Talking_with_AI_using_Whisper,_GPT_3,_and_Eleven_Labs.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/sungkim11/AI_Playground/blob/main/Talking_with_AI_using_Whisper%2C_GPT_3%2C_and_Eleven_Labs.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#Talking with AI using OpenAI's Whisper, OpenAI's GPT-3, and ElevenLab's Speech Synthesis"
      ],
      "metadata": {
        "id": "SP-1vIxcPMaN"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "This is my endeavor to combine three technologies to converse with AI:\n",
        "\n",
        "- OpenAI Whisper: an automatic speech recognition (ASR) system (https://openai.com/blog/whisper/)\n",
        "- OpenAI GPT-3: capable of performing various natural language tasks\n",
        "- ElevenLab’s Speech Synthesis: uses context understanding to produce highly realistic human speech."
      ],
      "metadata": {
        "id": "YxuZ69jNPqfk"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "##1. Prerequisites"
      ],
      "metadata": {
        "id": "sCbsZRlCROPU"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The following are prerequisites for this tutorial:\n",
        "\n",
        "- Python Package: ffmpeg\n",
        "- Python Package: openai-whisper\n",
        "- Python Package: openai"
      ],
      "metadata": {
        "id": "_Wp_bj1_RQ4B"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "###1.1. Python Packages"
      ],
      "metadata": {
        "id": "ig2pxyjrRf06"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####1.1.1. Install Python Packages"
      ],
      "metadata": {
        "id": "dwZ00kizRmO7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%writefile requirements.txt\n",
        "ffmpeg-python\n",
        "openai-whisper\n",
        "openai"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lYYF9gITmWoZ",
        "outputId": "f7d0912e-92bf-4b60-adf5-f3123645c8d9"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Overwriting requirements.txt\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xuKJ4wBU6gxx",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "5a68abd9-9dd8-44aa-9689-5ce00dfe2f43"
      },
      "source": [
        "%pip install -r requirements.txt"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: ffmpeg-python in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 1)) (0.2.0)\n",
            "Requirement already satisfied: openai-whisper in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 2)) (20230124)\n",
            "Requirement already satisfied: openai in /usr/local/lib/python3.8/dist-packages (from -r requirements.txt (line 3)) (0.26.4)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.8/dist-packages (from ffmpeg-python->-r requirements.txt (line 1)) (0.16.0)\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.8/dist-packages (from openai-whisper->-r requirements.txt (line 2)) (4.64.1)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from openai-whisper->-r requirements.txt (line 2)) (1.21.6)\n",
            "Requirement already satisfied: torch in /usr/local/lib/python3.8/dist-packages (from openai-whisper->-r requirements.txt (line 2)) (1.13.1+cu116)\n",
            "Requirement already satisfied: transformers>=4.19.0 in /usr/local/lib/python3.8/dist-packages (from openai-whisper->-r requirements.txt (line 2)) (4.26.0)\n",
            "Requirement already satisfied: more-itertools in /usr/local/lib/python3.8/dist-packages (from openai-whisper->-r requirements.txt (line 2)) (9.0.0)\n",
            "Requirement already satisfied: requests>=2.20 in /usr/local/lib/python3.8/dist-packages (from openai->-r requirements.txt (line 3)) (2.25.1)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.8/dist-packages (from openai->-r requirements.txt (line 3)) (3.8.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20->openai->-r requirements.txt (line 3)) (2.10)\n",
            "Requirement already satisfied: chardet<5,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20->openai->-r requirements.txt (line 3)) (4.0.0)\n",
            "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20->openai->-r requirements.txt (line 3)) (1.24.3)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests>=2.20->openai->-r requirements.txt (line 3)) (2022.12.7)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (21.3)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (0.12.0)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (6.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (3.9.0)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (2022.6.2)\n",
            "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.8/dist-packages (from transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (0.13.2)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (4.0.2)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (1.3.1)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (6.0.4)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (22.2.0)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (1.8.2)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (1.3.3)\n",
            "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /usr/local/lib/python3.8/dist-packages (from aiohttp->openai->-r requirements.txt (line 3)) (2.1.1)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch->openai-whisper->-r requirements.txt (line 2)) (4.4.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.0->transformers>=4.19.0->openai-whisper->-r requirements.txt (line 2)) (3.0.9)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "##2. Code"
      ],
      "metadata": {
        "id": "491rx6NKRsno"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9ol3xVNL6gy3"
      },
      "source": [
        "###2.1. Record audio from your microphone"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "This section's code to record from microphone was copied from [https://ricardodeazambuja.com/](https://colab.research.google.com/gist/ricardodeazambuja/03ac98c31e87caf284f7b06286ebf7fd/microphone-to-numpy-array-from-your-browser-in-colab.ipynb). Please note that you will need provide a permission to your browser to record the audio, using your computer's microphone."
