Utilizing systems messages
Chat models support three different chat message roles:
- System: controls assistant's behavior
- User: instruct the assistant
- Assistant: response to user instruction
In this exercise, you'll begin to design an AI system for helping people learn new skills, using a system message to set an appropriate model behavior.
Cet exercice fait partie du cours
Working with DeepSeek in Python
Instructions
- Create a request using both system and user messages to create a study plan to learn to speak Dutch.
- Extract and print the assistant's text response.
Exercice interactif pratique
Essayez cet exercice en complétant cet exemple de code.
client = OpenAI(api_key="", base_url="https://api.together.xyz/v1")
# Create a request to the chat model
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V3",
max_tokens=150,
messages=[
{"role": ____,
"content": "You are a study planning assistant that creates plans for learning new skills. Only return the structured plan."},
{"____": "____",
"____": "I want to learn to speak Dutch."}
]
)
# Extract the assistant's text response
print(response.choices[0].____.____)