Stripping outputs of thoughts
One of the main strengths of reasoning models is their thought process, captured in their thinking tokens. However, storing and processing all of these extra tokens can become problematic in multi-turn conversations in chatbot applications.
One approach is to strip model outputs of their "thoughts" (the thinking content), which you can do with regular expressions (RegEx). Have a try doing this on an example response stored in the response_content string.
Este ejercicio forma parte del curso
Working with DeepSeek in Python
Instrucciones del ejercicio
- Remove the thinking tokens and tags from the
response_contentstring using the RegEx pattern provided. - Strip
final_responseof leading and trailing whitespace.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
import re
# Remove the thinking tokens and tags
final_response = re.____(r'[\s\S]*?<\/think>\s*', ____, ____, re.DOTALL)
# Strip final_response of whitespace
print(final_response.____())