ComfyUI Node: CLIPTokenCounter

CLIPTokenCounter:

The CLIPTokenCounter node is designed to help you analyze and understand the tokenization process of text inputs when using the CLIP model. This node takes a text input and processes it to count the number of tokens generated by the CLIP tokenizer. It is particularly useful for AI artists who want to ensure their text prompts are within the token limits of the CLIP model, thereby optimizing the performance and accuracy of their AI-generated art. By providing a detailed count of tokens, this node helps you manage and refine your text inputs effectively, ensuring that they are well-suited for the CLIP model's capabilities.

CLIPTokenCounter Input Parameters:

text

This parameter accepts a string input, which can be multiline, representing the text you want to tokenize and analyze. The text can include multiple prompts separated by the keyword "BREAK". Each prompt will be tokenized separately, and the token counts for each will be provided. There is no minimum or maximum length specified, but it is advisable to keep the text within reasonable limits to ensure efficient processing.

clip

This parameter expects a CLIP model instance. The CLIP model is used to tokenize the input text and analyze the tokens. The model should be properly initialized and compatible with the node to ensure accurate tokenization and analysis.

debug_print

This is a boolean parameter that controls whether debug information is printed during the execution of the node. If set to True, the node will print detailed information about the token counts and the tokens themselves. This can be useful for debugging and understanding the tokenization process. The default value is False.

CLIPTokenCounter Output Parameters:

STRING

The output is a string that represents the count of tokens for each prompt in the input text. If the input text contains multiple prompts separated by "BREAK", the output will provide the token counts for each prompt separately. This information helps you understand the length and complexity of your text inputs in terms of tokens, which is crucial for optimizing the use of the CLIP model.

CLIPTokenCounter Usage Tips:

• To ensure accurate token counts, make sure your input text is well-formatted and clearly separated by "BREAK" if you are using multiple prompts.
• Use the debug_print parameter set to True if you want to see detailed information about the tokens generated. This can help you understand how the CLIP model tokenizes your text and identify any potential issues.
• Keep your text inputs concise and within reasonable limits to avoid excessive tokenization, which can slow down the processing and affect the performance of the CLIP model.

CLIPTokenCounter Common Errors and Solutions:

"Invalid CLIP model instance"

• Explanation: This error occurs if the provided CLIP model instance is not properly initialized or compatible with the node.
• Solution: Ensure that you are passing a valid and properly initialized CLIP model instance to the clip parameter.

"Text input is too long"

• Explanation: This error occurs if the input text is excessively long, causing the tokenization process to be inefficient or fail.
• Solution: Break down your text input into smaller, more manageable chunks and ensure each chunk is within reasonable length limits.

"Tokenization failed"

• Explanation: This error occurs if the tokenization process encounters an unexpected issue, such as unsupported characters or formatting errors in the input text.
• Solution: Review your input text for any unsupported characters or formatting issues and correct them before re-running the node.