Text generation

Working with DeepSeek in Python

James Chapman

Curriculum Manager, DataCamp

  • Text most likely to complete the conversation
response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3",

messages=[{"role": "user", "content": "Hi! I'm James and I'm a Curriculum Manager at DataCamp."}]
) print(response.choices[0].message.content)
Hi James! It's great to meet you. As a **Curriculum Manager at DataCamp**, you must
play a key role in shaping the learning experience for data science and analytics
students. How can I assist you today?
  • Response is non-deterministic (inherently random)
Working with DeepSeek in Python

A customer support chatbot receiving two semantically similar requests.

1 Created with GPT-4o
Working with DeepSeek in Python

Controlling response randomness

  • temperature: control on determinism 0 (highly deterministic) to 2 (very random)
response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3",
    messages=[{"role": "user",
             "content": "Hi! I'm James and I'm a Curriculum Manager at DataCamp."}],

temperature=2
) print(response.choices[0].message.content)
Hi James! Welcome to DataCamp — it's great to connect with someone who works on
shaping learning experiences for data skills. What does your role typically involve
as a Curriculum Manager at **DataCamp?** Perhaps one-on95 kWielpulses.Z.blog.from...
Working with DeepSeek in Python

Text generation: marketing

prompt = "Generate a powerful tagline for a new electric vehicle 
that highlights innovation and sustainability."
response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V3",
    messages=[{"role": "user", "content": prompt}]
)

print(response.choices[0].message.content)
**"Drive the Future - Zero Emissions, Infinite Innovation."**  
This tagline captures the essence of cutting-edge technology and eco-conscious...
Working with DeepSeek in Python

Cleaning up responses

prompt = "Generate a powerful tagline for a new electric vehicle 
that highlights innovation and sustainability. Return only the tagline
without formatting."

# Create a request to the chat model
# ...
"Drive the Future - Clean, Smart, Electric."
Working with DeepSeek in Python

Text generation: product description

prompt = """Write a compelling e-commmerce product description for the UltraFit
Smartwatch in paragraph form. Highlight its key features:

10-day battery life, 24/7 heart rate and sleep tracking, built-in GPS, water
resistance up to 50 meters, and lightweight design.

Use a persuasive and engaging tone to appeal to fitness enthusiasts and busy
professionals.
"""

response = client.chat.completions.create( model="deepseek-ai/DeepSeek-V3", messages=[{"role": "user", "content": prompt}])
Working with DeepSeek in Python

Text generation: product description

print(response.choices[0].message.content)
"The UltraFit Smartwatch is your all-in-one health and fitness companion. 
Stay on top of your wellness with 24/7 heart rate and sleep tracking, 
while the built-in GPS keeps you on course during runs. 
With a 10-day battery life, you can track your progress without constant recharging. 
Designed for both workouts and daily wear, its  lightweight build and 50-meter
water resistance make it the perfect smartwatch for an active lifestyle."
  • Iterate! Add more details to the prompt and re-run the request
  • Next video → providing examples to the model
Working with DeepSeek in Python

Let's practice!

Working with DeepSeek in Python

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