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Quickstart

This guide will help you make your first API call with Lunar SDK.

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1. Install the SDK

pip install lunar

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2. Set Your API Key

Set the LUNAR_API_KEY environment variable: 
export LUNAR_API_KEY="your-api-key"
Or pass it directly to the client: 
from lunar import Lunar

client = Lunar(api_key="your-api-key")

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3. Make Your First Request

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Chat Completion

from lunar import Lunar

client = Lunar()

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of France?"}
    ]
)

print(response.choices[0].message.content)
# Output: The capital of France is Paris.

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Text Completion

response = client.completions.create(
    model="gpt-4o-mini",
    prompt="The capital of France is",
    max_tokens=10
)

print(response.choices[0].text)
# Output: Paris, which is also...

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4. Check Cost and Usage

Every response includes detailed usage information: 
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}]
)

# Token counts
print(f"Prompt tokens: {response.usage.prompt_tokens}")
print(f"Completion tokens: {response.usage.completion_tokens}")
print(f"Total tokens: {response.usage.total_tokens}")

# Cost breakdown
print(f"Input cost: ${response.usage.input_cost_usd}")
print(f"Output cost: ${response.usage.output_cost_usd}")
print(f"Total cost: ${response.usage.total_cost_usd}")

# Performance
print(f"Latency: {response.usage.latency_ms}ms")

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5. Use Fallbacks

Add fallback models to automatically retry if the primary model fails: 
response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[{"role": "user", "content": "Hello!"}],
    fallbacks=["claude-3-haiku", "llama-3.1-8b"]
)

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6. Async Usage

For async applications, use AsyncLunar: 
from lunar import AsyncLunar

async def main():
    async with AsyncLunar() as client:
        response = await client.chat.completions.create(
            model="gpt-4o-mini",
            messages=[{"role": "user", "content": "Hello!"}]
        )
        print(response.choices[0].message.content)

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Next Steps

Installation

Full configuration options

Chat Completions

Detailed Chat API guide

Fallbacks

Configure intelligent fallbacks

Evaluations

Test your LLM outputs