mcp-run-python

# Cerebras ## Install To use `CerebrasModel`, you need to either install `pydantic-ai`, or install `pydantic-ai-slim` with the `cerebras` optional group: ```bash pip/uv-add "pydantic-ai-slim[cerebras]" ``` ## Configuration To use [Cerebras](https://cerebras.ai/) through their API, go to [cloud.cerebras.ai](https://cloud.cerebras.ai/?utm_source=3pi_pydantic-ai&utm_campaign=partner_doc) and generate an API key. For a list of available models, see the [Cerebras models documentation](https://inference-docs.cerebras.ai/models). ## Environment variable Once you have the API key, you can set it as an environment variable: ```bash export CEREBRAS_API_KEY='your-api-key' ``` You can then use `CerebrasModel` by name: ```python from pydantic_ai import Agent agent = Agent('cerebras:llama-3.3-70b') ... ``` Or initialise the model directly with just the model name: ```python from pydantic_ai import Agent from pydantic_ai.models.cerebras import CerebrasModel model = CerebrasModel('llama-3.3-70b') agent = Agent(model) ... ``` ## `provider` argument You can provide a custom `Provider` via the `provider` argument: ```python from pydantic_ai import Agent from pydantic_ai.models.cerebras import CerebrasModel from pydantic_ai.providers.cerebras import CerebrasProvider model = CerebrasModel( 'llama-3.3-70b', provider=CerebrasProvider(api_key='your-api-key') ) agent = Agent(model) ... ``` You can also customize the `CerebrasProvider` with a custom `httpx.AsyncClient`: ```python from httpx import AsyncClient from pydantic_ai import Agent from pydantic_ai.models.cerebras import CerebrasModel from pydantic_ai.providers.cerebras import CerebrasProvider custom_http_client = AsyncClient(timeout=30) model = CerebrasModel( 'llama-3.3-70b', provider=CerebrasProvider(api_key='your-api-key', http_client=custom_http_client), ) agent = Agent(model) ... ```