import { ChatAnthropic } from "@langchain/anthropic";
import { Annotation, END, START, StateGraph } from "@langchain/langgraph";
import { GenerativeUIAnnotation } from "../types";
import { z } from "zod";
import { AIMessage, ToolMessage } from "@langchain/langgraph-sdk";
import { v4 as uuidv4 } from "uuid";

const PizzaOrdererAnnotation = Annotation.Root({
  messages: GenerativeUIAnnotation.spec.messages,
})

async function sleep(ms = 5000) {
  return new Promise((resolve) => setTimeout(resolve, ms));
}

const workflow = new StateGraph(PizzaOrdererAnnotation)
  .addNode("findStore", async (state) => {
    const findShopSchema = z.object({
      location: z.string().describe("The location the user is in. E.g. 'San Francisco' or 'New York'"),
      pizza_company: z.string().optional().describe("The name of the pizza company. E.g. 'Dominos' or 'Papa John's'. Optional, if not defined it will search for all pizza shops"),
    }).describe("The schema for finding a pizza shop for the user")
    const model = new ChatAnthropic({ model: "claude-3-5-sonnet-latest", temperature: 0 }).withStructuredOutput(findShopSchema, {
      name: "find_pizza_shop",
      includeRaw: true,
    })

    const response = await model.invoke([
      {
        role: "system",
        content: "You are a helpful AI assistant, tasked with extracting information from the conversation between you, and the user, in order to find a pizza shop for them."
      },
      ...state.messages,
    ])

    await sleep();

    const toolResponse: ToolMessage = {
      type: "tool",
      id: uuidv4(),
      content: "I've found a pizza shop at 1119 19th St, San Francisco, CA 94107. The phone number for the shop is 415-555-1234.",
      tool_call_id: (response.raw as unknown as AIMessage).tool_calls?.[0].id ?? "",
    }
    
    return {
      messages: [response.raw, toolResponse]
    }
  })
  .addNode("orderPizza", async (state) => {
    await sleep(1500);

    const placeOrderSchema = z.object({
      address: z.string().describe("The address of the store to order the pizza from"),
      phone_number: z.string().describe("The phone number of the store to order the pizza from"),
      order: z.string().describe("The full pizza order for the user"),
    }).describe("The schema for ordering a pizza for the user")
    const model = new ChatAnthropic({ model: "claude-3-5-sonnet-latest", temperature: 0 }).withStructuredOutput(placeOrderSchema, {
      name: "place_pizza_order",
      includeRaw: true,
    })

    const response = await model.invoke([
      {
        role: "system",
        content: "You are a helpful AI assistant, tasked with placing an order for a pizza for the user."
      },
      ...state.messages,
    ])

    const toolResponse: ToolMessage = {
      type: "tool",
      id: uuidv4(),
      content: "Pizza order successfully placed.",
      tool_call_id: (response.raw as unknown as AIMessage).tool_calls?.[0].id ?? "",
    }
    
    return {
      messages: [response.raw, toolResponse]
    }
  })
  .addEdge(START, "findStore")
  .addEdge("findStore", "orderPizza")
  .addEdge("orderPizza", END)

export const graph = workflow.compile()
graph.name = "Order Pizza Graph";