Text summarization
One really common use case for using OpenAI 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 a chat completion model.
Questo esercizio fa parte del corso
Working with the OpenAI API
Istruzioni dell'esercizio
- Use an f-string to insert
finance_textintoprompt. - Create a request, sending the
promptprovided; use a maximum of400tokens.
Esercizio pratico interattivo
Prova a risolvere questo esercizio completando il codice di esempio.
client = OpenAI(api_key="")
# 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 Completions endpoint
response = client.chat.completions.create(
model="gpt-4o-mini",
messages=[{"role": "user", "content": prompt}],
____
)
print(response.choices[0].message.content)