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"""Dynamic A2UI tool: LLM-generated UI from conversation context.
This module provides the data preparation for a secondary LLM call that
generates v0.9 A2UI components. The actual LLM call is made by the
framework-specific wrapper (LangGraph, CrewAI, etc.) since each framework
has its own way of invoking LLMs.
"""
from __future__ import annotations
import logging
from typing import Any, Optional
_logger = logging.getLogger(__name__)
CUSTOM_CATALOG_ID = "copilotkit://app-dashboard-catalog"
# The _design_a2ui_surface tool schema that the secondary LLM is bound to.
DESIGN_A2UI_SURFACE_TOOL_SCHEMA = {
"name": "_design_a2ui_surface",
"description": (
"Render a dynamic A2UI v0.9 surface.\n\n"
"Args:\n"
" surfaceId: Unique surface identifier.\n"
' catalogId: The catalog ID (use "copilotkit://app-dashboard-catalog").\n'
" components: A2UI v0.9 component array (flat format). "
'The root component must have id "root".\n'
" data: Optional initial data model for the surface."
),
"parameters": {
"type": "object",
"properties": {
"surfaceId": {
"type": "string",
"description": "Unique surface identifier.",
},
"catalogId": {"type": "string", "description": "The catalog ID."},
"components": {
"type": "array",
"items": {"type": "object"},
"description": "A2UI v0.9 component array (flat format).",
},
"data": {
"type": "object",
"description": "Optional initial data model for the surface.",
},
},
"required": ["surfaceId", "catalogId", "components"],
},
}
def generate_a2ui_impl(
messages: list[dict[str, Any]],
context_entries: Optional[list[dict[str, Any]]] = None,
) -> dict[str, Any]:
"""Prepare inputs for a secondary LLM call that generates A2UI components.
Returns a dict with:
- system_prompt: The system prompt for the secondary LLM (built from context)
- tool_schema: The _design_a2ui_surface tool schema to bind to the LLM
- tool_choice: The tool name to force
- messages: The conversation messages to pass through
- catalog_id: The default catalog ID
The framework wrapper should:
1. Make an LLM call with these inputs
2. Extract the tool call args (surfaceId, catalogId, components, data)
3. Build a2ui_operations from the args and return them
"""
context_text = ""
if context_entries:
context_text = "\n\n".join(
entry.get("value", "")
for entry in context_entries
if isinstance(entry, dict) and entry.get("value")
)
return {
"system_prompt": context_text,
"tool_schema": DESIGN_A2UI_SURFACE_TOOL_SCHEMA,
"tool_choice": "_design_a2ui_surface",
"messages": messages,
"catalog_id": CUSTOM_CATALOG_ID,
}
def build_a2ui_operations_from_tool_call(args: dict[str, Any]) -> dict[str, Any]:
"""Build a2ui_operations dict from the secondary LLM's tool call args.
Call this after the framework wrapper extracts the tool call arguments.
The returned operations use the A2UI v0.9 NESTED shape (mirroring
`copilotkit.a2ui.create_surface` / `update_components` / `update_data_model`
from langgraph-python). The `@ag-ui/a2ui-middleware` extracts the
surfaceId via `op.createSurface?.surfaceId ?? op.updateComponents?.surfaceId
?? ...` — a flat `{"type": "create_surface", "surfaceId": ...}` shape leaves
every op under a "default" surface and the renderer never binds to the
registered catalog.
"""
surface_id = args.get("surfaceId", "dynamic-surface")
catalog_id = args.get("catalogId", CUSTOM_CATALOG_ID)
components = args.get("components", [])
if not components:
_logger.warning(
"build_a2ui_operations_from_tool_call received empty components list"
)
data = args.get("data")
ops: list[dict[str, Any]] = [
{
"version": "v0.9",
"createSurface": {
"surfaceId": surface_id,
"catalogId": catalog_id,
},
},
{
"version": "v0.9",
"updateComponents": {
"surfaceId": surface_id,
"components": components,
},
},
]
if data:
ops.append(
{
"version": "v0.9",
"updateDataModel": {
"surfaceId": surface_id,
"path": "/",
"value": data,
},
}
)
return {"a2ui_operations": ops}