> ## 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. # 使用 Gemini 图像模型 > 通过 Google Gen AI SDK 在 CometAPI 上调用 Gemini 图像模型（Nano Banana 2 / Pro），用于文生图、图生图和多图合成。 本指南演示如何通过 CometAPI 使用 **Google Gen AI SDK** 调用 Gemini 图像模型。内容包括： * 文生图 * 图像到图像编辑 * 多图合成 * 保存生成的图像 - **Base URL：** `https://api.cometapi.com` - 安装 SDK：`pip install google-genai`（Python）或 `npm install @google/genai`（Node.js） *** ## 设置 使用 CometAPI 的 base URL 初始化客户端： ```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... } ``` *** ## 文本转图像生成 根据文本 Prompt 生成图像并将其保存到文件中。 ```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"] } }' ``` **保存最终图像部分：** 图像数据位于 `candidates[0].content.parts` 中，其中可能同时包含文本部分和/或图像部分。Gemini 图像模型也可能在最终图像之前返回中间 thought 部分，尤其是在你同时请求文本和图像，或者显式启用 thinking 输出时。不要盲目保存第一个 `inlineData`；应跳过 `thought` 为 `true` 的部分，然后保存最后一个剩余的图像部分。 仅包含最终图像的典型响应： ```json theme={null} { "candidates": [{ "content": { "parts": [ { "text": "Here is your image..." }, { "inlineData": { "mimeType": "image/png", "data": "" } } ] } }] } ``` 包含文本部分、中间 thought 图像以及最终图像的响应： ```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" }] } ``` 对每个 Gemini 图像响应都使用这条解析规则： ```javascript theme={null} const imageParts = response.candidates[0].content.parts.filter( (part) => part.inlineData && part.thought !== true, ); const finalImagePart = imageParts.at(-1); ``` *** ## 图生图生成 上传输入图像，并使用文本提示词对其进行转换。 ```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 可直接接受 `PIL.Image` 对象——无需手动进行 Base64 编码。 * 传递原始 Base64 字符串时，**不要**包含 `data:image/jpeg;base64,` 前缀。 *** ## 多图像合成 基于多个输入图像生成一张新图像。CometAPI 支持两种方式： ### 方法 1：单张拼贴图像 将多个源图像合并为一张拼贴图，然后描述期望的输出。 输入拼贴示例 生成结果 ```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"] } }' ``` ### 方法 2：多张独立图像（最多 14 张） 直接传入多张图像。Gemini 3 模型最多支持 14 张参考图像（物体 + 角色）： ```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"] } }' ``` 多图像生成结果 *** ## 4K 图像生成 指定带有 `aspect_ratio` 和 `image_size` 的 `image_config` 以获得高分辨率输出： ```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"} } }' ``` 对于高分辨率请求，请以最后一个非 thought 的图像 part 作为输出判断依据。如果你的集成保存的是第一个 `inlineData` part，则可能会保存一个中间 thought 图像，其分辨率会低于请求的 `imageSize`。 *** ## 多轮图像编辑（聊天） 使用 SDK 的聊天功能来迭代优化图像： ```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") ``` ## 第二轮：优化 response = chat.send\_message("将这张信息图更新为西班牙语。不要更改任何其他元素。") 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")); } ```` *** ## 提示 明确指定风格关键词（例如 `"cyberpunk, film grain, low contrast"`）、宽高比、主体、背景、光照和细节级别。 使用原始 HTTP 时，不要包含 `data:image/png;base64,` 前缀——只使用原始 Base64 字符串。Python SDK 会通过 `PIL.Image` 对象自动处理这一点。 将 `"responseModalities"` 仅设置为 `["IMAGE"]`，以保证只输出图像而不输出文本。 检查你的代码是否保存了中间思考图像。Gemini 图像响应可能包含 `thought` 为 `true` 的图像部分；这些不是最终输出。请跳过 `thought: true` 的部分，并保存最后一个存在 `inlineData` 且 `thought` 不为 `true` 的图像部分。如果你不需要文本输出，请请求 `"responseModalities": ["IMAGE"]`，以减少处理文本/图像混合响应的复杂度。 更多详情，请参阅 [API 参考](/api/image/gemini/gemini-generates-image)。 **官方文档：** [Nano Banana 图像生成](https://ai.google.dev/gemini-api/docs/image-generation) * [Gemini 图像理解](https://ai.google.dev/gemini-api/docs/image-understanding)