Customer-support-bot.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Customer Support Bot"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Import libraries"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import dotenv\n",
    "from dotenv import load_dotenv\n",
    "import shutil\n",
    "import sqlite3\n",
    "\n",
    "\n",
    "import pandas as pd\n",
    "import requests\n",
    "import re\n",
    "import numpy as np\n",
    "import openai\n",
    "from langchain_core.tools import tool\n",
    "\n",
    "import sqlite3\n",
    "from datetime import date, datetime\n",
    "from typing import Optional\n",
    "import pytz\n",
    "from langchain_core.runnables import ensure_config\n",
    "\n",
    "from langchain_core.runnables import RunnableLambda\n",
    "from langchain_core.messages import ToolMessage\n",
    "from langgraph.prebuilt import ToolNode\n",
    "\n",
    "from typing import Annotated, Literal, Optional, Union, Callable\n",
    "from typing_extensions import TypedDict\n",
    "from langgraph.graph.message import AnyMessage, add_messages\n",
    "\n",
    "\n",
    "from langchain_openai import ChatOpenAI\n",
    "from langchain_community.tools.tavily_search import TavilySearchResults\n",
    "from langchain_core.prompts import ChatPromptTemplate\n",
    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
    "from langchain_core.runnables import Runnable, RunnableConfig\n",
    "\n",
    "from langgraph.checkpoint.sqlite import  SqliteSaver\n",
    "from langgraph.graph import END, StateGraph\n",
    "from langgraph.prebuilt import tools_condition\n",
    "\n",
    "from IPython.display import Image, display\n",
    "import shutil\n",
    "import uuid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prerequisities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "os.environ['LANGCHAIN_TRACING_V2'] = 'true'\n",
    "os.environ['LANGCHAIN_PROJECT'] = 'Customer Support Bot'\n",
    "load_dotenv()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Populate the database"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "db_url = \"https://storage.googleapis.com/benchmarks-artifacts/travel-db/travel2.sqlite\"\n",
    "local_file = '/Users/azamatkuzdibayev/train/llm/projects/data/travel.sqlite'\n",
    "# The backup lets  restart \n",
    "backup_file = '/Users/azamatkuzdibayev/train/llm/projects/data/travel.backup.sqlite'\n",
    "overwrite = False\n",
    "if overwrite or not os.path.exists(local_file):\n",
    "    response = requests.get(db_url)\n",
    "    response.raise_for_status()  # Ensure the request was successful\n",
    "    with open(local_file, \"wb\") as f:\n",
    "        f.write(response.content)\n",
    "    # Backup - we will use this to \"reset\"  DB in each section\n",
    "    shutil.copy(local_file, backup_file)\n",
    "\n",
    "conn = sqlite3.connect(local_file)\n",
    "cursor = conn.cursor()\n",
    "\n",
    "tables = pd.read_sql(\n",
    "    \"SELECT name FROM sqlite_master WHERE type='table';\", conn\n",
    ").name.tolist()\n",
    "tdf = {}\n",
    "for t in tables:\n",
    "    tdf[t] = pd.read_sql(f\"SELECT * from {t}\", conn)\n",
    "\n",
    "example_time = pd.to_datetime(\n",
    "    tdf[\"flights\"][\"actual_departure\"].replace(\"\\\\N\", pd.NaT)\n",
    ").max()\n",
    "current_time = pd.to_datetime(\"now\").tz_localize(example_time.tz)\n",
    "time_diff = current_time - example_time\n",
    "\n",
    "tdf[\"bookings\"][\"book_date\"] = (\n",
    "    pd.to_datetime(tdf[\"bookings\"][\"book_date\"].replace(\"\\\\N\", pd.NaT), utc=True)\n",
    "    + time_diff\n",
    ")\n",
    "\n",
    "datetime_columns = [\n",
    "    \"scheduled_departure\",\n",
    "    \"scheduled_arrival\",\n",
    "    \"actual_departure\",\n",
    "    \"actual_arrival\",\n",
    "]\n",
    "for column in datetime_columns:\n",
    "    tdf[\"flights\"][column] = (\n",
    "        pd.to_datetime(tdf[\"flights\"][column].replace(\"\\\\N\", pd.NaT)) + time_diff\n",
    "    )\n",
    "\n",
    "for table_name, df in tdf.items():\n",
    "    df.to_sql(table_name, conn, if_exists=\"replace\", index=False)\n",
    "del df\n",
    "del tdf\n",
    "conn.commit()\n",
    "conn.close()\n",
    "\n",
    "db = local_file  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Tools"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Lookup Company policies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "response = requests.get(\n",
    "    \"https://storage.googleapis.com/benchmarks-artifacts/travel-db/swiss_faq.md\"\n",
    ")\n",
    "response.raise_for_status()\n",
    "faq_text = response.text\n",
    "\n",
    "docs = [{\"page_content\": txt} for txt in re.split(r\"(?=\\n##)\", faq_text)]\n",
    "\n",
    "\n",
    "class VectorStoreRetriever:\n",
    "    def __init__(self, docs: list, vectors: list, oai_client):\n",
    "        self._arr = np.array(vectors)\n",
    "        self._docs = docs\n",
    "        self._client = oai_client\n",
    "\n",
    "    @classmethod\n",
    "    def from_docs(cls, docs, oai_client):\n",
    "        embeddings = oai_client.embeddings.create(\n",
    "            model=\"text-embedding-3-small\", input=[doc[\"page_content\"] for doc in docs]\n",
    "        )\n",
    "        vectors = [emb.embedding for emb in embeddings.data]\n",
    "        return cls(docs, vectors, oai_client)\n",
    "\n",
    "    def query(self, query: str, k: int = 5) -> list[dict]:\n",
    "        embed = self._client.embeddings.create(\n",
    "            model=\"text-embedding-3-small\", input=[query]\n",
    "        )\n",
    "        scores = np.array(embed.data[0].embedding) @ self._arr.T\n",
    "        top_k_idx = np.argpartition(scores, -k)[-k:]\n",
    "        top_k_idx_sorted = top_k_idx[np.argsort(-scores[top_k_idx])]\n",
    "        return [\n",
    "            {**self._docs[idx], \"similarity\": scores[idx]} for idx in top_k_idx_sorted\n",
    "        ]\n",
    "\n",
    "\n",
    "retriever = VectorStoreRetriever.from_docs(docs, openai.Client())\n",
    "\n",
    "\n",
    "@tool\n",
    "def lookup_policy(query: str) -> str:\n",
    "    \"\"\"Consult the company policies to check whether certain options are permitted.\n",
    "    Use this before making any flight changes performing other 'write' events.\"\"\"\n",
    "    docs = retriever.query(query, k=2)\n",
    "    return \"\\n\\n\".join([doc[\"page_content\"] for doc in docs])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Flight Tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "@tool\n",
    "def fetch_user_flight_information() -> list[dict]:\n",
    "    \"\"\"Fetch all tickets for the user along with corresponding flight information and seat assignments.\n",
    "\n",
    "    Returns:\n",
    "        A list of dictionaries where each dictionary contains the ticket details,\n",
    "        associated flight details, and the seat assignments for each ticket belonging to the user.\n",
    "    \"\"\"\n",
    "    config = ensure_config()  # Fetch from the context\n",
    "    configuration = config.get(\"configurable\", {})\n",
    "    passenger_id = configuration.get(\"passenger_id\", None)\n",
    "    if not passenger_id:\n",
    "        raise ValueError(\"No passenger ID configured.\")\n",
    "\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    query = \"\"\"\n",
    "    SELECT \n",
    "        t.ticket_no, t.book_ref,\n",
    "        f.flight_id, f.flight_no, f.departure_airport, f.arrival_airport, f.scheduled_departure, f.scheduled_arrival,\n",
    "        bp.seat_no, tf.fare_conditions\n",
    "    FROM \n",
    "        tickets t\n",
    "        JOIN ticket_flights tf ON t.ticket_no = tf.ticket_no\n",
    "        JOIN flights f ON tf.flight_id = f.flight_id\n",
    "        JOIN boarding_passes bp ON bp.ticket_no = t.ticket_no AND bp.flight_id = f.flight_id\n",
    "    WHERE \n",
    "        t.passenger_id = ?\n",
    "    \"\"\"\n",
    "    cursor.execute(query, (passenger_id,))\n",
    "    rows = cursor.fetchall()\n",
    "    column_names = [column[0] for column in cursor.description]\n",
    "    results = [dict(zip(column_names, row)) for row in rows]\n",
    "\n",
    "    cursor.close()\n",
    "    conn.close()\n",
    "\n",
    "    return results\n",
    "\n",
    "\n",
    "@tool\n",
    "def search_flights(\n",
    "    departure_airport: Optional[str] = None,\n",
    "    arrival_airport: Optional[str] = None,\n",
    "    start_time: Optional[date | datetime] = None,\n",
    "    end_time: Optional[date | datetime] = None,\n",
    "    limit: int = 20,\n",
    ") -> list[dict]:\n",
    "    \"\"\"Search for flights based on departure airport, arrival airport, and departure time range.\"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    query = \"SELECT * FROM flights WHERE 1 = 1\"\n",
    "    params = []\n",
    "\n",
    "    if departure_airport:\n",
    "        query += \" AND departure_airport = ?\"\n",
    "        params.append(departure_airport)\n",
    "\n",
    "    if arrival_airport:\n",
    "        query += \" AND arrival_airport = ?\"\n",
    "        params.append(arrival_airport)\n",
    "\n",
    "    if start_time:\n",
    "        query += \" AND scheduled_departure >= ?\"\n",
    "        params.append(start_time)\n",
