--- title: Anyscale description: Guide to using instructor with Anyscale --- # Structured outputs with Anyscale, a complete guide w/ instructor [Anyscale](https://www.anyscale.com/) is a platform that provides access to various open-source LLMs like Mistral and Llama models. This guide shows how to use instructor with Anyscale to get structured outputs from these models. ## Quick Start First, install the required packages: ```bash pip install instructor ``` You'll need an Anyscale API key which you can set as an environment variable: ```bash export ANYSCALE_API_KEY=your_api_key_here ``` ## Basic Example Here's how to extract structured data from Anyscale models: ```python import instructor from pydantic import BaseModel # Initialize the client with Anyscale base URL client = instructor.from_provider( "anyscale/Mixtral-8x7B-Instruct-v0.1", mode=instructor.Mode.JSON_SCHEMA, ) class UserExtract(BaseModel): name: str age: int # Extract structured data user = client.create( response_model=UserExtract, messages=[ {"role": "user", "content": "Extract jason is 25 years old"}, ], ) print(user) # Output: UserExtract(name='Jason', age=25) ``` ### Async Example ```python import asyncio import instructor from pydantic import BaseModel async_client = instructor.from_provider( "anyscale/Mixtral-8x7B-Instruct-v0.1", async_client=True, mode=instructor.Mode.JSON_SCHEMA, ) class UserExtract(BaseModel): name: str age: int async def fetch_user(): return await async_client.create( messages=[{"role": "user", "content": "Extract jason is 25 years old"}], response_model=UserExtract, ) user = asyncio.run(fetch_user()) print(user) ``` ## Supported Modes Anyscale supports the following instructor modes: - `Mode.TOOLS` - `Mode.JSON` - `Mode.JSON_SCHEMA` - `Mode.MD_JSON` ## Models Anyscale provides access to various models, including: - Mistral models (e.g., `mistralai/Mixtral-8x7B-Instruct-v0.1`) - Llama models - Other open-source LLMs available through their platform