import os
from typing import TypedDict, Annotated
from dotenv import load_dotenv
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, MessagesState
from langgraph.prebuilt import tools_condition
from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_groq import ChatGroq
from langchain_openai import ChatOpenAI

from tools import (
    divide,
    multiply,
    modulus,
    add,
    subtract,
    power,
    square_root,
    web_search,
    wiki_search,
    arxiv_search,
)

# load api key
load_dotenv()


def buildAgent(provider="huggingface"):
    # Generate the chat interface, including the tools
    if provider == "huggingface":
        llm = ChatHuggingFace(
            llm=HuggingFaceEndpoint(repo_id="Qwen/Qwen2.5-Coder-32B-Instruct"),
        )
    elif provider == "groq":
        llm = ChatGroq(model="qwen-qwq-32b")
    elif provider == "openrouter":
        llm = ChatOpenAI(
            base_url="https://openrouter.ai/api/v1",
            api_key=os.environ.get("OPENROUTER_API_KEY"),
            model="google/gemini-2.0-flash-exp",
        )

    tools = [
        multiply,
        add,
        subtract,
        divide,
        modulus,
        power,
        square_root,
        web_search,
        wiki_search,
        arxiv_search,
    ]

    chat_with_tools = llm.bind_tools(tools)

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

    ## The graph
    builder = StateGraph(MessagesState)
    # 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")
    return builder.compile()


if __name__ == "__main__":
    question = "When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?"
    graph = buildAgent(provider="groq")
    messages = [HumanMessage(content=question)]
    print(messages)
    messages = graph.invoke({"messages": messages})
    for m in messages["messages"]:
        m.pretty_print()