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The ai.fix_grammar function uses generative AI to correct the spelling, grammar, and punctuation of input text, with a single line of code.
Note
- This article covers using ai.fix_grammar with PySpark. To use ai.fix_grammar with pandas, see this article.
- See other AI functions in this overview article.
- Learn how to customize the configuration of AI functions.
Overview
The ai.fix_grammar function is available for Spark DataFrames. You must specify the name of an existing input column as a parameter.
The function returns a new DataFrame that includes corrected text for each input text row, stored in an output column.
Syntax
df.ai.fix_grammar(input_col="input", output_col="corrections")
Parameters
| Name | Description |
|---|---|
input_col Required |
A string that contains the name of an existing column with input text values to correct for spelling, grammar, and punctuation. |
output_col Optional |
A string that contains the name of a new column to store corrected text for each row of input text. If you don't set this parameter, a default name generates for the output column. |
error_col Optional |
A string that contains the name of a new column to store any OpenAI errors that result from processing each row of input text. If you don't set this parameter, a default name generates for the error column. If there are no errors for a row of input, the value in this column is null. |
Returns
The function returns a Spark DataFrame that includes a new column that contains corrected text for each row of text in the input column. If the input text is null, the result is null.
Example
# This code uses AI. Always review output for mistakes.
df = spark.createDataFrame([
("There are an error here.",),
("She and me go weigh back. We used to hang out every weeks.",),
("The big picture are right, but you're details is all wrong.",)
], ["text"])
results = df.ai.fix_grammar(input_col="text", output_col="corrections")
display(results)
This example code cell provides the following output:
Related content
Detect sentiment with ai.analyze_sentiment.
Categorize text with ai.classify.
Generate vector embeddings with ai.embed.
Extract entities with ai_extract.
Fix grammar with ai.fix_grammar.
Answer custom user prompts with ai.generate_response.
Calculate similarity with ai.similarity.
Summarize text with ai.summarize.
Translate text with ai.translate.
Learn more about the full set of AI functions.
Customize the configuration of AI functions.
Did we miss a feature you need? Suggest it on the Fabric Ideas forum.