Testing and refining system messages
At Redwood Consulting, the marketing team is promoting the annual Tech Forecast whitepaper on LinkedIn. Posts need to feel conversational yet professional, but your first iteration produced bland, hashtag-free posts. You’ll have to write an improved system message that delivers lively, on-brand content every time.
The anthropic library, client, content_request, and current_system strings are pre-loaded.
Diese Übung ist Teil des Kurses
Introduction to Claude Models
Anleitung zur Übung
- Set the rolefor the user's content request.
- Write an improved_systemmessage that addresses social media requirements, including to use emojis.
- Apply the improved_systemmessage to the final test.
Interaktive Übung
Vervollständige den Beispielcode, um diese Übung erfolgreich abzuschließen.
# Test current system message
test_response = client.messages.create(
    model="claude-3-7-sonnet-latest", max_tokens=75, system=current_system,
    messages=[{"role": ____, "content": content_request}])
print("Current output:", test_response.content[0].text)
# Create improved system message based on problems identified
improved_system = ____
final_response = client.messages.create(
          # Apply the improved system message
    model="claude-3-7-sonnet-latest", max_tokens=75, system=____,
    messages=[{"role": "user", "content": content_request}])
print("\nImproved output:", final_response.content[0].text)