> ## Documentation Index > Fetch the complete documentation index at: https://apidoc.cometapi.com/llms.txt > Use this file to discover all available pages before exploring further. # Bruk Gemini-bildemodeller > Kall Gemini-bildemodeller (Nano Banana 2 / Pro) på CometAPI med Google Gen AI SDK for tekst-til-bilde, bilde-til-bilde og komposisjon med flere bilder. Denne veiledningen viser hvordan du bruker Gemini-bildemodeller via CometAPI med **Google Gen AI SDK**. Den dekker: * Tekst-til-bilde-generering * Bilde-til-bilde-redigering * Komposisjon med flere bilder * Lagring av genererte bilder - **Base URL:** `https://api.cometapi.com` - Installer SDK-en: `pip install google-genai` (Python) eller `npm install @google/genai` (Node.js) *** ## Oppsett Initialiser klienten med CometAPIs base URL: ```python Python theme={null} from google import genai from google.genai import types import os COMETAPI_KEY = os.environ["COMETAPI_KEY"] client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=COMETAPI_KEY, ) ``` ```javascript Node.js theme={null} import { GoogleGenAI } from "@google/genai"; const COMETAPI_KEY = process.env.COMETAPI_KEY; const ai = new GoogleGenAI({ apiKey: COMETAPI_KEY, httpOptions: { apiVersion: "v1beta", baseUrl: "https://api.cometapi.com" }, }); ``` ```go Go theme={null} package main import ( "context" "os" "google.golang.org/genai" ) func main() { ctx := context.Background() apiKey := os.Getenv("COMETAPI_KEY") client, _ := genai.NewClient(ctx, &genai.ClientConfig{ APIKey: apiKey, Backend: genai.BackendGeminiAPI, HTTPOptions: genai.HTTPOptions{ BaseURL: "https://api.cometapi.com", }, }) // use client below... } ``` *** ## Tekst-til-bilde-generering Generer et bilde fra en tekst Prompt og lagre det til en fil. ```python Python theme={null} from google import genai from google.genai import types from PIL import Image import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) response = client.models.generate_content( model="gemini-3.1-flash-image-preview", contents="Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme", config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], ), ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.text is not None: print(part.text) elif part.inline_data is not None: final_image = part.as_image() if final_image: final_image.save("generated_image.png") print("Image saved to generated_image.png") ``` ```javascript Node.js theme={null} import { GoogleGenAI } from "@google/genai"; import * as fs from "fs"; const ai = new GoogleGenAI({ apiKey: process.env.COMETAPI_KEY, httpOptions: { apiVersion: "v1beta", baseUrl: "https://api.cometapi.com" }, }); const response = await ai.models.generateContent({ model: "gemini-3.1-flash-image-preview", contents: "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme", config: { responseModalities: ["TEXT", "IMAGE"] }, }); let finalImagePart; for (const part of response.candidates[0].content.parts) { if (part.thought === true) { continue; } if (part.text) { console.log(part.text); } if (part.inlineData) { finalImagePart = part; } } if (finalImagePart) { const buffer = Buffer.from(finalImagePart.inlineData.data, "base64"); fs.writeFileSync("generated_image.png", buffer); console.log("Image saved to generated_image.png"); } ``` ```bash Shell theme={null} curl -s -X POST \ "https://api.cometapi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent" \ -H "Authorization: Bearer $COMETAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "contents": [{ "parts": [{"text": "Create a picture of a nano banana dish in a fancy restaurant with a Gemini theme"}] }], "generationConfig": { "responseModalities": ["TEXT", "IMAGE"] } }' ``` **Lagre den endelige bildedelen:** Bildedataene ligger i `candidates[0].content.parts`, som kan inneholde tekst- og/eller bildedeler. Gemini-bildemodeller kan også returnere mellomliggende thought-deler før det endelige bildet, spesielt når du ber om både tekst og bilder eller eksplisitt aktiverer thinking-utdata. Ikke lagre den første `inlineData` blindt; hopp over deler der `thought` er `true`, og lagre deretter den siste gjenværende bildedelen. Typisk respons med bare det endelige bildet: ```json theme={null} { "candidates": [{ "content": { "parts": [ { "text": "Here is your image..." }, { "inlineData": { "mimeType": "image/png", "data": "" } } ] } }] } ``` Respons med en tekstdel, et mellomliggende thought-bilde og det endelige bildet: ```json theme={null} { "candidates": [{ "content": { "role": "model", "parts": [ { "text": "Here is your image..." }, { "inlineData": { "mimeType": "image/jpeg", "data": "" }, "thought": true }, { "inlineData": { "mimeType": "image/jpeg", "data": "" }, "thought": false, "thoughtSignature": "" } ] }, "finishReason": "STOP" }] } ``` Bruk denne parseregelen for hver Gemini-bilderespons: ```javascript theme={null} const imageParts = response.