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fix numerous typos (#95)
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Makefile

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@@ -80,8 +80,9 @@ else ifeq ($(PPPR_TOKEN),)
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@exit 1
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else
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@echo 'installing insiders packages...'
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@uv pip install -U mkdocs-material mkdocstrings-python \
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--extra-index-url https://pydantic:${PPPR_TOKEN}@pppr.pydantic.dev/simple/
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@uv pip install -U \
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--extra-index-url https://pydantic:${PPPR_TOKEN}@pppr.pydantic.dev/simple/ \
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mkdocs-material mkdocstrings-python
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endif
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.PHONY: docs-insiders # Build the documentation using insiders packages
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uv python install 3.12
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uv sync --python 3.12 --frozen --group docs
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uv pip install -U \
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--extra-index-url https://pydantic:$(PPPR_TOKEN)@pppr.pydantic.dev/simple/ \
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--extra-index-url https://pydantic:${PPPR_TOKEN}@pppr.pydantic.dev/simple/ \
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mkdocs-material mkdocstrings-python
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uv pip freeze
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uv run --no-sync mkdocs build
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uv run --no-sync mkdocs build -f mkdocs.insiders.yml
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.PHONY: all
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all: format lint typecheck testcov

docs/examples/index.md

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# Examples
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Examples of how to use Pydantic AI and what it can do.
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Examples of how to use PydanticAI and what it can do.
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## Usage
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docs/examples/pydantic-model.md

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Simple example of using Pydantic AI to construct a Pydantic model from a text input.
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# Pydantic Model
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Simple example of using PydanticAI to construct a Pydantic model from a text input.
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Demonstrates:
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docs/examples/rag.md

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* RAG search
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This is done by creating a database containing each section of the markdown documentation, then registering
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the search tool as a retriever with the Pydantic AI agent.
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the search tool as a retriever with the PydanticAI agent.
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Logic for extracting sections from markdown files and a JSON file with that data is available in
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[this gist](https://gist.github.com/samuelcolvin/4b5bb9bb163b1122ff17e29e48c10992).
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python/uv-run -m pydantic_ai_examples.rag build
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```
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(Note building the database doesn't use Pydantic AI right now, instead it uses the OpenAI SDK directly.)
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(Note building the database doesn't use PydanticAI right now, instead it uses the OpenAI SDK directly.)
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You can then ask the agent a question with:
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docs/examples/sql-gen.md

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# SQL Generation
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Example demonstrating how to use Pydantic AI to generate SQL queries based on user input.
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Example demonstrating how to use PydanticAI to generate SQL queries based on user input.
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Demonstrates:
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docs/examples/weather-agent.md

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Example of Pydantic AI with multiple tools which the LLM needs to call in turn to answer a question.
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Example of PydanticAI with multiple tools which the LLM needs to call in turn to answer a question.
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Demonstrates:
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pydantic_ai_examples/README.md

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# Pydantic AI Examples
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# PydanticAI Examples
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Examples of how to use Pydantic AI and what it can do.
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Examples of how to use PydanticAI and what it can do.
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Full documentation of these examples and how to run them is available at [ai.pydantic.dev/examples/](https://ai.pydantic.dev/examples/).

pydantic_ai_examples/pydantic_model.py

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"""Simple example of using Pydantic AI to construct a Pydantic model from a text input.
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"""Simple example of using PydanticAI to construct a Pydantic model from a text input.
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Run with:
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pydantic_ai_examples/pyproject.toml

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[project]
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name = "pydantic-ai-examples"
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version = "0.0.6"
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description = "Agent Framework / shim to use Pydantic with LLMs"
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description = "Examples of how to use PydanticAI and what it can do."
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authors = [
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{ name = "Samuel Colvin", email = "[email protected]" },
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]

pydantic_ai_examples/roulette_wheel.py

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"""Example demonstrating how to use Pydantic AI to create a simple roulette game.
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"""Example demonstrating how to use PydanticAI to create a simple roulette game.
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Run with:
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uv run -m pydantic_ai_examples.roulette_wheel

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