      ],
      "metadata": {
        "id": "ACAwglBIlGCz"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.1.1. Import Python Packages"
      ],
      "metadata": {
        "id": "wlWtpFexSYFi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from IPython.display import HTML, Audio, display\n",
        "from google.colab.output import eval_js\n",
        "from base64 import b64decode\n",
        "import numpy as np\n",
        "import scipy\n",
        "from scipy.io.wavfile import read as wav_read\n",
        "import io\n",
        "import ffmpeg\n",
        "import whisper\n",
        "import openai\n",
        "import platform\n",
        "import os\n",
        "import requests\n",
        "\n",
        "print('Python: ', platform.python_version())\n",
        "print(\"google.colab: \", google.colab.__version__)\n",
        "print(\"numpy: \", np.__version__)\n",
        "print(\"scipy: \", scipy.__version__)\n",
        "print(\"whisper: \", whisper.__version__)\n",
        "print(\"requests: \", requests.__version__)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "O6v6h_JbfaVX",
        "outputId": "cf88f0ab-56eb-41fa-8e53-592aca83311b"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Python:  3.8.10\n",
            "google.colab:  0.0.1a2\n",
            "numpy:  1.21.6\n",
            "scipy:  1.7.3\n",
            "whisper:  20230124\n",
            "requests:  2.25.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.1.2. Javascript code for recording audio in your browser."
      ],
      "metadata": {
        "id": "w3qLtRapSdS_"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RtMcXr3o6gxN"
      },
      "source": [
        "AUDIO_HTML = \"\"\"\n",
        "<script>\n",
        "var my_div = document.createElement(\"DIV\");\n",
        "var my_p = document.createElement(\"P\");\n",
        "var my_btn = document.createElement(\"BUTTON\");\n",
        "var t = document.createTextNode(\"Press to start recording\");\n",
        "\n",
        "my_btn.appendChild(t);\n",
        "//my_p.appendChild(my_btn);\n",
        "my_div.appendChild(my_btn);\n",
        "document.body.appendChild(my_div);\n",
        "\n",
        "var base64data = 0;\n",
        "var reader;\n",
        "var recorder, gumStream;\n",
        "var recordButton = my_btn;\n",
        "\n",
        "var handleSuccess = function(stream) {\n",
        "  gumStream = stream;\n",
        "  var options = {\n",
        "    //bitsPerSecond: 8000, //chrome seems to ignore, always 48k\n",
        "    mimeType : 'audio/webm;codecs=opus'\n",
        "    //mimeType : 'audio/webm;codecs=pcm'\n",
        "  };            \n",
        "  //recorder = new MediaRecorder(stream, options);\n",
        "  recorder = new MediaRecorder(stream);\n",
        "  recorder.ondataavailable = function(e) {            \n",
        "    var url = URL.createObjectURL(e.data);\n",
        "    var preview = document.createElement('audio');\n",
        "    preview.controls = true;\n",
        "    preview.src = url;\n",
        "    document.body.appendChild(preview);\n",
        "\n",
        "    reader = new FileReader();\n",
        "    reader.readAsDataURL(e.data); \n",
        "    reader.onloadend = function() {\n",
        "      base64data = reader.result;\n",
        "      //console.log(\"Inside FileReader:\" + base64data);\n",
        "    }\n",
        "  };\n",
        "  recorder.start();\n",
        "  };\n",
        "\n",
        "recordButton.innerText = \"Recording... press to stop\";\n",
        "\n",
        "navigator.mediaDevices.getUserMedia({audio: true}).then(handleSuccess);\n",
        "\n",
        "\n",
        "function toggleRecording() {\n",
        "  if (recorder && recorder.state == \"recording\") {\n",
        "      recorder.stop();\n",
        "      gumStream.getAudioTracks()[0].stop();\n",
        "      recordButton.innerText = \"Saving the recording... pease wait!\"\n",
        "  }\n",
        "}\n",
        "\n",
        "// https://stackoverflow.com/a/951057\n",
        "function sleep(ms) {\n",
        "  return new Promise(resolve => setTimeout(resolve, ms));\n",
        "}\n",
        "\n",
        "var data = new Promise(resolve=>{\n",
        "//recordButton.addEventListener(\"click\", toggleRecording);\n",
        "recordButton.onclick = ()=>{\n",
        "toggleRecording()\n",
        "\n",
        "sleep(2000).then(() => {\n",
        "  // wait 2000ms for the data to be available...\n",
        "  // ideally this should use something like await...\n",
        "  //console.log(\"Inside data:\" + base64data)\n",
        "  resolve(base64data.toString())\n",
        "\n",
        "});\n",
        "\n",
        "}\n",
        "});\n",
        "      \n",
        "</script>\n",
        "\"\"\""
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.1.2. Python function for recording audio in your browser."
