web

web/agent/.gitignore

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+venv/
+__pycache__/
+*.pyc
+.env
+.vercel
+
+# python
+.venv/
+.langgraph_api/

web/agent/langgraph.json

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+{
+  "python_version": "3.12",
+  "dockerfile_lines": [],
+  "dependencies": ["."],
+  "package_manager": "uv",
+  "graphs": {
+    "sample_agent": "./main.py:graph"
+  },
+  "env": ".env"
+}

web/agent/main.py

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+"""
+This is the main entry point for the agent.
+It defines the workflow graph, state, tools, nodes and edges.
+"""
+
+from typing import Any, List
+
+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, MessagesState, StateGraph
+from langgraph.prebuilt import ToolNode
+from langgraph.types import Command
+
+
+class AgentState(MessagesState):
+    """
+    Here we define the state of the agent
+
+    In this instance, we're inheriting from CopilotKitState, which will bring in
+    the CopilotKitState fields. We're also adding a custom field, `language`,
+    which will be used to set the language of the agent.
+    """
+
+    proverbs: List[str]
+    tools: List[Any]
+    # your_custom_agent_state: str = ""
+
+
+@tool
+def get_weather(location: str):
+    """
+    Get the weather for a given location.
+    """
+    return f"The weather for {location} is 70 degrees."
+
+
+# @tool
+# def your_tool_here(your_arg: str):
+#     """Your tool description here."""
+#     print(f"Your tool logic here")
+#     return "Your tool response here."
+
+backend_tools = [
+    get_weather
+    # your_tool_here
+]
+
+# Extract tool names from backend_tools for comparison
+backend_tool_names = [tool.name for tool in backend_tools]
+
+
+async def chat_node(state: AgentState, config: RunnableConfig) -> Command[str]:
+    """
+    Standard chat node based on the ReAct design pattern. It handles:
+    - The model to use (and binds in CopilotKit actions and the tools defined above)
+    - The system prompt
+    - Getting a response from the model
+    - Handling tool calls
+
+    For more about the ReAct design pattern, see:
+    https://www.perplexity.ai/search/react-agents-NcXLQhreS0WDzpVaS4m9Cg
+    """
+
+    # 1. Define the model
+    model = ChatOpenAI(model="gpt-5-mini")
+
+    # 2. Bind the tools to the model
+    model_with_tools = model.bind_tools(
+        [
+            *state.get("tools", []),  # bind tools defined by ag-ui
+            *backend_tools,
+            # your_tool_here
+        ],
+        # 2.1 Disable parallel tool calls to avoid race conditions,
+        #     enable this for faster performance if you want to manage
+        #     the complexity of running tool calls in parallel.
+        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")
+
+graph = workflow.compile()

web/agent/pyproject.toml

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+[project]
+name = "sample-agent"
+version = "0.1.0"
+description = "A LangGraph agent"
+requires-python = ">=3.12"
+dependencies = [
+    "langchain==1.1.0",
+    "langgraph==1.0.4",
+    "langsmith>=0.4.49",
+    "openai>=1.68.2,<2.0.0",
+    "fastapi>=0.115.5,<1.0.0",
+    "uvicorn>=0.29.0,<1.0.0",
+    "python-dotenv>=1.0.0,<2.0.0",
+    "langgraph-cli[inmem]>=0.4.7",
+    "langchain-openai>=1.1.0",
+]