Génération de texte

L'API Gemini peut générer une sortie textuelle à partir de diverses entrées, y compris du texte, des images, des vidéos et de l'audio, en exploitant les modèles Gemini.

Voici un exemple de base qui utilise une seule entrée textuelle:

Python

from google import genai

client = genai.Client(api_key="GEMINI_API_KEY")

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=["How does AI work?"]
)
print(response.text)

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: "How does AI work?",
  });
  console.log(response.text);
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  result, _ := client.Models.GenerateContent(
      ctx,
      "gemini-2.0-flash",
      genai.Text("Explain how AI works in a few words"),
      nil,
  )

  fmt.Println(result.Text())
}

REST

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "contents": [
      {
        "parts": [
          {
            "text": "How does AI work?"
          }
        ]
      }
    ]
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const payload = {
    contents: [
      {
        parts: [
          { text: 'How AI does work?' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

Instructions et configuration système

Vous pouvez orienter le comportement des modèles Gemini à l'aide d'instructions système. Pour ce faire, transmettez un objet GenerateContentConfig.

Python

from google import genai
from google.genai import types

client = genai.Client(api_key="GEMINI_API_KEY")

response = client.models.generate_content(
    model="gemini-2.0-flash",
    config=types.GenerateContentConfig(
        system_instruction="You are a cat. Your name is Neko."),
    contents="Hello there"
)

print(response.text)

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: "Hello there",
    config: {
      systemInstruction: "You are a cat. Your name is Neko.",
    },
  });
  console.log(response.text);
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  config := &genai.GenerateContentConfig{
      SystemInstruction: genai.NewContentFromText("You are a cat. Your name is Neko.", genai.RoleUser),
  }

  result, _ := client.Models.GenerateContent(
      ctx,
      "gemini-2.0-flash",
      genai.Text("Hello there"),
      config,
  )

  fmt.Println(result.Text())
}

REST

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
    "system_instruction": {
      "parts": [
        {
          "text": "You are a cat. Your name is Neko."
        }
      ]
    },
    "contents": [
      {
        "parts": [
          {
            "text": "Hello there"
          }
        ]
      }
    ]
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const systemInstruction = {
    parts: [{
      text: 'You are a cat. Your name is Neko.'
    }]
  };

  const payload = {
    systemInstruction,
    contents: [
      {
        parts: [
          { text: 'Hello there' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

L'objet GenerateContentConfig vous permet également de remplacer les paramètres de génération par défaut, tels que la température.

Python

from google import genai
from google.genai import types

client = genai.Client(api_key="GEMINI_API_KEY")

response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=["Explain how AI works"],
    config=types.GenerateContentConfig(
        max_output_tokens=500,
        temperature=0.1
    )
)
print(response.text)

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: "Explain how AI works",
    config: {
      maxOutputTokens: 500,
      temperature: 0.1,
    },
  });
  console.log(response.text);
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
    APIKey:  os.Getenv("GEMINI_API_KEY"),
    Backend: genai.BackendGeminiAPI,
  })

  temp := float32(0.9)
  topP := float32(0.5)
  topK := float32(20.0)
  maxOutputTokens := int32(100)

  config := &genai.GenerateContentConfig{
    Temperature:       &temp,
    TopP:              &topP,
    TopK:              &topK,
    MaxOutputTokens:   maxOutputTokens,
    ResponseMIMEType:  "application/json",
  }

  result, _ := client.Models.GenerateContent(
    ctx,
    "gemini-2.0-flash",
    genai.Text("What is the average size of a swallow?"),
    config,
  )

  fmt.Println(result.Text())
}

REST

curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "contents": [
      {
        "parts": [
          {
            "text": "Explain how AI works"
          }
        ]
      }
    ],
    "generationConfig": {
      "stopSequences": [
        "Title"
      ],
      "temperature": 1.0,
      "maxOutputTokens": 800,
      "topP": 0.8,
      "topK": 10
    }
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const generationConfig = {
    temperature: 1,
    topP: 0.95,
    topK: 40,
    maxOutputTokens: 8192,
    responseMimeType: 'text/plain',
  };

  const payload = {
    generationConfig,
    contents: [
      {
        parts: [
          { text: 'Explain how AI works in a few words' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

Consultez GenerateContentConfig dans notre documentation de référence de l'API pour obtenir la liste complète des paramètres configurables et leurs descriptions.

