This API provides access to the Responses endpoint from Globant Enterprise AI. It includes plain text inputs, function calling, and file inputs (PDFs and images).
Check the Globant Enterprise AI API Reference for generic variables needed to use the API.
Note: This endpoint currently supports only OpenAI models.
| Method |
Path |
| POST |
/responses |
This endpoint has the same interface (Request/Response) as the OpenAI Responses API.
curl --request POST \
--url $BASE_URL/responses \
-H "Authorization: Bearer $YOUR_SAIA_API_TOKEN" \
-H "Content-Type: application/json" \
--data '{
"model": "openai/o1-pro",
"input": "Tell me a three‑sentence bedtime story about a unicorn.",
"stream": false,
"max_tokens": 2000
}'
{
"instructions": null,
"metadata": {},
"reasoning": {
"effort": "medium"
},
"usage": {
"completion_tokens": 272,
"prompt_tokens": 18,
"total_cost": 0.1659,
"completion_tokens_details": {
"reasoning_tokens": 192
},
"prompt_tokens_details": {
"cached_tokens": 0
},
"total_tokens": 290,
"currency": "USD",
"completion_cost": 0.1632,
"prompt_cost": 0.0027
},
"created_at": 1746473821,
"error": null,
"tools": [],
"output":
{
"summary": [,
"id": "rs_6819...",
"type": "reasoning",
"status": null
},
{
"role": "assistant",
"id": "msg_68191...",
"type": "message",
"content":
{
"annotations": [,
"text": "Once upon a time, in a hidden meadow where flowers swayed like colored ribbons, a unicorn named Moonlight pranced gracefully beneath the twinkling stars. By day, she roamed among the sun-kissed hills, her soft mane shimmering with every gentle breeze. At night, Moonlight’s silvery horn glowed softly, granting sweet, soothing dreams to all who believed in magic.",
"type": "output_text"
}
],
"status": "completed"
}
],
"top_p": 1,
"previous_response_id": null,
"parallel_tool_calls": true,
"temperature": 1,
"tool_choice": "auto",
"model": "o1-pro-2025-03-19",
"id": "resp_bGl...",
"text": {
"format": {
"type": "text"
}
},
"incomplete_details": null,
"truncation": "disabled",
"user": null,
"object": "response",
"max_output_tokens": null,
"status": "completed"
}
curl --request POST \
--url $BASE_URL/responses \
-H "Authorization: Bearer $YOUR_SAIA_API_TOKEN" \
-H "Content-Type: application/json" \
--data '{
"model": "openai/o1-pro",
"input": "What is the weather like in Paris today?",
"tools":
{
"type": "function",
"name": "get_weather",
"description": "Get current temperature for a given location.",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City and country e.g. Bogotá, Colombia"
}
},
"required": [
"location"
,
"additionalProperties": false
}
}
]
}'
{
"instructions": null,
"metadata": {},
"reasoning": {
"effort": "medium"
},
"usage": {
"total_tokens": 0,
"currency": "USD"
},
"created_at": 1745243167,
"error": null,
"tools":
{
"name": "get_weather",
"description": "Get current temperature for a given location.",
"strict": true,
"type": "function",
"parameters": {
"additionalProperties": false,
"type": "object",
"properties": {
"location": {
"description": "City and country e.g. Bogotá, Colombia",
"type": "string"
}
},
"required": [
"location"
}
}
],
"output":
{
"summary": [,
"id": "rs_6806...",
"type": "reasoning",
"status": null
},
{
"name": "get_weather",
"arguments": "{\"location\":\"Paris, France\"}",
"id": "fc_6806...",
"type": "function_call",
"call_id": "call_ruYPRIF9qcOxft5XrfjCBQg8",
"status": "completed"
}
],
"top_p": 1,
"previous_response_id": null,
"parallel_tool_calls": true,
"temperature": 1,
"tool_choice": "auto",
"model": "o1-pro-2025-03-19",
"id": "resp_6806...",
"text": {
"format": {
"type": "text"
}
},
"incomplete_details": null,
"truncation": "disabled",
"user": null,
"object": "response",
"max_output_tokens": null,
"status": "completed"
}
There are two ways to attach an image:
- URL – pass a publicly reachable image_url. Recommended when the file is already hosted and you want a minimal payload.
- Base‑64 inline – embed the binary data in a data:image/...;base64, URI. Recommended for local files, private content, or CI pipelines with no public storage.
Option A — Public image URL (cURL)
curl --request POST \
--url $BASE_URL/responses \
-H "Authorization: Bearer $YOUR_SAIA_API_TOKEN" \
-H "Content-Type: application/json" \
--data '{
"model": "openai/gpt-4.1",
"input":
{
"role": "user",
"content": [
{"type": "input_text", "text": "What is in this image?"},
{
"type": "input_image",
"image_url": "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
}
}
]
}'
Option B — Inline base‑64 (Python)
import base64, json, requests
token = "YOUR_SAIA_API_TOKEN"
url = "$BASE_URL/responses"
headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
def encode_file(file_path):
with open(file_path, 'rb') as file:
return base64.b64encode(file.read()).decode('utf-8')
file_path = "/path/to/your/image.png"
encoded_file = encode_file(file_path)
payload = {
"model": "openai/gpt-4.1",
"input":
{
"role": "user",
"content": [{
"type": "input_text",
"text": "What's this image about?"
},
{
"type": "input_image",
"image_url": f"data:image/png;base64,{encoded_file}"
}
}
]
}
r = requests.post(url, headers=headers, json=payload)
print(json.dumps(r.json(), indent=2))
Supported MIME types for images
| Extension(s) |
MIME type |
Base64 prefix |
| .png |
image/png |
data:image/png;base64, |
| .jpg, .jpeg |
image/jpeg |
data:image/jpeg;base64, |
| .gif |
image/gif |
data:image/gif;base64, |
| .webp |
image/webp |
data:image/webp;base64, |
import base64, json, requests
token = "YOUR_SAIA_API_TOKEN"
url = "$BASE_URL/responses"
headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}
def encode_file(file_path):
with open(file_path, 'rb') as file:
return base64.b64encode(file.read()).decode('utf-8')
file_path = "/path/to/your/sample.pdf"
encoded_file = encode_file(file_path)
payload = {
"model": "openai/o4-mini",
"input":
{
"role": "user",
"content": [
{
"type": "input_text",
"text": "What's this file about?"
},
{
"type": "input_file",
"filename": "sample.pdf",
"file_data": f"data:application/pdf;base64,{encoded_file}"
}
}
]
}
r = requests.post(url, headers=headers, json=payload)
print(json.dumps(r.json(), indent=2))
Note: Only models that support both text and image inputs, such as gpt-4o, gpt-4.1, or o1, can accept PDF files as input.
Since May 2025 release.