streamGenerateContent
curl --request POST \
--url https://openp.ai/v1beta/models/{model}:streamGenerateContentimport requests
url = "https://openp.ai/v1beta/models/{model}:streamGenerateContent"
response = requests.post(url)
print(response.text)const options = {method: 'POST'};
fetch('https://openp.ai/v1beta/models/{model}:streamGenerateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://openp.ai/v1beta/models/{model}:streamGenerateContent",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://openp.ai/v1beta/models/{model}:streamGenerateContent"
req, _ := http.NewRequest("POST", url, nil)
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://openp.ai/v1beta/models/{model}:streamGenerateContent")
.asString();require 'uri'
require 'net/http'
url = URI("https://openp.ai/v1beta/models/{model}:streamGenerateContent")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
response = http.request(request)
puts response.read_bodyGoogle Gemini
streamGenerateContent
POST /v1beta/models/:streamGenerateContent —— Gemini 流式生成
POST
/
v1beta
/
models
/
{model}
:streamGenerateContent
streamGenerateContent
curl --request POST \
--url https://openp.ai/v1beta/models/{model}:streamGenerateContentimport requests
url = "https://openp.ai/v1beta/models/{model}:streamGenerateContent"
response = requests.post(url)
print(response.text)const options = {method: 'POST'};
fetch('https://openp.ai/v1beta/models/{model}:streamGenerateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));<?php
$curl = curl_init();
curl_setopt_array($curl, [
CURLOPT_URL => "https://openp.ai/v1beta/models/{model}:streamGenerateContent",
CURLOPT_RETURNTRANSFER => true,
CURLOPT_ENCODING => "",
CURLOPT_MAXREDIRS => 10,
CURLOPT_TIMEOUT => 30,
CURLOPT_HTTP_VERSION => CURL_HTTP_VERSION_1_1,
CURLOPT_CUSTOMREQUEST => "POST",
]);
$response = curl_exec($curl);
$err = curl_error($curl);
curl_close($curl);
if ($err) {
echo "cURL Error #:" . $err;
} else {
echo $response;
}package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://openp.ai/v1beta/models/{model}:streamGenerateContent"
req, _ := http.NewRequest("POST", url, nil)
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}HttpResponse<String> response = Unirest.post("https://openp.ai/v1beta/models/{model}:streamGenerateContent")
.asString();require 'uri'
require 'net/http'
url = URI("https://openp.ai/v1beta/models/{model}:streamGenerateContent")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Post.new(url)
response = http.request(request)
puts response.read_body与 generateContent 完全一致,但 以流式形式返回 —— 边生成边推送 chunk,降低首字延迟。
注意 query 参数
最后一块通常带
请求
curl "https://openp.ai/v1beta/models/gemini-3.1-pro-preview:streamGenerateContent?alt=sse" \
-H "x-goog-api-key: $OPENPAI_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"contents": [{"role": "user", "parts": [{"text": "讲个 100 字故事"}]}]
}'
?alt=sse —— 没有它时返回的是 JSON 数组(每条一个完整 candidate),
带上 alt=sse 才返回标准 SSE 流(data: {...} 形式)。
流式块
data: {"candidates":[{"content":{"role":"model","parts":[{"text":"在"}]},"index":0}]}
data: {"candidates":[{"content":{"role":"model","parts":[{"text":"一个"}]},"index":0}]}
...
data: {"candidates":[{"finishReason":"STOP","index":0}],"usageMetadata":{...}}
finishReason 与 usageMetadata。
Python(google-genai)
from google import genai
client = genai.Client(
api_key="sk-...",
http_options={"base_url": "https://openp.ai"},
)
stream = client.models.generate_content_stream(
model="gemini-3.1-pro-preview",
contents="讲个 100 字故事",
)
for chunk in stream:
print(chunk.text, end="", flush=True)
注意
- 流式响应中也支持
tools/ 函数调用 / 思考模式 —— 字段会出现在某个 chunk 内。 - 客户端要处理 SSE 连接断开后的重试(不可幂等,重试会重新计费)。