Entrées multimodales

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

Python

from PIL import Image
from google import genai

client = genai.Client(api_key="GEMINI_API_KEY")

image = Image.open("/path/to/organ.png")
response = client.models.generate_content(
    model="gemini-2.0-flash",
    contents=[image, "Tell me about this instrument"]
)
print(response.text)

JavaScript

import {
  GoogleGenAI,
  createUserContent,
  createPartFromUri,
} from "@google/genai";

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const image = await ai.files.upload({
    file: "/path/to/organ.png",
  });
  const response = await ai.models.generateContent({
    model: "gemini-2.0-flash",
    contents: [
      createUserContent([
        "Tell me about this instrument",
        createPartFromUri(image.uri, image.mimeType),
      ]),
    ],
  });
  console.log(response.text);
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  imagePath := "/path/to/organ.jpg"
  imgData, _ := os.ReadFile(imagePath)

  parts := []*genai.Part{
      genai.NewPartFromText("Tell me about this instrument"),
      &genai.Part{
          InlineData: &genai.Blob{
              MIMEType: "image/jpeg",
              Data:     imgData,
          },
      },
  }

  contents := []*genai.Content{
      genai.NewContentFromParts(parts, genai.RoleUser),
  }

  result, _ := client.Models.GenerateContent(
      ctx,
      "gemini-2.0-flash",
      contents,
      nil,
  )

  fmt.Println(result.Text())
}

REST

# Use a temporary file to hold the base64 encoded image data
TEMP_B64=$(mktemp)
trap 'rm -f "$TEMP_B64"' EXIT
base64 $B64FLAGS $IMG_PATH > "$TEMP_B64"

# Use a temporary file to hold the JSON payload
TEMP_JSON=$(mktemp)
trap 'rm -f "$TEMP_JSON"' EXIT

cat > "$TEMP_JSON" << EOF
{
  "contents": [
    {
      "parts": [
        {
          "text": "Tell me about this instrument"
        },
        {
          "inline_data": {
            "mime_type": "image/jpeg",
            "data": "$(cat "$TEMP_B64")"
          }
        }
      ]
    }
  ]
}
EOF

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY" \
  -H 'Content-Type: application/json' \
  -X POST \
  -d "@$TEMP_JSON"

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const imageUrl = 'http://image/url';
  const image = getImageData(imageUrl);
  const payload = {
    contents: [
      {
        parts: [
          { image },
          { text: 'Tell me about this instrument' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

function getImageData(url) {
  const blob = UrlFetchApp.fetch(url).getBlob();

  return {
    mimeType: blob.getContentType(),
    data: Utilities.base64Encode(blob.getBytes())
  };
}

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

Réponses en streaming

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

Pour des interactions plus fluides, utilisez le streaming pour recevoir des instances GenerateContentResponse de manière incrémentielle à mesure qu'elles sont générées.

Python

from google import genai

client = genai.Client(api_key="GEMINI_API_KEY")

response = client.models.generate_content_stream(
    model="gemini-2.0-flash",
    contents=["Explain how AI works"]
)
for chunk in response:
    print(chunk.text, end="")

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const response = await ai.models.generateContentStream({
    model: "gemini-2.0-flash",
    contents: "Explain how AI works",
  });

  for await (const chunk of response) {
    console.log(chunk.text);
  }
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  stream := client.Models.GenerateContentStream(
      ctx,
      "gemini-2.0-flash",
      genai.Text("Write a story about a magic backpack."),
      nil,
  )

  for chunk, _ := range stream {
      part := chunk.Candidates[0].Content.Parts[0]
      fmt.Print(part.Text)
  }
}

