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django-pydantic-agent

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The settings-agnostic agent-host substrate shared by Django's Pydantic-AI transports.

It takes an AgentConfig in and returns a built pydantic_ai.Agent — with composed toolsets, audit, and user resolution — and reads no Django settings of its own. Each transport owns its settings namespace, builds an AgentConfig, and hands it down:

  • django-ag-ui — AG-UI over SSE for a browser client.
  • django-a2a — agent-to-agent (planned).
pip install django-pydantic-agent

Most projects install a transport and get this as a dependency. Reach for it directly when you are building a transport, sharing agent construction between two of them, or embedding an agent with no HTTP surface at all.

from django_pydantic_agent import AgentConfig, ToolRegistry, build_agent, tool

registry = ToolRegistry()


@tool(registry)
def list_orders(status: str) -> list[dict]:
    """List orders with the given status."""
    ...


agent = build_agent(registry, AgentConfig(model="anthropic:claude-sonnet-4-5"))

What it provides

  • Agent constructionAgentConfigbuild_agent, model and provider resolution, and an escape hatch to replace construction entirely.
  • A tool registry@tool with destructive / category / confirm / summary metadata, and JSON Schema derived from the signature.
  • Storage contractsConversationStore / AttachmentStore protocols, reference implementations, and Django models in contrib.store.
  • Policy — an audit trail over every tool call, and a server-side approval gate for destructive tools. Both off by default.
  • Integrations — optional bridges exposing djangorestframework-services specs or a drf-mcp-server registry as agent tools, in process.

Optional extras: [drf-mcp] (bridge a drf-mcp-server registry as a toolset), [spec-tools] (drf-services specs as agent tools), [harness] (pydantic-ai-harness capabilities), and the provider extras [anthropic] / [openai] / [google].

Documentation

https://artui.github.io/django-pydantic-agent/

  • Concepts — how a config becomes an agent, and what belongs here versus in a transport.
  • Tools — registering tools and what the metadata does.
  • Storage — the store contracts, owner scoping, and the reference models.
  • Policy — audit and the destructive-tool gate.
  • Integrations — DRF specs and MCP tools as agent tools.
  • Reference — the full public API.

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