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Generación de texto

La API de Gemini puede generar salidas de texto a partir de varias entradas, como texto, imágenes, video y audio, aprovechando los modelos de Gemini.

Este es un ejemplo básico que toma una sola entrada de texto:

PythonJavaScriptGoRESTApps Script

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)

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();

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())
}

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?"
          }
        ]
      }
    ]
  }'

// 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);
}

Instrucciones y parámetros de configuración del sistema

Puedes guiar el comportamiento de los modelos de Gemini con instrucciones del sistema. Para ello, pasa un objeto GenerateContentConfig.

PythonJavaScriptGoRESTApps Script

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)

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();

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())
}

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"
          }
        ]
      }
    ]
  }'

// 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);
}

El objeto GenerateContentConfig también te permite anular los parámetros de generación predeterminados, como la temperatura.

PythonJavaScriptGoRESTApps Script

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)

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();

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())
}

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
    }
  }'

// 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);
}

Consulta GenerateContentConfig en nuestra referencia de la API para obtener una lista completa de los parámetros configurables y sus descripciones.

Entradas multimodales

La API de Gemini admite entradas multimodales, lo que te permite combinar texto con archivos multimedia. En el siguiente ejemplo, se muestra cómo proporcionar una imagen:

PythonJavaScriptGoRESTApps Script

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)

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();

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())
}

# 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"

// 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())
  };
}

Si deseas conocer métodos alternativos para proporcionar imágenes y un procesamiento de imágenes más avanzado, consulta nuestra guía de comprensión de imágenes. La API también admite entradas y comprensión de documentos, videos y audio.

Respuestas de transmisión

De forma predeterminada, el modelo devuelve una respuesta solo después de que se completa todo el proceso de generación.

Para obtener interacciones más fluidas, usa la transmisión para recibir instancias de GenerateContentResponse de forma incremental a medida que se generan.

PythonJavaScriptGoRESTApps Script

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="")

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();

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)
  }
}

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"
          }
        ]
      }
    ]
  }'

// 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);
}

Conversaciones de varios turnos (chat)

Nuestros SDKs proporcionan funcionalidad para recopilar varias rondas de instrucciones y respuestas en un chat, lo que te brinda una forma sencilla de hacer un seguimiento del historial de conversaciones.

PythonJavaScriptGoRESTApps Script

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)

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();

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)
  }
}

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?"
          }
        ]
      }
    ]
  }'

// 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);
}

La transmisión también se puede usar para conversaciones de varios turnos.

PythonJavaScriptGoRESTApps Script

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)

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();

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)
  }
}

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?"
          }
        ]
      }
    ]
  }'

// 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);
}

Modelos compatibles

Todos los modelos de la familia Gemini admiten la generación de texto. Para obtener más información sobre los modelos y sus funciones, visita la página Modelos.

Prácticas recomendadas

Sugerencias para las instrucciones

Para la generación de texto básica, a menudo es suficiente una instrucción sin ejemplos sin necesidad de ejemplos, instrucciones del sistema ni formato específico.

Para obtener resultados más personalizados, haz lo siguiente:

Usa las instrucciones del sistema para guiar el modelo.
Proporciona algunas entradas y salidas de ejemplo para guiar al modelo. Esto se denomina instrucciones con varios ejemplos.
Considera la optimización para casos de uso avanzados.

Consulta nuestra guía de ingeniería de instrucciones para obtener más sugerencias.

Resultados estructurados

En algunos casos, es posible que necesites un resultado estructurado, como JSON. Consulta nuestra guía de resultados estructurados para obtener información sobre cómo hacerlo.

¿Qué sigue?

Prueba el Colab de la API de Gemini para comenzar.
Explora las capacidades de comprensión de imágenes, videos, audios y documentos de Gemini.
Obtén información sobre las estrategias de instrucciones de archivos multimodales.