Merge pull request #655 from bharathchandrareddy/community-contributions-branch
Added my contribution for day 4
This commit is contained in:
Ed Donner
GitHub
249
week2/community-contributions/Day-4-Extension_to_project.ipynb
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249
week2/community-contributions/Day-4-Extension_to_project.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "87c471b2-6a46-47f6-9da9-81d2652dd1b6",
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"metadata": {},
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"source": [
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"# The code given by tutor results in an error when more than 1 city name is entered."
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]
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},
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{
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"cell_type": "markdown",
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"id": "d4c3cdc4-3af9-4b9e-a5d2-80cee3b120be",
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"metadata": {},
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"source": [
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"# This code aims to solve that by giving proper prices for all the given cities"
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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": "292b5152-8932-4341-b2c4-850f16a89e5e",
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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\n"
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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": "92d35c3d-cb2d-4ce8-a6da-3907ce3ce8b8",
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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(override=True)\n",
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"\n",
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"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
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"if openai_api_key:\n",
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" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
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"else:\n",
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" print(\"OpenAI API Key not set\")\n",
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" \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": "54e11038-795c-4451-ad3b-f797abb57728",
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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 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": "e06c982f-59f1-4e33-a1c1-2f56415efbde",
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"metadata": {
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"scrolled": true
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},
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"outputs": [],
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"source": [
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"# This function looks rather simpler than the one from my video, because we're taking advantage of the latest Gradio updates\n",
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"\n",
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"def chat(message, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history + [{\"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, type=\"messages\").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": "d895e0ff-c47f-4b01-b987-4a236c452ba6",
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"metadata": {},
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"outputs": [],
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"source": [
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"# we'll try to impliment methods handle multi inputs in the query\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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" #return_prices = []\n",
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" #for city in destination_city:\n",
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" city = destination_city.lower()\n",
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" #return_prices.append(ticket_prices.get(city,\"unknown\"))\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": "e2387fe7-a7ac-4192-ad46-9ec2a9bc49fa",
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"metadata": {},
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"outputs": [],
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"source": [
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"get_ticket_price(\"paris\")"
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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": "b63e229e-08c9-49b4-b7af-1883736f12cd",
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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\": \"List of cities 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": "0162af66-2ea4-4221-93df-dd22f0ad92f7",
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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}]"
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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": "8b2a5434-63d0-4519-907e-bce21852d48f",
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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}] + history + [{\"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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" print(f\"response ----------------- \\n {response}\")\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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" print(f\"message: -----------------\\n\",message)\n",
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" response, city = handle_tool_call(message)\n",
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" # print('response is --------', response)\n",
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" # print('city is ----------',city)\n",
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" messages.append(message)\n",
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" messages.extend(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": "d7dfa28c-95f8-4d25-8f3c-cd677bb4a4d1",
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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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" responses = []\n",
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" all_cities = []\n",
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" for tool_call in message.tool_calls:\n",
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" \n",
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" arguments = json.loads(tool_call.function.arguments)\n",
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" list_of_city = arguments.get('destination_city')\n",
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" print(f'list of city is ======== {list_of_city}')\n",
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" price = get_ticket_price(list_of_city)\n",
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" print(f'price of ticket to {list_of_city} is {price}')\n",
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" response = {\n",
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" \"role\": \"tool\",\n",
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" \"content\": json.dumps({\"destination_city\": list_of_city,\"price\": price}),\n",
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" \"tool_call_id\": tool_call.id\n",
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" }\n",
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" responses.append(response)\n",
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" all_cities.append(list_of_city)\n",
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" print(f'responses ====== {responses}')\n",
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" print(f'cities ======= {all_cities}')\n",
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" return responses,all_cities"
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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": "15a4152d-6455-4116-bb63-6700eedf0626",
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"metadata": {},
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"outputs": [],
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"source": [
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"gr.ChatInterface(fn=chat, type=\"messages\").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": "c6b0fcfa-38b7-4063-933e-1c8177bf55f1",
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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": "3.11.13"
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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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