Resumir y editar texto

Trabajar con DeepSeek en Python

James Chapman

AI Curriculum Lead, DataCamp

Resumen...

Preguntas y respuestas

response = client.chat.completions.create(
  model="deepseek-ai/DeepSeek-V4.1-Flash",
  messages=[{"role": "user", "content": "How many days are in October?"}]
)

print(response.choices[0].message.content)

October has **31 days**.  

It's one of the seven months in the Gregorian calendar with 31 days...

Edición de texto

Ejemplo: actualizar nombre, pronombres y cargo

prompt = """
Update name to Maarten, pronouns to he/him, and job title to Senior Content Developer
in the following text:

Joanne is a Content Developer at DataCamp. Her favorite programming language is R,
which she uses for her statistical analyses.
"""

Edición de texto

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4.1-Flash",

    messages=[{"role": "user", "content": prompt}]

)

print(response.choices[0].message.content)

Here's the updated text with the requested changes:

Maarten is a Senior Content Developer at DataCamp. His favorite programming language
is R, which he uses for his statistical analyses.

Let me know if you'd like any further adjustments!

Resumen de texto

Ejemplo: resumen de chats con clientes

Equipo de soporte al cliente

text = """
Customer: Hi, I'm trying to log into 
my account, but it keeps saying 
my password is incorrect. I'm sure 
I'm entering the right one.  

Support: I'm sorry to hear that! 
Have you tried resetting your password?  
...
"""

Resumen de texto

prompt = f"""Summarize the customer support chat 
             in three concise key points: {text}"""


response = client.chat.completions.create(
  model="deepseek-ai/DeepSeek-V4.1-Flash",
  messages=[{"role": "user", "content": prompt}]
)
print(response.choices[0].message.content)

1. **Login Issue**: Customer couldn't log in due to a password issue and missing reset link.  
2. **Password Reset Suggestion**: Support resent the reset email after confirming it was sent.  
3. **Prompt Assistance**: Customer resolved the issue by using Google sign-in.

Controlar la longitud de la respuesta

max_tokens = 5

response = client.chat.completions.create(
  model="deepseek-ai/DeepSeek-V4.1-Flash",
  messages=[{"role":"user",
      "content":"Write a haiku about AI."}],
  max_tokens=5
)

**Silent circuits hum

max_tokens = 30

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4.1-Flash",
    messages=[{"role":"user",
      "content":"Write a haiku about AI."}],
    max_tokens=30
)

**Silent circuits hum,**  
**thoughts of light and logic bloom—**  
**minds beyond our own.**

Entender los tokens

Tokens: unidades de texto que ayudan a la IA a comprender e interpretar el texto

La frase «How can the OpenAI API deliver business value?» con cada token resaltado con un color distinto.

¹ https://lunary.ai/deepseek-tokenizer

Calcular el coste

El coste de uso de la API depende de la plataforma, el modelo y el número de tokens 💰
- Los modelos se tarifican por coste/tokens
- Los tokens de entrada y salida pueden tener costes distintos
Aumentar max_tokens incrementa el coste 📈

Screenshot 2025-03-05 at 11.46.54.png

Calcular el coste

prompt = f"""Summarize the customer support chat 
             in three concise key points: {text}"""

max_tokens = 500

response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-V4.1-Flash",
    messages=[{"role": "user", "content": prompt}], 
    max_tokens=max_tokens
)

Calcular el coste

# Define price per token
input_token_price = 2.1 / 1_000_000
output_token_price = 4.4 / 1_000_000

# Extract token usage
input_tokens = response.usage.prompt_tokens

output_tokens = max_tokens

# Calculate cost
cost = (input_tokens * input_token_price + output_tokens * output_token_price)
print(f"Estimated cost: ${cost}")

Estimated cost: $0.0153964

¡Vamos a practicar!

Trabajar con DeepSeek en Python