Anthropic_LLM_Model.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "toc_visible": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "#Install Dependency"
      ],
      "metadata": {
        "id": "rFmVb2xjk7qI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%capture --no-stderr\n",
        "!pip install -U langgraph langchain-community langchain-anthropic tavily-python pandas\n",
        "!pip -q install -U voyageai"
      ],
      "metadata": {
        "id": "M7fpsChzM8lB"
      },
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Set API Keys"
      ],
      "metadata": {
        "id": "YAi6syCDlr4X"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import getpass\n",
        "import os\n",
        "\n",
        "\n",
        "def _set_env(var: str):\n",
        "    if not os.environ.get(var):\n",
        "        os.environ[var] = getpass.getpass(f\"{var}: \")\n",
        "\n",
        "\n",
        "_set_env(\"ANTHROPIC_API_KEY\")\n",
        "_set_env(\"TAVILY_API_KEY\")\n",
        "\n",
        "_set_env(\"LANGCHAIN_API_KEY\")\n",
        "os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
        "os.environ[\"LANGCHAIN_PROJECT\"] = \"Customer Support Bot Tutorial\""
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "g72M5Ha5A2Pe",
        "outputId": "b2edf861-c569-42d1-ab1a-d104375a6454"
      },
      "execution_count": 2,
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "ANTHROPIC_API_KEY: ··········\n",
            "TAVILY_API_KEY: ··········\n",
            "LANGCHAIN_API_KEY: ··········\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Set Up and Preprocess Travel SQLite Database"
      ],
      "metadata": {
        "id": "jVp4UUFolv0v"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "import shutil\n",
        "import sqlite3\n",
        "\n",
        "import pandas as pd\n",
        "import requests\n",
        "\n",
        "db_url = \"https://storage.googleapis.com/benchmarks-artifacts/travel-db/travel2.sqlite\"\n",
        "local_file = \"travel2.sqlite\"\n",
        "# The backup lets us restart for each tutorial section\n",
        "backup_file = \"travel2.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\" our DB in each section\n",
        "    shutil.copy(local_file, backup_file)\n",
        "# Convert the flights to present time for our tutorial\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  # We'll be using this local file as our DB in this tutorial"
      ],
      "metadata": {
        "id": "rXulSj94BJ9L"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "import voyageai\n",
        "import numpy as np\n",
        "from langchain_core.tools import tool\n",
        "\n",
        "client = voyageai.Client(api_key=\"your_api\")\n",
        "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",
        "\n",
        "        truncated_texts = [doc[\"page_content\"][:10] for doc in docs]\n",
        "        embeddings = oai_client.embed(texts= truncated_texts,\n",
        "               model=\"voyage-2\",\n",
        "               input_type= \"document\")\n",
        "        vectors = embeddings.embeddings\n",
        "\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",
        "        # \"@\" is just a matrix multiplication in python\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,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])"
      ],
      "metadata": {
        "id": "8yzRWjidIPuX"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Tools"
      ],
      "metadata": {
        "id": "Db8v_JOMnRls"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Flights"
      ],
      "metadata": {
        "id": "4lMk_97-S--f"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import sqlite3\n",
        "from datetime import date, datetime, timedelta\n",
        "from typing import Optional\n",
        "\n",
        "import pytz\n",
        "from langchain_core.runnables import ensure_config\n",
        "\n",
        "\n",
        "@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[datetime | datetime] = None,\n",
        "    end_time: Optional[datetime | 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.\""
      ],
      "metadata": {
        "id": "yo_il_xBKLk7"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Car Rental Tools"
      ],
      "metadata": {
        "id": "wqIhHwUmS6KE"
      }
    },
    {
      "cell_type": "code",
      "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, datetime]] = None,\n",
        "    end_date: Optional[Union[datetime, datetime]] = 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, datetime]] = None,\n",
        "    end_date: Optional[Union[datetime, datetime]] = 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}.\""
      ],
      "metadata": {
        "id": "soxe550nSLE8"
      },
      "execution_count": 8,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Hotels"
      ],
      "metadata": {
        "id": "t21_L-4hS2W-"
      }
    },
    {
      "cell_type": "code",
      "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, datetime]] = None,\n",
        "    checkout_date: Optional[Union[datetime, datetime]] = 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, datetime]] = None,\n",
        "    checkout_date: Optional[Union[datetime, datetime]] = 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}.\""
      ],
      "metadata": {
        "id": "mJUXGmLiSO2g"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Excursions"
      ],
      "metadata": {
