Call Gemini with the Chat Completions API
The following sample shows you how to send non-streaming requests:
REST
curl -X POST \ -H "Authorization: Bearer $( gcloud auth print-access-token ) " \ -H "Content-Type: application/json" \ https:// ${ LOCATION } -aiplatform.googleapis.com/v1beta1/projects/ ${ PROJECT_ID } /locations/ ${ LOCATION } /endpoints/openapi/chat/completions \ -d '{ "model": "google/${MODEL_ID}", "messages": [{ "role": "user", "content": "Write a story about a magic backpack." }] }'
Python
Before trying this sample, follow the Python setup instructions in the Agent Platform quickstart using client libraries . For more information, see the Agent Platform Python API reference documentation .
To authenticate to Agent Platform, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
The following sample shows you how to send streaming requests to a Gemini model by using the Chat Completions API:
REST
curl -X POST \ -H "Authorization: Bearer $( gcloud auth print-access-token ) " \ -H "Content-Type: application/json" \ https:// ${ LOCATION } -aiplatform.googleapis.com/v1beta1/projects/ ${ PROJECT_ID } /locations/ ${ LOCATION } /endpoints/openapi/chat/completions \ -d '{ "model": "google/${MODEL_ID}", "stream": true, "messages": [{ "role": "user", "content": "Write a story about a magic backpack." }] }'
Python
Before trying this sample, follow the Python setup instructions in the Agent Platform quickstart using client libraries . For more information, see the Agent Platform Python API reference documentation .
To authenticate to Agent Platform, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
Send a prompt and an image to the Gemini API in Gemini Enterprise Agent Platform
Python
Before trying this sample, follow the Python setup instructions in the Agent Platform quickstart using client libraries . For more information, see the Agent Platform Python API reference documentation .
To authenticate to Agent Platform, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
Call a self-deployed model with the Chat Completions API
The following sample shows you how to send non-streaming requests:
REST
curl -X POST \ -H "Authorization: Bearer $( gcloud auth print-access-token ) " \ -H "Content-Type: application/json" \ https://aiplatform.googleapis.com/v1beta1/projects/ ${ PROJECT_ID } /locations/global/endpoints/ ${ ENDPOINT } /chat/completions \ -d '{ "messages": [{ "role": "user", "content": "Write a story about a magic backpack." }] }'
Python
Before trying this sample, follow the Python setup instructions in the Agent Platform quickstart using client libraries . For more information, see the Agent Platform Python API reference documentation .
To authenticate to Agent Platform, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
The following sample shows you how to send streaming requests to a self-deployed model by using the Chat Completions API:
REST
curl -X POST \ -H "Authorization: Bearer $( gcloud auth print-access-token ) " \ -H "Content-Type: application/json" \ https://aiplatform.googleapis.com/v1beta1/projects/ ${ PROJECT_ID } /locations/global/endpoints/ ${ ENDPOINT } /chat/completions \ -d '{ "stream": true, "messages": [{ "role": "user", "content": "Write a story about a magic backpack." }] }'
Python
Before trying this sample, follow the Python setup instructions in the Agent Platform quickstart using client libraries . For more information, see the Agent Platform Python API reference documentation .
To authenticate to Agent Platform, set up Application Default Credentials. For more information, see Set up authentication for a local development environment .
extra_body
examples
You can use either the SDK or the REST API to pass in extra_body
.
Add thought_tag_marker
{
...
,
"extra_body"
:
{
"google"
:
{
...
,
"thought_tag_marker"
:
"..."
}
}
}
Add extra_body
using the SDK
clie
nt
.cha
t
.comple
t
io
ns
.crea
te
(
...
,
ex
tra
_body
=
{
'ex
tra
_body'
:
{
'google'
:
{
...
}
}
},
)
extra_content
examples
You can populate this field by using the REST API directly.
extra_content
with string content
{
"messages"
:
[
{
"role"
:
"..."
,
"content"
:
"..."
,
"extra_content"
:
{
"google"
:
{
...
}
}
}
]
}
Per-message extra_content
{
"messages"
:
[
{
"role"
:
"..."
,
"content"
:
[
{
"type"
:
"..."
,
...
,
"extra_content"
:
{
"google"
:
{
...
}
}
}
]
}
}
Per-tool call extra_content
{
"messages"
:
[
{
"role"
:
"..."
,
"tool_calls"
:
[
{
...
,
"extra_content"
:
{
"google"
:
{
...
}
}
}
]
}
]
}
Sample curl
requests
You can use these curl
requests directly, rather than going through the SDK.
