Batch Run

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The Batch Run component runs a language model over each row of one text column in a DataFrame, and then returns a new DataFrame with the original text and an LLM response. The output contains the following columns:

• text_input: The original text from the input DataFrame
• model_response: The model's response for each input
• batch_index: The 0-indexed processing order for all rows in the DataFrame
• metadata (optional): Additional information about the processing

Use the Batch Run component in a flow

If you pass the Batch Run output to a Parser component, you can use variables in the parsing template to reference these keys, such as {text_input} and {model_response}. This is demonstrated in the following example.

1. Connect any language model component to a Batch Run component's Language model port.

2. Connect DataFrame output from another component to the Batch Run component's DataFrame input. For example, you could connect a Read File component with a CSV file.

3. In the Batch Run component's Column Name field, enter the name of the column in the incoming DataFrame that contains the text to process. For example, if you want to extract text from a name column in a CSV file, enter name in the Column Name field.

4. Connect the Batch Run component's Batch Results output to a Parser component's DataFrame input.

5. Optional: In the Batch Run component menu, enable the System Message parameter, click Close, and then enter an instruction for how you want the LLM to process each cell extracted from the file. For example, Create a business card for each name.

6. In the Parser component's Template field, enter a template for processing the Batch Run component's new DataFrame columns (text_input, model_response, and batch_index):

   For example, this template uses three columns from the resulting, post-batch DataFrame:

   textCopy

   record_number: {batch_index}, name: {text_input}, summary: {model_response}
   

7. To test the processing, click the Parser component, click <Icon name="Play" aria-hidden="true" /> Run component, and then click <Icon name="TextSearch" aria-hidden="true" /> Inspect output to view the final DataFrame.

   You can also connect a Chat Output component to the Parser component if you want to see the output in the Playground.

Batch Run parameters

<PartialParams />

Name	Type	Description
model	HandleInput	Input parameter. Connect the 'Language Model' output from a language model component. Required.
system_message	MultilineInput	Input parameter. A multi-line system instruction for all rows in the DataFrame.
df	DataFrameInput	Input parameter. The DataFrame whose column is treated as text messages, as specified by 'column_name'. Required.
column_name	MessageTextInput	Input parameter. The name of the DataFrame column to treat as text messages. If empty, all columns are formatted in TOML.
output_column_name	MessageTextInput	Input parameter. Name of the column where the model's response is stored. Default=model_response.
enable_metadata	BoolInput	Input parameter. If True, add metadata to the output DataFrame.
batch_results	DataFrame	Output parameter. A DataFrame with all original columns plus the model's response column.