Integration guide
How to use GCP Cloud Functions with an OpenAI-compatible endpoint (Python)
GCP Cloud Functions integration guide for Python. Connect to an OpenAI-compatible endpoint with a base URL swap and keep the same request schema.
Updated 2026-01-06
GCP Cloud Functions works with OpenAI-compatible APIs by switching the base URL and API key.
This guide shows a Python example plus a test vector you can run to validate responses.
import os
import requests
payload = {
"model": "abliterated-model",
"messages": [{"role": "user", "content": "Respond with: GCP Cloud Functions Python ready."}],
"temperature": 0.2,
}
resp = requests.post(
"https://api.abliteration.ai/v1/chat/completions",
headers={
"Authorization": f"Bearer {os.getenv('ABLIT_KEY')}",
"Content-Type": "application/json",
},
json=payload,
)
resp.raise_for_status()
print(resp.json()["choices"][0]["message"]["content"])Configure GCP Cloud Functions
Follow this checklist to point your integration at the OpenAI-compatible endpoint.
OpenAI-compatible payload
Use this request body as a known-good payload before customizing parameters.
{
"model": "abliterated-model",
"messages": [
{ "role": "user", "content": "Respond with: GCP Cloud Functions Python ready." }
],
"temperature": 0.2
}Streaming and tool calling readiness
If you stream responses or send tool definitions, keep the OpenAI-compatible schema and validate against the OpenAPI spec.