligns with your creative vision.
• Adjust the num_beams parameter to explore more potential sequences and improve the quality of the generated text, especially for complex prompts.

⛔ Generate Negative Prompt Common Errors and Solutions:

Cannot execute because a node is missing the class_type property.

• Explanation: This error occurs when a required node property is missing, preventing execution.
• Solution: Ensure that all nodes in your prompt have the class_type property correctly defined.

Cannot execute because node {class_type} does not exist.

• Explanation: This error indicates that a specified node type does not exist in the node class mappings.
• Solution: Verify that the node type is correctly specified and that it exists in the NODE_CLASS_MAPPINGS.

Prompt has no outputs

• Explanation: This error occurs when the prompt does not produce any outputs.
• Solution: Ensure that your prompt includes nodes that generate outputs and that they are correctly configured.