See[Monitoring and Performance](logfire.md) to learn more.

The PydanticAI documentation is available in the[llms.txt](https://llmstxt.org/) format.

This format is defined in Markdown and suited for large language models.

Two formats are available:

-[llms.txt](https://ai.pydantic.dev/llms.txt): a file containing a brief description

of the project, along with links to the different sections of the documentation. The structure

of this file is described in details[here](https://llmstxt.org/#format).

-[llms-full.txt](https://ai.pydantic.dev/llms-full.txt): Similar to the`llms.txt` file,

but every link content is included. Note that this file may be too large for some LLMs.

As of today, these files*cannot* be natively leveraged by LLM frameworks or IDEs. Alternatively,

an[MCP server](https://modelcontextprotocol.io/) can be implemented to properly parse the`llms.txt`

file.

To try PydanticAI yourself, follow the instructions[in the examples](examples/index.md).

-url:https://typing-extensions.readthedocs.io/en/latest/objects.inv

-url:https://rich.readthedocs.io/en/stable/objects.inv

-llmstxt:

enabled:!ENV [CI, false]

full_output:llms-full.txt

markdown_description:|-

sections:

Concepts documentation:

-agents.md

-dependencies.md

-tools.md

-common-tools.md

-results.md

-message-history.md

-multi-agent-applications.md

Models:

-models/*.md

Graphs:

-graph.md

Evals:

-evals.md

MCP:

-mcp/*.md

Optional:

-testing.md

-cli.md

-logfire.md

-examples/*.md

hooks:

-"docs/.hooks/main.py"

-"docs/.hooks/build_llms_txt.py"

-"docs/.hooks/algolia.py"

lint = ["mypy>=1.11.2","pyright>=1.1.390","ruff>=0.6.9"]

docs = [

"black>=24.10.0",

"bs4>=0.0.2",

"markdownify>=0.14.1",

"mkdocs>=1.6.1",

"mkdocs-glightbox>=0.4.0",

"mkdocs-llmstxt>=0.2.0",

"mkdocs-material[imaging]>=9.5.45",

"mkdocstrings-python>=1.12.2",

]