Generazione di testo

L'API Gemini può generare output di testo da input di testo, immagini, video e audio.

Ecco un esempio di base:

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="How does AI work?"
)
print(interaction.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "How does AI work?",
  });
  console.log(interaction.steps.at(-1).content[0].text);
}

await main();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How does AI work?"
  }'

Pensare con Gemini

I modelli Gemini spesso hanno la "funzione di ragionamento" attivata per impostazione predefinita, il che consente al modello di ragionare prima di rispondere a una richiesta.

Ogni modello supporta configurazioni di pensiero diverse, il che ti consente di controllare costo, latenza e intelligenza. Per maggiori dettagli, consulta la guida al pensiero.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="How does AI work?",
    generation_config={
        "thinking_level": "low"
    }
)
print(interaction.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "How does AI work?",
    generation_config: {
      thinking_level: "low",
    },
  });
  console.log(interaction.steps.at(-1).content[0].text);
}

await main();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How does AI work?",
    "generation_config": {
      "thinking_level": "low"
    }
  }'

Istruzioni di sistema e altre configurazioni

Puoi guidare il comportamento dei modelli Gemini con le istruzioni di sistema. Passa un parametro system_instruction per configurare il comportamento del modello.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    system_instruction="You are a cat. Your name is Neko.",
    input="Hello there"
)

print(interaction.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "Hello there",
    system_instruction: "You are a cat. Your name is Neko.",
  });
  console.log(interaction.steps.at(-1).content[0].text);
}

await main();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "system_instruction": "You are a cat. Your name is Neko.",
    "input": "Hello there"
  }'

Puoi anche sostituire i parametri di generazione predefiniti, ad esempio la temperatura, utilizzando il parametro generation_config.

Python

from google import genai

client = genai.Client()

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input="Explain how AI works",
    generation_config={
        "temperature": 0.1
    }
)
print(interaction.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "Explain how AI works",
    generation_config: {
      temperature: 0.1,
    },
  });
  console.log(interaction.steps.at(-1).content[0].text);
}

await main();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Explain how AI works",
    "generation_config": {
      "temperature": 0.1
    }
  }'

Per un elenco completo dei parametri configurabili e delle relative descrizioni, consulta il riferimento all'API Interactions.

Input multimodali

L'API Gemini supporta input multimodali, consentendoti di combinare testo e file multimediali. L'esempio seguente mostra come fornire un'immagine:

Python

from google import genai

client = genai.Client()

uploaded_file = client.files.upload(file="path/to/organ.jpg")

interaction = client.interactions.create(
    model="gemini-3-flash-preview",
    input=[
        {"type": "text", "text": "Tell me about this instrument"},
        {
            "type": "image",
            "uri": uploaded_file.uri,
            "mime_type": uploaded_file.mime_type
        }
    ]
)
print(interaction.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const uploadedFile = await ai.files.upload({
    file: "path/to/organ.jpg",
    config: { mimeType: "image/jpeg" }
  });

  const interaction = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: [
      {type: "text", text: "Tell me about this instrument"},
      {
        type: "image",
        uri: uploadedFile.uri,
        mimeType: uploadedFile.mimeType
      }
    ],
  });
  console.log(interaction.steps.at(-1).content[0].text);
}

await main();

REST

# First upload the file using the Files API, then use the URI:
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": [
      {"type": "text", "text": "Tell me about this instrument"},
      {
        "type": "image",
        "uri": "YOUR_FILE_URI",
        "mime_type": "image/jpeg"
      }
    ]
  }'

Per metodi alternativi di fornitura di immagini ed elaborazione più avanzata delle immagini, consulta la nostra guida alla comprensione delle immagini. L'API supporta anche l'input e la comprensione di documenti, video e audio.

Risposte dinamiche

Per impostazione predefinita, il modello restituisce una risposta solo dopo il completamento dell'intero processo di generazione.

Per interazioni più fluide, utilizza lo streaming per gestire i blocchi di risposta man mano che vengono generati.

Python

from google import genai

client = genai.Client()

stream = client.interactions.create(
    model="gemini-3-flash-preview",
    input="Explain how AI works",
    stream=True
)
for event in stream:
    if event.event_type == "step.delta":
        if event.delta.type == "text":
            print(event.delta.text, end="")

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const stream = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "Explain how AI works",
    stream: true,
  });

  for await (const event of stream) {
    if (event.type === "step.delta") {
      if (event.delta.type === "text") {
        process.stdout.write(event.delta.text);
      }
    }
  }
}

await main();

REST

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?alt=sse" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  --no-buffer \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Explain how AI works",
    "stream": true
  }'

Conversazioni a più turni

L'API Interactions supporta le conversazioni multi-turno concatenando le interazioni utilizzando previous_interaction_id. Ogni turno è un'interazione separata e l'API gestisce automaticamente la cronologia delle conversazioni.

Python

from google import genai

client = genai.Client()

interaction1 = client.interactions.create(
    model="gemini-3-flash-preview",
    input="I have 2 dogs in my house.",
)
print(interaction1.steps[-1].content[0].text)

interaction2 = client.interactions.create(
    model="gemini-3-flash-preview",
    input="How many paws are in my house?",
    previous_interaction_id=interaction1.id,
)
print(interaction2.steps[-1].content[0].text)

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction1 = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "I have 2 dogs in my house.",
  });
  console.log("Response 1:", interaction1.steps.at(-1).content[0].text);

  const interaction2 = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "How many paws are in my house?",
    previousInteractionId: interaction1.id,
  });
  console.log("Response 2:", interaction2.steps.at(-1).content[0].text);
}

await main();

REST

RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have 2 dogs in my house."
  }')

INTERACTION_ID=$(echo "$RESPONSE1" | jq -r '.name')

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have two dogs in my house. How many paws are in my house?",
    "previous_interaction_id": "'$INTERACTION_ID'"
  }'

Lo streaming può essere utilizzato anche per conversazioni multi-turno combinando previous_interaction_id con i metodi di streaming.

Python

from google import genai

client = genai.Client()

interaction1 = client.interactions.create(
    model="gemini-3-flash-preview",
    input="I have 2 dogs in my house.",
)
print(interaction1.steps[-1].content[0].text)

stream = client.interactions.create(
    model="gemini-3-flash-preview",
    input="How many paws are in my house?",
    previous_interaction_id=interaction1.id,
    stream=True
)
for event in stream:
    if event.event_type == "step.delta":
        if event.delta.type == "text":
            print(event.delta.text, end="")

JavaScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  const interaction1 = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "I have 2 dogs in my house.",
  });
  console.log("Response 1:", interaction1.steps.at(-1).content[0].text);

  const stream = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    input: "How many paws are in my house?",
    previousInteractionId: interaction1.id,
    stream: true,
  });
  for await (const event of stream) {
    if (event.type === "step.delta") {
      if (event.delta.type === "text") {
        process.stdout.write(event.delta.text);
      }
    }
  }
}

await main();

REST

RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have 2 dogs in my house."
  }')
INTERACTION_ID=$(echo "$RESPONSE1" | jq -r '.name')

curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?alt=sse" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  --no-buffer \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How many paws are in my house?",
    "previous_interaction_id": "'$INTERACTION_ID'",
    "stream": true
  }'

Suggerimenti per i prompt

Consulta la nostra guida all'ingegneria dei prompt per suggerimenti su come ottenere il massimo da Gemini.

Passaggi successivi