REST

curl "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?alt=sse&key=${GEMINI_API_KEY}" \
  -H 'Content-Type: application/json' \
  --no-buffer \
  -d '{
    "contents": [
      {
        "parts": [
          {
            "text": "Explain how AI works"
          }
        ]
      }
    ]
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const payload = {
    contents: [
      {
        parts: [
          { text: 'Explain how AI works' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

Conversations multitours (chat)

Nos SDK offrent la possibilité de collecter plusieurs séries d'invites et de réponses dans une discussion, ce qui vous permet de suivre facilement l'historique des conversations.

Python

from google import genai

client = genai.Client(api_key="GEMINI_API_KEY")
chat = client.chats.create(model="gemini-2.0-flash")

response = chat.send_message("I have 2 dogs in my house.")
print(response.text)

response = chat.send_message("How many paws are in my house?")
print(response.text)

for message in chat.get_history():
    print(f'role - {message.role}',end=": ")
    print(message.parts[0].text)

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const chat = ai.chats.create({
    model: "gemini-2.0-flash",
    history: [
      {
        role: "user",
        parts: [{ text: "Hello" }],
      },
      {
        role: "model",
        parts: [{ text: "Great to meet you. What would you like to know?" }],
      },
    ],
  });

  const response1 = await chat.sendMessage({
    message: "I have 2 dogs in my house.",
  });
  console.log("Chat response 1:", response1.text);

  const response2 = await chat.sendMessage({
    message: "How many paws are in my house?",
  });
  console.log("Chat response 2:", response2.text);
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  history := []*genai.Content{
      genai.NewContentFromText("Hi nice to meet you! I have 2 dogs in my house.", genai.RoleUser),
      genai.NewContentFromText("Great to meet you. What would you like to know?", genai.RoleModel),
  }

  chat, _ := client.Chats.Create(ctx, "gemini-2.0-flash", nil, history)
  res, _ := chat.SendMessage(ctx, genai.Part{Text: "How many paws are in my house?"})

  if len(res.Candidates) > 0 {
      fmt.Println(res.Candidates[0].Content.Parts[0].Text)
  }
}

REST

curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=$GEMINI_API_KEY \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [
          {
            "text": "Hello"
          }
        ]
      },
      {
        "role": "model",
        "parts": [
          {
            "text": "Great to meet you. What would you like to know?"
          }
        ]
      },
      {
        "role": "user",
        "parts": [
          {
            "text": "I have two dogs in my house. How many paws are in my house?"
          }
        ]
      }
    ]
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const payload = {
    contents: [
      {
        role: 'user',
        parts: [
          { text: 'Hello' },
        ],
      },
      {
        role: 'model',
        parts: [
          { text: 'Great to meet you. What would you like to know?' },
        ],
      },
      {
        role: 'user',
        parts: [
          { text: 'I have two dogs in my house. How many paws are in my house?' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

Le streaming peut également être utilisé pour les conversations multitours.

Python

from google import genai

client = genai.Client(api_key="GEMINI_API_KEY")
chat = client.chats.create(model="gemini-2.0-flash")

response = chat.send_message_stream("I have 2 dogs in my house.")
for chunk in response:
    print(chunk.text, end="")

response = chat.send_message_stream("How many paws are in my house?")
for chunk in response:
    print(chunk.text, end="")

for message in chat.get_history():
    print(f'role - {message.role}', end=": ")
    print(message.parts[0].text)

