Extract to CSV Node

Extract data to a CSV using AI.

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Node Inputs

1. Text for extraction: Text to extract table from
   • Type: Text
2. Additional Context: Provide any additional context that may help the AI model extract the data.
   • Type: Text
3. Select CSV: Your file should contain headers in the first row.
   • Type: File

If Add columns manually is selected:

1. Column Name: The name of the column.
   • Type: Text
2. Column Value: The value of the column.
   • Type: Text

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Node Parameters

On the face of the node:

1. Extract multiple rows: Choose the mode of extraction. If checked, it will extract multiple rows of data. If unchecked, it will extract a single row.
   • Type: Toggle
2. Add columns manually: Add data points for some columns manually instead of having them extracted by the AI model.
   • Type: Toggle

In the gear:

1. Provider: The model provider.
   • Type: Dropdown
2. Model: The specific model for extracting the table
   • Type: Dropdown

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Node Outputs

1. Table: The table extracted from the text.
   • Type: File
   • Example usage: {{extract_to_table_0.table}}

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Example

The below example shows a pipeline that extracts employee information from text and saves it as a CSV file.

1. Text Node: Contains the text with employee information.
   • Text: Our company has 3 employees. John Smith is our CEO and earns $120,000 per year. Sarah Johnson is our CTO with a salary of $110,000. Mike Brown is our Marketing Manager making $90,000 annually.
2. Input Node: Contains the CSV file.
   • Type: File
3. Extract to CSV Node: Extracts the data and saves it as CSV.
   • Text for extraction: {{text_0.text}}
   • Additional Context: Please extract employee information including name, role, and salary.
   • Select CSV: {{input_0.file}}
   • Extract multiple rows: True
   • Add columns manually: False
4. Output: The extracted CSV file
   • Output: {{extract_to_csv_0.table}}