Added my contribution to week2 with a great working notebook that contains booking, translation to 6 languages and speech-to-text functionality
This commit is contained in:
Dan Palade
581
week2/community-contributions/week2-exercise-btsp.ipynb
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581
week2/community-contributions/week2-exercise-btsp.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": "ddfa9ae6-69fe-444a-b994-8c4c5970a7ec",
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"metadata": {},
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"source": [
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"# Week 2 Exercise - with Booking, Translation and Speech-To-Text"
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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": "8ccbf174-a724-46a8-9db4-addd249923a0",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Note: The speech-to-text functionality requires FFmpeg to be installed. Go to FFmpeg website and downoad the corresponding OS installer.\n",
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"# !pip install openai-whisper sounddevice scipy numpy"
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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\n",
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"from anthropic import Anthropic\n",
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"import numpy as np\n",
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"import sounddevice as sd\n",
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"import scipy.io.wavfile as wav\n",
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"import tempfile\n",
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"import whisper"
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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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"load_dotenv(override=True)\n",
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"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
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"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
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"# Initialize clients\n",
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"MODEL = \"gpt-4o-mini\"\n",
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"STT_DURATION = 3\n",
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"openai = OpenAI()\n",
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"anthropic = Anthropic(api_key=anthropic_api_key)"
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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 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": "0696acb1-0b05-4dc2-80d5-771be04f1fb2",
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"metadata": {},
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"outputs": [],
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"source": [
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"# get ticket price function\n",
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"\n",
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"ticket_prices = {\"london\": \"$799\", \"paris\": \"$899\", \"tokyo\": \"$1400\", \"berlin\": \"$499\", \"rome\": \"$699\", \"bucharest\": \"$949\", \"moscow\": \"$1199\"}\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\")\n",
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"\n",
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"# create booking function\n",
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"import random\n",
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"\n",
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"def create_booking(destination_city):\n",
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" # Generate a random 6-digit number\n",
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" digits = ''.join([str(random.randint(0, 9)) for _ in range(6)]) \n",
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" booking_number = f\"AI{digits}\"\n",
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" \n",
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" # Print the booking confirmation message\n",
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" print(f\"Booking {booking_number} created for the flight to {destination_city}\")\n",
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" \n",
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" return booking_number"
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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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"# price function structure:\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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"}\n",
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"\n",
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"# booking function structure:\n",
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"booking_function = {\n",
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" \"name\": \"make_booking\",\n",
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" \"description\": \"Make a flight booking for the customer. Call this whenever a customer wants to book a flight to a destination.\",\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": "bdca8679-935f-4e7f-97e6-e71a4d4f228c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# List of tools:\n",
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"\n",
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"tools = [\n",
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" {\"type\": \"function\", \"function\": price_function},\n",
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" {\"type\": \"function\", \"function\": booking_function}\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": "b0992986-ea09-4912-a076-8e5603ee631f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# 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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" function_name = tool_call.function.name\n",
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" arguments = json.loads(tool_call.function.arguments)\n",
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" \n",
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" if function_name == \"get_ticket_price\":\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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" response = {\n",
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" \"role\": \"tool\",\n",
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" \"content\": json.dumps({\"destination_city\": city,\"price\": price}),\n",
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" \"tool_call_id\": tool_call.id\n",
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" }\n",
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" return response, city\n",