JavaScript

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

const ai = new GoogleGenAI({ apiKey: "GEMINI_API_KEY" });

async function main() {
  const chat = ai.chats.create({
    model: "gemini-2.0-flash",
    history: [
      {
        role: "user",
        parts: [{ text: "Hello" }],
      },
      {
        role: "model",
        parts: [{ text: "Great to meet you. What would you like to know?" }],
      },
    ],
  });

  const stream1 = await chat.sendMessageStream({
    message: "I have 2 dogs in my house.",
  });
  for await (const chunk of stream1) {
    console.log(chunk.text);
    console.log("_".repeat(80));
  }

  const stream2 = await chat.sendMessageStream({
    message: "How many paws are in my house?",
  });
  for await (const chunk of stream2) {
    console.log(chunk.text);
    console.log("_".repeat(80));
  }
}

await main();

Go

package main

import (
  "context"
  "fmt"
  "os"
  "google.golang.org/genai"
)

func main() {

  ctx := context.Background()
  client, _ := genai.NewClient(ctx, &genai.ClientConfig{
      APIKey:  os.Getenv("GEMINI_API_KEY"),
      Backend: genai.BackendGeminiAPI,
  })

  history := []*genai.Content{
      genai.NewContentFromText("Hi nice to meet you! I have 2 dogs in my house.", genai.RoleUser),
      genai.NewContentFromText("Great to meet you. What would you like to know?", genai.RoleModel),
  }

  chat, _ := client.Chats.Create(ctx, "gemini-2.0-flash", nil, history)
  stream := chat.SendMessageStream(ctx, genai.Part{Text: "How many paws are in my house?"})

  for chunk, _ := range stream {
      part := chunk.Candidates[0].Content.Parts[0]
      fmt.Print(part.Text)
  }
}

REST

curl https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?alt=sse&key=$GEMINI_API_KEY \
  -H 'Content-Type: application/json' \
  -X POST \
  -d '{
    "contents": [
      {
        "role": "user",
        "parts": [
          {
            "text": "Hello"
          }
        ]
      },
      {
        "role": "model",
        "parts": [
          {
            "text": "Great to meet you. What would you like to know?"
          }
        ]
      },
      {
        "role": "user",
        "parts": [
          {
            "text": "I have two dogs in my house. How many paws are in my house?"
          }
        ]
      }
    ]
  }'

Apps Script

// See https://developers.google.com/apps-script/guides/properties
// for instructions on how to set the API key.
const apiKey = PropertiesService.getScriptProperties().getProperty('GEMINI_API_KEY');

function main() {
  const payload = {
    contents: [
      {
        role: 'user',
        parts: [
          { text: 'Hello' },
        ],
      },
      {
        role: 'model',
        parts: [
          { text: 'Great to meet you. What would you like to know?' },
        ],
      },
      {
        role: 'user',
        parts: [
          { text: 'I have two dogs in my house. How many paws are in my house?' },
        ],
      },
    ],
  };

  const url = `https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:streamGenerateContent?key=${apiKey}`;
  const options = {
    method: 'POST',
    contentType: 'application/json',
    payload: JSON.stringify(payload)
  };

  const response = UrlFetchApp.fetch(url, options);
  const data = JSON.parse(response);
  const content = data['candidates'][0]['content']['parts'][0]['text'];
  console.log(content);
}

Modèles compatibles

Tous les modèles de la famille Gemini sont compatibles avec la génération de texte. Pour en savoir plus sur les modèles et leurs fonctionnalités, consultez la page Modèles.

Bonnes pratiques

Conseils concernant les requêtes

Pour la génération de texte de base, une invite sans entraînement suffit souvent, sans avoir besoin d'exemples, d'instructions système ni de mise en forme spécifique.

Pour obtenir des résultats plus personnalisés:

  • Utilisez les instructions système pour guider le modèle.
  • Fournissez quelques exemples d'entrées et de sorties pour guider le modèle. On parle souvent de requêtes few-shot.
  • Envisagez d'effectuer un ajustement fin pour les cas d'utilisation avancés.

Pour en savoir plus, consultez notre guide d'ingénierie des requêtes.

Résultat structuré

Dans certains cas, vous devrez peut-être obtenir une sortie structurée, comme JSON. Pour en savoir plus, consultez notre guide sur les sorties structurées.

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