feat: use create_agent

Signed-off-by: Tyler Slaton <tyler@copilotkit.ai>

Author: tylerslaton

agent/main.py

@@ -5,20 +5,9 @@
 
 from typing import List
 
-from copilotkit import CopilotKitState
 from langchain.tools import tool
-from langchain_core.messages import BaseMessage, SystemMessage
-from langchain_core.runnables import RunnableConfig
-from langchain_openai import ChatOpenAI
-from langgraph.graph import END, StateGraph
-from langgraph.prebuilt import ToolNode
-from langgraph.types import Command
-
-
-class AgentState(CopilotKitState):
-    proverbs: List[str]
-    # your_custom_agent_state: str = ""
-
+from langchain.agents import create_agent
+from copilotkit import CopilotKitMiddleware, CopilotKitState
 
 @tool
 def get_weather(location: str):
@@ -27,77 +16,15 @@ def get_weather(location: str):
     """
     return f"The weather for {location} is 70 degrees."
 
+class AgentState(CopilotKitState):
+    proverbs: List[str]
 
-# Extract tool names from backend_tools for comparison
-backend_tools = [get_weather]
-backend_tool_names = [tool.name for tool in backend_tools]
-
-
-async def chat_node(state: AgentState, config: RunnableConfig) -> Command[str]:
-    # 1. Define the model
-    model = ChatOpenAI(model="gpt-4.1-mini")
-
-    # 2. Bind the tools to the model
-    model_with_tools = model.bind_tools(
-        [
-            *state.get("copilotkit", {}).get("actions", []),
-            *backend_tools,
-        ],
-        parallel_tool_calls=False,
-    )
-
-    # 3. Define the system message by which the chat model will be run
-    system_message = SystemMessage(
-        content=f"You are a helpful assistant. The current proverbs are {state.get('proverbs', [])}."
-    )
-
-    # 4. Run the model to generate a response
-    response = await model_with_tools.ainvoke(
-        [
-            system_message,
-            *state["messages"],
-        ],
-        config,
-    )
-
-    # only route to tool node if tool is not in the tools list
-    if route_to_tool_node(response):
-        print("routing to tool node")
-        return Command(
-            goto="tool_node",
-            update={
-                "messages": [response],
-            },
-        )
-
-    # 5. We've handled all tool calls, so we can end the graph.
-    return Command(
-        goto=END,
-        update={
-            "messages": [response],
-        },
-    )
-
-
-def route_to_tool_node(response: BaseMessage):
-    """
-    Route to tool node if any tool call in the response matches a backend tool name.
-    """
-    tool_calls = getattr(response, "tool_calls", None)
-    if not tool_calls:
-        return False
-
-    for tool_call in tool_calls:
-        if tool_call.get("name") in backend_tool_names:
-            return True
-    return False
-
-
-# Define the workflow graph
-workflow = StateGraph(AgentState)
-workflow.add_node("chat_node", chat_node)
-workflow.add_node("tool_node", ToolNode(tools=backend_tools))
-workflow.add_edge("tool_node", "chat_node")
-workflow.set_entry_point("chat_node")
+agent = create_agent(
+    model="gpt-4.1-mini",
+    tools=[get_weather],
+    middleware=[CopilotKitMiddleware()],
+    state_schema=AgentState,
+    system_prompt="You are a helpful research assistant."
+)
 
-graph = workflow.compile()
+graph = agent