Creating a conversation history
An online math learning platform called Easy as Pi has contracted you to help them develop an AI tutor. You immediately see that you can build this application by utilizing DeepSeek's chat models, and start to design a simple proof-of-concept (POC) for the major stakeholders at the company to review.
To start, you'll demonstrate how responses to student messages can be stored in a message history, which will enable full conversations.
Este ejercicio forma parte del curso
Working with DeepSeek in Python
Instrucciones del ejercicio
- Send
messagesto the model in a chat request. - Extract the assistant message from
response, convert it to a message dictionary, and append it tomessages.
Ejercicio interactivo práctico
Prueba este ejercicio y completa el código de muestra.
client = OpenAI(api_key="", base_url="https://api.together.xyz/v1")
messages = [
{"role": "system", "content": "You are a helpful math tutor that generates concise, one-sentence responses."},
{"role": "user", "content": "Explain what pi is."}
]
# Send the chat messages to the model
response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V3",
messages=____,
max_tokens=100
)
# Extract the assistant message from the response
assistant_dict = {"role": "____", "content": ____}
# Add assistant_dict to the messages dictionary
messages.____(assistant_dict)
print(messages)