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" elif function_name == \"make_booking\":\n",
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" city = arguments.get('destination_city')\n",
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" booking_number = create_booking(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, \"booking_number\": booking_number}),\n",
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" \"tool_call_id\": tool_call.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": "773a9f11-557e-43c9-ad50-56cbec3a0f8f",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Image generation\n",
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"\n",
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"import base64\n",
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"from io import BytesIO\n",
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"from PIL import Image\n",
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"\n",
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"def artist(city, testing_mode=False):\n",
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" if testing_mode:\n",
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" print(f\"Image generation skipped for {city} - in testing mode\")\n",
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" return None\n",
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" \n",
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" image_response = openai.images.generate(\n",
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" model=\"dall-e-3\",\n",
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" prompt=f\"An image representing a vacation in {city}, showing tourist spots and everything unique about {city}, in a realistic style\",\n",
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" size=\"1024x1024\",\n",
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" n=1,\n",
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" response_format=\"b64_json\",\n",
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" )\n",
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" image_base64 = image_response.data[0].b64_json\n",
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" image_data = base64.b64decode(image_base64)\n",
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" return Image.open(BytesIO(image_data))"
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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": "7d1519a8-98ed-4673-ade0-aaba6341f155",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Text to speech \n",
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"\n",
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"import base64\n",
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"from io import BytesIO\n",
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"from PIL import Image\n",
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"from IPython.display import Audio, display\n",
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"\n",
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"def talker(message, testing_mode=False):\n",
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" \"\"\"Generate speech from text and return the path to the audio file for Gradio to play\"\"\"\n",
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" if testing_mode:\n",
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" print(f\"Text-to-speech skipped - in testing mode\")\n",
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" return None\n",
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" \n",
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" try:\n",
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" response = openai.audio.speech.create(\n",
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" model=\"tts-1\",\n",
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" voice=\"onyx\",\n",
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" input=message)\n",
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"\n",
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" # Save to a unique filename based on timestamp to avoid caching issues\n",
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" import time\n",
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" timestamp = int(time.time())\n",
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" output_filename = f\"output_audio_{timestamp}.mp3\"\n",
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" \n",
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" with open(output_filename, \"wb\") as f:\n",
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" f.write(response.content)\n",
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" \n",
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" print(f\"Audio saved to {output_filename}\")\n",
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" return output_filename\n",
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" except Exception as e:\n",
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" print(f\"Error generating speech: {e}\")\n",
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" return None"
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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": "68149e08-d2de-4790-914a-6def79ff5612",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Speech to text function\n",
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"\n",
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"def recorder_and_transcriber(duration=STT_DURATION, samplerate=16000, testing_mode=False):\n",
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" \"\"\"Record audio for the specified duration and transcribe it using Whisper\"\"\"\n",
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" if testing_mode:\n",
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" print(\"Speech-to-text skipped - in testing mode\")\n",
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" return \"This is a test speech input\"\n",
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" \n",
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" print(f\"Recording for {duration} seconds...\")\n",
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" \n",
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" # Record audio using sounddevice\n",
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" recording = sd.rec(int(duration * samplerate), samplerate=samplerate, channels=1, dtype='float32')\n",
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" sd.wait() # Wait until recording is finished\n",
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" \n",
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" # Save the recording to a temporary WAV file\n",
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" with tempfile.NamedTemporaryFile(suffix=\".wav\", delete=False) as temp_audio:\n",
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" temp_filename = temp_audio.name\n",
