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Text summarization

One really common use case for DeepSeek models is summarizing text. This has a ton of applications in business settings, including summarizing reports into concise one-pagers or a handful of bullet points, or extracting the next steps and timelines for different stakeholders.

In this exercise, you'll summarize a passage of text on financial investment (finance_text) into two concise bullet points using DeepSeek's chat model.

Este ejercicio forma parte del curso

Working with DeepSeek in Python

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Instrucciones del ejercicio

  • Use an f-string to insert finance_text into prompt.
  • Create a request, sending the prompt provided; use a maximum of 400 tokens.

Ejercicio interactivo práctico

Prueba este ejercicio y completa el código de muestra.

client = OpenAI(api_key="", base_url="https://api.together.xyz/v1")

# Use an f-string to format the prompt
prompt = f"""Summarize the following text into two concise bullet points:
{____}"""

# Create a request to the chat model
response = client.chat.completions.create(
  model="deepseek-ai/DeepSeek-V3",
  messages=[{"role": "user", "content": ____}],
  ____
)

print(response.choices[0].message.content)
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