ComfyUI Node: 🔥FlowBuilderSetter

🔥FlowBuilderSetter:

The FlowBuilderSetter node is designed to facilitate the management and assignment of values within a workflow, specifically tailored for AI art generation processes. This node allows you to set and cache values dynamically, ensuring that specific data points are readily available for subsequent nodes in the workflow. By using this node, you can streamline the flow of data, making it easier to manage complex workflows and ensuring that key values are consistently accessible. The primary function of the FlowBuilderSetter is to assign a value to a specified key and store it in a cache, which can then be retrieved by other nodes as needed. This capability is particularly useful in scenarios where certain values need to be reused or referenced multiple times throughout the workflow, enhancing efficiency and reducing redundancy.

🔥FlowBuilderSetter Input Parameters:

value

The value parameter is a required input that accepts any type of data. This is the primary data that you want to assign to a specific key and store in the cache. The type of data can vary depending on your specific needs, ranging from simple strings and numbers to more complex data structures.

key

The key parameter is a required input of type STRING. This parameter specifies the unique identifier for the value being set. By assigning a key to a value, you ensure that the value can be easily retrieved later in the workflow. The default value for this parameter is an empty string.

batch_size

The batch_size parameter is an optional input of type INT. It defines the number of items to process in a single batch. This parameter is useful when dealing with large datasets or when you need to process data in chunks. The default value is 1, with a minimum value of 1 and a maximum value of 10,000. The step value for this parameter is 1, allowing for precise control over the batch size.

🔥FlowBuilderSetter Output Parameters:

value

The value output parameter returns the value that was set and cached using the FlowBuilderSetter node. This output ensures that the assigned value is available for subsequent nodes in the workflow, allowing for seamless data flow and reuse of key values.

🔥FlowBuilderSetter Usage Tips:

• Ensure that the key parameter is unique for each value you set to avoid overwriting existing values in the cache.
• Use the batch_size parameter to optimize performance when processing large datasets by breaking them into manageable chunks.
• Leverage the FlowBuilderSetter node to store intermediate results that need to be accessed multiple times throughout the workflow, reducing redundancy and improving efficiency.

🔥FlowBuilderSetter Common Errors and Solutions:

No value assigned for key: <key>, inputs: <kwargs>

• Explanation: This error occurs when no value is provided for the specified key in the input parameters.
• Solution: Ensure that you provide a valid value for the value parameter when using the FlowBuilderSetter node. Double-check the input parameters to confirm that the value is correctly assigned.

KeyError: <key>

• Explanation: This error occurs when the specified key is not found in the cache.
• Solution: Verify that the key you are using to retrieve the value has been correctly set and cached using the FlowBuilderSetter node. Ensure that the key is unique and matches the key used during the value assignment.

Invalid batch size: <batch_size>

• Explanation: This error occurs when the batch_size parameter is set to a value outside the allowed range.
• Solution: Adjust the batch_size parameter to a value within the allowed range (1 to 10,000). Ensure that the batch size is appropriate for your specific use case and data processing requirements.