    "\n",
    "    if end_time:\n",
    "        query += \" AND scheduled_departure <= ?\"\n",
    "        params.append(end_time)\n",
    "    query += \" LIMIT ?\"\n",
    "    params.append(limit)\n",
    "    cursor.execute(query, params)\n",
    "    rows = cursor.fetchall()\n",
    "    column_names = [column[0] for column in cursor.description]\n",
    "    results = [dict(zip(column_names, row)) for row in rows]\n",
    "\n",
    "    cursor.close()\n",
    "    conn.close()\n",
    "\n",
    "    return results\n",
    "\n",
    "\n",
    "@tool\n",
    "def update_ticket_to_new_flight(ticket_no: str, new_flight_id: int) -> str:\n",
    "    \"\"\"Update the user's ticket to a new valid flight.\"\"\"\n",
    "    config = ensure_config()\n",
    "    configuration = config.get(\"configurable\", {})\n",
    "    passenger_id = configuration.get(\"passenger_id\", None)\n",
    "    if not passenger_id:\n",
    "        raise ValueError(\"No passenger ID configured.\")\n",
    "\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\n",
    "        \"SELECT departure_airport, arrival_airport, scheduled_departure FROM flights WHERE flight_id = ?\",\n",
    "        (new_flight_id,),\n",
    "    )\n",
    "    new_flight = cursor.fetchone()\n",
    "    if not new_flight:\n",
    "        cursor.close()\n",
    "        conn.close()\n",
    "        return \"Invalid new flight ID provided.\"\n",
    "    column_names = [column[0] for column in cursor.description]\n",
    "    new_flight_dict = dict(zip(column_names, new_flight))\n",
    "    timezone = pytz.timezone(\"Etc/GMT-3\")\n",
    "    current_time = datetime.now(tz=timezone)\n",
    "    departure_time = datetime.strptime(\n",
    "        new_flight_dict[\"scheduled_departure\"], \"%Y-%m-%d %H:%M:%S.%f%z\"\n",
    "    )\n",
    "    time_until = (departure_time - current_time).total_seconds()\n",
    "    if time_until < (3 * 3600):\n",
    "        return f\"Not permitted to reschedule to a flight that is less than 3 hours from the current time. Selected flight is at {departure_time}.\"\n",
    "\n",
    "    cursor.execute(\n",
    "        \"SELECT flight_id FROM ticket_flights WHERE ticket_no = ?\", (ticket_no,)\n",
    "    )\n",
    "    current_flight = cursor.fetchone()\n",
    "    if not current_flight:\n",
    "        cursor.close()\n",
    "        conn.close()\n",
    "        return \"No existing ticket found for the given ticket number.\"\n",
    "\n",
    "    # Check the signed-in user actually has this ticket\n",
    "    cursor.execute(\n",
    "        \"SELECT * FROM tickets WHERE ticket_no = ? AND passenger_id = ?\",\n",
    "        (ticket_no, passenger_id),\n",
    "    )\n",
    "    current_ticket = cursor.fetchone()\n",
    "    if not current_ticket:\n",
    "        cursor.close()\n",
    "        conn.close()\n",
    "        return f\"Current signed-in passenger with ID {passenger_id} not the owner of ticket {ticket_no}\"\n",
    "\n",
    "    # In a real application, you'd likely add additional checks here to enforce business logic,\n",
    "    # like \"does the new departure airport match the current ticket\", etc.\n",
    "    # While it's best to try to be *proactive* in 'type-hinting' policies to the LLM\n",
    "    # it's inevitably going to get things wrong, so you **also** need to ensure your\n",
    "    # API enforces valid behavior\n",
    "    cursor.execute(\n",
    "        \"UPDATE ticket_flights SET flight_id = ? WHERE ticket_no = ?\",\n",
    "        (new_flight_id, ticket_no),\n",
    "    )\n",
    "    conn.commit()\n",
    "\n",
    "    cursor.close()\n",
    "    conn.close()\n",
    "    return \"Ticket successfully updated to new flight.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def cancel_ticket(ticket_no: str) -> str:\n",
    "    \"\"\"Cancel the user's ticket and remove it from the database.\"\"\"\n",
    "    config = ensure_config()\n",
    "    configuration = config.get(\"configurable\", {})\n",
    "    passenger_id = configuration.get(\"passenger_id\", None)\n",
    "    if not passenger_id:\n",
    "        raise ValueError(\"No passenger ID configured.\")\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\n",
    "        \"SELECT flight_id FROM ticket_flights WHERE ticket_no = ?\", (ticket_no,)\n",
    "    )\n",
    "    existing_ticket = cursor.fetchone()\n",
    "    if not existing_ticket:\n",
    "        cursor.close()\n",
    "        conn.close()\n",
    "        return \"No existing ticket found for the given ticket number.\"\n",
    "\n",
    "    # Check the signed-in user actually has this ticket\n",
    "    cursor.execute(\n",
    "        \"SELECT flight_id FROM tickets WHERE ticket_no = ? AND passenger_id = ?\",\n",
    "        (ticket_no, passenger_id),\n",
    "    )\n",
    "    current_ticket = cursor.fetchone()\n",
    "    if not current_ticket:\n",
    "        cursor.close()\n",
    "        conn.close()\n",
    "        return f\"Current signed-in passenger with ID {passenger_id} not the owner of ticket {ticket_no}\"\n",
    "\n",
    "    cursor.execute(\"DELETE FROM ticket_flights WHERE ticket_no = ?\", (ticket_no,))\n",
    "    conn.commit()\n",
    "\n",
    "    cursor.close()\n",
    "    conn.close()\n",
    "    return \"Ticket successfully cancelled.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Car Rental Tools"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datetime import date, datetime\n",
    "from typing import Optional, Union\n",
    "\n",
    "\n",
    "@tool\n",
    "def search_car_rentals(\n",
    "    location: Optional[str] = None,\n",
    "    name: Optional[str] = None,\n",
    "    price_tier: Optional[str] = None,\n",
    "    start_date: Optional[Union[datetime, date]] = None,\n",
    "    end_date: Optional[Union[datetime, date]] = None,\n",
    ") -> list[dict]:\n",
    "    \"\"\"\n",
    "    Search for car rentals based on location, name, price tier, start date, and end date.\n",
    "\n",
    "    Args:\n",
    "        location (Optional[str]): The location of the car rental. Defaults to None.\n",
    "        name (Optional[str]): The name of the car rental company. Defaults to None.\n",
    "        price_tier (Optional[str]): The price tier of the car rental. Defaults to None.\n",
    "        start_date (Optional[Union[datetime, date]]): The start date of the car rental. Defaults to None.\n",
    "        end_date (Optional[Union[datetime, date]]): The end date of the car rental. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        list[dict]: A list of car rental dictionaries matching the search criteria.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    query = \"SELECT * FROM car_rentals WHERE 1=1\"\n",
    "    params = []\n",
    "\n",
    "    if location:\n",
    "        query += \" AND location LIKE ?\"\n",
    "        params.append(f\"%{location}%\")\n",
    "    if name:\n",
    "        query += \" AND name LIKE ?\"\n",
    "        params.append(f\"%{name}%\")\n",
    "    # For our tutorial, we will let you match on any dates and price tier.\n",
    "    # (since our toy dataset doesn't have much data)\n",
    "    cursor.execute(query, params)\n",
    "    results = cursor.fetchall()\n",
    "\n",
    "    conn.close()\n",
    "\n",
    "    return [\n",
    "        dict(zip([column[0] for column in cursor.description], row)) for row in results\n",
    "    ]\n",
    "\n",
    "\n",
    "@tool\n",
    "def book_car_rental(rental_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Book a car rental by its ID.\n",
    "\n",
    "    Args:\n",
    "        rental_id (int): The ID of the car rental to book.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the car rental was successfully booked or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\"UPDATE car_rentals SET booked = 1 WHERE id = ?\", (rental_id,))\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Car rental {rental_id} successfully booked.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No car rental found with ID {rental_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def update_car_rental(\n",
    "    rental_id: int,\n",
    "    start_date: Optional[Union[datetime, date]] = None,\n",
    "    end_date: Optional[Union[datetime, date]] = None,\n",
    ") -> str:\n",
    "    \"\"\"\n",
    "    Update a car rental's start and end dates by its ID.\n",
    "\n",
    "    Args:\n",
    "        rental_id (int): The ID of the car rental to update.\n",
    "        start_date (Optional[Union[datetime, date]]): The new start date of the car rental. Defaults to None.\n",
    "        end_date (Optional[Union[datetime, date]]): The new end date of the car rental. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the car rental was successfully updated or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    if start_date:\n",
    "        cursor.execute(\n",
    "            \"UPDATE car_rentals SET start_date = ? WHERE id = ?\",\n",
    "            (start_date, rental_id),\n",
    "        )\n",
    "    if end_date:\n",
    "        cursor.execute(\n",
    "            \"UPDATE car_rentals SET end_date = ? WHERE id = ?\", (end_date, rental_id)\n",
    "        )\n",