      ],
      "metadata": {
        "id": "5ej8f1HLSstC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "def get_audio():\n",
        "  display(HTML(AUDIO_HTML))\n",
        "  data = eval_js(\"data\")\n",
        "  binary = b64decode(data.split(',')[1])\n",
        "  \n",
        "  process = (ffmpeg\n",
        "    .input('pipe:0')\n",
        "    .output('pipe:1', format='wav')\n",
        "    .run_async(pipe_stdin=True, pipe_stdout=True, pipe_stderr=True, quiet=True, overwrite_output=True)\n",
        "  )\n",
        "  output, err = process.communicate(input=binary)\n",
        "  \n",
        "  riff_chunk_size = len(output) - 8\n",
        "  # Break up the chunk size into four bytes, held in b.\n",
        "  q = riff_chunk_size\n",
        "  b = []\n",
        "  for i in range(4):\n",
        "      q, r = divmod(q, 256)\n",
        "      b.append(r)\n",
        "\n",
        "  # Replace bytes 4:8 in proc.stdout with the actual size of the RIFF chunk.\n",
        "  riff = output[:4] + bytes(b) + output[8:]\n",
        "\n",
        "  sr, audio = wav_read(io.BytesIO(riff))\n",
        "\n",
        "  return audio, sr"
      ],
      "metadata": {
        "id": "ztacfrCQhkyu"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.1.3. Record audio on your browser. The audio file will be saved as “prompt_request.wav.”"
      ],
      "metadata": {
        "id": "gZCl2kmjS5JJ"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "57xW3GSb6gv0",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 96
        },
        "outputId": "bce651e8-73d9-4f75-a90e-1795d2d8eaec"
      },
      "source": [
        "audio, sr = get_audio()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "<script>\n",
              "var my_div = document.createElement(\"DIV\");\n",
              "var my_p = document.createElement(\"P\");\n",
              "var my_btn = document.createElement(\"BUTTON\");\n",
              "var t = document.createTextNode(\"Press to start recording\");\n",
              "\n",
              "my_btn.appendChild(t);\n",
              "//my_p.appendChild(my_btn);\n",
              "my_div.appendChild(my_btn);\n",
              "document.body.appendChild(my_div);\n",
              "\n",
              "var base64data = 0;\n",
              "var reader;\n",
              "var recorder, gumStream;\n",
              "var recordButton = my_btn;\n",
              "\n",
              "var handleSuccess = function(stream) {\n",
              "  gumStream = stream;\n",
              "  var options = {\n",
              "    //bitsPerSecond: 8000, //chrome seems to ignore, always 48k\n",
              "    mimeType : 'audio/webm;codecs=opus'\n",
              "    //mimeType : 'audio/webm;codecs=pcm'\n",
              "  };            \n",
              "  //recorder = new MediaRecorder(stream, options);\n",
              "  recorder = new MediaRecorder(stream);\n",
              "  recorder.ondataavailable = function(e) {            \n",
              "    var url = URL.createObjectURL(e.data);\n",
              "    var preview = document.createElement('audio');\n",
              "    preview.controls = true;\n",
              "    preview.src = url;\n",
              "    document.body.appendChild(preview);\n",
              "\n",
              "    reader = new FileReader();\n",
              "    reader.readAsDataURL(e.data); \n",
              "    reader.onloadend = function() {\n",
              "      base64data = reader.result;\n",
              "      //console.log(\"Inside FileReader:\" + base64data);\n",
              "    }\n",
              "  };\n",
              "  recorder.start();\n",
              "  };\n",
              "\n",
              "recordButton.innerText = \"Recording... press to stop\";\n",
              "\n",
              "navigator.mediaDevices.getUserMedia({audio: true}).then(handleSuccess);\n",
              "\n",
              "\n",
              "function toggleRecording() {\n",
              "  if (recorder && recorder.state == \"recording\") {\n",
              "      recorder.stop();\n",
              "      gumStream.getAudioTracks()[0].stop();\n",
              "      recordButton.innerText = \"Saving the recording... pease wait!\"\n",
              "  }\n",
              "}\n",
              "\n",