Use thinking_config
with extra_body
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://us-central1-aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/us-central1/endpoints/openapi/chat/completions
\
-d
'{ \
"model": "google/gemini-2.5-flash-preview-04-17", \
"messages": [ \
{ "role": "user", \
"content": [ \
{ "type": "text", \
"text": "Are there any primes number of the form n*ceil(log(n))" \
}] }], \
"extra_body": { \
"google": { \
"thinking_config": { \
"include_thoughts": true, "thinking_budget": 10000 \
}, \
"thought_tag_marker": "think" } }, \
"stream": true }'
Use stream_function_call_arguments
Example request:
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/global/endpoints/openapi/chat/completions
\
-d
'{
"model": "google/gemini-3-pro-preview", \
"messages": [ \
{ "role": "user", "content": "What is the weather like in Boston and New Delhi today?" } ], \
"tools": [ \
{ \
"type": "function", \
"function": { \
"name": "get_current_weather", \
"description": "Get the current weather in a given location", \
"parameters": { \
"type": "object", \
"properties": { \
"location": { \
"type": "string", \
"description": "The city and state, e.g. San Francisco, CA" \
}, \
"unit": { \
"type": "string", \
"enum": [ \
"celsius", \
"fahrenheit" \
] \
} \
}, \
"required": [ \
"location", \
"unit" \
] \
} \
} \
} \
], \
"extra_body": { \
"google": { \
"stream_function_call_arguments": true \
} \
}, \
"stream": true \
}'
Example responses:
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"extra_content"
: {
"google"
: {
"thought_signature"
: "..."
}}
, "function"
: {
"arguments"
: ""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:1, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "{\"location\":\"Boston, MA"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "\""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: ",\"unit\":\"celsius"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "\""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "}"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-c855348a-459a-46a4-a8ad-aa0a4e7c3563"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: ""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:0, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "{\"location\":\"New Delhi, India"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:1, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "\""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:1, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: ",\"unit\":\"celsius"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:1, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "\""
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:1, "type"
: "function"
}]}
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
}
data:
{
"choices"
: [{
"delta"
: {
"role"
: "assistant"
, "tool_calls"
: [{
"function"
: {
"arguments"
: "}"
, "name"
: "get_current_weather"
}
, "id"
: "function-call-df0d087c-ad74-46f1-ba4a-9353cbf288a8"
, "index"
:1, "type"
: "function"
}]}
, "finish_reason"
: "tool_calls"
, "index"
:0, "logprobs"
:null }]
, "created"
:1770850461, "id"
: "nQiNafGyF5rw998PstqooAY"
, "model"
: "google/gemini-3-pro-preview"
, "object"
: "chat.completion.chunk"
, "system_fingerprint"
: ""
, "usage"
: {
"completion_tokens"
:45, "completion_tokens_details"
: {
"reasoning_tokens"
:504 }
, "extra_properties"
: {
"google"
: {
"traffic_type"
: "PROVISIONED_THROUGHPUT"
}}
, "prompt_tokens"
:27, "total_tokens"
:576 }}
data:
[
DONE ]
Image generation
To remain compatible with the OpenAI response format, the audio
field of the response is explicitly populated with an extra_content.google.mime_type
indicating the mime type of the result.
Example request:
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/global/endpoints/openapi/chat/completions
\
-d
'{"model":"google/gemini-3-pro-image-preview", "messages":[{ "role": "user", "content": "Generate an image of a cat." }], "modalities": ["image"] }'
Example response:
{
"choices"
:
[
{
"finish_reason"
:
"stop"
,
"index"
:
0
,
"logprobs"
:
null,
"message"
:
{
"audio"
:
{
"data"
:
"<BASE64_BYTES>"
,
"extra_content"
:
{
"google"
:
{
"mime_type"
:
"image/png"
}
}
}
,
"content"
:
null,
"extra_content"
:
{
"google"
:
{
"thought_signature"
:
"..."
}
}
,
"role"
:
"assistant"
}
}
]
,
"created"
:
1770850692
,
"id"
:
"hAmNaZb8BZOX4_UPlNXoEA"
,
"model"
:
"google/gemini-3-pro-image-preview"
,
"object"
:
"chat.completion"
,
"system_fingerprint"
:
""
,
"usage"
:
{
"completion_tokens"
:
1120
,
"completion_tokens_details"
:
{
"reasoning_tokens"
:
251
}
,
"extra_properties"
:
{
"google"
:
{
"traffic_type"
:
"PROVISIONED_THROUGHPUT"
}
}
,
"prompt_tokens"
:
7
,
"total_tokens"
:
1378
}
}
Multimodal requests
The Chat Completions API supports a variety of multimodal input, including both audio and video.
