PipeSequence

The PipeSequence controller is used to execute a series of pipes one after another. It is the fundamental building block for creating linear workflows where the output of one step becomes the input for the next.

How it works

A PipeSequence defines a list of steps. Each step calls another pipe and gives a name to its output. The working memory is passed from one step to the next, accumulating results along the way.

• The input of the PipeSequence is passed to the first pipe in the sequence.
• The output of each intermediate step is named via the result key and becomes available in the working memory for all subsequent steps.
• The final output of the PipeSequence is the output produced by the very last step in the sequence.

Configuration

PipeSequence is configured in your pipeline's .plx file.

PLX Parameters

Parameter	Type	Description	Required
type	string	The type of the pipe: PipeSequence	Yes
description	string	A description of the sequence operation.	Yes
inputs	dictionary	The input concept(s) for the first pipe in the sequence, as a dictionary mapping input names to concept codes.	No
output	string	The output concept produced by the last pipe in the sequence.	Yes
steps	array of tables	An ordered list of the pipes to execute. Each table in the array defines a single step.	Yes

Step Configuration

Each entry in the steps array is a table with the following keys:

Key	Type	Description	Required
pipe	string	The name of the pipe to execute for this step.	Yes
result	string	The name to give to the output of this step in the working memory.	Yes

Output Concept Matching

The output concept of the PipeSequence has to match the output of the last pipe in the sequence.

Example

Let's imagine a pipeline that first extracts text from an image, then summarizes that text, and finally translates the summary into French.

[pipe.extract_text_from_image]
type = "PipeExtract"
description = "Extract text from an image"
output = "Text"
model = "mistral-ocr"

[pipe.summarize_text]
type = "PipeLLM"
description = "Summarize text"
inputs = { text = "Text" }
output = "Text"

[pipe.translate_to_french]
type = "PipeLLM"
description = "Translate text to French"
inputs = { text = "Text" }
output = "Text"


[pipe.image_to_french_summary]
type = "PipeSequence"
description = "Extract, summarize, and translate text from an image"
inputs = { image = "source.Image" }
output = "target.FrenchText"
steps = [
    { pipe = "extract_text_from_image", result = "extracted_text" },
    { pipe = "summarize_text", result = "english_summary" },
    { pipe = "translate_to_french", result = "french_summary" },
]