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mcp-run-python

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by pydantic
groq.md1.77 kB
# Groq ## Install To use `GroqModel`, you need to either install `pydantic-ai`, or install `pydantic-ai-slim` with the `groq` optional group: ```bash pip/uv-add "pydantic-ai-slim[groq]" ``` ## Configuration To use [Groq](https://groq.com/) through their API, go to [console.groq.com/keys](https://console.groq.com/keys) and follow your nose until you find the place to generate an API key. `GroqModelName` contains a list of available Groq models. ## Environment variable Once you have the API key, you can set it as an environment variable: ```bash export GROQ_API_KEY='your-api-key' ``` You can then use `GroqModel` by name: ```python from pydantic_ai import Agent agent = Agent('groq:llama-3.3-70b-versatile') ... ``` Or initialise the model directly with just the model name: ```python from pydantic_ai import Agent from pydantic_ai.models.groq import GroqModel model = GroqModel('llama-3.3-70b-versatile') 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.groq import GroqModel from pydantic_ai.providers.groq import GroqProvider model = GroqModel( 'llama-3.3-70b-versatile', provider=GroqProvider(api_key='your-api-key') ) agent = Agent(model) ... ``` You can also customize the `GroqProvider` with a custom `httpx.AsyncHTTPClient`: ```python from httpx import AsyncClient from pydantic_ai import Agent from pydantic_ai.models.groq import GroqModel from pydantic_ai.providers.groq import GroqProvider custom_http_client = AsyncClient(timeout=30) model = GroqModel( 'llama-3.3-70b-versatile', provider=GroqProvider(api_key='your-api-key', http_client=custom_http_client), ) agent = Agent(model) ... ```

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