# import gradio as gr
# import random
# from smolagents import GradioUI, CodeAgent, HfApiModel

# # Import our custom tools from their modules
# from tools import DuckDuckGoSearchTool, WeatherInfoTool, HubStatsTool
# from retriever import load_guest_dataset

# # Initialize the Hugging Face model
# model = HfApiModel()

# # Initialize the web search tool
# search_tool = DuckDuckGoSearchTool()

# # Initialize the weather tool
# weather_info_tool = WeatherInfoTool()

# # Initialize the Hub stats tool
# hub_stats_tool = HubStatsTool()

# # Load the guest dataset and initialize the guest info tool
# guest_info_tool = load_guest_dataset()

# # Create Alfred with all the tools
# alfred = CodeAgent(
#     tools=[guest_info_tool, weather_info_tool, hub_stats_tool, search_tool], 
#     model=model,
#     add_base_tools=True,  # Add any additional base tools
#     planning_interval=3   # Enable planning every 3 steps
# )

# if __name__ == "__main__":
#     GradioUI(alfred).launch()


from typing import TypedDict, Annotated
from langgraph.graph.message import add_messages
from langchain_core.messages import AnyMessage, HumanMessage, AIMessage
from langgraph.prebuilt import ToolNode
from langgraph.graph import START, StateGraph
from langgraph.prebuilt import tools_condition
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace

from tools import DuckDuckGoSearchRun, weather_info_tool, hub_stats_tool
from retriever import guest_info_tool

# Initialize the web search tool
search_tool = DuckDuckGoSearchRun()

# Generate the chat interface, including the tools
llm = HuggingFaceEndpoint(
    repo_id="Qwen/Qwen2.5-Coder-32B-Instruct",
    huggingfacehub_api_token=HUGGINGFACEHUB_API_TOKEN,
)

chat = ChatHuggingFace(llm=llm, verbose=True)
tools = [guest_info_tool, search_tool, weather_info_tool, hub_stats_tool]
chat_with_tools = chat.bind_tools(tools)

# Generate the AgentState and Agent graph
class AgentState(TypedDict):
    messages: Annotated[list[AnyMessage], add_messages]

def assistant(state: AgentState):
    return {
        "messages": [chat_with_tools.invoke(state["messages"])],
    }

## The graph
builder = StateGraph(AgentState)

# Define nodes: these do the work
builder.add_node("assistant", assistant)
builder.add_node("tools", ToolNode(tools))

# Define edges: these determine how the control flow moves
builder.add_edge(START, "assistant")
builder.add_conditional_edges(
    "assistant",
    # If the latest message requires a tool, route to tools
    # Otherwise, provide a direct response
    tools_condition,
)
builder.add_edge("tools", "assistant")
alfred = builder.compile()

if __name__ == "__main__":
    GradioUI(alfred).launch()