copilotkit--copilotkit/showcase/integrations/pydantic-ai/PARITY_NOTES.md

Parity Notes

Baseline: showcase/integrations/langgraph-python/.

This document lists demos present in the langgraph-python reference that are not ported to the PydanticAI showcase, with the reason for each skip. See manifest.yaml for the full list of demos that are shipped in this package.

Recently ported demos

• gen-ui-tool-based — Tool-based generative UI with frontend-registered render_bar_chart and render_pie_chart components. The PydanticAI agent uses a chart-viz system prompt and relies on the runtime to surface frontend-registered tool definitions on each run; no backend tool implementations are required because the components handle rendering directly on the client.

New demos (post-PR #4271)

The following demos introduced on main via PR #4271 are now ported:

• byoc-json-render — @json-render/react BYOC pattern with JSONUIProvider wrapping <Renderer /> and MetricCard children forwarding (both post-#4271 fixes preserved).
• byoc-hashbrown — @hashbrownai/react BYOC pattern. The PydanticAI agent emits the post-#4271 JSON envelope {"ui": [{componentName: {"props": {...}}}]} verbatim.
• multimodal — image / PDF attachments. Images flow to GPT-4o vision natively via OpenAIResponsesModel. PDFs are flattened to inline text via pypdf inside a PydanticAI history_processors hook (equivalent to langgraph-python's _PdfFlattenMiddleware). The frontend's onRunInitialized shim and LFS-pointer guard are kept intact.
• voice — audio transcription. Route reuses the main sales agent at the PydanticAI root as a neutral backing agent; the GuardedOpenAITranscriptionService + direct-instance wiring pattern is lifted verbatim from the langgraph-python reference.
• agent-config — forwardedProps routing. The TS runtime route subclasses HttpAgent to repack provider properties into an AG-UI context entry tagged agent-config-properties; the Python agent's dynamic @agent.system_prompt reads that entry. Framework-specific adaptation vs. langgraph-python's forwardedProps.config.configurable path — user-visible behaviour is identical.
• auth — bearer token auth. Gate is built on createCopilotRuntimeHandler from @copilotkit/runtime/v2 with the onRequest hook, framework-agnostic. Post-#4271 fixes preserved (default authenticated, ChatErrorBoundary, inverted button labels).

Skipped demos

• mcp-apps — Requires CopilotKit MCP Apps middleware wired to a remote MCP server (Excalidraw). The PydanticAI integration exposes tools via agent.to_ag_ui() and does not yet have a documented MCP-apps path through the Python SDK's A2UI middleware as of this writing. Can be revisited when copilotkit-sdk-python grows first-class MCP client support across AG-UI integrations. The beautiful-chat and headless-complete cells are ported with their Excalidraw suggestion pills intentionally omitted (the rest of each cell is at parity).

• agentic-chat-reasoning, reasoning-default-render, tool-rendering-reasoning-chain — These three demos depend on deepagents.create_deep_agent to emit reasoning/thinking tokens alongside regular tool calls. PydanticAI has its own reasoning model support (OpenAIResponsesModel with reasoning enabled) but does not currently stream reasoning content as AG-UI THINKING_* events through agent.to_ag_ui(). Skipped until that bridge exists; a faked version would not reflect the real integration.

• gen-ui-interrupt, interrupt-headless, hitl-in-chat, hitl-in-chat-booking — All four demos are built on LangGraph's interrupt() primitive (pauses graph execution mid-tool-call and surfaces the payload to the client via useInterrupt). PydanticAI does not have an equivalent interrupt/resume primitive — its tools run to completion. Skipped as framework-specific. (The HITL experience in this package is delivered via the hitl and hitl-in-app cells, which use a frontend-tool-driven approval pattern that does not require backend interrupts.)

Parked for future parity

These demos are intentionally not in scope for the PydanticAI package today — none remain now that the post-#4271 demos listed above have landed.

Partial parity — ported with documented gaps

The following demos are in the package but do not ship 100% of the langgraph-python behaviour:

• headless-complete — ported without the Excalidraw-via-MCP suggestion (see mcp-apps skip above). The reasoning-message branch of use-rendered-messages.tsx is omitted because @ag-ui/core@0.0.43 (the version pinned in this package) does not export ReasoningMessage and PydanticAI's AG-UI adapter does not emit reasoning content today. All other rendering surfaces (per-tool renderers, frontend components, default catch-all) are at parity.

• beautiful-chat — ported without the Excalidraw-via-MCP suggestion. Shared todo state uses PydanticAI's StateSnapshotEvent (emitted on manage_todos completion) instead of langgraph-python's StateStreamingMiddleware per-token deltas — the shared todo list still syncs, just without per-character streaming animation. All other surfaces (A2UI fixed + dynamic, Open Generative UI, HITL, frontend tools) are at parity.