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Add these nodes with the pipeline builder: pipeline.add(name="...").<node>(...). Each entry lists the node’s configuration parameters. See the Pipeline reference for add, run, and lifecycle methods.

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browser_extension — Browser Extension

Run a VectorShift workflow using the current page captured by the VectorShift chrome extension as input.
Platform docs: Browser Extension
Parameters
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str
default:"''"
​
str
default:"''"
​
list[str]
default:"[]"
​
AcceptsImage
default:"{}"
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bool
default:"True"
​
str
default:"''"

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input — Input

Pass data of different types into your workflow
Platform docs: Input
Parameters
​
str
default:"'string'"
Raw Text
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bool
default:"False"
Set default value to be used if no value is provided
​
str
default:"''"
The input description. If pipeline is used as a tool in an agent, the description will be passed to the agent to help the agent know how to fill this input.
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AcceptsAgent | AcceptsAudio | AcceptsDataframe | AcceptsFile | AcceptsFileList | AcceptsImage | AcceptsKnowledgeBase | AcceptsPipeline | AcceptsTable | AcceptsTimestamp | ListType | bool | float | int | list[AcceptsFileList] | list[list[str]] | list[str] | str
default:"{}"
The default value to be used if no value is provided
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str
default:"'table'"
The type of dataframe to be used One of: csv, dataframe_file, json, md, sql, table
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str
default:"'default'"
The processing model with which the document will be processed. Default processing model includes standard document parsing / OCR. Llamaparse will allow for ability to read documents with complex features (e.g., tables, charts, etc.). Llamaparse will be charged at 0.3 cents per page. Textract for most advanced data extraction and will be charged at 1.5 cents per page. Reducto enables rich structured parsing. One of: contextual_ai, default, docling, llama_parse, mistral_ocr, reducto, textract

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output — Output

Output data of different types from your workflow.
Platform docs: Output
Parameters
​
str
default:"'string'"
​
str
default:"''"
The output description. If pipeline is used as a tool in an agent, the description will be passed to the agent to help the agent know how to fill this output.
​
bool
default:"True"
​
AcceptsAudio | AcceptsDataframe | AcceptsFile | AcceptsFileList | AcceptsImage | AcceptsStream | AcceptsTimestamp | bool | float | int | str
required
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str
default:"'table'"
The type of dataframe to be used One of: csv, dataframe_file, json, md, sql, table

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start_flag — Start a conversation

Start a conversation
Platform docs: Start a conversation

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sticky_note — sticky_note

Platform docs: sticky_note
Parameters
​
str
default:"''"