              "// https://stackoverflow.com/a/951057\n",
              "function sleep(ms) {\n",
              "  return new Promise(resolve => setTimeout(resolve, ms));\n",
              "}\n",
              "\n",
              "var data = new Promise(resolve=>{\n",
              "//recordButton.addEventListener(\"click\", toggleRecording);\n",
              "recordButton.onclick = ()=>{\n",
              "toggleRecording()\n",
              "\n",
              "sleep(2000).then(() => {\n",
              "  // wait 2000ms for the data to be available...\n",
              "  // ideally this should use something like await...\n",
              "  //console.log(\"Inside data:\" + base64data)\n",
              "  resolve(base64data.toString())\n",
              "\n",
              "});\n",
              "\n",
              "}\n",
              "});\n",
              "      \n",
              "</script>\n"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-YilAhGr6gtZ"
      },
      "source": [
        "scipy.io.wavfile.write('prompt_request.wav', sr, audio)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "euCPDeHHhgEc"
      },
      "source": [
        "###2.2. Transcribe the audio recording to text using OpenAI’s Whisper."
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Please note that there are five available models. For more information, please refer to https://github.com/openai/whisper."
      ],
      "metadata": {
        "id": "Iv5jMXm_ULjK"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "There are five model sizes, four with English-only versions, offering speed and accuracy tradeoffs. Below are the names of the available models and their approximate memory requirements and relative speed.\n",
        "- tiny\n",
        "- base\n",
        "- small\n",
        "- medium\n",
        "- large"
      ],
      "metadata": {
        "id": "Z6BKcXJNTSMo"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "For this exercise, I used the medium English-only model, which will be automatically downloaded to your computer upon first use."
      ],
      "metadata": {
        "id": "gnZlabFkUWWn"
      }
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wEJ5-9218LK9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2b9f3918-17ef-4a49-e188-8cae14750740"
      },
      "source": [
        "model = whisper.load_model(\"medium.en\")\n",
        "result = model.transcribe(\"prompt_request.wav\")\n",
        "\n",
        "prompt_request = result[\"text\"]\n",
        "print(prompt_request)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " Tell me about Philadelphia campaign 1977 in less than 200 characters.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###2.3. Send recording text as a prompt for OpenAI's GPT-3 API"
      ],
      "metadata": {
        "id": "NrHxBEAnobVZ"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "To talk with AI, the voice recording is transcribed to text and sent as a prompt to illicit response from OpenAI's GPT-3."
      ],
      "metadata": {
        "id": "6PAnANBvU65N"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.3.1. Set OpenAI API Key"
      ],
      "metadata": {
        "id": "L2kJjIDLVfhp"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Please note that OpenAI's API service is not free, unlike ChatGPT demo. You will need to sign up for a service with them to get an API key, which requires payment information."
      ],
      "metadata": {
        "id": "wUv1Dbv2VlDn"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Set an environment variable called “OPEN_API_KEY” and assign a secret API key from OpenAI (https://beta.openai.com/account/api-keys)."
      ],
      "metadata": {
        "id": "1tkDJKEqObp6"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "os.environ[\"OPENAI_API_KEY\"] = OPENAI_API_KEY"
      ],
      "metadata": {
        "id": "JDmOi6slo-v0"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "openai.api_key = os.getenv(\"OPENAI_API_KEY\")"
      ],
      "metadata": {
        "id": "gYRaQ5tbx0Jv"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.3.2. Send a request to OpenAI's GPT-3 API."
      ],
      "metadata": {
        "id": "MFUe8yAMV0y3"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Make an API request to OpenAI where the prompt instruction is stored in the “prompt_request” variable."