        "id": "4Jhf101ZSxQM"
      }
    },
    {
      "cell_type": "code",
      "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}.\""
      ],
      "metadata": {
        "id": "_EnEKziuSSKU"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Utilities"
      ],
      "metadata": {
        "id": "3p8_vEMISqx1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain_core.runnables import RunnableLambda\n",
        "\n",
        "from langgraph.prebuilt import ToolNode\n",
        "\n",
        "\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)"
      ],
      "metadata": {
        "id": "4ONFli5FSZM1"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Zero-shot Agent"
      ],
      "metadata": {
        "id": "nU74TbkSTJk4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from typing import Annotated\n",
        "\n",
        "from typing_extensions import TypedDict\n",
        "\n",
        "from langgraph.graph.message import AnyMessage, add_messages\n",
        "\n",
        "\n",
        "class State(TypedDict):\n",
        "    messages: Annotated[list[AnyMessage], add_messages]"
      ],
      "metadata": {
        "id": "a8rnNt8MSlFy"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Agent"
      ],
      "metadata": {
        "id": "w5zMfrgdTPmU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from langchain_anthropic import ChatAnthropic\n",
        "from langchain_community.tools.tavily_search import TavilySearchResults\n",
        "from langchain_core.prompts import ChatPromptTemplate\n",
        "from langchain_core.runnables import Runnable, RunnableConfig\n",
        "\n",
        "\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",
        "            passenger_id = config.get(\"passenger_id\", None)\n",
        "            state = {**state, \"user_info\": passenger_id}\n",
        "            result = self.runnable.invoke(state)\n",
        "            # If the LLM happens to return an empty response, we will re-prompt it\n",
        "            # for an actual response.\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",
        "            else:\n",
        "                break\n",
        "        return {\"messages\": result}\n",
        "\n",
        "llm = ChatAnthropic(model=\"claude-3-sonnet-20240229\", temperature=1)\n",
        "\n",
        "primary_assistant_prompt = ChatPromptTemplate.from_messages(\n",
        "\n",
        "    [\n",
        "        (\n",
        "            \"system\",\n",
        "            \"You are a helpful customer support assistant for Swiss Airlines. \"\n",
        "            \" Use the provided tools to search for flights, company policies, and other information to assist the user's queries. \"\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:\\n\\n{user_info}\\n\"\n",
        "            \"\\nCurrent time: {time}.\",\n",
        "        ),\n",
        "        (\"placeholder\", \"{messages}\"),\n",
        "    ]\n",
        ").partial(time=datetime.now())\n",
        "\n",
        "part_1_tools = [\n",
        "    TavilySearchResults(max_results=1),\n",
        "    fetch_user_flight_information,\n",
        "    search_flights,\n",
        "    lookup_policy,\n",
        "    update_ticket_to_new_flight,\n",
        "    cancel_ticket,\n",
        "    search_car_rentals,\n",
        "    book_car_rental,\n",
        "    update_car_rental,\n",
        "    cancel_car_rental,\n",
        "    search_hotels,\n",
        "    book_hotel,\n",
        "\n",
        "    update_hotel,\n",
        "    cancel_hotel,\n",
        "    search_trip_recommendations,\n",
        "    book_excursion,\n",
        "    update_excursion,\n",
        "\n",
        "    cancel_excursion,\n",
        "]\n",
        "#part_1_assistant_runnable = primary_assistant_prompt | llm.bind_tools(part_1_tools)\n",
        "part_1_assistant_runnable = primary_assistant_prompt | llm.bind_tools(part_1_tools)"
      ],
      "metadata": {
        "id": "xBomq7LbTRNr",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "d3fbf8af-3ca4-490f-fc49-c6ec21f9019f"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/langchain_core/_api/beta_decorator.py:87: LangChainBetaWarning: The method `ChatAnthropic.bind_tools` is in beta. It is actively being worked on, so the API may change.\n",
            "  warn_beta(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(part_1_tools)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5rxgWkqdugUQ",
        "outputId": "0bba1271-770f-4e00-8b74-31bcae469fe0"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[TavilySearchResults(max_results=1), StructuredTool(name='fetch_user_flight_information', description='fetch_user_flight_information() -> list[dict] - 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.', args_schema=<class 'pydantic.v1.main.fetch_user_flight_informationSchema'>, func=<function fetch_user_flight_information at 0x7d4b3f584550>), StructuredTool(name='search_flights', description='search_flights(departure_airport: Optional[str] = None, arrival_airport: Optional[str] = None, start_time: Optional[datetime.datetime] = None, end_time: Optional[datetime.datetime] = None, limit: int = 20) -> list[dict] - Search for flights based on departure airport, arrival airport, and departure time range.', args_schema=<class 'pydantic.v1.main.search_flightsSchema'>, func=<function search_flights at 0x7d4b3f5845e0>), StructuredTool(name='lookup_policy', description=\"lookup_policy(query: str) -> str - Consult the company policies to check whether certain options are permitted.