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" wav.write(temp_filename, samplerate, recording)\n",
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" \n",
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" # Load Whisper model and transcribe\n",
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" model = whisper.load_model(\"base\") # You can use \"tiny\", \"base\", \"small\", \"medium\", or \"large\"\n",
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" result = model.transcribe(temp_filename)\n",
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" \n",
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" # Clean up the temporary file\n",
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" import os\n",
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" os.unlink(temp_filename)\n",
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" \n",
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" return result[\"text\"].strip()"
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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": "bf1d5600-8df8-4cc2-8bf5-b0b33818b385",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import glob\n",
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"\n",
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"def cleanup_audio_files():\n",
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" \"\"\"Delete all MP3 files in the current directory that match our output pattern\"\"\"\n",
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" \n",
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" # Get all mp3 files that match our naming pattern\n",
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" mp3_files = glob.glob(\"output_audio_*.mp3\")\n",
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" \n",
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" # Delete each file\n",
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" count = 0\n",
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" for file in mp3_files:\n",
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" try:\n",
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" os.remove(file)\n",
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" count += 1\n",
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" except Exception as e:\n",
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" print(f\"Error deleting {file}: {e}\")\n",
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" \n",
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" print(f\"Cleaned up {count} audio files\")\n",
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" return None"
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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": "44a6f8e0-c111-4e40-a5ae-68dd0aa9f65d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Translation function\n",
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"\n",
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"def translate_text(text, target_language):\n",
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" if not text or not target_language:\n",
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" return \"\"\n",
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" \n",
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" # Map the language dropdown values to language names for Claude\n",
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" language_map = {\n",
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" \"French\": \"French\",\n",
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" \"Spanish\": \"Spanish\",\n",
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" \"German\": \"German\",\n",
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" \"Italian\": \"Italian\",\n",
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" \"Russian\": \"Russian\",\n",
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" \"Romanian\": \"Romanian\"\n",
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" }\n",
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" \n",
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" full_language_name = language_map.get(target_language, \"French\")\n",
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" \n",
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" try:\n",
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" response = anthropic.messages.create(\n",
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" model=\"claude-3-haiku-20240307\",\n",
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" max_tokens=1024,\n",
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" messages=[\n",
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" {\n",
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" \"role\": \"user\",\n",
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" \"content\": f\"Translate the following text to {full_language_name}. Provide only the translation, no explanations: \\n\\n{text}\"\n",
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" }\n",
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" ]\n",
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" )\n",
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" return response.content[0].text\n",
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" except Exception as e:\n",
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||||
" print(f\"Translation error: {e}\")\n",
|
||||
" return f\"[Translation failed: {str(e)}]\""
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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": "ba820c95-02f5-499e-8f3c-8727ee0a6c0c",
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"metadata": {},
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"outputs": [],
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"source": [
|
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"def chat(history, image, testing_mode=False):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history\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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" \n",
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||||
" # Only generate image if not in testing mode\n",
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||||
" if not testing_mode and image is None:\n",
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" image = artist(city, testing_mode)\n",
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" \n",
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||||
" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
|
||||
" \n",
|
||||
" reply = response.choices[0].message.content\n",
|
||||
" history += [{\"role\":\"assistant\", \"content\":reply}] \n",
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||||
"\n",
|
||||
" # Return the reply directly - we'll handle TTS separately\n",
|
||||
" return history, image, reply"
|
||||
]
