Génération de texte

L'API Gemini peut générer une sortie de texte à partir d'entrées de texte, d'images, de vidéos et audio.

Voici un exemple de base :

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How does AI work?"
  }'

Réflexion avec Gemini

Les modèles Gemini sont souvent activés par défaut, ce qui leur permet de raisonner avant de répondre à une requête.

Chaque modèle est compatible avec différentes configurations de réflexion, ce qui vous permet de contrôler les coûts, la latence et l'intelligence. Pour en savoir plus, consultez le guide de réflexion.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How does AI work?",
    "generation_config": {
      "thinking_level": "low"
    }
  }'

Instructions système et autres configurations

Vous pouvez guider le comportement des modèles Gemini à l'aide d'instructions système. Transmettez un paramètre system_instruction pour configurer le comportement du modèle.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "system_instruction": "You are a cat. Your name is Neko.",
    "input": "Hello there"
  }'

Vous pouvez également remplacer les paramètres de génération par défaut, tels que la température, à l'aide du paramètre generation_config.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Explain how AI works",
    "generation_config": {
      "temperature": 0.1
    }
  }'

Consultez la documentation de référence de l'API Interactions pour obtenir la liste complète des paramètres configurables et leur description.

Entrées multimodales

L'API Gemini est compatible avec les entrées multimodales, ce qui vous permet de combiner du texte avec des fichiers multimédias. L'exemple suivant montre comment fournir une image :

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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,
        mime_type: 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:
# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -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"
      }
    ]
  }'

Pour découvrir d'autres méthodes permettant de fournir des images et un traitement d'image plus avancé, consultez notre guide sur la compréhension des images. L'API est également compatible avec les entrées et la compréhension de documents, de vidéos et audio.

Réponses en streaming

Par défaut, le modèle ne renvoie une réponse qu'une fois l'ensemble du processus de génération terminé.

Pour des interactions plus fluides, utilisez le streaming pour gérer les blocs de réponse au fur et à mesure de leur génération.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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.event_type === "step.delta") {
      if (event.delta.type === "text") {
        process.stdout.write(event.delta.text);
      }
    }
  }
}

await main();

REST

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?alt=sse" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  --no-buffer \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "Explain how AI works",
    "stream": true
  }'

Conversations multitours

L'API Interactions est compatible avec les conversations multitours en enchaînant les interactions à l'aide de previous_interaction_id. Chaque tour est une interaction distincte, et l'API gère automatiquement l'historique des conversations.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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?",
    previous_interaction_id: interaction1.id,
  });
  console.log("Response 2:", interaction2.steps.at(-1).content[0].text);
}

await main();

REST

# Specifies the API revision to avoid breaking changes when they become default
RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have 2 dogs in my house."
  }')

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

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have two dogs in my house. How many paws are in my house?",
    "previous_interaction_id": "'$INTERACTION_ID'"
  }'

Le streaming peut également être utilisé pour les conversations multitours en combinant previous_interaction_id avec les méthodes de streaming.

Python

# This will only work for SDK newer than 2.0.0
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

// This will only work for SDK newer than 2.0.0
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?",
    previous_interaction_id: interaction1.id,
    stream: true,
  });
  for await (const event of stream) {
    if (event.event_type === "step.delta") {
      if (event.delta.type === "text") {
        process.stdout.write(event.delta.text);
      }
    }
  }
}

await main();

REST

# Specifies the API revision to avoid breaking changes when they become default
RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "I have 2 dogs in my house."
  }')
INTERACTION_ID=$(echo "$RESPONSE1" | jq -r '.id')

# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions?alt=sse" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  --no-buffer \
  -d '{
    "model": "gemini-3-flash-preview",
    "input": "How many paws are in my house?",
    "previous_interaction_id": "'$INTERACTION_ID'",
    "stream": true
  }'

Conversations sans état

Par défaut, l'API Interactions gère l'état des conversations côté serveur lorsque vous utilisez previous_interaction_id. Toutefois, vous pouvez également fonctionner en mode sans état en gérant vous-même l'historique des conversations côté client.