    "\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Car rental {rental_id} successfully updated.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No car rental found with ID {rental_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def cancel_car_rental(rental_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Cancel a car rental by its ID.\n",
    "\n",
    "    Args:\n",
    "        rental_id (int): The ID of the car rental to cancel.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the car rental was successfully cancelled or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\"UPDATE car_rentals SET booked = 0 WHERE id = ?\", (rental_id,))\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Car rental {rental_id} successfully cancelled.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No car rental found with ID {rental_id}.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Hotels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "@tool\n",
    "def search_hotels(\n",
    "    location: Optional[str] = None,\n",
    "    name: Optional[str] = None,\n",
    "    price_tier: Optional[str] = None,\n",
    "    checkin_date: Optional[Union[datetime, date]] = None,\n",
    "    checkout_date: Optional[Union[datetime, date]] = None,\n",
    ") -> list[dict]:\n",
    "    \"\"\"\n",
    "    Search for hotels based on location, name, price tier, check-in date, and check-out date.\n",
    "\n",
    "    Args:\n",
    "        location (Optional[str]): The location of the hotel. Defaults to None.\n",
    "        name (Optional[str]): The name of the hotel. Defaults to None.\n",
    "        price_tier (Optional[str]): The price tier of the hotel. Defaults to None. Examples: Midscale, Upper Midscale, Upscale, Luxury\n",
    "        checkin_date (Optional[Union[datetime, date]]): The check-in date of the hotel. Defaults to None.\n",
    "        checkout_date (Optional[Union[datetime, date]]): The check-out date of the hotel. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        list[dict]: A list of hotel dictionaries matching the search criteria.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    query = \"SELECT * FROM hotels WHERE 1=1\"\n",
    "    params = []\n",
    "\n",
    "    if location:\n",
    "        query += \" AND location LIKE ?\"\n",
    "        params.append(f\"%{location}%\")\n",
    "    if name:\n",
    "        query += \" AND name LIKE ?\"\n",
    "        params.append(f\"%{name}%\")\n",
    "    # For the sake of this tutorial, we will let you match on any dates and price tier.\n",
    "    cursor.execute(query, params)\n",
    "    results = cursor.fetchall()\n",
    "\n",
    "    conn.close()\n",
    "\n",
    "    return [\n",
    "        dict(zip([column[0] for column in cursor.description], row)) for row in results\n",
    "    ]\n",
    "\n",
    "\n",
    "@tool\n",
    "def book_hotel(hotel_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Book a hotel by its ID.\n",
    "\n",
    "    Args:\n",
    "        hotel_id (int): The ID of the hotel to book.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the hotel was successfully booked or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\"UPDATE hotels SET booked = 1 WHERE id = ?\", (hotel_id,))\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Hotel {hotel_id} successfully booked.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No hotel found with ID {hotel_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def update_hotel(\n",
    "    hotel_id: int,\n",
    "    checkin_date: Optional[Union[datetime, date]] = None,\n",
    "    checkout_date: Optional[Union[datetime, date]] = None,\n",
    ") -> str:\n",
    "    \"\"\"\n",
    "    Update a hotel's check-in and check-out dates by its ID.\n",
    "\n",
    "    Args:\n",
    "        hotel_id (int): The ID of the hotel to update.\n",
    "        checkin_date (Optional[Union[datetime, date]]): The new check-in date of the hotel. Defaults to None.\n",
    "        checkout_date (Optional[Union[datetime, date]]): The new check-out date of the hotel. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the hotel was successfully updated or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    if checkin_date:\n",
    "        cursor.execute(\n",
    "            \"UPDATE hotels SET checkin_date = ? WHERE id = ?\", (checkin_date, hotel_id)\n",
    "        )\n",
    "    if checkout_date:\n",
    "        cursor.execute(\n",
    "            \"UPDATE hotels SET checkout_date = ? WHERE id = ?\",\n",
    "            (checkout_date, hotel_id),\n",
    "        )\n",
    "\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Hotel {hotel_id} successfully updated.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No hotel found with ID {hotel_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def cancel_hotel(hotel_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Cancel a hotel by its ID.\n",
    "\n",
    "    Args:\n",
    "        hotel_id (int): The ID of the hotel to cancel.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the hotel was successfully cancelled or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\"UPDATE hotels SET booked = 0 WHERE id = ?\", (hotel_id,))\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Hotel {hotel_id} successfully cancelled.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No hotel found with ID {hotel_id}.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Excursions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "@tool\n",
    "def search_trip_recommendations(\n",
    "    location: Optional[str] = None,\n",
    "    name: Optional[str] = None,\n",
    "    keywords: Optional[str] = None,\n",
    ") -> list[dict]:\n",
    "    \"\"\"\n",
    "    Search for trip recommendations based on location, name, and keywords.\n",
    "\n",
    "    Args:\n",
    "        location (Optional[str]): The location of the trip recommendation. Defaults to None.\n",
    "        name (Optional[str]): The name of the trip recommendation. Defaults to None.\n",
    "        keywords (Optional[str]): The keywords associated with the trip recommendation. Defaults to None.\n",
    "\n",
    "    Returns:\n",
    "        list[dict]: A list of trip recommendation dictionaries matching the search criteria.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    query = \"SELECT * FROM trip_recommendations WHERE 1=1\"\n",
    "    params = []\n",
    "\n",
    "    if location:\n",
    "        query += \" AND location LIKE ?\"\n",
    "        params.append(f\"%{location}%\")\n",
    "    if name:\n",
    "        query += \" AND name LIKE ?\"\n",
    "        params.append(f\"%{name}%\")\n",
    "    if keywords:\n",
    "        keyword_list = keywords.split(\",\")\n",
    "        keyword_conditions = \" OR \".join([\"keywords LIKE ?\" for _ in keyword_list])\n",
    "        query += f\" AND ({keyword_conditions})\"\n",
    "        params.extend([f\"%{keyword.strip()}%\" for keyword in keyword_list])\n",
    "\n",
    "    cursor.execute(query, params)\n",
    "    results = cursor.fetchall()\n",
    "\n",
    "    conn.close()\n",
    "\n",
    "    return [\n",
    "        dict(zip([column[0] for column in cursor.description], row)) for row in results\n",
    "    ]\n",
    "\n",
    "\n",
    "@tool\n",
    "def book_excursion(recommendation_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Book a excursion by its recommendation ID.\n",
    "\n",
    "    Args:\n",
    "        recommendation_id (int): The ID of the trip recommendation to book.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the trip recommendation was successfully booked or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\n",
    "        \"UPDATE trip_recommendations SET booked = 1 WHERE id = ?\", (recommendation_id,)\n",
    "    )\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Trip recommendation {recommendation_id} successfully booked.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No trip recommendation found with ID {recommendation_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def update_excursion(recommendation_id: int, details: str) -> str:\n",
    "    \"\"\"\n",
    "    Update a trip recommendation's details by its ID.\n",
    "\n",
    "    Args:\n",
    "        recommendation_id (int): The ID of the trip recommendation to update.\n",
    "        details (str): The new details of the trip recommendation.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the trip recommendation was successfully updated or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\n",
    "        \"UPDATE trip_recommendations SET details = ? WHERE id = ?\",\n",
    "        (details, recommendation_id),\n",
    "    )\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Trip recommendation {recommendation_id} successfully updated.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No trip recommendation found with ID {recommendation_id}.\"\n",
    "\n",
    "\n",
    "@tool\n",
    "def cancel_excursion(recommendation_id: int) -> str:\n",
    "    \"\"\"\n",
    "    Cancel a trip recommendation by its ID.\n",
    "\n",
    "    Args:\n",
    "        recommendation_id (int): The ID of the trip recommendation to cancel.\n",
    "\n",
    "    Returns:\n",