\\n    Use this before making any flight changes performing other 'write' events.\", args_schema=<class 'pydantic.v1.main.lookup_policySchema'>, func=<function lookup_policy at 0x7d4b42d97010>), StructuredTool(name='update_ticket_to_new_flight', description=\"update_ticket_to_new_flight(ticket_no: str, new_flight_id: int) -> str - Update the user's ticket to a new valid flight.\", args_schema=<class 'pydantic.v1.main.update_ticket_to_new_flightSchema'>, func=<function update_ticket_to_new_flight at 0x7d4b3f584670>), StructuredTool(name='cancel_ticket', description=\"cancel_ticket(ticket_no: str) -> str - Cancel the user's ticket and remove it from the database.\", args_schema=<class 'pydantic.v1.main.cancel_ticketSchema'>, func=<function cancel_ticket at 0x7d4b3f584790>), StructuredTool(name='search_car_rentals', description='search_car_rentals(location: Optional[str] = None, name: Optional[str] = None, price_tier: Optional[str] = None, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None) -> list[dict] - Search for car rentals based on location, name, price tier, start date, and end date.\\n\\nArgs:\\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\\nReturns:\\n    list[dict]: A list of car rental dictionaries matching the search criteria.', args_schema=<class 'pydantic.v1.main.search_car_rentalsSchema'>, func=<function search_car_rentals at 0x7d4b42d97520>), StructuredTool(name='book_car_rental', description='book_car_rental(rental_id: int) -> str - Book a car rental by its ID.\\n\\nArgs:\\n    rental_id (int): The ID of the car rental to book.\\n\\nReturns:\\n    str: A message indicating whether the car rental was successfully booked or not.', args_schema=<class 'pydantic.v1.main.book_car_rentalSchema'>, func=<function book_car_rental at 0x7d4b7b6ac8b0>), StructuredTool(name='update_car_rental', description=\"update_car_rental(rental_id: int, start_date: Optional[datetime.datetime] = None, end_date: Optional[datetime.datetime] = None) -> str - Update a car rental's start and end dates by its ID.\\n\\nArgs:\\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\\nReturns:\\n    str: A message indicating whether the car rental was successfully updated or not.\", args_schema=<class 'pydantic.v1.main.update_car_rentalSchema'>, func=<function update_car_rental at 0x7d4b3f585ab0>), StructuredTool(name='cancel_car_rental', description='cancel_car_rental(rental_id: int) -> str - Cancel a car rental by its ID.\\n\\nArgs:\\n    rental_id (int): The ID of the car rental to cancel.\\n\\nReturns:\\n    str: A message indicating whether the car rental was successfully cancelled or not.', args_schema=<class 'pydantic.v1.main.cancel_car_rentalSchema'>, func=<function cancel_car_rental at 0x7d4b3f585fc0>), StructuredTool(name='search_hotels', description='search_hotels(location: Optional[str] = None, name: Optional[str] = None, price_tier: Optional[str] = None, checkin_date: Optional[datetime.datetime] = None, checkout_date: Optional[datetime.datetime] = None) -> list[dict] - Search for hotels based on location, name, price tier, check-in date, and check-out date.\\n\\nArgs:\\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\\nReturns:\\n    list[dict]: A list of hotel dictionaries matching the search criteria.', args_schema=<class 'pydantic.v1.main.search_hotelsSchema'>, func=<function search_hotels at 0x7d4b3f585c60>), StructuredTool(name='book_hotel', description='book_hotel(hotel_id: int) -> str - Book a hotel by its ID.\\n\\nArgs:\\n    hotel_id (int): The ID of the hotel to book.\\n\\nReturns:\\n    str: A message indicating whether the hotel was successfully booked or not.', args_schema=<class 'pydantic.v1.main.book_hotelSchema'>, func=<function book_hotel at 0x7d4b3f587130>), StructuredTool(name='update_hotel', description=\"update_hotel(hotel_id: int, checkin_date: Optional[datetime.datetime] = None, checkout_date: Optional[datetime.datetime] = None) -> str - Update a hotel's check-in and check-out dates by its ID.\\n\\nArgs:\\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\\nReturns:\\n    str: A message indicating whether the hotel was successfully updated or not.\", args_schema=<class 'pydantic.v1.main.update_hotelSchema'>, func=<function update_hotel at 0x7d4b3f585cf0>), StructuredTool(name='cancel_hotel', description='cancel_hotel(hotel_id: int) -> str - Cancel a hotel by its ID.\\n\\nArgs:\\n    hotel_id (int): The ID of the hotel to cancel.\\n\\nReturns:\\n    str: A message indicating whether the hotel was successfully cancelled or not.', args_schema=<class 'pydantic.v1.main.cancel_hotelSchema'>, func=<function cancel_hotel at 0x7d4b7a99c940>), StructuredTool(name='search_trip_recommendations', description='search_trip_recommendations(location: Optional[str] = None, name: Optional[str] = None, keywords: Optional[str] = None) -> list[dict] - Search for trip recommendations based on location, name, and keywords.\\n\\nArgs:\\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\\nReturns:\\n    list[dict]: A list of trip recommendation dictionaries matching the search criteria.', args_schema=<class 'pydantic.v1.main.search_trip_recommendationsSchema'>, func=<function search_trip_recommendations at 0x7d4b3f584e50>), StructuredTool(name='book_excursion', description='book_excursion(recommendation_id: int) -> str - Book a excursion by its recommendation ID.\\n\\nArgs:\\n    recommendation_id (int): The ID of the trip recommendation to book.