Esegui la migrazione dall'API PaLM all'API Gemini

Questa guida mostra come eseguire la migrazione del codice Python dall'API PaLM all'API Gemini. Con Gemini puoi generare sia conversazioni di testo che conversazioni multi-turno (chat), ma assicurati di controllare le tue risposte poiché potrebbero essere diverse dagli output di PaLM.

Riepilogo delle differenze delle API

  1. I nomi dei metodi sono cambiati. Anziché avere metodi separati per generare testo e chat, esiste un metodo generate_content che può fare entrambe le cose.
  2. Chat offre un metodo di supporto start_chat che semplifica la chat.
  3. Anziché funzioni autonome, le nuove API sono metodi della classe GenerativeModel.
  4. La struttura della risposta di output è stata modificata.
  5. Le categorie delle impostazioni di sicurezza sono cambiate. Per informazioni dettagliate, consulta la guida alle impostazioni di sicurezza.

Generazione del testo: di base

PaLM API 
pip install google-generativeai

import google.generativeai as palm
import os

palm.configure(
    api_key=os.environ['API_KEY'])

response = palm.generate_text(
    prompt="The opposite of hot is")
print(response.result) #  'cold.'
        
pip install google-generativeai

import google.generativeai as genai
import os

genai.configure(
    api_key=os.environ['API_KEY'])
model = genai.GenerativeModel(
    model_name='gemini-pro')

response = model.generate_content(
          'The opposite of hot is')
print(response.text)
    #  The opposite of hot is cold.'

Generazione del testo: parametri facoltativi

PaLM API 
pip install google-generativeai

import google.generativeai as palm
import os

palm.configure(
    api_key=os.environ['API_KEY'])

prompt = """
You are an expert at solving word
problems.

Solve the following problem:

I have three houses, each with three
cats. Each cat owns 4 mittens, and a hat.
Each mitten was knit from 7m of yarn,
each hat from 4m. How much yarn was
needed to make all the items?

Think about it step by step, and show
your work.
"""

completion = palm.generate_text(
    model=model,
    prompt=prompt,
    temperature=0,
    # The maximum length of response
    max_output_tokens=800,
)

print(completion.result)
        
pip install google-generativeai

import google.generativeai as genai
import os

genai.configure(
    api_key=os.environ['API_KEY'])
model = genai.GenerativeModel(
    model_name='gemini-pro')

prompt = """
You are an expert at solving word
problems.

Solve the following problem:

I have three houses, each with three
cats. Each cat owns 4 mittens, and a hat.
Each mitten was knit from 7m of yarn,
each hat from 4m. How much yarn was
needed to make all the items?

Think about it step by step, and show
your work.
"""

completion = model.generate_content(
    prompt,
    generation_config={
        'temperature': 0,
        'max_output_tokens': 800
    }
)

print(completion.text)

Chat: base

PaLM API 
pip install google-generativeai

import google.generativeai as palm
import os

palm.configure(
    api_key=os.environ['API_KEY'])

chat = palm.chat(
    messages=["Hello."])
print(chat.last)
    #  'Hello! What can I help you with?'
chat = chat.reply(
    "Just chillin'")
print(chat.last)
    #  'That's great! ...'
        
pip install google-generativeai

import google.generativeai as genai
import os

genai.configure(
    api_key=os.environ['API_KEY'])
model = genai.GenerativeModel(
    model_name='gemini-pro')
chat = model.start_chat()

response = chat.send_message(
          "Hello.")
print(response.text)
response = chat.send_message(
          "Just chillin'")
print(response.text)

Chat: cronologia delle conversazioni

PaLM API 
chat.messages

[{'author': '0', 'content': 'Hello'},
 {'author': '1', 'content': 'Hello! How can I help you today?'},
 {'author': '0', 'content': "Just chillin'"},
 {'author': '1',
  'content': "That's great! I'm glad you're able to relax and
      take some time for yourself. What are you up to today?"}]
        
chat.history

[parts {
   text: "Hello."
 }
 role: "user",
 parts {
   text: "Greetings! How may I assist you today?"
 }
 role: "assistant",
 parts {
   text: "Just chillin\'"
 }
 role: "user",
 parts {
   text: "That\'s great! I\'m glad to hear
   you\'re having a relaxing time.
   May I offer you any virtual entertainment
   or assistance? I can provide
   you with music recommendations, play
   games with you, or engage in a
   friendly conversation.\n\nAdditionally,
   I\'m capable of generating
   creative content, such as poems, stories,
   or even song lyrics.
   If you\'d like, I can surprise you with
   something unique.\n\nJust
   let me know what you\'re in the mood for,
   and I\'ll be happy to oblige."
 }
 role: "assistant"]

Chat: Temperatura

PaLM API 
# Setting temperature=1 usually produces more zany responses!
chat = palm.chat(messages="What should I eat for dinner tonight? List a few options", temperature=1)
chat.last

'Here are a few ideas ...
        
model = genai.GenerativeModel(model_name='gemini-pro')
chat = model.start_chat()

# Setting temperature=1 usually produces more zany responses!
response = chat.send_message(
        "What should I eat for dinner tonight? List a few options",
          generation_config={
          'temperature': 1.0
        })

print(response.text)

'1. Grilled Salmon with Roasted Vegetables: ...'

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