    "        str: A message indicating whether the trip recommendation was successfully cancelled or not.\n",
    "    \"\"\"\n",
    "    conn = sqlite3.connect(db)\n",
    "    cursor = conn.cursor()\n",
    "\n",
    "    cursor.execute(\n",
    "        \"UPDATE trip_recommendations SET booked = 0 WHERE id = ?\", (recommendation_id,)\n",
    "    )\n",
    "    conn.commit()\n",
    "\n",
    "    if cursor.rowcount > 0:\n",
    "        conn.close()\n",
    "        return f\"Trip recommendation {recommendation_id} successfully cancelled.\"\n",
    "    else:\n",
    "        conn.close()\n",
    "        return f\"No trip recommendation found with ID {recommendation_id}.\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Utilities"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "def handle_tool_error(state) -> dict:\n",
    "    error = state.get(\"error\")\n",
    "    tool_calls = state['messages'][-1].tool_calls\n",
    "    return {\n",
    "        \"messages\": [\n",
    "            ToolMessage(\n",
    "                content=f\"Error: {repr(error)}\\n please fix your mistakes.\",\n",
    "                tool_call_id=tc['id'],\n",
    "            )\n",
    "            for tc in tool_calls\n",
    "        ]\n",
    "    }\n",
    "\n",
    "def create_tool_node_with_fallback(tools: list) -> dict:\n",
    "    return ToolNode(tools).with_fallbacks(\n",
    "        [RunnableLambda(handle_tool_error)], exception_key='error'\n",
    "    )\n",
    "def _print_event(event: dict, _printed: set, max_length=1500):\n",
    "    current_state = event.get('dialog_state')\n",
    "    if current_state:\n",
    "        print(f\"Currently in: \", current_state[-1])\n",
    "    message = event.get(\"messages\")\n",
    "    if message:\n",
    "        if isinstance(message, list):\n",
    "            message = message[-1]\n",
    "        if message.id not in _printed:\n",
    "            msg_repr = message.pretty_repr(html=True)\n",
    "            if len(msg_repr) > max_length:\n",
    "                msg_repr = msg_repr[:max_length] + \" ... (truncated)\"\n",
    "            print(msg_repr)\n",
    "            _printed.add(message.id)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Specialized Workflows"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## State"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "from typing import Annotated, Literal, Optional\n",
    "\n",
    "from typing_extensions import TypedDict\n",
    "\n",
    "from langgraph.graph.message import AnyMessage, add_messages\n",
    "\n",
    "\n",
    "def update_dialog_stack(left: list[str], right: Optional[str]) -> list[str]:\n",
    "    \"\"\"Push or pop the state.\"\"\"\n",
    "    if right is None:\n",
    "        return left\n",
    "    if right == \"pop\":\n",
    "        return left[:-1]\n",
    "    return left + [right]\n",
    "\n",
    "\n",
    "class State(TypedDict):\n",
    "    messages: Annotated[list[AnyMessage], add_messages]\n",
    "    user_info: str\n",
    "    dialog_state: Annotated[\n",
    "        list[\n",
    "            Literal[\n",
    "                \"assistant\",\n",
    "                \"update_flight\",\n",
    "                \"book_car_rental\",\n",
    "                \"book_hotel\",\n",
    "                \"book_excursion\",\n",
    "            ]\n",
    "        ],\n",
    "        update_dialog_stack,\n",
    "    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "def handle_tool_error(state) -> dict:\n",
    "    error = state.get(\"error\")\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    return {\n",
    "        \"messages\": [\n",
    "            ToolMessage(\n",
    "                content=f\"Error: {repr(error)}\\n please fix your mistakes.\",\n",
    "                tool_call_id=tc[\"id\"],\n",
    "            )\n",
    "            for tc in tool_calls\n",
    "        ]\n",
    "    }\n",
    "\n",
    "\n",
    "def create_tool_node_with_fallback(tools: list) -> dict:\n",
    "    return ToolNode(tools).with_fallbacks(\n",
    "        [RunnableLambda(handle_tool_error)], exception_key=\"error\"\n",
    "    )\n",
    "\n",
    "\n",
    "def _print_event(event: dict, _printed: set, max_length=1500):\n",
    "    current_state = event.get(\"dialog_state\")\n",
    "    if current_state:\n",
    "        print(f\"Currently in: \", current_state[-1])\n",
    "    message = event.get(\"messages\")\n",
    "    if message:\n",
    "        if isinstance(message, list):\n",
    "            message = message[-1]\n",
    "        if message.id not in _printed:\n",
    "            msg_repr = message.pretty_repr(html=True)\n",
    "            if len(msg_repr) > max_length:\n",
    "                msg_repr = msg_repr[:max_length] + \" ... (truncated)\"\n",
    "            print(msg_repr)\n",
    "            _printed.add(message.id)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Assistants"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "ename": "NotImplementedError",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNotImplementedError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[15], line 75\u001b[0m\n\u001b[1;32m     73\u001b[0m update_flight_sensitive_tools \u001b[38;5;241m=\u001b[39m [update_ticket_to_new_flight, cancel_ticket]\n\u001b[1;32m     74\u001b[0m update_flight_tools \u001b[38;5;241m=\u001b[39m update_flight_safe_tools \u001b[38;5;241m+\u001b[39m update_flight_sensitive_tools\n\u001b[0;32m---> 75\u001b[0m update_flight_runnable \u001b[38;5;241m=\u001b[39m flight_booking_prompt \u001b[38;5;241m|\u001b[39m \u001b[43mllm\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mbind_tools\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     76\u001b[0m \u001b[43m    \u001b[49m\u001b[43mupdate_flight_tools\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m[\u001b[49m\u001b[43mCompleteOrEscalate\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m     77\u001b[0m \u001b[43m)\u001b[49m\n\u001b[1;32m     79\u001b[0m \u001b[38;5;66;03m# Hotel Booking Assistant\u001b[39;00m\n\u001b[1;32m     80\u001b[0m book_hotel_prompt \u001b[38;5;241m=\u001b[39m ChatPromptTemplate\u001b[38;5;241m.\u001b[39mfrom_messages(\n\u001b[1;32m     81\u001b[0m     [\n\u001b[1;32m     82\u001b[0m         (\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    101\u001b[0m     ]\n\u001b[1;32m    102\u001b[0m )\u001b[38;5;241m.\u001b[39mpartial(time\u001b[38;5;241m=\u001b[39mdatetime\u001b[38;5;241m.\u001b[39mnow())\n",
      "File \u001b[0;32m/opt/homebrew/Caskroom/miniconda/base/envs/llm/lib/python3.11/site-packages/langchain_core/language_models/chat_models.py:912\u001b[0m, in \u001b[0;36mBaseChatModel.bind_tools\u001b[0;34m(self, tools, **kwargs)\u001b[0m\n\u001b[1;32m    907\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mbind_tools\u001b[39m(\n\u001b[1;32m    908\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m    909\u001b[0m     tools: Sequence[Union[Dict[\u001b[38;5;28mstr\u001b[39m, Any], Type[BaseModel], Callable, BaseTool]],\n\u001b[1;32m    910\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m    911\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Runnable[LanguageModelInput, BaseMessage]:\n\u001b[0;32m--> 912\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m()\n",
      "\u001b[0;31mNotImplementedError\u001b[0m: "
     ]
    }
   ],
   "source": [
    "llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=1)\n",
    "\n",
    "#from langchain_community.chat_models import ChatOllama\n",
    "#llm = ChatOllama(model=\"llama3:8b-instruct-q8_0\", temperature=1)\n",
    "class Assistant:\n",
    "    def __init__(self, runnable: Runnable):\n",
    "        self.runnable = runnable\n",
    "\n",
    "    def __call__(self, state: State, config: RunnableConfig):\n",
    "        while True:\n",
    "            result = self.runnable.invoke(state)\n",
    "\n",
    "            if not result.tool_calls and (\n",
    "                not result.content\n",
    "                or isinstance(result.content, list)\n",
    "                and not result.content[0].get(\"text\")\n",
    "            ):\n",
    "                messages = state[\"messages\"] + [(\"user\", \"Respond with a real output.\")]\n",
    "                state = {**state, \"messages\": messages}\n",
    "                messages = state[\"messages\"] + [(\"user\", \"Respond with a real output.\")]\n",
    "                state = {**state, \"messages\": messages}\n",
    "            else:\n",
    "                break\n",
    "        return {\"messages\": result}\n",
    "\n",
    "\n",
    "class CompleteOrEscalate(BaseModel):\n",
    "    \"\"\"A tool to mark the current task as completed and/or to escalate control of the dialog to the main assistant,\n",
    "    who can re-route the dialog based on the user's needs.\"\"\"\n",
    "\n",
    "    cancel: bool = True\n",
    "    reason: str\n",
    "\n",
    "    class Config:\n",
    "        schema_extra = {\n",
    "            \"example\": {\n",
    "                \"cancel\": True,\n",
    "                \"reason\": \"User changed their mind about the current task.\",\n",
    "            },\n",
    "            \"example 2\": {\n",
    "                \"cancel\": True,\n",
