301 lines
9.4 KiB
Plaintext
301 lines
9.4 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "ddfa9ae6-69fe-444a-b994-8c4c5970a7ec",
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"metadata": {},
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"source": [
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"# Project - Airline AI Assistant\n",
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"\n",
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"We'll now bring together what we've learned to make an AI Customer Support assistant for an Airline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8b50bbe2-c0b1-49c3-9a5c-1ba7efa2bcb4",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import json\n",
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"from dotenv import load_dotenv\n",
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"from openai import OpenAI\n",
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"import gradio as gr"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "747e8786-9da8-4342-b6c9-f5f69c2e22ae",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Initialization\n",
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"\n",
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"load_dotenv()\n",
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"os.environ['OPENAI_API_KEY'] = os.getenv('OPENAI_API_KEY', 'your-key-if-not-using-env')\n",
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"MODEL = \"gpt-4o-mini\"\n",
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"openai = OpenAI()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0a521d84-d07c-49ab-a0df-d6451499ed97",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_message = \"You are a helpful assistant for an Airline called FlightAI. \"\n",
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"system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n",
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"system_message += \"Always get a price confirmation from the traveler before booking the flight.\"\n",
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"system_message += \"Always ask the departure city before confirm the booking.\"\n",
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"system_message += \"Always be accurate. If you don't know the answer, say so.\""
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "61a2a15d-b559-4844-b377-6bd5cb4949f6",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}]\n",
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" for human, assistant in history:\n",
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" messages.append({\"role\": \"user\", \"content\": human})\n",
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" messages.append({\"role\": \"assistant\", \"content\": assistant})\n",
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" messages.append({\"role\": \"user\", \"content\": message})\n",
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" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
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" return response.choices[0].message.content\n",
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"\n",
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"gr.ChatInterface(fn=chat).launch()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "36bedabf-a0a7-4985-ad8e-07ed6a55a3a4",
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"metadata": {},
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"source": [
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"## Tools\n",
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"\n",
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"Tools are an incredibly powerful feature provided by the frontier LLMs.\n",
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"\n",
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"With tools, you can write a function, and have the LLM call that function as part of its response.\n",
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"\n",
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"Sounds almost spooky.. we're giving it the power to run code on our machine?\n",
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"\n",
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"Well, kinda."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0696acb1-0b05-4dc2-80d5-771be04f1fb2",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Let's start by making a useful function\n",
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"\n",
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"ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\"}\n",
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"\n",
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"def get_ticket_price(destination_city):\n",
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" print(f\"Tool get_ticket_price called for {destination_city}\")\n",
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" city = destination_city.lower()\n",
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" return ticket_prices.get(city, \"Unknown\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "80ca4e09-6287-4d3f-997d-fa6afbcf6c85",
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"metadata": {},
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"outputs": [],
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"source": [
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"get_ticket_price(\"Berlin\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "4afceded-7178-4c05-8fa6-9f2085e6a344",
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"metadata": {},
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"outputs": [],
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"source": [
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"# There's a particular dictionary structure that's required to describe our function:\n",
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"\n",
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"price_function = {\n",
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" \"name\": \"get_ticket_price\",\n",
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" \"description\": \"Get the price of a return ticket to the destination city. Call this whenever you need to know the ticket price, for example when a customer asks 'How much is a ticket to this city'\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"destination_city\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"The city that the customer wants to travel to\",\n",
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" },\n",
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" },\n",
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" \"required\": [\"destination_city\"],\n",
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" \"additionalProperties\": False\n",
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" }\n",
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"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8c2d843a-a4b2-40fd-a3ed-365938e4fb1b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def book_ticket(destination_city):\n",
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" print(f\"Tool book_ticket called for {destination_city}\")\n",
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" return (f\"The ticket to {destination_city} has been booked. Thank you.\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "8e25cf39-191e-4c0b-a1e4-95e7b1208c7a",
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"metadata": {},
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"outputs": [],
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"source": [
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"book_function = {\n",
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" \"name\": \"book_ticket\",\n",
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" \"description\": \"Get the confirmation of booking a ticket to the destination city. Call this whenever you need to book the ticket, for example when a customer asks 'I'd like to book this ticket'\",\n",
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" \"parameters\": {\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"destination_city\": {\n",
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" \"type\": \"string\",\n",
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" \"description\": \"The city that the customer wants to book the ticket\",\n",
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" },\n",
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" },\n",
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" \"required\": [\"destination_city\"],\n",
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" \"additionalProperties\": False\n",
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" }\n",
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"}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "bdca8679-935f-4e7f-97e6-e71a4d4f228c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# And this is included in a list of tools:\n",
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"\n",
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"tools = [{\"type\": \"function\", \"function\": price_function},\n",
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" {\"type\": \"function\", \"function\": book_function}]"
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]
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},
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{
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"cell_type": "markdown",
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"id": "c3d3554f-b4e3-4ce7-af6f-68faa6dd2340",
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"metadata": {},
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"source": [
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"## Getting OpenAI to use our Tool\n",
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"\n",
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"There's some fiddly stuff to allow OpenAI \"to call our tool\"\n",
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"\n",
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"What we actually do is give the LLM the opportunity to inform us that it wants us to run the tool.\n",
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"\n",
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"Here's how the new chat function looks:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "ce9b0744-9c78-408d-b9df-9f6fd9ed78cf",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}]\n",
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" for human, assistant in history:\n",
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" messages.append({\"role\": \"user\", \"content\": human})\n",
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" messages.append({\"role\": \"assistant\", \"content\": assistant})\n",
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" messages.append({\"role\": \"user\", \"content\": message})\n",
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" response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n",
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"\n",
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" if response.choices[0].finish_reason==\"tool_calls\":\n",
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" message = response.choices[0].message\n",
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" response, city = handle_tool_call(message)\n",
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" messages.append(message)\n",
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" messages.append(response)\n",
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" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
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" \n",
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" return response.choices[0].message.content"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b0992986-ea09-4912-a076-8e5603ee631f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# We have to write that function handle_tool_call:\n",
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"\n",
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"def handle_tool_call(message):\n",
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" tool_call = message.tool_calls[0]\n",
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" arguments = json.loads(tool_call.function.arguments)\n",
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" city = arguments.get('destination_city')\n",
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" price = get_ticket_price(city)\n",
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" if price != \"Unknow\":\n",
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" ticket_booked = book_ticket(city)\n",
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" response = {\n",
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" \"role\": \"tool\",\n",
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" \"content\": json.dumps({\"destination_city\": city,\n",
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" \"price\": price,\n",
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" \"ticket_booked\": ticket_booked}),\n",
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" \"tool_call_id\": message.tool_calls[0].id\n",
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" }\n",
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" return response, city"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "f4be8a71-b19e-4c2f-80df-f59ff2661f14",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat).launch()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "11c9da69-d0cf-4cf2-a49e-e5669deec47b",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.10"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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