Parse LLM Output

PromptFormatter provides methods to parse a Value from the output string returned by the LLM.

Internally, it uses the ValueFormatter, so for more details, refer to Parsing the Value.

PromptFormatter has a parameter named output_formatter of type ValueFormatter. This parameter is used to convert a Value to the output string from LLM and vice versa.

Converting Output to a Python Object

Let's try converting the output to a Python object. Using the formatter.parse method, you can parse the output string from the LLM using the output parameters of the prompt. The result of the parsing is stored in a Python dict.

The prompt named summarizer used on this page was created in Prompt Example and has two output parameters, summary and keywords.

If summary or keywords are not found during parsing, a ValueError occurs, and if there is an invalid syntax, a SyntaxError will be raised.

import promptogen as pg

formatter = pg.KeyValuePromptFormatter()

raw_resp = """summary: "This is a summary of the text."
keywords: ['sample', 'text', 'summarize']"""
summarized_resp = formatter.parse(summarizer, raw_resp)
print(summarized_resp)

Console Output:

{'summary': 'This is a summary of the text.', 'keywords': ['sample', 'text', 'summarize']}