\\n\\nReturns:\\n    str: A message indicating whether the trip recommendation was successfully booked or not.', args_schema=<class 'pydantic.v1.main.book_excursionSchema'>, func=<function book_excursion at 0x7d4b3f587910>), StructuredTool(name='update_excursion', description=\"update_excursion(recommendation_id: int, details: str) -> str - Update a trip recommendation's details by its ID.\\n\\nArgs:\\n    recommendation_id (int): The ID of the trip recommendation to update.\\n    details (str): The new details of the trip recommendation.\\n\\nReturns:\\n    str: A message indicating whether the trip recommendation was successfully updated or not.\", args_schema=<class 'pydantic.v1.main.update_excursionSchema'>, func=<function update_excursion at 0x7d4b3f587a30>), StructuredTool(name='cancel_excursion', description='cancel_excursion(recommendation_id: int) -> str - Cancel a trip recommendation by its ID.\\n\\nArgs:\\n    recommendation_id (int): The ID of the trip recommendation to cancel.\\n\\nReturns:\\n    str: A message indicating whether the trip recommendation was successfully cancelled or not.', args_schema=<class 'pydantic.v1.main.cancel_excursionSchema'>, func=<function cancel_excursion at 0x7d4b4ba9a950>)]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Define Graph"
      ],
      "metadata": {
        "id": "N5RMJRuLTV3e"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from langgraph.checkpoint.sqlite import SqliteSaver\n",
        "from langgraph.graph import END, StateGraph\n",
        "from langgraph.prebuilt import ToolNode, tools_condition\n",
        "\n",
        "builder = StateGraph(State)\n",
        "\n",
        "\n",
        "# Define nodes: these do the work\n",
        "builder.add_node(\"assistant\", Assistant(part_1_assistant_runnable))\n",
        "builder.add_node(\"action\", create_tool_node_with_fallback(part_1_tools))\n",
        "# Define edges: these determine how the control flow moves\n",
        "builder.set_entry_point(\"assistant\")\n",
        "builder.add_conditional_edges(\n",
        "    \"assistant\",\n",
        "    tools_condition,\n",
        "    # \"action\" calls one of our tools. END causes the graph to terminate (and respond to the user)\n",
        "    {\"action\": \"action\", END: END},\n",
        ")\n",
        "builder.add_edge(\"action\", \"assistant\")\n",
        "\n",
        "# The checkpointer lets the graph persist its state\n",
        "# this is a complete memory for the entire graph.\n",
        "memory = SqliteSaver.from_conn_string(\":memory:\")\n",
        "part_1_graph = builder.compile(checkpointer=memory)"
      ],
      "metadata": {
        "id": "mHUTxC1dTS9f"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import Image, display\n",
        "\n",
        "try:\n",
        "    display(Image(part_1_graph.get_graph(xray=True).draw_mermaid_png()))\n",
        "except:\n",
        "    # This requires some extra dependencies and is optional\n",
        "    pass"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 235
        },
        "id": "tcKINN0TTYzA",
        "outputId": "a8239ca4-5b14-4aa7-c2c7-5964d2ecb3a3"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/jpeg": "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\n",
            "text/plain": [
              "<IPython.core.display.Image object>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##Example Conversation"
      ],
      "metadata": {
        "id": "D_LGCgc4TexB"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import shutil\n",
        "import uuid\n",
        "\n",
        "# Let's create an example conversation a user might have with the assistant\n",
        "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",
        "# Update with the backup file so we can restart from the original palce 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",
        "\n",
        "_printed = set()\n",
        "for question in tutorial_questions:\n",
        "    events = part_1_graph.stream(\n",
        "        {\"messages\": (\"user\", question)}, config, stream_mode=\"values\"\n",
        "    )\n",
        "    for event in events:\n",
        "        _print_event(event, _printed)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 408
        },
        "id": "2a_wu0BcTcBC",
        "outputId": "0018cdc8-5018-47d9-9efc-bed8f36959b6"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "================================\u001b[1m Human Message \u001b[0m=================================\n",
            "\n",
            "Hi there, what time is my flight?\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "BadRequestError",
          "evalue": "Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits.'