From 3dad3d050dea77a35ba0cf3950c47f4199825867 Mon Sep 17 00:00:00 2001 From: Phi-Li-Ne Date: Sun, 2 Mar 2025 20:41:04 +0100 Subject: [PATCH] move day4 folder --- ...tended with flight availability tool.ipynb | 355 ------------------ 1 file changed, 355 deletions(-) delete mode 100644 week2/community-contributions/day4-FlightAI extended with flight availability tool.ipynb diff --git a/week2/community-contributions/day4-FlightAI extended with flight availability tool.ipynb b/week2/community-contributions/day4-FlightAI extended with flight availability tool.ipynb deleted file mode 100644 index 4577470..0000000 --- a/week2/community-contributions/day4-FlightAI extended with flight availability tool.ipynb +++ /dev/null @@ -1,355 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "ddfa9ae6-69fe-444a-b994-8c4c5970a7ec", - "metadata": {}, - "source": [ - "# Project - Airline AI Assistant\n", - "\n", - "We'll now bring together what we've learned to make an AI Customer Support assistant for an Airline" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "8b50bbe2-c0b1-49c3-9a5c-1ba7efa2bcb4", - "metadata": {}, - "outputs": [], - "source": [ - "# imports\n", - "\n", - "import os\n", - "import json\n", - "from dotenv import load_dotenv\n", - "from openai import OpenAI\n", - "import gradio as gr" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "747e8786-9da8-4342-b6c9-f5f69c2e22ae", - "metadata": {}, - "outputs": [], - "source": [ - "# Initialization\n", - "\n", - "load_dotenv(override=True)\n", - "\n", - "openai_api_key = os.getenv('OPENAI_API_KEY')\n", - "if openai_api_key:\n", - " print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n", - "else:\n", - " print(\"OpenAI API Key not set\")\n", - " \n", - "MODEL = \"gpt-4o-mini\"\n", - "openai = OpenAI()\n", - "\n", - "# As an alternative, if you'd like to use Ollama instead of OpenAI\n", - "# Check that Ollama is running for you locally (see week1/day2 exercise) then uncomment these next 2 lines\n", - "# MODEL = \"llama3.2\"\n", - "# openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0a521d84-d07c-49ab-a0df-d6451499ed97", - "metadata": {}, - "outputs": [], - "source": [ - "system_message = \"You are a helpful assistant for an Airline called FlightAI. \"\n", - "system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n", - "system_message += \"Always be accurate. If you don't know the answer, say so.\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "61a2a15d-b559-4844-b377-6bd5cb4949f6", - "metadata": {}, - "outputs": [], - "source": [ - "# This function looks rather simpler than the one from my video, because we're taking advantage of the latest Gradio updates\n", - "\n", - "def chat(message, history):\n", - " messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n", - " response = openai.chat.completions.create(model=MODEL, messages=messages)\n", - " return response.choices[0].message.content\n", - "\n", - "gr.ChatInterface(fn=chat, type=\"messages\").launch()" - ] - }, - { - "cell_type": "markdown", - "id": "36bedabf-a0a7-4985-ad8e-07ed6a55a3a4", - "metadata": {}, - "source": [ - "## Tools\n", - "\n", - "Tools are an incredibly powerful feature provided by the frontier LLMs.\n", - "\n", - "With tools, you can write a function, and have the LLM call that function as part of its response.\n", - "\n", - "Sounds almost spooky.. we're giving it the power to run code on our machine?\n", - "\n", - "Well, kinda." - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0696acb1-0b05-4dc2-80d5-771be04f1fb2", - "metadata": {}, - "outputs": [], - "source": [ - "# Let's start by making a useful function\n", - "\n", - "ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\"}\n", - "\n", - "def get_ticket_price(destination_city):\n", - " print(f\"Tool get_ticket_price called for {destination_city}\")\n", - " city = destination_city.lower()\n", - " return ticket_prices.get(city, \"Unknown\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "80ca4e09-6287-4d3f-997d-fa6afbcf6c85", - "metadata": {}, - "outputs": [], - "source": [ - "get_ticket_price(\"Berlin\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "4afceded-7178-4c05-8fa6-9f2085e6a344", - "metadata": {}, - "outputs": [], - "source": [ - "# There's a particular dictionary structure that's required to describe our function:\n", - "\n", - "price_function = {\n", - " \"name\": \"get_ticket_price\",\n", - " \"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", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"destination_city\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The city that the customer wants to travel to\",\n", - " },\n", - " },\n", - " \"required\": [\"destination_city\"],\n", - " \"additionalProperties\": False\n", - " }\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b6c73b6b-1f9f-4df3-bd36-f6c8bf45a670", - "metadata": {}, - "outputs": [], - "source": [ - "from datetime import date, datetime\n", - "\n", - "availabilities = {\"london\": \"01/01/2025-31/03/2025\", \"paris\": \"01/01/2025-31/12/2025\", \"tokyo\": \"05/06/2024-04/06/2025\", \"berlin\": \"01/12/2024-30/09/2025\"}\n", - "\n", - "def get_availability_period(destination_city, flight_date):\n", - " \"\"\"Check for dates as LLM answers on this are not reliable.