Use image_url
to pass in image data
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://us-central1-aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/us-central1/endpoints/openapi/chat/completions
\
-d
'{ \
"model": "google/gemini-2.0-flash-001", \
"messages": [{ "role": "user", "content": [ \
{ "type": "text", "text": "Describe this image" }, \
{ "type": "image_url", "image_url": "gs://cloud-samples-data/generative-ai/image/scones.jpg" }] }] }'
Use input_audio
to pass in audio data
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://us-central1-aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/us-central1/endpoints/openapi/chat/completions
\
-d
'{ \
"model": "google/gemini-2.0-flash-001", \
"messages": [ \
{ "role": "user", \
"content": [ \
{ "type": "text", "text": "Describe this: " }, \
{ "type": "input_audio", "input_audio": { \
"format": "audio/mp3", \
"data": "gs://cloud-samples-data/generative-ai/audio/pixel.mp3" } }] }] }'
Multi-modal function responses
Example request:
curl
-X
POST
\
-H
"Authorization: Bearer
$(
gcloud
auth
print-access-token )
"
\
-H
"Content-Type: application/json"
\
https://aiplatform.googleapis.com/v1/projects/ ${
PROJECT_ID
}
/locations/global/endpoints/openapi/chat/completions
\
-d
'{ \
"model": "google/gemini-3-pro-preview", \
"messages": [ \
{ "role": "user", "content": "Show me the green shirt I ordered last month." }, \
{ \
"role": "assistant", \
"tool_calls": [ \
{ \
"extra_content": { \
"google": { \
"thought_signature": "<THOUGHT_SIGNATURE>" \
} \
}, \
"function": { \
"arguments": "{\"item_name\":\"green shirt\"}", \
"name": "get_image" \
}, \
"id": "function-call-a350228d-0283-4792-8bfa-40da064fb959", \
"type": "function" \
} \
] \
}, \
{ \
"role": "tool", \
"tool_call_id": "function-call-a350228d-0283-4792-8bfa-40da064fb959", \
"content": "{\"image_ref\":{\"$ref\":\"dress.jpg\"}}", \
"extra_content": { \
"google": { \
"parts": [ \
{ \
"file_data": { \
"mime_type": "image/jpg", \
"display_name": "dress.jpg", \
"file_uri": "gs://cloud-samples-data/generative-ai/image/dress.jpg" \
} \
} \
] \
} \
} \
} \
], \
"tools": [ \
{ \
"type": "function", \
"function": { \
"name": "get_image", \
"description": "Retrieves the image file reference for a specific order item.", \
"parameters": { \
"type": "object", \
"properties": { \
"item_name": { \
"type": "string", \
"description": "The name or description of the item ordered (e.g., '
green
shirt ')." \
} \
}, \
"required": [ \
"item_name" \
] \
} \
} \
} \
] \
}'
Example response:
{
"choices"
:
[
{
"finish_reason"
:
"stop"
,
"index"
:
0
,
"logprobs"
:
null,
"message"
:
{
"content"
:
"Here is the image of the green shirt you ordered."
,
"role"
:
"assistant"
}
}
]
,
"created"
:
1770852204
,
"id"
:
"bA-NacCPKoae_9MPsNCn6Qc"
,
"model"
:
"google/gemini-3-pro-preview"
,
"object"
:
"chat.completion"
,
"system_fingerprint"
:
""
,
"usage"
:
{
"completion_tokens"
:
16
,
"extra_properties"
:
{
"google"
:
{
"traffic_type"
:
"ON_DEMAND"
}
}
,
"prompt_tokens"
:
1139
,
"total_tokens"
:
1155
}
}
Structured output
You can use the response_format
parameter to get structured output.
Example using SDK
from
pydantic
import
BaseModel
from
openai
import
OpenAI
client
=
OpenAI
()
class
CalendarEvent
(
BaseModel
):
name
:
str
date
:
str
participants
:
list
[
str
]
completion
=
client
.
beta
.
chat
.
completions
.
parse
(
model
=
"google/gemini-2.5-flash-preview-04-17"
,
messages
=
[
{
"role"
:
"system"
,
"content"
:
"Extract the event information."
},
{
"role"
:
"user"
,
"content"
:
"Alice and Bob are going to a science fair on Friday."
},
],
response_format
=
CalendarEvent
,
)
print
(
completion
.
choices
[
0
]
.
message
.
parsed
)
Using the global endpoint in OpenAI compatible mode
The following sample shows how to use the global endpoint in OpenAI compatible mode:
REST
curl -X POST \ -H "Authorization: Bearer $( gcloud auth print-access-token ) " \ -H "Content-Type: application/json" \ https://aiplatform.googleapis.com/v1beta1/projects/ ${ PROJECT_ID } /locations/global/endpoints/openapi/chat/completions \ -d '{ \ "model": "google/gemini-2.0-flash-001", \ "messages": [ \ {"role": "user", \ "content": "Hello World" \ }] \ }'
What's next
- See examples of calling the Inference API with the OpenAI-compatible syntax.
- See examples of calling the Function Calling API with OpenAI-compatible syntax.
- Learn more about the Gemini API .
- Learn more about migrating from Azure OpenAI to the Gemini API .