}}",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mBadRequestError\u001b[0m                           Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-17-e2229a983731>\u001b[0m in \u001b[0;36m<cell line: 38>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     40\u001b[0m         \u001b[0;34m{\u001b[0m\u001b[0;34m\"messages\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m\"user\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mquestion\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_mode\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"values\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     41\u001b[0m     )\n\u001b[0;32m---> 42\u001b[0;31m     \u001b[0;32mfor\u001b[0m \u001b[0mevent\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mevents\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     43\u001b[0m         \u001b[0m_print_event\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0m_printed\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langgraph/pregel/__init__.py\u001b[0m in \u001b[0;36mstream\u001b[0;34m(self, input, config, stream_mode, output_keys, input_keys, interrupt_before, interrupt_after, debug)\u001b[0m\n\u001b[1;32m    769\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    770\u001b[0m                     \u001b[0;31m# panic on failure or timeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 771\u001b[0;31m                     \u001b[0m_panic_or_proceed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minflight\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    772\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    773\u001b[0m                     \u001b[0;31m# combine pending writes from all tasks\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langgraph/pregel/__init__.py\u001b[0m in \u001b[0;36m_panic_or_proceed\u001b[0;34m(done, inflight, step)\u001b[0m\n\u001b[1;32m   1261\u001b[0m                 \u001b[0minflight\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpop\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcancel\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1262\u001b[0m             \u001b[0;31m# raise the exception\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1263\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1264\u001b[0m             \u001b[0;31m# TODO this is where retry of an entire step would happen\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1265\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/lib/python3.10/concurrent/futures/thread.py\u001b[0m in \u001b[0;36mrun\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     56\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     57\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 58\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfn\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     59\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mBaseException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     60\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfuture\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_exception\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/runnables/base.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config)\u001b[0m\n\u001b[1;32m   2497\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2498\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2499\u001b[0;31m                 input = step.invoke(\n\u001b[0m\u001b[1;32m   2500\u001b[0m                     \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2501\u001b[0m                     \u001b[0;31m# mark each step as a child run\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langgraph/utils.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config)\u001b[0m\n\u001b[1;32m     86\u001b[0m                 \u001b[0;32melse\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     87\u001b[0m             )\n\u001b[0;32m---> 88\u001b[0;31m             \u001b[0mret\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcontext\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrun\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfunc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     89\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mret\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mRunnable\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecurse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     90\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mret\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvoke\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m<ipython-input-13-6ce1617080e0>\u001b[0m in \u001b[0;36m__call__\u001b[0;34m(self, state, config)\u001b[0m\n\u001b[1;32m     13\u001b[0m             \u001b[0mpassenger_id\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"passenger_id\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     14\u001b[0m             \u001b[0mstate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"user_info\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mpassenger_id\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 15\u001b[0;31m             \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrunnable\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0minvoke\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     16\u001b[0m             \u001b[0;31m# If the LLM happens to return an empty response, we will re-prompt it\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     17\u001b[0m             \u001b[0;31m# for an actual response.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/runnables/base.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config)\u001b[0m\n\u001b[1;32m   2497\u001b[0m         \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2498\u001b[0m             \u001b[0;32mfor\u001b[0m \u001b[0mi\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstep\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2499\u001b[0;31m                 input = step.invoke(\n\u001b[0m\u001b[1;32m   2500\u001b[0m                     \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2501\u001b[0m                     \u001b[0;31m# mark each step as a child run\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/runnables/base.