Generowanie tekstu

Wprowadzenie do generatywnej AI w Snowflake

James Cha-Earley

Senior Developer Advocate, Snowflake

Zarządzanie odpowiedziami na recenzje hotelu

Hotel na wybrzeżu o zachodzie słońca

1 Obraz wygenerowany przez Google Gemini 2.5 Pro
Wprowadzenie do generatywnej AI w Snowflake

`summarize()`

long_review = """
This hotel was nothing short of amazing. The best views; the best location;
and the best staff. It's clean; conveniently located to other restaurants
on the strip; although we ate at the restaurants on site and each was so good
there's really no reason to leave. Ohhh the views. The beach was free of seaweed; 
amazingly clean and plenty of space; it wasn't crowded at all. 
Stay here; you will not regret it. Did I mention how comfortable the beds were. 
Yes save yourself trouble and stay here. It's really perfect.
"""

from snowflake.cortex import summarize summarized_review = summarize(text=long_review)
Wprowadzenie do generatywnej AI w Snowflake

Wyświetlanie podsumowania

print(summarized_review)
The hotel exceeded expectations with stunning views, exceptional staff,
comfortable beds, and top-notch on-site dining, making it a perfect and 
highly recommended stay.
Wprowadzenie do generatywnej AI w Snowflake

Pobieranie danych z bazy danych

Zapytanie SQL w komórce 1

Kod Pythona w komórce 2

Wprowadzenie do generatywnej AI w Snowflake

Generowanie odpowiedzi

from snowflake.cortex import complete


prompt = f"Write a short response to this hotel review: {latest_review}."
# Pass the prompt response = complete(prompt=prompt,
Wprowadzenie do generatywnej AI w Snowflake

Generowanie odpowiedzi

from snowflake.cortex import complete


prompt = f"Write a short response to this hotel review: {latest_review}."
# Specify the model response = complete(prompt=prompt, model='llama3.1-8b',
Wprowadzenie do generatywnej AI w Snowflake

Generowanie odpowiedzi

from snowflake.cortex import complete


prompt = f"Write a short response to this hotel review: {latest_review}."
# Set the temperature - control predictability of output response = complete(prompt=prompt, model='llama3.1-8b', options={ 'temperature':0.3,
Wprowadzenie do generatywnej AI w Snowflake

Generowanie odpowiedzi

from snowflake.cortex import complete


prompt = f"Write a short response to this hotel review: {latest_review}."
# Limit the number of tokens with max_tokens response = complete(prompt=prompt, model='llama3.1-8b', options={ 'temperature':0.3, 'max_tokens':150 } )
Wprowadzenie do generatywnej AI w Snowflake

Wyświetlanie odpowiedzi

print(response)
Thank you so much for sharing your wonderful experience at the Hyatt Nice! 
We're thrilled to hear that you had a fantastic stay with us.
  • Szybkie, elastyczne, autentyczne
Wprowadzenie do generatywnej AI w Snowflake

Generowanie tekstu z `AI_COMPLETE()`

SELECT
  DESCRIPTION,
  AI_COMPLETE(

'llama3.1-8b',
PROMPT('Write a short response to this hotel review: {0}.', DESCRIPTION),
{'temperature': 0.3, 'max_tokens': 150}
) AS completion FROM HOTELS.REVIEWS ORDER BY date DESC LIMIT 1;
Wprowadzenie do generatywnej AI w Snowflake

Wynik w notatniku Snowflake

Wynik działania AI_COMPLETE() w notatniku Snowflake

  • AI_COMPLETE() dostępna od razu
Wprowadzenie do generatywnej AI w Snowflake

Generowanie tekstu w Snowflake

-- Coding in SQL cells
AI_COMPLETE(
  'llama3.1-8b',
  PROMPT('Write a short response 
          to this hotel review: {0}.', 
          DESCRIPTION),
  {'temperature': 0.3, 
   'max_tokens': 150}
    )
  • Generowanie tekstu dla wielu wierszy
# Coding in Python cells
complete(
    model='llama3.1-8b', 
    prompt = f"""Write a short response
        to this hotel review: 
        {latest_review}.""",
    options={'temperature':0.3,
             'max_tokens':150}
    )
  • Łączenie wieloetapowych przepływów pracy
Wprowadzenie do generatywnej AI w Snowflake

Czas na ćwiczenia!

Wprowadzenie do generatywnej AI w Snowflake

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