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart = imageParts.at(-1); ``` *** ## Bilde-til-bilde-generering Last opp et inndatabilde og transformer det med en tekst-Prompt. ```python Python theme={null} from google import genai from google.genai import types from PIL import Image import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) # Load the source image source_image = Image.open("source.jpg") response = client.models.generate_content( model="gemini-3.1-flash-image-preview", contents=["Transform this into a watercolor painting", source_image], config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], ), ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.text is not None: print(part.text) elif part.inline_data is not None: final_image = part.as_image() if final_image: final_image.save("watercolor_output.png") ``` ```javascript Node.js theme={null} import { GoogleGenAI } from "@google/genai"; import * as fs from "fs"; const ai = new GoogleGenAI({ apiKey: process.env.COMETAPI_KEY, httpOptions: { apiVersion: "v1beta", baseUrl: "https://api.cometapi.com" }, }); const imageData = fs.readFileSync("source.jpg").toString("base64"); const response = await ai.models.generateContent({ model: "gemini-3.1-flash-image-preview", contents: [ { text: "Transform this into a watercolor painting" }, { inlineData: { mimeType: "image/jpeg", data: imageData } }, ], config: { responseModalities: ["TEXT", "IMAGE"] }, }); const imageParts = response.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart = imageParts.at(-1); if (finalImagePart) { fs.writeFileSync("watercolor_output.png", Buffer.from(finalImagePart.inlineData.data, "base64")); } ``` ```bash Shell theme={null} curl -s -X POST \ "https://api.cometapi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent" \ -H "Authorization: Bearer $COMETAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "contents": [{ "role": "user", "parts": [ { "text": "Transform this into a watercolor painting" }, { "inline_data": { "mime_type": "image/jpeg", "data": "" } } ] }], "generationConfig": { "responseModalities": ["TEXT", "IMAGE"] } }' ``` * Python SDK-en godtar `PIL.Image`-objekter direkte — ingen manuell Base64-koding er nødvendig. * Ikke inkluder prefikset `data:image/jpeg;base64,` når du sender rå Base64-strenger. *** ## Komponering med flere bilder Generer et nytt bilde fra flere inndatabilder. CometAPI støtter to tilnærminger: ### Metode 1: Ett kollasjbilde Kombiner flere kildebilder til én kollasj, og beskriv deretter ønsket utdata. Eksempel på inndatakollasj Generert utdata ```python Python theme={null} from google import genai from google.genai import types from PIL import Image import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) collage = Image.open("collage.jpg") response = client.models.generate_content( model="gemini-3.1-flash-image-preview", contents=[ "A model is posing and leaning against a pink BMW with a green alien keychain attached to a pink handbag, a pink parrot on her shoulder, and a pug wearing a pink collar and gold headphones", collage, ], config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], ), ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.inline_data is not None: final_image = part.as_image() if final_image: final_image.save("composition_output.png") ``` ```bash Shell theme={null} curl -s -X POST \ "https://api.cometapi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent" \ -H "Authorization: Bearer $COMETAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "contents": [{ "role": "user", "parts": [ { "text": "A model is posing and leaning against a pink BMW with a green alien keychain attached to a pink handbag, a pink parrot on her shoulder, and a pug wearing a pink collar and gold headphones" }, { "inline_data": { "mime_type": "image/jpeg", "data": "" } } ] }], "generationConfig": { "responseModalities": ["TEXT", "IMAGE"] } }' ``` ### Metode 2: Flere separate bilder (opptil 14) Send flere bilder direkte. Gemini 3-modeller støtter opptil 14 referansebilder (objekter + karakterer): ```python Python theme={null} from google import genai from google.genai import types from PIL import Image import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) image1 = Image.open("image1.jpg") image2 = Image.open("image2.jpg") image3 = Image.open("image3.jpg") response = client.models.generate_content( model="gemini-3.1-flash-image-preview", contents=["Merge the three images", image1, image2, image3], config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], ), ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.inline_data is not None: final_image = part.as_image() if final_image: final_image.save("merged_output.png") ``` ```bash Shell theme={null} curl -s -X POST \ "https://api.cometapi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent" \ -H "Authorization: Bearer $COMETAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "contents": [{ "role": "user", "parts": [ { "text": "Merge the three images" }, { "inline_data": { "mime_type": "image/jpeg", "data": "" } }, { "inline_data": { "mime_type": "image/jpeg", "data": "" } }, { "inline_data": { "mime_type": "image/jpeg", "data": "" } } ] }], "generationConfig": { "responseModalities": ["TEXT", "IMAGE"] } }' ``` Resultat for generering med flere bilder *** ## 4K-bildegenerering Spesifiser `image_config` med `aspect_ratio` og `image_size` for høyoppløselig utdata: ```python Python theme={null} from google import genai from google.genai import types import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) response = client.models.generate_content( model="gemini-3.1-flash-image-preview", contents="Da Vinci style anatomical sketch of a Monarch butterfly on textured