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   4523\u001b[0m         \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mAny\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4524\u001b[0m     ) -> Output:\n\u001b[0;32m-> 4525\u001b[0;31m         return self.bound.invoke(\n\u001b[0m\u001b[1;32m   4526\u001b[0m             \u001b[0minput\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   4527\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_merge_configs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mconfig\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/chat_models.py\u001b[0m in \u001b[0;36minvoke\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    156\u001b[0m         return cast(\n\u001b[1;32m    157\u001b[0m             \u001b[0mChatGeneration\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 158\u001b[0;31m             self.generate_prompt(\n\u001b[0m\u001b[1;32m    159\u001b[0m                 \u001b[0;34m[\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_convert_input\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minput\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    160\u001b[0m                 \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/chat_models.py\u001b[0m in \u001b[0;36mgenerate_prompt\u001b[0;34m(self, prompts, stop, callbacks, **kwargs)\u001b[0m\n\u001b[1;32m    558\u001b[0m     ) -> LLMResult:\n\u001b[1;32m    559\u001b[0m         \u001b[0mprompt_messages\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mto_messages\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mp\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mprompts\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 560\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mprompt_messages\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mcallbacks\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcallbacks\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    561\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    562\u001b[0m     async def agenerate_prompt(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/chat_models.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[0m\n\u001b[1;32m    419\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mrun_managers\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    420\u001b[0m                     \u001b[0mrun_managers\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mi\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mon_llm_error\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0me\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mresponse\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mLLMResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerations\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 421\u001b[0;31m                 \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    422\u001b[0m         flattened_outputs = [\n\u001b[1;32m    423\u001b[0m             \u001b[0mLLMResult\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mgenerations\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mres\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mgenerations\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mllm_output\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mres\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mllm_output\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# type: ignore[list-item]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/chat_models.py\u001b[0m in \u001b[0;36mgenerate\u001b[0;34m(self, messages, stop, callbacks, tags, metadata, run_name, run_id, **kwargs)\u001b[0m\n\u001b[1;32m    409\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    410\u001b[0m                 results.append(\n\u001b[0;32m--> 411\u001b[0;31m                     self._generate_with_cache(\n\u001b[0m\u001b[1;32m    412\u001b[0m                         \u001b[0mm\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    413\u001b[0m                         \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_core/language_models/chat_models.py\u001b[0m in \u001b[0;36m_generate_with_cache\u001b[0;34m(self, messages, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m    630\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    631\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0minspect\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msignature\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_generate\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mparameters\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"run_manager\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 632\u001b[0;31m                 result = self._generate(\n\u001b[0m\u001b[1;32m    633\u001b[0m                     \u001b[0mmessages\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstop\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstop\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrun_manager\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mrun_manager\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    634\u001b[0m                 )\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/langchain_anthropic/chat_models.py\u001b[0m in \u001b[0;36m_generate\u001b[0;34m(self, messages, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m    510\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mgenerate_from_stream\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstream_iter\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    511\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0m_tools_in_params\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 512\u001b[0;31m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mbeta\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtools\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmessages\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    513\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    514\u001b[0m             \u001b[0mdata\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_client\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmessages\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0mparams\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/anthropic/_utils/_utils.