Chat & Text

Multi-Turn Conversations

Build a back-and-forth conversation by appending each assistant reply to your messages array before sending the next user message.

Python

python

import requests

BASE_URL = "https://api.oneinfer.ai"
token = requests.post(
    f"{BASE_URL}/v1/ula/oauth-authentication?api_key=YOUR_API_KEY"
).json()["access_token"]
headers = {"Authorization": f"Bearer {token}", "Content-Type": "application/json"}

messages = [{"role": "system", "content": "You are a concise technical assistant."}]

def chat(user_message: str) -> str:
    messages.append({"role": "user", "content": user_message})
    response = requests.post(
        f"{BASE_URL}/v1/ula/chat/completions",
        headers=headers,
        json={"provider": "openai", "model": "gpt-4o-mini", "messages": messages, "max_tokens": 256},
    )
    reply = response.json()["data"]["text"]
    messages.append({"role": "assistant", "content": reply})
    return reply

print(chat("What is a transformer?"))
print(chat("How does attention work in it?"))
print(chat("Give me a Python code snippet."))