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mcp-run-python

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by pydantic
setup.md1.97 kB
# Examples Here we include some examples of how to use Pydantic AI and what it can do. ## Usage These examples are distributed with `pydantic-ai` so you can run them either by cloning the [pydantic-ai repo](https://github.com/pydantic/pydantic-ai) or by simply installing `pydantic-ai` from PyPI with `pip` or `uv`. ### Installing required dependencies Either way you'll need to install extra dependencies to run some examples, you just need to install the `examples` optional dependency group. If you've installed `pydantic-ai` via pip/uv, you can install the extra dependencies with: ```bash pip/uv-add "pydantic-ai[examples]" ``` If you clone the repo, you should instead use `uv sync --extra examples` to install extra dependencies. ### Setting model environment variables These examples will need you to set up authentication with one or more of the LLMs, see the [model configuration](../models/overview.md) docs for details on how to do this. TL;DR: in most cases you'll need to set one of the following environment variables: === "OpenAI" ```bash export OPENAI_API_KEY=your-api-key ``` === "Google Gemini" ```bash export GEMINI_API_KEY=your-api-key ``` ### Running Examples To run the examples (this will work whether you installed `pydantic_ai`, or cloned the repo), run: ```bash python/uv-run -m pydantic_ai_examples.<example_module_name> ``` For examples, to run the very simple [`pydantic_model`](./pydantic-model.md) example: ```bash python/uv-run -m pydantic_ai_examples.pydantic_model ``` If you like one-liners and you're using uv, you can run a pydantic-ai example with zero setup: ```bash OPENAI_API_KEY='your-api-key' \ uv run --with "pydantic-ai[examples]" \ -m pydantic_ai_examples.pydantic_model ``` --- You'll probably want to edit examples in addition to just running them. You can copy the examples to a new directory with: ```bash python/uv-run -m pydantic_ai_examples --copy-to examples/ ```

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