567-labs--instructor/docs/integrations/sambanova.md

title, description

title	description
SambaNova	Use Instructor with SambaNova's LLM API for structured outputs.

See Also

• Getting Started - Quick start guide
• from_provider Guide - Detailed client configuration
• Provider Examples - Quick examples for all providers
• Enterprise Integration - More enterprise examples

SambaNova Integration

Instructor supports SambaNova's LLM API, allowing you to use structured outputs with their models.

Installation

pip install "instructor[openai]"

Basic Usage

import instructor
from pydantic import BaseModel

client = instructor.from_provider("sambanova/Meta-Llama-3.1-405B-Instruct")

class User(BaseModel):
    name: str
    age: int

user = client.create(
    messages=[
        {"role": "user", "content": "Ivan is 28"},
    ],
    response_model=User,
)

print(user)
# > User(name='Ivan', age=28)

Async Usage

import instructor
from pydantic import BaseModel

client = instructor.from_provider(
    "sambanova/Meta-Llama-3.1-405B-Instruct",
    async_client=True,
)

class User(BaseModel):
    name: str
    age: int

async def get_user():
    user = await client.create(
        messages=[
            {"role": "user", "content": "Ivan is 28"},
        ],
        response_model=User,
    )
    return user

# Run with asyncio
import asyncio
user = asyncio.run(get_user())
print(user)
# > User(name='Ivan', age=28)

Available Models

Check the SambaNova documentation for the latest model offerings and capabilities.