Use your Betopia API key to call LLM models directly. The API is OpenAI-compatible — swap the base URL and key and existing integrations work immediately.
https://api.betopia.aiSend a list of messages and receive a completion. Supports system, user, and assistant roles. Add "stream": true for SSE — see .
import requests
API_KEY = "sk_your_api_key_here"
BASE_URL = "https://api.betopia.ai"
response = requests.post(
f"{BASE_URL}/v1/chat/completions",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json",
},
json={
"model": "gpt-5.4-mini",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain quantum computing in simple terms."},
],
"max_completion_tokens": 512,
"temperature": 0.7,
},
)
data = response.json()
print(data["content"])
print(f"Tokens: {data['input_tokens']} in / {data['output_tokens']} out"){
"request_id": "req_a1b2c3d4e5",
"model": "gpt-5.4-mini",
"content": "Quantum computing uses quantum bits (qubits) that can exist in multiple states at once...",
"input_tokens": 24,
"output_tokens": 187,
"latency_ms": 430
}request_idstringUnique request identifier for debuggingmodelstringModel that processed the requestcontentstringGenerated text responseinput_tokensintegerTokens consumed by your promptoutput_tokensintegerTokens in the generated responselatency_msintegerEnd-to-end inference time in ms