from openai import OpenAI

client = OpenAI(
    base_url="https://api.emby.dev/v1",
    api_key="your-emby-key"
)

# Kimi K2
resp = client.chat.completions.create(
    model="kimi-k2",
    messages=[{"role": "user", "content": "Hello!"}]
)

# DeepSeek V3
resp = client.chat.completions.create(
    model="deepseek-v3",
    messages=[{"role": "user", "content": "Explain async in Python"}]
)

# Qwen 3.5 Coder
resp = client.chat.completions.create(
    model="qwen3.5-coder-large",
    messages=[{"role": "user", "content": "Refactor this code"}]
)

const response = await fetch("https://api.emby.dev/v1/chat/completions", {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${process.env.EMBY_API_KEY}`,
    "Content-Type": "application/json"
  },
  body: JSON.stringify({
    model: "kimi-k2",
    messages: [{ role: "user", content: "Hello!" }]
  })
});

console.log(await response.json());

curl https://api.emby.dev/v1/chat/completions \
  -H "Authorization: Bearer $EMBY_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "deepseek-v3",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

client.chat.completions.create(
    model="kimi-k2",
    messages=messages,
    fallback_models=["deepseek-v3", "qwen3.5-coder-large"],
    fallback_on_rate_limit=True,
    fallback_on_error=True,
)