parchment", config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], image_config=types.ImageConfig( aspect_ratio="1:1", image_size="4K", ), ), ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.text is not None: print(part.text) elif image := part.as_image(): final_image = image if final_image: final_image.save("butterfly_4k.png") ``` ```javascript Node.js theme={null} import { GoogleGenAI } from "@google/genai"; import * as fs from "fs"; const ai = new GoogleGenAI({ apiKey: process.env.COMETAPI_KEY, httpOptions: { apiVersion: "v1beta", baseUrl: "https://api.cometapi.com" }, }); const response = await ai.models.generateContent({ model: "gemini-3.1-flash-image-preview", contents: "Da Vinci style anatomical sketch of a Monarch butterfly on textured parchment", config: { responseModalities: ["TEXT", "IMAGE"], imageConfig: { aspectRatio: "1:1", imageSize: "4K" }, }, }); const imageParts = response.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart = imageParts.at(-1); if (finalImagePart) { fs.writeFileSync("butterfly_4k.png", Buffer.from(finalImagePart.inlineData.data, "base64")); } ``` ```bash Shell theme={null} curl -s -X POST \ "https://api.cometapi.com/v1beta/models/gemini-3.1-flash-image-preview:generateContent" \ -H "Authorization: Bearer $COMETAPI_KEY" \ -H "Content-Type: application/json" \ -d '{ "contents": [{"parts": [{"text": "Da Vinci style anatomical sketch of a Monarch butterfly on textured parchment"}]}], "generationConfig": { "responseModalities": ["TEXT", "IMAGE"], "imageConfig": {"aspectRatio": "1:1", "imageSize": "4K"} } }' ``` For høyoppløselige forespørsler bør du vurdere resultatet ut fra den siste ikke-thought-bildedelen. Hvis integrasjonen din lagrer den første `inlineData`-delen, kan den lagre et mellomliggende thought-bilde med lavere oppløsning enn den forespurte `imageSize`. *** ## Flerturns bilderedigering (chat) Bruk SDK-ens chat-funksjon til å forbedre bilder iterativt: ```python Python theme={null} from google import genai from google.genai import types import os client = genai.Client( http_options={"api_version": "v1beta", "base_url": "https://api.cometapi.com"}, api_key=os.environ.get("COMETAPI_KEY"), ) chat = client.chats.create( model="gemini-3.1-flash-image-preview", config=types.GenerateContentConfig( response_modalities=["TEXT", "IMAGE"], ), ) ## First turn: Generate response = chat.send_message( "Create a vibrant infographic explaining photosynthesis as a recipe, styled like a colorful kids cookbook" ) final_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.text is not None: print(part.text) elif image := part.as_image(): final_image = image if final_image: final_image.save("photosynthesis.png") ``` ## Andre omgang: Forfin response = chat.send\_message("Oppdater denne infografikken til å være på spansk. Ikke endre noen andre elementer.") final\_image = None for part in response.parts: if getattr(part, "thought", False): continue if part.text is not None: print(part.text) elif image := part.as\_image(): final\_image = image if final\_image: final\_image.save("photosynthesis\_spanish.png") ```` ```javascript Node.js import { GoogleGenAI } from "@google/genai"; import * as fs from "fs"; const ai = new GoogleGenAI({ apiKey: process.env.COMETAPI_KEY, httpOptions: { apiVersion: "v1beta", baseUrl: "https://api.cometapi.com" }, }); const chat = ai.chats.create({ model: "gemini-3.1-flash-image-preview", config: { responseModalities: ["TEXT", "IMAGE"] }, }); // First turn: generate const response1 = await chat.sendMessage( "Create a vibrant infographic explaining photosynthesis as a recipe, styled like a colorful kids cookbook" ); const imageParts1 = response1.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart1 = imageParts1.at(-1); if (finalImagePart1) { fs.writeFileSync("photosynthesis.png", Buffer.from(finalImagePart1.inlineData.data, "base64")); } // Second turn: refine const response2 = await chat.sendMessage( "Update this infographic to be in Spanish. Do not change any other elements." ); const imageParts2 = response2.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart2 = imageParts2.at(-1); if (finalImagePart2) { fs.writeFileSync("photosynthesis_spanish.png", Buffer.from(finalImagePart2.inlineData.data, "base64")); } ```` *** ## Tips Spesifiser stilnøkkelord (f.eks. "cyberpunk, film grain, low contrast"), sideforhold, motiv, bakgrunn, belysning og detaljnivå. Når du bruker rå HTTP, ikke inkluder prefikset `data:image/png;base64,` — bruk bare den rå Base64-strengen. Python SDK håndterer dette automatisk med `PIL.Image`-objekter. Sett `"responseModalities"` til bare `["IMAGE"]` for å garantere bildeutdata uten tekst. Sjekk om koden din lagret et mellomliggende thought-bilde. Gemini-bildesvar kan inkludere bildedeler der `thought` er `true`; disse er ikke den endelige utdataen. Hopp over deler med `thought: true` og lagre den siste bildedelen der `inlineData` finnes og `thought` ikke er `true`. Hvis du ikke trenger tekstutdata, be om `"responseModalities": ["IMAGE"]` for å redusere håndtering av blandede tekst-/bildesvar. For flere detaljer, se [API-referansen](/api/image/gemini/gemini-generates-image). **Offisiell dokumentasjon:** [Nano Banana-bildegenerering](https://ai.google.dev/gemini-api/docs/image-generation) * [Gemini bildeforståelse](https://ai.google.dev/gemini-api/docs/image-understanding)