Wyodrębnianie odpowiedzi

Wprowadzenie do generatywnej AI w Snowflake

James Cha-Earley

Senior Developer Advocate, Snowflake

Do czego służy wyodrębnianie odpowiedzi?

Identyfikowanie skarg
Wyodrębnianie opinii o udogodnieniach
Odpowiadanie na pytania na podstawie długich dokumentów

Dokument ze znakiem zapytania otoczonym emotikonami z uśmiechniętymi lub smutnymi twarzami, symbolizujący brak wiedzy o tym, czego dotyczy każda recenzja

Częsty problem biznesowy

review = """
The property needs updating and management needs to hire more staff. 
The staff does everything they can but it is not enough for the number of guests. 
The rooms look old as well as everything in the bathrooms. 
Definitely better options in the hotel zone.
"""

Snowflake Cortex przychodzi z pomocą!

Wyodrębnianie odpowiedzi

from snowflake.cortex import extract_answer


response = extract_answer(
    from_text=review,
    question="What did the guest complain about?"
)

Wynik

print(response)

[
    {
    "answer": "Management needs to hire more staff.",
    "score": 0.8013839254
    }
]

Wynik (score) w przedziale od 0 do 1

Budowanie przepływu pracy

SELECT DESCRIPTION
FROM HOTELS.REVIEWS
WHERE RATING < 6
    AND DATE = '2023-08-23';

Wynik SQL

I will never book a vacation through Expedia not only did I pay over 5;000 dollars
but they false advertise the resort; in my reservation It clearly stated that
breakfast and dinner was included. When I got to the resort they informed me that 
these issues have happed before with Expedia because the resort does not offer an
all exclusive. After flighting practically all day I called Expedia and they had me
on hold for 45min and nothing got resolved. I ended up spending over 1000.00 more
just on food. I am beyond me they are not only false advertising but refused to
take any responsibility on their part for the issues they caused me and my family.  Again I will never chose Expedia to plan a vacation!!!

Zadawanie pytania

negative_review = dataframe_1.to_pandas()['DESCRIPTION'].iloc[0]


response = extract_answer(
    from_text=negative_review,
    question="What was the primary issue that the guest mentioned?"
)

print(response)

Analiza odpowiedzi

[
    {
    "answer" : "Expedia falsely advertised that meals were included, but the
                resort did not offer an all-inclusive package.",
    "score": 0.75829312442
    }
]

Ograniczenia

Może zwracać fragmentaryczne lub niejasne sformułowania
Najlepiej działa na akapitach, a nie dokumentach wielotematycznych
Zawsze sprawdzaj kluczowe wyniki

Znak ostrzegawczy

Czas na praktykę!

Wprowadzenie do generatywnej AI w Snowflake