    "                \"reason\": \"I have fully completed the task.\",\n",
    "            },\n",
    "            \"example 3\": {\n",
    "                \"cancel\": False,\n",
    "                \"reason\": \"I need to search the user's emails or calendar for more information.\",\n",
    "            },\n",
    "        }\n",
    "\n",
    "\n",
    "# Flight booking assistant\n",
    "\n",
    "flight_booking_prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a specialized assistant for handling flight updates. \"\n",
    "            \" The primary assistant delegates work to you whenever the user needs help updating their bookings. \"\n",
    "            \"Confirm the updated flight details with the customer and inform them of any additional fees. \"\n",
    "            \" When searching, be persistent. Expand your query bounds if the first search returns no results. \"\n",
    "            \"If you need more information or the customer changes their mind, escalate the task back to the main assistant.\"\n",
    "            \" Remember that a booking isn't completed until after the relevant tool has successfully been used.\"\n",
    "            \"\\n\\nCurrent user flight information:\\n\\n{user_info}\\n\"\n",
    "            \"\\nCurrent time: {time}.\"\n",
    "            \"\\n\\nIf the user needs help, and none of your tools are appropriate for it, then\"\n",
    "            ' \"CompleteOrEscalate\" the dialog to the host assistant. Do not waste the user\\'s time. Do not make up invalid tools or functions.',\n",
    "        ),\n",
    "        (\"placeholder\", \"{messages}\"),\n",
    "    ]\n",
    ").partial(time=datetime.now())\n",
    "\n",
    "update_flight_safe_tools = [search_flights]\n",
    "update_flight_sensitive_tools = [update_ticket_to_new_flight, cancel_ticket]\n",
    "update_flight_tools = update_flight_safe_tools + update_flight_sensitive_tools\n",
    "update_flight_runnable = flight_booking_prompt | llm.bind_tools(\n",
    "    update_flight_tools + [CompleteOrEscalate]\n",
    ")\n",
    "\n",
    "# Hotel Booking Assistant\n",
    "book_hotel_prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a specialized assistant for handling hotel bookings. \"\n",
    "            \"The primary assistant delegates work to you whenever the user needs help booking a hotel. \"\n",
    "            \"Search for available hotels based on the user's preferences and confirm the booking details with the customer. \"\n",
    "            \" When searching, be persistent. Expand your query bounds if the first search returns no results. \"\n",
    "            \"If you need more information or the customer changes their mind, escalate the task back to the main assistant.\"\n",
    "            \" Remember that a booking isn't completed until after the relevant tool has successfully been used.\"\n",
    "            \"\\nCurrent time: {time}.\"\n",
    "            '\\n\\nIf the user needs help, and none of your tools are appropriate for it, then \"CompleteOrEscalate\" the dialog to the host assistant.'\n",
    "            \" Do not waste the user's time. Do not make up invalid tools or functions.\"\n",
    "            \"\\n\\nSome examples for which you should CompleteOrEscalate:\\n\"\n",
    "            \" - 'what's the weather like this time of year?'\\n\"\n",
    "            \" - 'nevermind i think I'll book separately'\\n\"\n",
    "            \" - 'i need to figure out transportation while i'm there'\\n\"\n",
    "            \" - 'Oh wait i haven't booked my flight yet i'll do that first'\\n\"\n",
    "            \" - 'Hotel booking confirmed'\",\n",
    "        ),\n",
    "        (\"placeholder\", \"{messages}\"),\n",
    "    ]\n",
    ").partial(time=datetime.now())\n",
    "\n",
    "book_hotel_safe_tools = [search_hotels]\n",
    "book_hotel_sensitive_tools = [book_hotel, update_hotel, cancel_hotel]\n",
    "book_hotel_tools = book_hotel_safe_tools + book_hotel_sensitive_tools\n",
    "book_hotel_runnable = book_hotel_prompt | llm.bind_tools(\n",
    "    book_hotel_tools + [CompleteOrEscalate]\n",
    ")\n",
    "\n",
    "# Car Rental Assistant\n",
    "book_car_rental_prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a specialized assistant for handling car rental bookings. \"\n",
    "            \"The primary assistant delegates work to you whenever the user needs help booking a car rental. \"\n",
    "            \"Search for available car rentals based on the user's preferences and confirm the booking details with the customer. \"\n",
    "            \" When searching, be persistent. Expand your query bounds if the first search returns no results. \"\n",
    "            \"If you need more information or the customer changes their mind, escalate the task back to the main assistant.\"\n",
    "            \" Remember that a booking isn't completed until after the relevant tool has successfully been used.\"\n",
    "            \"\\nCurrent time: {time}.\"\n",
    "            \"\\n\\nIf the user needs help, and none of your tools are appropriate for it, then \"\n",
    "            '\"CompleteOrEscalate\" the dialog to the host assistant. Do not waste the user\\'s time. Do not make up invalid tools or functions.'\n",
    "            \"\\n\\nSome examples for which you should CompleteOrEscalate:\\n\"\n",
    "            \" - 'what's the weather like this time of year?'\\n\"\n",
    "            \" - 'What flights are available?'\\n\"\n",
    "            \" - 'nevermind i think I'll book separately'\\n\"\n",
    "            \" - 'Oh wait i haven't booked my flight yet i'll do that first'\\n\"\n",
    "            \" - 'Car rental booking confirmed'\",\n",
    "        ),\n",
    "        (\"placeholder\", \"{messages}\"),\n",
    "    ]\n",
    ").partial(time=datetime.now())\n",
    "\n",
    "book_car_rental_safe_tools = [search_car_rentals]\n",
    "book_car_rental_sensitive_tools = [\n",
    "    book_car_rental,\n",
    "    update_car_rental,\n",
    "    cancel_car_rental,\n",
    "]\n",
    "book_car_rental_tools = book_car_rental_safe_tools + book_car_rental_sensitive_tools\n",
    "book_car_rental_runnable = book_car_rental_prompt | llm.bind_tools(\n",
    "    book_car_rental_tools + [CompleteOrEscalate]\n",
    ")\n",
    "\n",
    "# Excursion Assistant\n",
    "\n",
    "book_excursion_prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a specialized assistant for handling trip recommendations. \"\n",
    "            \"The primary assistant delegates work to you whenever the user needs help booking a recommended trip. \"\n",
    "            \"Search for available trip recommendations based on the user's preferences and confirm the booking details with the customer. \"\n",
    "            \"If you need more information or the customer changes their mind, escalate the task back to the main assistant.\"\n",
    "            \" When searching, be persistent. Expand your query bounds if the first search returns no results. \"\n",
    "            \" Remember that a booking isn't completed until after the relevant tool has successfully been used.\"\n",
    "            \"\\nCurrent time: {time}.\"\n",
    "            '\\n\\nIf the user needs help, and none of your tools are appropriate for it, then \"CompleteOrEscalate\" the dialog to the host assistant. Do not waste the user\\'s time. Do not make up invalid tools or functions.'\n",
    "            \"\\n\\nSome examples for which you should CompleteOrEscalate:\\n\"\n",
    "            \" - 'nevermind i think I'll book separately'\\n\"\n",
    "            \" - 'i need to figure out transportation while i'm there'\\n\"\n",
    "            \" - 'Oh wait i haven't booked my flight yet i'll do that first'\\n\"\n",
    "            \" - 'Excursion booking confirmed!'\",\n",
    "        ),\n",
    "        (\"placeholder\", \"{messages}\"),\n",
    "    ]\n",
    ").partial(time=datetime.now())\n",
    "\n",
    "book_excursion_safe_tools = [search_trip_recommendations]\n",
    "book_excursion_sensitive_tools = [book_excursion, update_excursion, cancel_excursion]\n",
    "book_excursion_tools = book_excursion_safe_tools + book_excursion_sensitive_tools\n",
    "book_excursion_runnable = book_excursion_prompt | llm.bind_tools(\n",
    "    book_excursion_tools + [CompleteOrEscalate]\n",
    ")\n",
    "\n",
    "\n",
    "# Primary Assistant\n",
    "class ToFlightBookingAssistant(BaseModel):\n",
    "    \"\"\"Transfers work to a specialized assistant to handle flight updates and cancellations.\"\"\"\n",
    "\n",
    "    request: str = Field(\n",
    "        description=\"Any necessary followup questions the update flight assistant should clarify before proceeding.\"\n",
    "    )\n",
    "\n",
    "\n",
    "class ToBookCarRental(BaseModel):\n",
    "    \"\"\"Transfers work to a specialized assistant to handle car rental bookings.\"\"\"\n",
    "\n",
    "    location: str = Field(\n",
    "        description=\"The location where the user wants to rent a car.\"\n",
    "    )\n",
    "    start_date: str = Field(description=\"The start date of the car rental.\")\n",
    "    end_date: str = Field(description=\"The end date of the car rental.\")\n",
    "    request: str = Field(\n",
    "        description=\"Any additional information or requests from the user regarding the car rental.\"\n",
