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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "# prompt: install gradio\n",
        "\n",
        "!pip install gradio\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dB_WGDMH_Jg7",
        "outputId": "14709167-3e69-4e92-b2b6-e5ed2b6b41eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting gradio\n",
            "  Downloading gradio-4.27.0-py3-none-any.whl (17.1 MB)\n",
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            "\u001b[?25hCollecting aiofiles<24.0,>=22.0 (from gradio)\n",
            "  Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n",
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            "  Downloading fastapi-0.110.2-py3-none-any.whl (91 kB)\n",
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            "\u001b[?25hCollecting ffmpy (from gradio)\n",
            "  Downloading ffmpy-0.3.2.tar.gz (5.5 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Collecting gradio-client==0.15.1 (from gradio)\n",
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            "\u001b[?25hCollecting httpx>=0.24.1 (from gradio)\n",
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            "Collecting orjson~=3.0 (from gradio)\n",
            "  Downloading orjson-3.10.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (141 kB)\n",
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            "\u001b[?25hCollecting semantic-version~=2.0 (from gradio)\n",
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            "Collecting uvicorn>=0.14.0 (from gradio)\n",
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            "Collecting websockets<12.0,>=10.0 (from gradio-client==0.15.1->gradio)\n",
            "  Downloading websockets-11.0.3-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (129 kB)\n",
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            "Collecting h11<0.15,>=0.13 (from httpcore==1.*->httpx>=0.24.1->gradio)\n",
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            "Requirement already satisfied: click>=8.0.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0,>=0.12->gradio) (8.1.7)\n",
            "Collecting shellingham>=1.3.0 (from typer<1.0,>=0.12->gradio)\n",
            "  Downloading shellingham-1.5.4-py2.py3-none-any.whl (9.8 kB)\n",
            "Requirement already satisfied: rich>=10.11.0 in /usr/local/lib/python3.10/dist-packages (from typer<1.0,>=0.12->gradio) (13.7.1)\n",
            "Collecting starlette<0.38.0,>=0.37.2 (from fastapi->gradio)\n",
            "  Downloading starlette-0.37.2-py3-none-any.whl (71 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m71.9/71.9 kB\u001b[0m \u001b[31m8.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6.0,>=4.2.0->gradio) (23.2.0)\n",
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            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich>=10.11.0->typer<1.0,>=0.12->gradio) (2.16.1)\n",
            "Requirement already satisfied: exceptiongroup in /usr/local/lib/python3.10/dist-packages (from anyio->httpx>=0.24.1->gradio) (1.2.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub>=0.19.3->gradio) (3.3.2)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich>=10.11.0->typer<1.0,>=0.12->gradio) (0.1.2)\n",
            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=8b3d6c749336f5072c89cbdbeb30524b3b95af140100aec2253a3cecc540a44e\n",
            "  Stored in directory: /root/.cache/pip/wheels/bd/65/9a/671fc6dcde07d4418df0c592f8df512b26d7a0029c2a23dd81\n",
            "Successfully built ffmpy\n",
            "Installing collected packages: pydub, ffmpy, websockets, tomlkit, shellingham, semantic-version, ruff, python-multipart, orjson, h11, aiofiles, uvicorn, starlette, httpcore, typer, httpx, fastapi, gradio-client, gradio\n",
            "  Attempting uninstall: typer\n",
            "    Found existing installation: typer 0.9.4\n",
            "    Uninstalling typer-0.9.4:\n",
            "      Successfully uninstalled typer-0.9.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n",
            "weasel 0.3.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed aiofiles-23.2.1 fastapi-0.110.2 ffmpy-0.3.2 gradio-4.27.0 gradio-client-0.15.1 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 orjson-3.10.1 pydub-0.25.1 python-multipart-0.0.9 ruff-0.4.1 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.37.2 tomlkit-0.12.0 typer-0.12.3 uvicorn-0.29.0 websockets-11.0.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# prompt: install transformers\n",
        "\n",
        "!pip install transformers\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IPgLOAbX_USh",
        "outputId": "2123a2fa-68b4-4272-c4d4-6a56611442ac"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: transformers in /usr/local/lib/python3.10/dist-packages (4.38.2)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers) (3.13.4)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.19.3 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.20.3)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (1.25.2)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers) (24.0)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (6.0.1)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from transformers) (2023.12.25)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from transformers) (2.31.0)\n",
            "Requirement already satisfied: tokenizers<0.19,>=0.14 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.15.2)\n",
