Merge pull request #311 from KhadatkarSameer/community-contributions-branch
Added my contributions to community-contributions
This commit is contained in:
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"cells": [
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{
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"cell_type": "markdown",
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"id": "d006b2ea-9dfe-49c7-88a9-a5a0775185fd",
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"metadata": {},
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"source": [
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"# Project to take Audio Input to the Airlines ChatBot"
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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": "a07e7793-b8f5-44f4-aded-5562f633271a",
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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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"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"
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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": "9e2315a3-f80c-4d3f-8073-f5b61d709564",
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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": "40da9de1-b350-49de-8acd-052f40ce5611",
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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": "5537635c-a60d-4983-8018-375c6a912e19",
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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": "c7132dd0-8788-4885-a415-d59664f68fd8",
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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": "7703ca0c-5da4-4641-bcb1-7727d1b2f2bf",
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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": "29ce724b-d998-4c3f-bc40-6b8576c0fd34",
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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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" 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"
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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": "931d0565-b01d-4aa8-bd18-72bafff8fb3b",
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"metadata": {},
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"outputs": [],
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"source": [
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"def artist(city):\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 vibrant pop-art 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": "fa165f7f-9796-4513-b923-2fa0b0b9ddd8",
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"metadata": {},
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"outputs": [],
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"source": [
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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):\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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" audio_stream = BytesIO(response.content)\n",
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" output_filename = \"output_audio.mp3\"\n",
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" with open(output_filename, \"wb\") as f:\n",
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" f.write(audio_stream.read())\n",
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"\n",
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" # Play the generated audio\n",
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" display(Audio(output_filename, autoplay=True))\n",
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"\n",
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"talker(\"Well, hi there\")"
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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": "b512d4ff-0f7b-4148-b161-4ee0ebf14776",
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"metadata": {},
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"outputs": [],
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"source": [
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"def transcribe_audio(audio_file):\n",
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" with open(audio_file, \"rb\") as f:\n",
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" transcript = openai.audio.transcriptions.create(\n",
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" model=\"whisper-1\",\n",
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" file=f\n",
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" )\n",
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" return transcript.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": "c3852570-fb26-4507-a001-f50fd94b7655",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Translate between languages using GPT\n",
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"def translate(text, source_lang, target_lang):\n",
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" translation_prompt = (\n",
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" f\"Translate the following text from {source_lang} to {target_lang}:\\n\\n{text}\"\n",
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" )\n",
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" response = openai.chat.completions.create(\n",
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" model=\"gpt-3.5-turbo\",\n",
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" messages=[{\"role\": \"user\", \"content\": translation_prompt}]\n",
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" )\n",
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" return response.choices[0].message.content.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": "3d75abc2-870e-48af-a8fe-8dd463418b3d",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Chatbot logic: handle both text and audio input\n",
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"def chatbot_dual(history):\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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" image = None\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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" image = artist(city)\n",
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" response = openai.chat.completions.create(model=MODEL, messages=messages)\n",
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" \n",
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" reply = response.choices[0].message.content\n",
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" history += [{\"role\":\"assistant\", \"content\":reply}]\n",
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"\n",
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" # Comment out or delete the next line if you'd rather skip Audio for now..\n",
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" # audio_response = talker(reply)\n",
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" talker(reply)\n",
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" return history, image# Chatbot logic here — replace with real logic"
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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": "512fec09-c2f7-4847-817b-bc20f8b30319",
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"metadata": {},
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"outputs": [],
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"source": [
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"# More involved Gradio code as we're not using the preset Chat interface!\n",
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"# Passing in inbrowser=True in the last line will cause a Gradio window to pop up immediately.\n",
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"\n",
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"with gr.Blocks() as ui:\n",
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" with gr.Row():\n",
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" chatbot = gr.Chatbot(height=500, type=\"messages\")\n",
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" image_output = gr.Image(height=500)\n",
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"\n",
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" with gr.Row():\n",
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" text_input = gr.Textbox(label=\"Chat with our AI Assistant:\")\n",
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" audio_input = gr.Audio(sources=\"microphone\", type=\"filepath\", label=\"Or speak to the assistant\")\n",
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"\n",
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" with gr.Row():\n",
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" # voice_output = gr.Audio(label=\"Bot Voice Reply\", autoplay=True)\n",
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" clear = gr.Button(\"Clear\")\n",
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"\n",
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" def do_entry(message, audio, history):\n",
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" if message:\n",
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" history += [{\"role\":\"user\", \"content\":message}]\n",
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" if audio:\n",
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" history += [{\"role\":\"user\", \"content\":transcribe_audio(audio)}]\n",
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" return \"\", None, history\n",
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"\n",
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" text_input.submit(do_entry, inputs=[text_input, audio_input, chatbot], outputs=[text_input, audio_input, chatbot]).then(chatbot_dual, inputs=chatbot, outputs=[chatbot, image_output]\n",
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" )\n",
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"\n",
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" audio_input.change(do_entry, inputs=[text_input, audio_input, chatbot], outputs=[text_input, audio_input, chatbot]).then(chatbot_dual, inputs=chatbot, outputs=[chatbot, image_output]\n",
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" )\n",
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"\n",
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" clear.click(lambda: None, inputs=None, outputs=chatbot, queue=False)\n",
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"\n",
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"ui.launch(inbrowser=True)"
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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": "3e1294e2-caf0-4f0f-b09e-b0d52c8ca6ec",
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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": "3.11.11"
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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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