    "    )\n",
    "\n",
    "    class Config:\n",
    "        schema_extra = {\n",
    "            \"example\": {\n",
    "                \"location\": \"Basel\",\n",
    "                \"start_date\": \"2023-07-01\",\n",
    "                \"end_date\": \"2023-07-05\",\n",
    "                \"request\": \"I need a compact car with automatic transmission.\",\n",
    "            }\n",
    "        }\n",
    "\n",
    "\n",
    "class ToHotelBookingAssistant(BaseModel):\n",
    "    \"\"\"Transfer work to a specialized assistant to handle hotel bookings.\"\"\"\n",
    "\n",
    "    location: str = Field(\n",
    "        description=\"The location where the user wants to book a hotel.\"\n",
    "    )\n",
    "    checkin_date: str = Field(description=\"The check-in date for the hotel.\")\n",
    "    checkout_date: str = Field(description=\"The check-out date for the hotel.\")\n",
    "    request: str = Field(\n",
    "        description=\"Any additional information or requests from the user regarding the hotel booking.\"\n",
    "    )\n",
    "\n",
    "    class Config:\n",
    "        schema_extra = {\n",
    "            \"example\": {\n",
    "                \"location\": \"Zurich\",\n",
    "                \"checkin_date\": \"2023-08-15\",\n",
    "                \"checkout_date\": \"2023-08-20\",\n",
    "                \"request\": \"I prefer a hotel near the city center with a room that has a view.\",\n",
    "            }\n",
    "        }\n",
    "\n",
    "\n",
    "class ToBookExcursion(BaseModel):\n",
    "    \"\"\"Transfers work to a specialized assistant to handle trip recommendation and other excursion bookings.\"\"\"\n",
    "\n",
    "    location: str = Field(\n",
    "        description=\"The location where the user wants to book a recommended trip.\"\n",
    "    )\n",
    "    request: str = Field(\n",
    "        description=\"Any additional information or requests from the user regarding the trip recommendation.\"\n",
    "    )\n",
    "\n",
    "    class Config:\n",
    "        schema_extra = {\n",
    "            \"example\": {\n",
    "                \"location\": \"Lucerne\",\n",
    "                \"request\": \"The user is interested in outdoor activities and scenic views.\",\n",
    "            }\n",
    "        }\n",
    "\n",
    "\n",
    "# The top-level assistant performs general Q&A and delegates specialized tasks to other assistants.\n",
    "# The task delegation is a simple form of semantic routing / does simple intent detection\n",
    "\n",
    "\n",
    "primary_assistant_prompt = ChatPromptTemplate.from_messages(\n",
    "    [\n",
    "        (\n",
    "            \"system\",\n",
    "            \"You are a helpful customer support assistant for Swiss Airlines. \"\n",
    "            \"Your primary role is to search for flight information and company policies to answer customer queries. \"\n",
    "            \"If a customer requests to update or cancel a flight, book a car rental, book a hotel, or get trip recommendations, \"\n",
    "            \"delegate the task to the appropriate specialized assistant by invoking the corresponding tool. You are not able to make these types of changes yourself.\"\n",
    "            \" Only the specialized assistants are given permission to do this for the user.\"\n",
    "            \"The user is not aware of the different specialized assistants, so do not mention them; just quietly delegate through function calls. \"\n",
    "            \"Provide detailed information to the customer, and always double-check the database before concluding that information is unavailable. \"\n",
    "            \" When searching, be persistent. Expand your query bounds if the first search returns no results. \"\n",
    "            \" If a search comes up empty, expand your search before giving up.\"\n",
    "            \"\\n\\nCurrent user flight information:\\n\\n{user_info}\\n\"\n",
    "            \"\\nCurrent time: {time}.\",\n",
    "        ),\n",
    "        (\"placeholder\", \"{messages}\"),\n",
    "    ]\n",
    ").partial(time=datetime.now())\n",
    "primary_assistant_tools = [\n",
    "    TavilySearchResults(max_results=1),\n",
    "    search_flights,\n",
    "    lookup_policy,\n",
    "]\n",
    "assistant_runnable = primary_assistant_prompt | llm.bind_tools(\n",
    "    primary_assistant_tools\n",
    "    + [\n",
    "        ToFlightBookingAssistant,\n",
    "        ToBookCarRental,\n",
    "        ToHotelBookingAssistant,\n",
    "        ToBookExcursion,\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Create Assistant"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Utility\n",
    "\n",
    "**Create a function to make an \"entry\" node for each workflow, stating \"the current\" assistant in `assistant_name`**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "def create_entry_node(assistant_name: str, new_dialog_state: str) -> Callable:\n",
    "    def entry_node(state: State) -> dict:\n",
    "        tool_call_id = state[\"messages\"][-1].tool_calls[0][\"id\"]\n",
    "        return {\n",
    "            \"messages\": [\n",
    "                ToolMessage(\n",
    "                    content=f\"The assistant is now the {assistant_name}. Reflect on the above conversation between the host assistant and the user.\"\n",
    "                    f\" The user's intent is unsatisfied. Use the provided tools to assist the user. Remember, you are {assistant_name},\"\n",
    "                    \" and the booking, update, other other action is not complete until after you have successfully invoked the appropriate tool.\"\n",
    "                    \" If the user changes their mind or needs help for other tasks, call the CompleteOrEscalate function to let the primary host assistant take control.\"\n",
    "                    \" Do not mention who you are - just act as the proxy for the assistant.\",\n",
    "                    tool_call_id=tool_call_id,\n",
    "                )\n",
    "            ],\n",
    "            \"dialog_state\": new_dialog_state,\n",
    "        }\n",
    "\n",
    "    return entry_node"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Define Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "builder = StateGraph(State)\n",
    "\n",
    "\n",
    "def user_info(state: State):\n",
    "    return {\"user_info\": fetch_user_flight_information.invoke({})}\n",
    "\n",
    "\n",
    "builder.add_node(\"fetch_user_info\", user_info)\n",
    "builder.set_entry_point(\"fetch_user_info\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Flight Booking assistant graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Flight booking assistant\n",
    "builder.add_node(\n",
    "    \"enter_update_flight\",\n",
    "    create_entry_node(\"Flight Updates & Booking Assistant\", \"update_flight\"),\n",
    ")\n",
    "builder.add_node(\"update_flight\", Assistant(update_flight_runnable))\n",
    "builder.add_edge(\"enter_update_flight\", \"update_flight\")\n",
    "builder.add_node(\n",
    "    \"update_flight_sensitive_tools\",\n",
    "    create_tool_node_with_fallback(update_flight_sensitive_tools),\n",
    ")\n",
    "builder.add_node(\n",
    "    \"update_flight_safe_tools\",\n",
    "    create_tool_node_with_fallback(update_flight_safe_tools),\n",
    ")\n",
    "\n",
    "\n",
    "def route_update_flight(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"update_flight_sensitive_tools\",\n",
    "    \"update_flight_safe_tools\",\n",
    "    \"leave_skill\",\n",
    "    \"__end__\",\n",
    "]:\n",
    "    route = tools_condition(state)\n",
    "    if route == END:\n",
    "        return END\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    did_cancel = any(tc[\"name\"] == CompleteOrEscalate.__name__ for tc in tool_calls)\n",
    "    if did_cancel:\n",
    "        return \"leave_skill\"\n",
    "    safe_toolnames = [t.name for t in update_flight_safe_tools]\n",
    "    if all(tc[\"name\"] in safe_toolnames for tc in tool_calls):\n",
    "        return \"update_flight_safe_tools\"\n",
    "    return \"update_flight_sensitive_tools\"\n",
    "\n",
    "\n",
    "builder.add_edge(\"update_flight_sensitive_tools\", \"update_flight\")\n",
    "builder.add_edge(\"update_flight_safe_tools\", \"update_flight\")\n",
    "builder.add_conditional_edges(\"update_flight\", route_update_flight)\n",
    "\n",
    "\n",
    "# This node will be shared for exiting all specialized assistants\n",
    "def pop_dialog_state(state: State) -> dict:\n",
    "    \"\"\"Pop the dialog stack and return to the main assistant.\n",
    "\n",
    "    This lets the full graph explicitly track the dialog flow and delegate control\n",
    "    to specific sub-graphs.\n",
    "    \"\"\"\n",
    "    messages = []\n",
    "    if state[\"messages\"][-1].tool_calls:\n",
    "        # Note: Doesn't currently handle the edge case where the llm performs parallel tool calls\n",
    "        messages.append(\n",
    "            ToolMessage(\n",
    "                content=\"Resuming dialog with the host assistant. Please reflect on the past conversation and assist the user as needed.\",\n",
