> ## Documentation Index
> Fetch the complete documentation index at: https://phaseo.app/docs/llms.txt
> Use this file to discover all available pages before exploring further.

> ## Agent Instructions
> Phaseo Gateway base URL: https://api.phaseo.app/v1. Send `Authorization: Bearer $PHASEO_API_KEY` with every request.
> Model IDs look like `provider/model`, for example `openai/gpt-6-astra`. Do not guess IDs: list them with `GET /v1/models` or check https://phaseo.app/models. `phaseo/free` routes to an available free model and needs no wallet balance.
> For new text integrations prefer `POST /v1/responses`. `POST /v1/chat/completions` (OpenAI format) and `POST /v1/messages` (Anthropic format) suit existing code.
> The full API contract is https://phaseo.app/docs/openapi/v1/openapi.yaml. Official SDKs: `@phaseo/sdk` (TypeScript) and `phaseo` (Python), plus Go, C#, PHP, Ruby and Rust.
> Search these docs over MCP at https://phaseo.app/docs/mcp, and install Phaseo skills with `npx skills add https://phaseo.app/docs`. If a page is wrong or out of date, report it with the MCP `submit_feedback` tool.
> Manage Phaseo accounts with the `phaseo` CLI (`npm install -g @phaseo/cli`, then `phaseo login` or `phaseo login --device-code`), the `/v1` Management API or the MCP server at `https://mcp.phaseo.app/mcp?access=manage`. Do not send users to the dashboard for account tasks. A person is still needed for sign-up, approving a sign-in, paying the first top-up on the checkout link that `phaseo credits add` returns when no card is saved, confirming each saved-card top-up from the emailed link, and account security (password, MFA, passkeys). Create API keys with `phaseo keys create --name <name> --json`; never guess one. Credit top-ups need `phaseo login --scopes billing:write` first. Task map: https://phaseo.app/docs/v1/developers/manage-from-an-agent.md.

# PydanticAI

> Build typed Python agents with PydanticAI and Phaseo.

Use PydanticAI when you want Python agents with typed outputs, validation, and a compact OpenAI-compatible model setup.

## Install

```bash theme={null}
pip install "pydantic-ai-slim[openai]"
```

## Configure the model

```python theme={null}
import os
from pydantic_ai import Agent
from pydantic_ai.models.openai import OpenAIChatModel
from pydantic_ai.providers.openai import OpenAIProvider

model = OpenAIChatModel(
    "openai/gpt-5-nano",
    provider=OpenAIProvider(
        api_key=os.environ["PHASEO_API_KEY"],
        base_url="https://api.phaseo.app/v1",
    ),
)

agent = Agent(model, system_prompt="Answer concisely.")
result = agent.run_sync("Reply with only: ok")
print(result.output)
```

## Notes

* PydanticAI's OpenAI-compatible path uses OpenAI-style chat behavior.
* Use direct Phaseo Responses calls for Responses-only features such as `phaseo:apply_patch`.
* Keep structured output schemas small enough for the selected model's context window.

## Related

* [Structured Outputs](https://phaseo.app/docs/v1/guides/structured-outputs.md)
* [OpenAI SDK](https://phaseo.app/docs/v1/guides/integrations/openai-sdk.md)
* [Models](https://phaseo.app/docs/v1/api-reference/endpoint/models.md)


This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.