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LLM Quickstart

This guide makes your first chat completion against Shisa LLM. You will need an API key — create one in the Shisa platform. New accounts include $10 in free credits.

1. Set your endpoint and key​

Shisa LLM is OpenAI-compatible. Point any OpenAI client at the Shisa base URL and authenticate with a bearer token:

Base URL:  https://api.shisa.ai/openai/v1
Auth:      Authorization: Bearer YOUR_API_KEY
Model:     shisa-ai/shisa-v2.1-llama3.3-70b
tip

Keep your API key out of source control. Read it from an environment variable (for example SHISA_API_KEY) in real applications.

2. Make a request​

curl
curl -XPOST https://api.shisa.ai/openai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "shisa-ai/shisa-v2.1-llama3.3-70b",
    "stream": true,
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant fluent in Japanese and English."
      },
      {
        "role": "user",
        "content": "日本の四季について教えてください。"
      }
    ],
    "temperature": 0.7
  }'
Python
from openai import OpenAI

# Initialize client with Shisa AI endpoint
client = OpenAI(
    base_url="https://api.shisa.ai/openai/v1",
    api_key="YOUR_API_KEY"
)

def chat_with_shisa(message, model="shisa-ai/shisa-v2.1-llama3.3-70b"):
    response = client.chat.completions.create(
        model=model,
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": message}
        ],
        stream=True,
        temperature=0.7
    )

    for chunk in response:
        if chunk.choices[0].delta.content:
            print(chunk.choices[0].delta.content, end="", flush=True)

# Example usage
chat_with_shisa("東京でおすすめの観光スポットを教えてください。")
Node.js
import OpenAI from 'openai';

const client = new OpenAI({
  baseURL: 'https://api.shisa.ai/openai/v1',
  apiKey: 'YOUR_API_KEY',
});

async function chatWithShisa(message) {
  const stream = await client.chat.completions.create({
    model: 'shisa-ai/shisa-v2.1-llama3.3-70b',
    messages: [
      { role: 'system', content: 'You are a helpful assistant.' },
      { role: 'user', content: message }
    ],
    stream: true,
    temperature: 0.7,
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content || '';
    process.stdout.write(content);
  }
}

// Example usage
await chatWithShisa('日本語で自己紹介をしてください。');

3. Read the response​

With "stream": true the API returns Server-Sent Events; each event carries a token in choices[0].delta.content. Set "stream": false to receive a single JSON response with the full message in choices[0].message.content. The response shape matches the OpenAI Chat Completions API — see the chat completions reference for the full schema.

Next steps​