    "                tool_call_id=state[\"messages\"][-1].tool_calls[0][\"id\"],\n",
    "            )\n",
    "        )\n",
    "    return {\n",
    "        \"dialog_state\": \"pop\",\n",
    "        \"messages\": messages,\n",
    "    }\n",
    "\n",
    "\n",
    "builder.add_node(\"leave_skill\", pop_dialog_state)\n",
    "builder.add_edge(\"leave_skill\", \"primary_assistant\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Car rental assistant graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Car rental assistant\n",
    "\n",
    "builder.add_node(\n",
    "    \"enter_book_car_rental\",\n",
    "    create_entry_node(\"Car Rental Assistant\", \"book_car_rental\"),\n",
    ")\n",
    "builder.add_node(\"book_car_rental\", Assistant(book_car_rental_runnable))\n",
    "builder.add_edge(\"enter_book_car_rental\", \"book_car_rental\")\n",
    "builder.add_node(\n",
    "    \"book_car_rental_safe_tools\",\n",
    "    create_tool_node_with_fallback(book_car_rental_safe_tools),\n",
    ")\n",
    "builder.add_node(\n",
    "    \"book_car_rental_sensitive_tools\",\n",
    "    create_tool_node_with_fallback(book_car_rental_sensitive_tools),\n",
    ")\n",
    "\n",
    "\n",
    "def route_book_car_rental(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"book_car_rental_safe_tools\",\n",
    "    \"book_car_rental_sensitive_tools\",\n",
    "    \"leave_skill\",\n",
    "    \"__end__\",\n",
    "]:\n",
    "    route = tools_condition(state)\n",
    "    if route == END:\n",
    "        return END\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    did_cancel = any(tc[\"name\"] == CompleteOrEscalate.__name__ for tc in tool_calls)\n",
    "    if did_cancel:\n",
    "        return \"leave_skill\"\n",
    "    safe_toolnames = [t.name for t in book_car_rental_safe_tools]\n",
    "    if all(tc[\"name\"] in safe_toolnames for tc in tool_calls):\n",
    "        return \"book_car_rental_safe_tools\"\n",
    "    return \"book_car_rental_sensitive_tools\"\n",
    "\n",
    "\n",
    "builder.add_edge(\"book_car_rental_sensitive_tools\", \"book_car_rental\")\n",
    "builder.add_edge(\"book_car_rental_safe_tools\", \"book_car_rental\")\n",
    "builder.add_conditional_edges(\"book_car_rental\", route_book_car_rental)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Hotel Booking assistant graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Hotel booking assistant\n",
    "builder.add_node(\n",
    "    \"enter_book_hotel\", create_entry_node(\"Hotel Booking Assistant\", \"book_hotel\")\n",
    ")\n",
    "builder.add_node(\"book_hotel\", Assistant(book_hotel_runnable))\n",
    "builder.add_edge(\"enter_book_hotel\", \"book_hotel\")\n",
    "builder.add_node(\n",
    "    \"book_hotel_safe_tools\",\n",
    "    create_tool_node_with_fallback(book_hotel_safe_tools),\n",
    ")\n",
    "builder.add_node(\n",
    "    \"book_hotel_sensitive_tools\",\n",
    "    create_tool_node_with_fallback(book_hotel_sensitive_tools),\n",
    ")\n",
    "\n",
    "\n",
    "def route_book_hotel(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"leave_skill\", \"book_hotel_safe_tools\", \"book_hotel_sensitive_tools\", \"__end__\"\n",
    "]:\n",
    "    route = tools_condition(state)\n",
    "    if route == END:\n",
    "        return END\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    did_cancel = any(tc[\"name\"] == CompleteOrEscalate.__name__ for tc in tool_calls)\n",
    "    if did_cancel:\n",
    "        return \"leave_skill\"\n",
    "    tool_names = [t.name for t in book_hotel_safe_tools]\n",
    "    if all(tc[\"name\"] in tool_names for tc in tool_calls):\n",
    "        return \"book_hotel_safe_tools\"\n",
    "    return \"book_hotel_sensitive_tools\"\n",
    "\n",
    "\n",
    "builder.add_edge(\"book_hotel_sensitive_tools\", \"book_hotel\")\n",
    "builder.add_edge(\"book_hotel_safe_tools\", \"book_hotel\")\n",
    "builder.add_conditional_edges(\"book_hotel\", route_book_hotel)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Excursion Assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Excursion assistant\n",
    "builder.add_node(\n",
    "    \"enter_book_excursion\",\n",
    "    create_entry_node(\"Trip Recommendation Assistant\", \"book_excursion\"),\n",
    ")\n",
    "builder.add_node(\"book_excursion\", Assistant(book_excursion_runnable))\n",
    "builder.add_edge(\"enter_book_excursion\", \"book_excursion\")\n",
    "builder.add_node(\n",
    "    \"book_excursion_safe_tools\",\n",
    "    create_tool_node_with_fallback(book_excursion_safe_tools),\n",
    ")\n",
    "builder.add_node(\n",
    "    \"book_excursion_sensitive_tools\",\n",
    "    create_tool_node_with_fallback(book_excursion_sensitive_tools),\n",
    ")\n",
    "\n",
    "\n",
    "def route_book_excursion(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"book_excursion_safe_tools\",\n",
    "    \"book_excursion_sensitive_tools\",\n",
    "    \"leave_skill\",\n",
    "    \"__end__\",\n",
    "]:\n",
    "    route = tools_condition(state)\n",
    "    if route == END:\n",
    "        return END\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    did_cancel = any(tc[\"name\"] == CompleteOrEscalate.__name__ for tc in tool_calls)\n",
    "    if did_cancel:\n",
    "        return \"leave_skill\"\n",
    "    tool_names = [t.name for t in book_excursion_safe_tools]\n",
    "    if all(tc[\"name\"] in tool_names for tc in tool_calls):\n",
    "        return \"book_excursion_safe_tools\"\n",
    "    return \"book_excursion_sensitive_tools\"\n",
    "\n",
    "\n",
    "builder.add_edge(\"book_excursion_sensitive_tools\", \"book_excursion\")\n",
    "builder.add_edge(\"book_excursion_safe_tools\", \"book_excursion\")\n",
    "builder.add_conditional_edges(\"book_excursion\", route_book_excursion)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Primary assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Primary assistant\n",
    "builder.add_node(\"primary_assistant\", Assistant(assistant_runnable))\n",
    "builder.add_node(\n",
    "    \"primary_assistant_tools\", create_tool_node_with_fallback(primary_assistant_tools)\n",
    ")\n",
    "\n",
    "\n",
    "def route_primary_assistant(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"primary_assistant_tools\",\n",
    "    \"enter_update_flight\",\n",
    "    \"enter_book_hotel\",\n",
    "    \"enter_book_excursion\",\n",
    "    \"__end__\",\n",
    "]:\n",
    "    route = tools_condition(state)\n",
    "    if route == END:\n",
    "        return END\n",
    "    tool_calls = state[\"messages\"][-1].tool_calls\n",
    "    if tool_calls:\n",
    "        if tool_calls[0][\"name\"] == ToFlightBookingAssistant.__name__:\n",
    "            return \"enter_update_flight\"\n",
    "        elif tool_calls[0][\"name\"] == ToBookCarRental.__name__:\n",
    "            return \"enter_book_car_rental\"\n",
    "        elif tool_calls[0][\"name\"] == ToHotelBookingAssistant.__name__:\n",
    "            return \"enter_book_hotel\"\n",
    "        elif tool_calls[0][\"name\"] == ToBookExcursion.__name__:\n",
    "            return \"enter_book_excursion\"\n",
    "        return \"primary_assistant_tools\"\n",
    "    raise ValueError(\"Invalid route\")\n",
    "\n",
    "\n",
    "# The assistant can route to one of the delegated assistants,\n",
    "# directly use a tool, or directly respond to the user\n",
    "builder.add_conditional_edges(\n",
    "    \"primary_assistant\",\n",
    "    route_primary_assistant,\n",
    "    {\n",
    "        \"enter_update_flight\": \"enter_update_flight\",\n",
    "        \"enter_book_car_rental\": \"enter_book_car_rental\",\n",
    "        \"enter_book_hotel\": \"enter_book_hotel\",\n",
    "        \"enter_book_excursion\": \"enter_book_excursion\",\n",
    "        \"primary_assistant_tools\": \"primary_assistant_tools\",\n",
    "        END: END,\n",
    "    },\n",
    ")\n",
    "builder.add_edge(\"primary_assistant_tools\", \"primary_assistant\")\n",
    "\n",
    "\n",
    "# Each delegated workflow can directly respond to the user\n",
    "# When the user responds, we want to return to the currently active workflow\n",
    "def route_to_workflow(\n",
    "    state: State,\n",
    ") -> Literal[\n",
    "    \"primary_assistant\",\n",
    "    \"update_flight\",\n",
    "    \"book_car_rental\",\n",
    "    \"book_hotel\",\n",
    "    \"book_excursion\",\n",
    "]:\n",
    "    \"\"\"If we are in a delegated state, route directly to the appropriate assistant.\"\"\"\n",
    "    dialog_state = state.get(\"dialog_state\")\n",
    "    if not dialog_state:\n",
    "        return \"primary_assistant\"\n",
    "    return dialog_state[-1]\n",
    "\n",
    "\n",
    "builder.add_conditional_edges(\"fetch_user_info\", route_to_workflow)\n",
    "\n",
    "# Compile graph\n",
    "memory = SqliteSaver.from_conn_string(\":memory:\")\n",
    "part_4_graph = builder.compile(\n",
    "    checkpointer=memory,\n",
    "    # Let the user approve or deny the use of sensitive tools\n",
    "    interrupt_before=[\n",
    "        \"update_flight_sensitive_tools\",\n",
    "        \"book_car_rental_sensitive_tools\",\n",
    "        \"book_hotel_sensitive_tools\",\n",
    "        \"book_excursion_sensitive_tools\",\n",