      ],
      "metadata": {
        "id": "cQ9R7SdBOhNt"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "response = openai.Completion.create(\n",
        "        model=\"text-davinci-003\",\n",
        "        prompt=prompt_request,\n",
        "        temperature=.5,\n",
        "        max_tokens=100,\n",
        "        top_p=1,\n",
        "        frequency_penalty=0,\n",
        "        presence_penalty=0\n",
        "    )"
      ],
      "metadata": {
        "id": "O5BRfEArpSuD"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.3.3. Print a response from OpenAI's GPT-3 API."
      ],
      "metadata": {
        "id": "U9yUAHVvWA8T"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Assign OpenAI’s response to the “prompt_response” variable and print the response from GPT-3’s API."
      ],
      "metadata": {
        "id": "Ggq2nculOo2O"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prompt_response = response[\"choices\"][0][\"text\"]\n",
        "print(prompt_response)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pwTeNtNkpy7u",
        "outputId": "d3385dbc-800f-4eee-dab0-fef15a5623ca"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "\n",
            "The 1977 Philadelphia mayoral election saw Frank Rizzo win a second term, defeating challenger Ed Rendell by a narrow margin. The campaign was marked by racial tensions and accusations of police brutality.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "###2.4. Convert text to speech using ElevenLabs’ API"
      ],
      "metadata": {
        "id": "kgxaI3bowfJb"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The ElevenLab’s API uses a curl request in this format, which requires obtaining an API key through sign-up with their service. ElevenLabs API Documentation provides a tool to generate a curl request template."
      ],
      "metadata": {
        "id": "sVGMOv8rBnna"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "The curl request template is provided here."
      ],
      "metadata": {
        "id": "6d6l_j_tO2jG"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "curl -X POST https://api.elevenlabs.io/v1/text-to-speech/pNInz6obpgDQGcFmaJgB \\\n",
        "  -H 'accept: audio/mpeg' \\\n",
        "  -H 'xi-api-key: ELEVENLABS_API_KEY \\\n",
        "  -H 'Content-Type: application/json' \\\n",
        "  -d '{\"text\":\"The 1977 Philadelphia mayoral election saw Frank Rizzo win a second term, defeating challenger Ed Rendell by a narrow margin. The campaign was marked by racial tensions and accusations of police brutality.\"}' \\\n",
        "  --output prompt_response.mp3"
      ],
      "metadata": {
        "id": "qZwNWgvzAQ-_"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.4.1. Set ElevenLabs's API Key"
      ],
      "metadata": {
        "id": "RIom3VRVWzB8"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Assign your ElevenLab API key to the ‘ELEVENLABS_API_KEY’ variable, then use the ‘requests’ package to make the curl request."
      ],
      "metadata": {
        "id": "K6uMhVamO7Iy"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "ELEVENLABS_API_KEY = ELEVENLABS_API_KEY"
      ],
      "metadata": {
        "id": "tytgZr8oy0SA"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.4.2. Send a request using curl."
      ],
      "metadata": {
        "id": "bAagroZ5W5L3"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "headers = {\n",
        "    'accept': 'audio/mpeg',\n",
        "    'xi-api-key': ELEVENLABS_API_KEY,\n",
        "    'Content-Type': 'application/json',\n",
        "}\n",
        "\n",
        "json_data = {\n",
        "    'text': prompt_response,\n",
        "}\n",
        "\n",
        "response = requests.post('https://api.elevenlabs.io/v1/text-to-speech/pNInz6obpgDQGcFmaJgB', headers=headers, json=json_data)\n",
        "\n",
        "with open('prompt_response.mp3', 'wb') as f:\n",
        "    f.write(response.content)"
      ],
      "metadata": {
        "id": "uqLG4pYZ-kud"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "####2.4.3. Play the speech file, saved in .mp3 format."
      ],
      "metadata": {
        "id": "fxZWY5pZXBQ4"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "prompt_response_speech = \"prompt_response.mp3\"\n",
        "display(Audio(prompt_response_speech, autoplay=True))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 75
        },
        "id": "w2hEVFefucqW",
        "outputId": "1defa93e-e1c5-465a-d239-66f32ee00b6e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ],
            "text/html": [
              "\n",
              "                <audio  controls=\"controls\" autoplay=\"autoplay\">\n",
              "                    <source 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\" 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}