\"\"\"\n", - " print(f\"Tool get_availability_period called for {destination_city}\")\n", - " \n", - " city = destination_city.lower()\n", - " availability = availabilities.get(city)\n", - " \n", - " if availability:\n", - " current_date = date.today()\n", - " if len(flight_date.split(\"-\")) == 2:\n", - " flight_date = f\"{flight_date}-{str(current_date.year)}\"\n", - " flight_date = datetime.strptime(flight_date, \"%d-%m-%Y\").date()\n", - " \n", - " start_str, end_str = availability.split(\"-\")\n", - " start_date = datetime.strptime(start_str, \"%d/%m/%Y\").date()\n", - " end_date = datetime.strptime(end_str, \"%d/%m/%Y\").date()\n", - " \n", - " if start_date < flight_date < end_date:\n", - " return \"Available\"\n", - " else:\n", - " return \"Not available for requested flight dates\"" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "9680afe1-65d8-4094-8a09-6ef37ebdad2b", - "metadata": {}, - "outputs": [], - "source": [ - "\n", - "availability_function = {\n", - " \"name\": \"get_availability_period\",\n", - " \"description\": \"Check if the requested flight dates are within the availability period of the flight schedule to the destination city. Call this whenever you need to know whether there is a flight to the requested city at the provided travel dates of the user, for example when a customer asks 'I want to book a flight to Tokyo on 5 Nov 2025'. \\\n", - " If the user's date does not include a year, the date will refer to a date after the current date. State in your response whether there will be a flight to the destination city at the requested flight date. \\\n", - " For example, an availability of '01/08/2025-31/10/2025' means that there are flights between 01 Aug 25 and 31 Oct 2025. \\\n", - " Parse the user's flight date as string in the format DD-MM-YYYY or DD-MM if no year is given\",\n", - " \"parameters\": {\n", - " \"type\": \"object\",\n", - " \"properties\": {\n", - " \"destination_city\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The city that the customer wants to travel to\",\n", - " },\n", - " \"flight_date\": {\n", - " \"type\": \"string\",\n", - " \"description\": \"The date on which the customer wants to travel\",\n", - " },\n", - " },\n", - " \"required\": [\"destination_city\", \"flight_date\"],\n", - " \"additionalProperties\": False\n", - " }\n", - "}" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "bdca8679-935f-4e7f-97e6-e71a4d4f228c", - "metadata": {}, - "outputs": [], - "source": [ - "# And this is included in a list of tools:\n", - "\n", - "tools = [{\"type\": \"function\", \"function\": price_function}, {\"type\": \"function\", \"function\": availability_function}]" - ] - }, - { - "cell_type": "markdown", - "id": "c3d3554f-b4e3-4ce7-af6f-68faa6dd2340", - "metadata": {}, - "source": [ - "## Getting OpenAI to use our Tool\n", - "\n", - "There's some fiddly stuff to allow OpenAI \"to call our tool\"\n", - "\n", - "What we actually do is give the LLM the opportunity to inform us that it wants us to run the tool.\n", - "\n", - "Here's how the new chat function looks:" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ce9b0744-9c78-408d-b9df-9f6fd9ed78cf", - "metadata": {}, - "outputs": [], - "source": [ - "def chat(message, history):\n", - " messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"role\": \"user\", \"content\": message}]\n", - " response = openai.chat.completions.create(model=MODEL, messages=messages, tools=tools)\n", - "\n", - " if response.choices[0].finish_reason==\"tool_calls\":\n", - " message = response.choices[0].message\n", - " response = handle_tools(message)\n", - " messages.append(message)\n", - " print(f\"Message: \\n {messages}\")\n", - " messages.append(response)\n", - " print(f\"Tool call response: \\n {response}\")\n", - " response = openai.chat.completions.create(model=MODEL, messages=messages)\n", - " \n", - " return response.choices[0].message.content" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "b0992986-ea09-4912-a076-8e5603ee631f", - "metadata": {}, - "outputs": [], - "source": [ - "# We have to write that function handle_tool_call:\n", - "\n", - "def handle_tool_call(message):\n", - " tool_call = message.tool_calls[0]\n", - " arguments = json.loads(tool_call.function.arguments)\n", - " city = arguments.get('destination_city')\n", - " price = get_ticket_price(city)\n", - " response = {\n", - " \"role\": \"tool\",\n", - " \"content\": json.dumps({\"destination_city\": city,\"price\": price}),\n", - " \"tool_call_id\": tool_call.id\n", - " }\n", - " return response, city" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "d772048a-310e-4ff1-8c20-3dd7edb14a19", - "metadata": {}, - "outputs": [], - "source": [ - "# Extended function to handle two tools\n", - "\n", - "def handle_tools(message):\n", - " print(f\"message.tool_calls:\\n {message.tool_calls}\")\n", - " tool_call = message.tool_calls[0] \n", - " if message.tool_calls[0].function.name == \"get_ticket_price\":\n", - " arguments = json.loads(tool_call.function.arguments)\n", - " city = arguments.get('destination_city')\n", - " price = get_ticket_price(city)\n", - " content = json.dumps({\"destination_city\": city,\"price\": price})\n", - " elif message.tool_calls[0].function.name == \"get_availability_period\":\n", - " arguments = json.loads(tool_call.function.arguments)\n", - " city = arguments.get('destination_city')\n", - " flight_date = arguments.get('flight_date')\n", - " availability_dates = get_availability_period(city, flight_date)\n", - " content = json.dumps({\"destination_city\": city,\"availability_dates\": availability_dates})\n", - " \n", - " response = {\n", - " \"role\": \"tool\",\n", - " \"content\": content,\n", - " \"tool_call_id\": tool_call.id\n", - " }\n", - "\n", - " return response" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f4be8a71-b19e-4c2f-80df-f59ff2661f14", - "metadata": {}, - "outputs": [], - "source": [ - "gr.ChatInterface(fn=chat, type=\"messages\").launch()" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}