    "    ],\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "try:\n",
    "    display(Image(part_4_graph.get_graph(xray=True).draw_mermaid_png()))\n",
    "except:\n",
    "    # This requires some extra depencies and is optional\n",
    "    pass"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Conversation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "================================\u001b[1m Human Message \u001b[0m=================================\n",
      "\n",
      "Hi there, what time is my flight?\n",
      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
      "\n",
      "Your flight with ticket number 7240005432906569 is scheduled to depart from CDG (Charles de Gaulle Airport) at 12:09 PM on April 30, 2024, and arrive at BSL (EuroAirport Basel-Mulhouse-Freiburg) at 1:39 PM on the same day.\n",
      "================================\u001b[1m Human Message \u001b[0m=================================\n",
      "\n",
      "Am i allowed to update my flight to something sooner? I want to leave later today.\n",
      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
      "Tool Calls:\n",
      "  lookup_policy (call_AVeBp8RxckfrgVyuwG6ziRCZ)\n",
      " Call ID: call_AVeBp8RxckfrgVyuwG6ziRCZ\n",
      "  Args:\n",
      "    query: Can a passenger update a flight to an earlier departure time?\n",
      "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
      "Name: lookup_policy\n",
      "\n",
      "\n",
      "## Booking and Cancellation\n",
      "\n",
      "1. How can I change my booking?\n",
      "\t* The ticket number must start with 724 (SWISS ticket no./plate).\n",
      "\t* The ticket was not paid for by barter or voucher (there are exceptions to voucher payments; if the ticket was paid for in full by voucher, then it may be possible to rebook online under certain circumstances. If it is not possible to rebook online because of the payment method, then you will be informed accordingly during the rebooking process).\n",
      "\t* There must be an active flight booking for your ticket. It is not possible to rebook open tickets or tickets without the corresponding flight segments online at the moment.\n",
      "\t* It is currently only possible to rebook outbound (one-way) tickets or return tickets with single flight routes (point-to-point).\n",
      "2. Which tickets/bookings cannot be rebooked online currently?\n",
      "\t* Bookings containing flight segments with other airlines\n",
      "\t* Bookings containing reservations, where a ticket has not yet been issued\n",
      "\t* Bookings with several valid tickets for the same person and route\n",
      "\t* Tickets with a status other than O (open) (A)\n",
      "\t* Bookings with segments with a status other than OK (e.g. containing flight segments with the status Waitlist) (HK|RR)\n",
      "\t* Tickets that do not display the tariff calculation (IT tickets)\n",
      "\t* Bookings that contain special services (e.g. transportation of animals/transportation of medica ... (truncated)\n",
      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
      "\n",
      "Based on the company policy, if you have booked an \"Economy Flex\" fare, you may be able to change to an earlier flight on the same day for free. This service is available for \"Economy Flex\" and \"Business Flex\" fares and can be done during online check-in via the airline's website or app, at a check-in machine, or at the airport check-in counter. It is important to note that this service applies to direct flights only, and a change of route or airline is not possible. \n",
      "\n",
      "If you would like to proceed with updating your flight to something sooner, I can transfer you to the specialized assistant who can assist with flight updates. Would you like me to do that for you?\n",
      "================================\u001b[1m Human Message \u001b[0m=================================\n",
      "\n",
      "Update my flight to sometime next week then\n",
      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
      "Tool Calls:\n",
      "  ToFlightBookingAssistant (call_gjz9ZbS8TUPZq7U713tgW3Rp)\n",
      " Call ID: call_gjz9ZbS8TUPZq7U713tgW3Rp\n",
      "  Args:\n",
      "    request: Update the flight to a date next week\n",
      "Currently in:  update_flight\n",
      "=================================\u001b[1m Tool Message \u001b[0m=================================\n",
      "\n",
      "The assistant is now the Flight Updates & Booking Assistant. Reflect on the above conversation between the host assistant and the user. The user's intent is unsatisfied. Use the provided tools to assist the user. Remember, you are Flight Updates & Booking Assistant, and the booking, update, other other action is not complete until after you have successfully invoked the appropriate tool. If the user changes their mind or needs help for other tasks, call the CompleteOrEscalate function to let the primary host assistant take control. Do not mention who you are - just act as the proxy for the assistant.\n",
      "Currently in:  update_flight\n",
      "==================================\u001b[1m Ai Message \u001b[0m==================================\n",
      "Tool Calls:\n",
      "  update_ticket_to_new_flight (call_Nom2U7Q8WmYZNjPqOYZF0pAc)\n",
      " Call ID: call_Nom2U7Q8WmYZNjPqOYZF0pAc\n",
      "  Args:\n",
      "    ticket_no: 7240005432906569\n",
      "    new_flight_id: 97735\n"
     ]
    }
   ],
   "source": [
    "tutorial_questions = [\n",
    "    \"Hi there, what time is my flight?\",\n",
    "    \"Am i allowed to update my flight to something sooner? I want to leave later today.\",\n",
    "    \"Update my flight to sometime next week then\",\n",
    "    \"The next available option is great\",\n",
    "    \"what about lodging and transportation?\",\n",
    "    \"Yeah i think i'd like an affordable hotel for my week-long stay (7 days). And I'll want to rent a car.\",\n",
    "    \"OK could you place a reservation for your recommended hotel? It sounds nice.\",\n",
    "    \"yes go ahead and book anything that's moderate expense and has availability.\",\n",
    "    \"Now for a car, what are my options?\",\n",
    "    \"Awesome let's just get the cheapest option. Go ahead and book for 7 days\",\n",
    "    \"Cool so now what recommendations do you have on excursions?\",\n",
    "    \"Are they available while I'm there?\",\n",
    "    \"interesting - i like the museums, what options are there? \",\n",
    "    \"OK great pick one and book it for my second day there.\",\n",
    "]\n",
    "\n",
    "\n",
    "# Update with the backup file so we can restart from the original place in each section\n",
    "shutil.copy(backup_file, db)\n",
    "thread_id = str(uuid.uuid4())\n",
    "\n",
    "config = {\n",
    "    \"configurable\": {\n",
    "        # The passenger_id is used in our flight tools to\n",
    "        # fetch the user's flight information\n",
    "        \"passenger_id\": \"3442 587242\",\n",
    "        # Checkpoints are accessed by thread_id\n",
    "        \"thread_id\": thread_id,\n",
    "    }\n",
    "}\n",
    "\n",
    "_printed = set()\n",
    "# We can reuse the tutorial questions from part 1 to see how it does.\n",
    "for question in tutorial_questions[:3]:\n",
    "    events = part_4_graph.stream(\n",
    "        {\"messages\": (\"user\", question)}, config, stream_mode=\"values\"\n",
    "    )\n",
    "    for event in events:\n",
    "        _print_event(event, _printed)\n",
    "    snapshot = part_4_graph.get_state(config)\n",
    "    while snapshot.next:\n",
    "        # We have an interrupt! The agent is trying to use a tool, and the user can approve or deny it\n",
    "        # Note: This code is all outside of your graph. Typically, you would stream the output to a UI.\n",
    "        # Then, you would have the frontend trigger a new run via an API call when the user has provided input.\n",
    "        user_input = input(\n",
    "            \"Do you approve of the above actions? Type 'y' to continue;\"\n",
    "            \" otherwise, explain your requested changed.\\n\\n\"\n",
    "        )\n",
    "        if user_input.strip() == \"y\":\n",
    "            # Just continue\n",
    "            result = part_4_graph.invoke(\n",
    "                None,\n",
    "                config,\n",
    "            )\n",
    "        else:\n",
    "            # Satisfy the tool invocation by\n",
    "            # providing instructions on the requested changes / change of mind\n",
    "            result = part_4_graph.invoke(\n",
    "                {\n",
    "                    \"messages\": [\n",
    "                        ToolMessage(\n",
    "                            tool_call_id=event[\"messages\"][-1].tool_calls[0][\"id\"],\n",
    "                            content=f\"API call denied by user. Reasoning: '{user_input}'. Continue assisting, accounting for the user's input.\",\n",
    "                        )\n",
    "                    ]\n",
    "                },\n",
    "                config,\n",
    "            )\n",
    "        snapshot = part_4_graph.get_state(config)\n",
    "     \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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