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||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "a3cc58f3-d0fc-47d1-b9cf-e5bf4c5edbdc",
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||||
"metadata": {},
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||||
"outputs": [],
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||||
"source": [
|
||||
"# Function to translate conversation history\n",
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||||
"def translate_history(history, target_language):\n",
|
||||
" if not history or not target_language:\n",
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" return []\n",
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||||
" \n",
|
||||
" translated_history = []\n",
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||||
" \n",
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||||
" for msg in history:\n",
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||||
" role = msg[\"role\"]\n",
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||||
" content = msg[\"content\"]\n",
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||||
" \n",
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||||
" translated_content = translate_text(content, target_language)\n",
|
||||
" translated_history.append({\"role\": role, \"content\": translated_content})\n",
|
||||
" \n",
|
||||
" return translated_history"
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||||
]
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||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "f38d0d27-33bf-4992-a2e5-5dbed973cde7",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# Update the Gradio interface to handle audio output properly\n",
|
||||
"def update_gradio_interface():\n",
|
||||
" with gr.Blocks() as ui:\n",
|
||||
" # Store chat history and audio output in state\n",
|
||||
" state = gr.State([])\n",
|
||||
" audio_state = gr.State(None)\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" testing_checkbox = gr.Checkbox(label=\"Testing\", info=\"Turn off multimedia features when checked\", value=False)\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" with gr.Column(scale=2):\n",
|
||||
" # Main panel with original chat and image\n",
|
||||
" with gr.Row():\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" with gr.Row():\n",
|
||||
" chatbot = gr.Chatbot(height=300, type=\"messages\")\n",
|
||||
" with gr.Row():\n",
|
||||
" language_dropdown = gr.Dropdown(\n",
|
||||
" choices=[\"French\", \"Spanish\", \"German\", \"Italian\", \"Russian\", \"Romanian\"],\n",
|
||||
" value=\"French\",\n",
|
||||
" label=\"Translation to\"\n",
|
||||
" )\n",
|
||||
" with gr.Row():\n",
|
||||
" translation_output = gr.Chatbot(height=200, type=\"messages\", label=\"Translated chat\")\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" with gr.Row():\n",
|
||||
" image_output = gr.Image(height=620)\n",
|
||||
" with gr.Row():\n",
|
||||
" audio_output = gr.Audio(label=\"Assistant's Voice\", visible=False, autoplay=True, type=\"filepath\")\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" entry = gr.Textbox(label=\"Chat with our AI Assistant:\")\n",
|
||||
" \n",
|
||||
" with gr.Row():\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" with gr.Row():\n",
|
||||
" md = gr.Markdown()\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" speak_button = gr.Button(value=\"🎤 Speak Command\", variant=\"primary\")\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" with gr.Row():\n",
|
||||
" md = gr.Markdown()\n",
|
||||
" with gr.Column(scale=1): \n",
|
||||
" with gr.Row():\n",
|
||||
" clear = gr.Button(value=\"Clear\", variant=\"secondary\")\n",
|
||||
" with gr.Column(scale=1):\n",
|
||||
" with gr.Row():\n",
|
||||
" md = gr.Markdown()\n",
|
||||
"\n",
|
||||
" # Function to handle speech input\n",
|
||||
" def do_speech_input(testing_mode):\n",
|
||||
" # Record and transcribe speech\n",
|
||||
" speech_text = recorder_and_transcriber(duration=STT_DURATION, testing_mode=testing_mode)\n",
|
||||
" return speech_text\n",
|
||||
" \n",
|
||||
" # Function to handle user input\n",
|
||||
" def do_entry(message, history, testing_mode):\n",
|
||||
" history += [{\"role\":\"user\", \"content\":message}]\n",
|
||||
" return \"\", history\n",
|
||||
" \n",
|
||||
" # Function to handle translation updates\n",
|
||||
" def do_translation(history, language):\n",
|
||||
" translated = translate_history(history, language)\n",
|
||||
" return translated\n",
|
||||
" \n",
|
||||
" # Function to handle text-to-speech\n",
|
||||
" def do_tts(reply, testing_mode):\n",
|
||||
" if not reply or testing_mode:\n",
|
||||
" return None\n",
|
||||
" \n",
|
||||
" audio_file = talker(reply, testing_mode)\n",
|
||||
" return audio_file\n",
|
||||
" \n",
|
||||
" # Handle user message submission\n",
|
||||
" entry.submit(do_entry, inputs=[entry, chatbot, testing_checkbox], outputs=[entry, chatbot]).then(\n",
|
||||
" chat, inputs=[chatbot, image_output, testing_checkbox], outputs=[chatbot, image_output, audio_state]\n",
|
||||
" ).then(\n",
|
||||
" do_tts, inputs=[audio_state, testing_checkbox], outputs=[audio_output]\n",
|
||||
" ).then(\n",
|
||||
" do_translation, inputs=[chatbot, language_dropdown], outputs=[translation_output]\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" # Add speech button handling\n",
|
||||
" speak_button.click(\n",
|
||||
" do_speech_input, \n",
|
||||
" inputs=[testing_checkbox], \n",
|
||||
" outputs=[entry]\n",
|
||||
" ).then(\n",
|
||||
" do_entry, \n",
|
||||
" inputs=[entry, chatbot, testing_checkbox], \n",
|
||||
" outputs=[entry, chatbot]\n",
|
||||
" ).then(\n",
|
||||
" chat, \n",
|
||||
" inputs=[chatbot, image_output, testing_checkbox], \n",
|
||||
" outputs=[chatbot, image_output, audio_state]\n",
|
||||
" ).then(\n",
|
||||
" do_tts, inputs=[audio_state, testing_checkbox], outputs=[audio_output]\n",
|
||||
" ).then(\n",
|
||||
" do_translation, \n",
|
||||
" inputs=[chatbot, language_dropdown], \n",
|
||||
" outputs=[translation_output]\n",
|
||||
" )\n",
|
||||
" \n",
|
||||
" # Update translation when language is changed\n",
|
||||
" language_dropdown.change(do_translation, inputs=[chatbot, language_dropdown], outputs=[translation_output])\n",
|
||||
" \n",
|
||||
" # Handle clear button\n",
|
||||
" def clear_all():\n",
|
||||
" # Clean up audio files\n",
|
||||
" cleanup_audio_files()\n",
|
||||
" # Return None for all outputs to clear the UI\n",
|
||||
" return None, None, None, None\n",
|
||||
" \n",
|
||||
" clear.click(clear_all, inputs=None, outputs=[chatbot, translation_output, image_output, audio_output], queue=False)\n",
|
||||
"\n",
|
||||
" return ui\n",
|
||||
"\n",
|
||||
"# Replace the original ui code with this:\n",
|
||||
"ui = update_gradio_interface()\n",
|
||||
"ui.launch(inbrowser=True)"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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": "3.11.12"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
Reference in New Issue
Block a user