टेक्स्ट जनरेट करना

Gemini API, Gemini मॉडल का इस्तेमाल करके, टेक्स्ट, इमेज, वीडियो, और ऑडियो जैसे अलग-अलग इनपुट से टेक्स्ट आउटपुट जनरेट कर सकता है.

यहां एक ऐसा बुनियादी उदाहरण दिया गया है जिसमें एक टेक्स्ट इनपुट लिया जाता है:

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(); 

शुरू करें

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); } 

सिस्टम के निर्देश और कॉन्फ़िगरेशन

सिस्टम के निर्देशों की मदद से, Gemini मॉडल के व्यवहार को कंट्रोल किया जा सकता है. ऐसा करने के लिए, GenerateContentConfig ऑब्जेक्ट पास करें.

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(); 

शुरू करें

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); } 

GenerateContentConfig ऑब्जेक्ट की मदद से, जनरेशन के डिफ़ॉल्ट पैरामीटर को बदला जा सकता है. जैसे, तापमान.

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(); 

शुरू करें

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); } 

कॉन्फ़िगर किए जा सकने वाले पैरामीटर और उनके ब्यौरे की पूरी सूची देखने के लिए, हमारे एपीआई रेफ़रंस में GenerateContentConfig देखें.

मल्टीमोडल इनपुट

Gemini API, अलग-अलग तरह के इनपुट के साथ काम करता है. इसकी मदद से, टेक्स्ट को मीडिया फ़ाइलों के साथ जोड़ा जा सकता है. इस उदाहरण में, इमेज जोड़ने का तरीका बताया गया है:

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(); 

शुरू करें

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())   }; } 

इमेज उपलब्ध कराने के अन्य तरीकों और इमेज प्रोसेस करने के बेहतर तरीके के बारे में जानने के लिए, इमेज को समझने से जुड़ी गाइड देखें. यह एपीआई, दस्तावेज़, वीडियो, और ऑडियो के इनपुट और समझने की सुविधा भी देता है.

जवाब स्ट्रीम करना

डिफ़ॉल्ट रूप से, मॉडल सिर्फ़ तब जवाब देता है, जब जनरेट करने की पूरी प्रोसेस पूरी हो जाती है.

बेहतर इंटरैक्शन के लिए, स्ट्रीमिंग का इस्तेमाल करें, ताकि GenerateContentResponse इंस्टेंस जनरेट होते ही, उन्हें धीरे-धीरे पाया जा सके.

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(); 

शुरू करें

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); } 

एक से ज़्यादा बार की गई बातचीत (Chat)

हमारे SDK, चैट में कई राउंड के प्रॉम्प्ट और जवाब इकट्ठा करने की सुविधा देते हैं. इससे आपको बातचीत के इतिहास को ट्रैक करने में आसानी होती है.

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(); 

शुरू करें

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); } 

स्ट्रीमिंग का इस्तेमाल, कई बार की जाने वाली बातचीत के लिए भी किया जा सकता है.

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(); 

शुरू करें

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); } 

काम करने वाले मॉडल

Gemini फ़ैमिली के सभी मॉडल, टेक्स्ट जनरेट करने की सुविधा के साथ काम करते हैं. मॉडल और उनकी सुविधाओं के बारे में ज़्यादा जानने के लिए, मॉडल पेज पर जाएं.

सबसे सही तरीके

प्रॉम्प्ट के बारे में सलाह

टेक्स्ट जनरेशन के बुनियादी लेवल के लिए, अक्सर ज़ीरो-शॉट प्रोम्प्ट काफ़ी होता है. इसके लिए, उदाहरणों, सिस्टम के निर्देशों या खास फ़ॉर्मैटिंग की ज़रूरत नहीं होती.

ज़्यादा काम के आउटपुट पाने के लिए:

  • मॉडल को निर्देश देने के लिए, सिस्टम के निर्देश का इस्तेमाल करें.
  • मॉडल को दिशा-निर्देश देने के लिए, इनपुट और आउटपुट के कुछ उदाहरण दें. इसे अक्सर फ़्यू-शॉट प्रॉम्प्टिंग कहा जाता है.
  • इस्तेमाल के बेहतर उदाहरणों के लिए, बेहतर तरीके से इस्तेमाल करें.

ज़्यादा सलाह पाने के लिए, प्रॉम्प्ट इंजीनियरिंग गाइड देखें.

स्ट्रक्चर्ड आउटपुट

कुछ मामलों में, आपको JSON जैसे स्ट्रक्चर्ड आउटपुट की ज़रूरत पड़ सकती है. इसके बारे में जानने के लिए, स्ट्रक्चर्ड आउटपुट की गाइड देखें.

आगे क्या करना है