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Extracting the model’s thoughts

The model response content from the previous exercise's math_problem has been stored under response_content.

Note that this may differ from what you saw when you ran the exercise, as LLM outputs are inherently random (more on this in Chapter 2).

Your job is to separate thought from answer using regular expressions (RegEx).

Este ejercicio forma parte del curso

Working with DeepSeek in Python

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Instrucciones del ejercicio

  • Import the re built-in Python module.
  • Search for the model's thoughts in the response by looking for strings between two <think> tags using the RegEx provided.
  • Extract the first group from match using the .group() method ,and strip these thoughts of any leading and trailing whitespace.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

# Import the re module
import re

# Search for strings between think tags
match = re.____(r'(.*?)', ____, re.DOTALL)

# Extract the group from the match and strip whitespace
think_content = match.____(1).____()
print(think_content)
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