Prebuilt Components

"""LangGraph agent for the CopilotKit Showcase (FastAPI variant).Uses copilotkit's create_agent (wrapping langgraph) with CopilotKitMiddlewareso frontend-registered tools (useHumanInTheLoop, useFrontendTool) are properlyinjected into the LLM's tool list and executed on the frontend rather thanlocally."""from tools import (    get_weather_impl,    query_data_impl,    schedule_meeting_impl,    manage_sales_todos_impl,    get_sales_todos_impl,    search_flights_impl,    build_a2ui_operations_from_tool_call,)from tools.types import SalesTodo, Flightimport jsonimport timefrom typing import Anyfrom langchain_openai import ChatOpenAIfrom langchain_core.tools import tool as lc_toolfrom langchain_core.messages import SystemMessagefrom langchain.agents import AgentState as BaseAgentState, create_agentfrom langchain.tools import ToolRuntime, toolfrom langchain.messages import ToolMessagefrom langgraph.types import Commandfrom copilotkit import CopilotKitMiddlewareclass AgentState(BaseAgentState):    todos: list[SalesTodo]@lc_tooldef get_weather(location: str):    """Get the current weather for a location."""    return get_weather_impl(location)@lc_tooldef query_data(query: str):    """Query the database. Takes natural language. Always call before showing a chart."""    return query_data_impl(query)@lc_tooldef schedule_meeting(reason: str, duration_minutes: int = 30):    """Schedule a meeting. The user will be asked to pick a time via the UI."""    return schedule_meeting_impl(reason, duration_minutes)@lc_tooldef search_flights(flights: list[Flight]) -> str:    """Search for flights and display the results as rich cards. Return exactly 2 flights.    Each flight must have: airline, airlineLogo, flightNumber, origin, destination,    date (short readable format like "Tue, Mar 18" -- use near-future dates),    departureTime, arrivalTime, duration (e.g. "4h 25m"),    status (e.g. "On Time" or "Delayed"),    statusColor (hex color for status dot),    price (e.g. "$289"), and currency (e.g. "USD").    For airlineLogo use Google favicon API:    https://www.google.com/s2/favicons?domain={airline_domain}&sz=128    """    result = search_flights_impl(flights)    return json.dumps(result)@tooldef manage_sales_todos(todos: list[SalesTodo], runtime: ToolRuntime) -> Command:    """    Manage the current sales todos. Pass the full updated list.    """    updated = manage_sales_todos_impl(todos)    return Command(        update={            "todos": updated,            "messages": [                ToolMessage(                    content="Successfully updated sales todos",                    tool_call_id=runtime.tool_call_id,                )            ],        }    )@tooldef get_sales_todos(runtime: ToolRuntime):    """    Get the current sales todos.    """    current = runtime.state.get("todos", [])    return get_sales_todos_impl(current if current else None)@lc_tooldef render_a2ui(    surfaceId: str,    catalogId: str,    components: list[dict],    data: dict | None = None,) -> str:    """Render a dynamic A2UI v0.9 surface."""    return "rendered"@tool()def generate_a2ui(runtime: ToolRuntime[Any]) -> str:    """Generate dynamic A2UI components based on the conversation.    A secondary LLM designs the UI schema and data.    """    t0 = time.time()    messages = runtime.state["messages"][:-1]    context_entries = runtime.state.get("copilotkit", {}).get("context", [])    context_text = "\n\n".join(        entry.get("value", "")        for entry in context_entries        if isinstance(entry, dict) and entry.get("value")    )    model = ChatOpenAI(model="gpt-4.1")    model_with_tool = model.bind_tools([render_a2ui], tool_choice="render_a2ui")    response = model_with_tool.invoke(        [SystemMessage(content=context_text), *messages],    )    if not response.tool_calls:        return json.dumps({"error": "LLM did not call render_a2ui"})    args = response.tool_calls[0]["args"]    result = build_a2ui_operations_from_tool_call(args)    return json.dumps(result)model = ChatOpenAI(model="gpt-4o-mini")SYSTEM_PROMPT = """You are a polished, professional demo assistant for CopilotKit.Keep responses brief and clear -- 1 to 2 sentences max.You can:- Chat naturally with the user- Change the UI background when asked (via frontend tool)- Query data and render charts (via query_data tool)- Get weather information (via get_weather tool)- Schedule meetings with the user (via schedule_meeting tool -- the user picks a time in the UI)- Manage sales pipeline todos (via manage_sales_todos / get_sales_todos tools)- Search flights and display rich A2UI cards (via search_flights tool)- Generate dynamic A2UI dashboards from conversation context (via generate_a2ui tool)- Generate step-by-step plans for user review (human-in-the-loop)"""graph = create_agent(    model=model,    tools=[        get_weather,        query_data,        schedule_meeting,        search_flights,        generate_a2ui,        manage_sales_todos,        get_sales_todos,    ],    middleware=[CopilotKitMiddleware()],    state_schema=AgentState,    system_prompt=SYSTEM_PROMPT,)