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    275\u001b[0m                         \u001b[0mmsg\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34mf\"Missing required argument: {quote(missing[0])}\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    276\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 277\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    278\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    279\u001b[0m         \u001b[0;32mreturn\u001b[0m \u001b[0mwrapper\u001b[0m  \u001b[0;31m# type: ignore\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/anthropic/resources/beta/tools/messages.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(self, max_tokens, messages, model, metadata, stop_sequences, stream, system, temperature, tools, top_k, top_p, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m    846\u001b[0m     ) -> ToolsBetaMessage | Stream[MessageStreamEvent]:\n\u001b[1;32m    847\u001b[0m         \u001b[0mextra_headers\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m\"anthropic-beta\"\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0;34m\"tools-2024-04-04\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mextra_headers\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0;34m{\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 848\u001b[0;31m         return self._post(\n\u001b[0m\u001b[1;32m    849\u001b[0m             \u001b[0;34m\"/v1/messages?beta=tools\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    850\u001b[0m             body=maybe_transform(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/anthropic/_base_client.py\u001b[0m in \u001b[0;36mpost\u001b[0;34m(self, path, cast_to, body, options, files, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1237\u001b[0m             \u001b[0mmethod\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"post\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0murl\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mjson_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mbody\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mfiles\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mto_httpx_files\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfiles\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1238\u001b[0m         )\n\u001b[0;32m-> 1239\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mcast\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mResponseT\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mopts\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstream\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstream_cls\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstream_cls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1240\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1241\u001b[0m     def patch(\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/anthropic/_base_client.py\u001b[0m in \u001b[0;36mrequest\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m    919\u001b[0m         \u001b[0mstream_cls\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtype\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0m_StreamT\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m|\u001b[0m \u001b[0;32mNone\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    920\u001b[0m     ) -> ResponseT | _StreamT:\n\u001b[0;32m--> 921\u001b[0;31m         return self._request(\n\u001b[0m\u001b[1;32m    922\u001b[0m             \u001b[0mcast_to\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcast_to\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    923\u001b[0m             \u001b[0moptions\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/anthropic/_base_client.py\u001b[0m in \u001b[0;36m_request\u001b[0;34m(self, cast_to, options, remaining_retries, stream, stream_cls)\u001b[0m\n\u001b[1;32m   1017\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1018\u001b[0m             \u001b[0mlog\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdebug\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Re-raising status error\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1019\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_status_error_from_response\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0merr\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1020\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1021\u001b[0m         return self._process_response(\n",
            "\u001b[0;31mBadRequestError\u001b[0m: Error code: 400 - {'type': 'error', 'error': {'type': 'invalid_request_error', 'message': 'Your credit balance is too low to access the Claude API. Please go to Plans & Billing to upgrade or purchase credits.'}}"
          ]
        }
      ]
    }
  ]
}