ask() Parameters | Teradata Package for Generative AI - ask() Parameters - Teradata VantageCloud Lake

Lake - Analyze Your Data with ClearScape Analytics™

Deployment
VantageCloud
Edition
Lake
Product
Teradata VantageCloud Lake
Release Number
Published
February 2025
ft:locale
en-US
ft:lastEdition
2026-02-20
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tcl1683670667798.ditamap
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pny1626732985837.ditaval
dita:id
tcl1683670667798

These parameters are supported when 'api_type' is set to aws, azure, gcp, or nim.

Name Required or Optional Description Type Default Value Permitted Values
column Required Specifies the column of the teradataml DataFrame. string N/A N/A
data Required Specifies the teradataml DataFrame containing the column specified in "column". teradataml DataFrame N/A N/A
context Required Specifies the teradataml DataFrame containing the context to be used for answering the questions. string N/A N/A
context_column Required Specifies the column in the "context" DataFrame containing the text data to be used as context for answering the questions. string N/A N/A
context_partition_column Required Specifies the column used to partition the context for processing. string N/A N/A
prompt Required Specifies the prompt template to be used for generating answers. The prompt should include placeholders for the data and question, which will be replaced during execution. string N/A N/A
data_position Required Specifies the placeholder in the prompt where the data will be inserted. string N/A N/A
question_position Required Specifies the placeholder in the prompt where the question will be inserted. string N/A N/A
persist Optional Specifies whether to persist the output or not. When set to True, results are stored in permanent tables, otherwise in volatile tables. boolean False True, False
accumulate Optional Specifies the names of input teradataml DataFrame columns to copy to the output. By default, the method copies no input teradataml DataFrame columns to the output. string or list of strings All columns Valid column from 'data' DataFrame.
data_partition_column Optional Specifies the column used to partition the the 'data' for processing. string Non Valid column from 'data' DataFrame.
is_debug Optional Specifies whether to enable error logging. boolean False True/False
volatile Optional Specifies whether to put the results of the function in a volatile table or not. When set to True, results are stored in a volatile table, otherwise not. boolean False True/False
show_num_tokens Optional Specifies whether to display token information in the query output. If set to True, it includes input and output token counts in the result. boolean False True/False
refresh_credential_time Optional Specifies the refresh interval, in seconds, for credentials used by AWS and Azure VMs when connecting to AWS Bedrock and Azure AI without requiring external credentials. Applicable only if "api_type" is 'azure' or 'aws'. integer 0  

Not supported when 'api_type' is hugging_face.