Stream generate content
curl --request POST \
--url https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent"
headers = {"Authorization": "Bearer <token>"}
response = requests.post(url, headers=headers)
print(response.text)const options = {method: 'POST', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent"
req, _ := http.NewRequest("POST", url, nil)
req.Header.Add("Authorization", "Bearer <token>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}Stream generate content
Stream Gemini generateContent output as server-sent events.
POST
/
v1beta
/
models
/
{model}
:streamGenerateContent
Stream generate content
curl --request POST \
--url https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent \
--header 'Authorization: Bearer <token>'import requests
url = "https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent"
headers = {"Authorization": "Bearer <token>"}
response = requests.post(url, headers=headers)
print(response.text)const options = {method: 'POST', headers: {Authorization: 'Bearer <token>'}};
fetch('https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent', options)
.then(res => res.json())
.then(res => console.log(res))
.catch(err => console.error(err));package main
import (
"fmt"
"net/http"
"io"
)
func main() {
url := "https://api.pipellm.ai/v1beta/models/{model}:streamGenerateContent"
req, _ := http.NewRequest("POST", url, nil)
req.Header.Add("Authorization", "Bearer <token>")
res, _ := http.DefaultClient.Do(req)
defer res.Body.Close()
body, _ := io.ReadAll(res.Body)
fmt.Println(string(body))
}Same request body as Generate content. The response is an SSE stream instead of a single JSON object.
Use
string
required
Gemini model ID, for example
gemini-3-flash-preview.curl "https://api.pipellm.ai/v1beta/models/gemini-3-flash-preview:streamGenerateContent" \
-H "Content-Type: application/json" \
-H "x-goog-api-key: $PIPELLM_API_KEY" \
-N \
-d '{
"contents": [
{
"role": "user",
"parts": [{"text": "Count to five."}]
}
]
}'
x-goog-api-key: $PIPELLM_API_KEY. Native Gemini routes only go to Gemini platforms. To keep Gemini format while calling OpenAI or Anthropic models, use the Gemini converter.Was this page helpful?