流式输出需要 Direct 分组令牌，需在控制台选择 Direct 分组。
核心能力
- SSE 流式输出 — 实时推送思考 chunk 与图片 chunk
- 思考模式 — 内部推理 chunk（
thought: true）在图片之前流式输出 - 文生图 — 根据文本描述生成图片
- 图片编辑 — 在
inline_data中传入参考图，配合文字指令进行编辑 - 宽高比控制 —
1:1、3:2、2:3、3:4、4:3、4:5、5:4、9:16、16:9、21:9 - 分辨率控制 — 支持
1K（1024px）。不支持 2K 和 4K
SSE 响应格式
流式端点返回换行分隔的 SSE 数据行，每行以data: 开头，后跟 JSON 对象。共有三种 chunk 类型：
- 思考 chunk — 最先到达；
parts[0].thought为true - 图片 chunk — 包含
parts[0].inlineData，含mimeType和 base64data（注意：流式响应中为驼峰命名） - 最终用量 chunk — 包含顶层
usageMetadata，含thoughtsTokenCount及各模态 token 详情
data: {"candidates":[{"content":{"role":"model","parts":[{"text":"...","thought":true}]}}],"usageMetadata":{"trafficType":"ON_DEMAND"},"modelVersion":"gemini-3.1-flash-lite-image","createTime":"...","responseId":"..."}
data: {"candidates":[{"content":{"role":"model","parts":[{"inlineData":{"mimeType":"image/png","data":"<base64>"}}]}}],...}
data: {"usageMetadata":{"promptTokenCount":8,"candidatesTokenCount":1120,"totalTokenCount":1392,"trafficType":"ON_DEMAND","promptTokensDetails":[{"modality":"TEXT","tokenCount":8}],"candidatesTokensDetails":[{"modality":"IMAGE","tokenCount":1120}],"thoughtsTokenCount":264}}
流式响应中图片字段名为
inlineData（驼峰），而请求体中字段名为 inline_data（下划线）。这是原生 Gemini API 的行为。文生图示例
curl "https://www.anyfast.ai/v1beta/models/gemini-3.1-flash-lite-image:streamGenerateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [
{
"role": "user",
"parts": [
{ "text": "生成一张山间日落的图片" }
]
}
],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {
"aspectRatio": "16:9",
"imageSize": "1K"
}
}
}'
import requests, base64, json
url = "https://www.anyfast.ai/v1beta/models/gemini-3.1-flash-lite-image:streamGenerateContent"
params = {"key": "YOUR_API_KEY"}
data = {
"contents": [
{
"role": "user",
"parts": [{"text": "生成一张山间日落的图片"}]
}
],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {"aspectRatio": "16:9", "imageSize": "1K"}
}
}
response = requests.post(url, params=params, json=data, stream=True)
for line in response.iter_lines():
if not line:
continue
decoded = line.decode("utf-8")
if not decoded.startswith("data:"):
continue
chunk = json.loads(decoded[len("data:"):].strip())
candidates = chunk.get("candidates", [])
if not candidates:
continue
parts = candidates[0].get("content", {}).get("parts", [])
for part in parts:
# 跳过思考 chunk
if part.get("thought"):
continue
# 保存图片 chunk
if "inlineData" in part:
img_bytes = base64.b64decode(part["inlineData"]["data"])
with open("output.png", "wb") as f:
f.write(img_bytes)
print("图片已保存至 output.png")
图片编辑示例（传入参考图）
在同一个parts 数组中同时传入 text 指令和 inline_data 参考图。
# 先将图片转为 base64：
# BASE64=$(base64 -i your_photo.jpg)
#
# 然后发送请求：
curl "https://www.anyfast.ai/v1beta/models/gemini-3.1-flash-lite-image:streamGenerateContent?key=YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [
{
"role": "user",
"parts": [
{
"text": "这是我的一张照片，请在我旁边加一只羊驼"
},
{
"inline_data": {
"mime_type": "image/jpeg",
"data": "<YOUR_BASE64_ENCODED_IMAGE>"
}
}
]
}
],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {
"aspectRatio": "1:1",
"imageSize": "1K"
}
}
}'
import requests, base64, json
# 读取并编码参考图片
with open("your_photo.jpg", "rb") as f:
image_b64 = base64.b64encode(f.read()).decode("utf-8")
url = "https://www.anyfast.ai/v1beta/models/gemini-3.1-flash-lite-image:streamGenerateContent"
params = {"key": "YOUR_API_KEY"}
data = {
"contents": [
{
"role": "user",
"parts": [
{
"text": "这是我的一张照片，请在我旁边加一只羊驼"
},
{
"inline_data": {
"mime_type": "image/jpeg",
"data": image_b64
}
}
]
}
],
"generationConfig": {
"responseModalities": ["TEXT", "IMAGE"],
"imageConfig": {"aspectRatio": "1:1", "imageSize": "1K"}
}
}
response = requests.post(url, params=params, json=data, stream=True)
for line in response.iter_lines():
if not line:
continue
decoded = line.decode("utf-8")
if not decoded.startswith("data:"):
continue
chunk = json.loads(decoded[len("data:"):].strip())
candidates = chunk.get("candidates", [])
if not candidates:
continue
parts = candidates[0].get("content", {}).get("parts", [])
for part in parts:
if part.get("thought"):
continue
if "inlineData" in part:
img_bytes = base64.b64decode(part["inlineData"]["data"])
with open("output.png", "wb") as f:
f.write(img_bytes)
print("图片已保存至 output.png")
参数说明
| 参数 | 类型 | 必填 | 说明 |
|---|---|---|---|
key | string | 是 | API 密钥（查询参数） |
alt | string | 否 | 设为 sse 可显式开启 SSE 模式（可选，流式为默认行为） |
contents[].parts[].text | string | 是 | 文字提示或指令 |
contents[].parts[].inline_data.mime_type | string | 否 | 参考图类型：image/jpeg、image/png、image/webp |
contents[].parts[].inline_data.data | string | 否 | Base64 编码的参考图数据 |
generationConfig.responseModalities | array | 是 | ["IMAGE"] 或 ["TEXT", "IMAGE"] |
generationConfig.imageConfig.aspectRatio | string | 否 | 1:1 / 3:2 / 2:3 / 3:4 / 4:3 / 4:5 / 5:4 / 9:16 / 16:9 / 21:9 |
generationConfig.imageConfig.imageSize | string | 否 | 仅支持 1K。不支持 2K 和 4K |
API 参考
查看 Gemini 3.1 Flash Lite Image (Stream) 的交互式 API Playground。