Pour utiliser le mode sans état : 1. Définissez store=false dans votre requête pour désactiver le stockage côté serveur. 2. Conservez l'historique des conversations sous forme de tableau d'étapes côté client. 3. Dans les requêtes suivantes, transmettez les étapes accumulées dans le champ input, puis ajoutez votre nouveau tour en tant qu'étape user_input.

Python

# This will only work for SDK newer than 2.0.0
from google import genai

client = genai.Client()

# Initialize history with the first user turn
history = [
    {
        "type": "user_input",
        "content": [{"type": "text", "text": "I have 2 dogs in my house."}]
    }
]

# Turn 1: Send request with store=False
interaction1 = client.interactions.create(
    model="gemini-3-flash-preview",
    store=False,
    input=history
)
print("Response 1:", interaction1.steps[-1].content[0].text)

# Append the model's response steps to history
for step in interaction1.steps:
    # Convert the SDK Step object to a dictionary
    history.append(step.model_dump())

# Append the next user turn as a user_input step
history.append({
    "type": "user_input",
    "content": [{"type": "text", "text": "How many paws are in my house?"}]
})

# Turn 2: Send full history with store=False
interaction2 = client.interactions.create(
    model="gemini-3-flash-preview",
    store=False,
    input=history
)
print("Response 2:", interaction2.steps[-1].content[0].text)

JavaScript

// This will only work for SDK newer than 2.0.0
import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});

async function main() {
  // Initialize history with the first user turn
  const history = [
    {
      type: "user_input",
      content: [{ type: "text", text: "I have 2 dogs in my house." }]
    }
  ];

  // Turn 1: Send request with store: false
  const interaction1 = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    store: false,
    input: history
  });
  console.log("Response 1:", interaction1.steps.at(-1).content[0].text);

  // Append model response steps to history
  history.push(...interaction1.steps);

  // Append the next user turn
  history.push({
    type: "user_input",
    content: [{ type: "text", text: "How many paws are in my house?" }]
  });

  // Turn 2: Send full history with store: false
  const interaction2 = await ai.interactions.create({
    model: "gemini-3-flash-preview",
    store: false,
    input: history
  });
  console.log("Response 2:", interaction2.steps.at(-1).content[0].text);
}

await main();

REST

# Turn 1: Send request with store: false
# Specifies the API revision to avoid breaking changes when they become default
RESPONSE1=$(curl -s -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d '{
    "model": "gemini-3-flash-preview",
    "store": false,
    "input": [
      {
        "type": "user_input",
        "content": [{"type": "text", "text": "I have 2 dogs in my house."}]
      }
    ]
  }')

# Extract the steps from response
MODEL_STEPS=$(echo "$RESPONSE1" | jq '.steps')

# Reconstruct the full history for Turn 2 by combining:
# 1. First user input
# 2. Model response steps
# 3. Second user input
HISTORY=$(jq -n \
  --argjson first_input '[{"type": "user_input", "content": [{"type": "text", "text": "I have 2 dogs in my house."}]}]' \
  --argjson model_steps "$MODEL_STEPS" \
  --argjson second_input '[{"type": "user_input", "content": [{"type": "text", "text": "How many paws are in my house?"}]}]' \
  "'"'"'$first_input + $model_steps + $second_input'"'"'")

# Turn 2: Send the full history
# Specifies the API revision to avoid breaking changes when they become default
curl -X POST "https://generativelanguage.googleapis.com/v1beta/interactions" \
  -H "x-goog-api-key: $GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -H "Api-Revision: 2026-05-20" \
  -d "{
    \"model\": \"gemini-3-flash-preview\",
    \"store\": false,
    \"input\": $HISTORY
  }"

Conseils pour écrire des prompts

Consultez notre guide d'ingénierie des prompts pour obtenir des suggestions sur la façon de tirer le meilleur parti de Gemini.

Étape suivante