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djangorestframework-pydantic-ai

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Expose djangorestframework-services services and selectors as a Pydantic-AI toolset, so a plain pydantic_ai.Agent can call them as tools — no MCP server and no AG-UI bridge in the path.

Every tool call routes through drf-services' transport-neutral surface (dispatch_spec plus its off-HTTP helpers), so a tool call runs the same input validation, the same permission_classes — both class-level has_permission and object-level has_object_permission on the resolved row — and the same serializer rendering your DRF views apply, just without the HTTP hop.

Install

pip install djangorestframework-pydantic-ai

It depends only on djangorestframework-services and pydantic-ai-slim. A model provider is pulled in separately, the usual Pydantic-AI way (e.g. pip install "pydantic-ai-slim[anthropic]").

Quickstart

from pydantic_ai import Agent
from rest_framework_pydantic_ai import AgentDeps, SpecToolset

toolset = SpecToolset(
    {
        "list_orders": orders_selector_spec,  # SelectorSpec -> read-only tool
        "create_order": create_order_spec,  # ServiceSpec  -> mutation tool
    }
)

agent = Agent("anthropic:claude-opus-4-8", deps_type=AgentDeps, toolsets=[toolset])

result = await agent.run(
    "create an order of 3 widgets",
    deps=AgentDeps(user=request.user),
)

The agent acts as deps.user: each call builds an off-HTTP request/view context, enforces the spec's permission_classes (class- and object-level), dispatches the spec, and renders the result through the spec's serializer. List selectors gain page / limit / order tool args, and return one page — {"items": [...], "page": 1, "totalPages": N, "hasNext": bool} — so a model reading a collection can tell whether it saw all of it.

Failures map onto the model loop so the agent self-corrects: invalid input, a bad page / limit / order value, and unexpected (hallucinated) arguments come back as ModelRetry; a business error or missing row becomes a readable ToolFailed, which the model sees as a failed call rather than a successful one carrying prose, and a call an Affordance refuses names the rule as well as the reason (The books are closed. (code: books_closed)); a denied permission raises PermissionDenied, which aborts the run under a plain pydantic_ai.Agent. A host that installs a tool-failure policy — django-pydantic-agent's build_agent does by default — turns that denial into a failed-tool result instead, so the run continues; the call is still denied either way. Unexpected arguments are rejected by default — pass unknown_arguments= to SpecToolset (IGNORE / PASSTHROUGH) to change that.

A tool whose Affordance condition is unmet right now, such as posting to a closed period, is left out of that step's tool list, and the step's instructions name it with its reason so the model can tell the user why. Permissions do not filter the list: a denied tool is still offered, and the denial comes on the call.

Every line of the instructions block is a field of AgentConventions, the heading of the unavailable list included, and so are a handle field's fallback description, the sentence scoping a paged tool's read-shaping parameters, and the missing-argument retry. SpecToolset(specs, conventions=AgentConventions(pagination=...)) rewords one line and leaves the rest as they are. The toolset still decides when each line is said, and None drops a line. Argument descriptions, such as those of limit and page, and the toolset's other retries stay fixed.

See the documentation for the full reference.

License

MIT

Metadata

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