            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers) (0.4.3)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.10/dist-packages (from transformers) (4.66.2)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (2023.6.0)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.19.3->transformers) (4.11.0)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->transformers) (2024.2.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# prompt: install numpy\n",
        "\n",
        "!pip install numpy\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7_KD_6a8_egG",
        "outputId": "eb9b250b-91fb-4365-ded8-a97326d18196"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (1.25.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "a_OP3PJZ_Hfm",
        "outputId": "2b07f1bc-2e3b-4598-aed9-3ce652df5132",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/config.json\n",
            "Model config WhisperConfig {\n",
            "  \"_name_or_path\": \"openai/whisper-base.en\",\n",
            "  \"activation_dropout\": 0.0,\n",
            "  \"activation_function\": \"gelu\",\n",
            "  \"apply_spec_augment\": false,\n",
            "  \"architectures\": [\n",
            "    \"WhisperForConditionalGeneration\"\n",
            "  ],\n",
            "  \"attention_dropout\": 0.0,\n",
            "  \"begin_suppress_tokens\": [\n",
            "    220,\n",
            "    50256\n",
            "  ],\n",
            "  \"bos_token_id\": 50257,\n",
            "  \"classifier_proj_size\": 256,\n",
            "  \"d_model\": 512,\n",
            "  \"decoder_attention_heads\": 8,\n",
            "  \"decoder_ffn_dim\": 2048,\n",
            "  \"decoder_layerdrop\": 0.0,\n",
            "  \"decoder_layers\": 6,\n",
            "  \"decoder_start_token_id\": 50257,\n",
            "  \"dropout\": 0.0,\n",
            "  \"encoder_attention_heads\": 8,\n",
            "  \"encoder_ffn_dim\": 2048,\n",
            "  \"encoder_layerdrop\": 0.0,\n",
            "  \"encoder_layers\": 6,\n",
            "  \"eos_token_id\": 50256,\n",
            "  \"forced_decoder_ids\": [\n",
            "    [\n",
            "      1,\n",
            "      50362\n",
            "    ]\n",
            "  ],\n",
            "  \"init_std\": 0.02,\n",
            "  \"is_encoder_decoder\": true,\n",
            "  \"mask_feature_length\": 10,\n",
            "  \"mask_feature_min_masks\": 0,\n",
            "  \"mask_feature_prob\": 0.0,\n",
            "  \"mask_time_length\": 10,\n",
            "  \"mask_time_min_masks\": 2,\n",
            "  \"mask_time_prob\": 0.05,\n",
            "  \"max_length\": 448,\n",
            "  \"max_source_positions\": 1500,\n",
            "  \"max_target_positions\": 448,\n",
            "  \"median_filter_width\": 7,\n",
            "  \"model_type\": \"whisper\",\n",
            "  \"num_hidden_layers\": 6,\n",
            "  \"num_mel_bins\": 80,\n",
            "  \"pad_token_id\": 50256,\n",
            "  \"scale_embedding\": false,\n",
            "  \"suppress_tokens\": [\n",
            "    1,\n",
            "    2,\n",
            "    7,\n",
            "    8,\n",
            "    9,\n",
            "    10,\n",
            "    14,\n",
            "    25,\n",
            "    26,\n",
            "    27,\n",
            "    28,\n",
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            "    31,\n",
            "    58,\n",
            "    59,\n",
            "    60,\n",
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            "    63,\n",
            "    90,\n",
            "    91,\n",
            "    92,\n",
            "    93,\n",
            "    357,\n",
            "    366,\n",
            "    438,\n",
            "    532,\n",
            "    685,\n",
            "    705,\n",
            "    796,\n",
            "    930,\n",
            "    1058,\n",
            "    1220,\n",
            "    1267,\n",
            "    1279,\n",
            "    1303,\n",
            "    1343,\n",
            "    1377,\n",
            "    1391,\n",
            "    1635,\n",
            "    1782,\n",
            "    1875,\n",
            "    2162,\n",
            "    2361,\n",
            "    2488,\n",
            "    3467,\n",
            "    4008,\n",
            "    4211,\n",
            "    4600,\n",
            "    4808,\n",
            "    5299,\n",
            "    5855,\n",
            "    6329,\n",
            "    7203,\n",
            "    9609,\n",
            "    9959,\n",
            "    10563,\n",
            "    10786,\n",
            "    11420,\n",
            "    11709,\n",
            "    11907,\n",
            "    13163,\n",
            "    13697,\n",
            "    13700,\n",
            "    14808,\n",
            "    15306,\n",
            "    16410,\n",
            "    16791,\n",
            "    17992,\n",
            "    19203,\n",
            "    19510,\n",
            "    20724,\n",
            "    22305,\n",
            "    22935,\n",
            "    27007,\n",
            "    30109,\n",
            "    30420,\n",
            "    33409,\n",
            "    34949,\n",
            "    40283,\n",
            "    40493,\n",
            "    40549,\n",
            "    47282,\n",
            "    49146,\n",
            "    50257,\n",
            "    50357,\n",
            "    50358,\n",
            "    50359,\n",
            "    50360,\n",
            "    50361\n",
            "  ],\n",
            "  \"torch_dtype\": \"float32\",\n",
            "  \"transformers_version\": \"4.38.2\",\n",
            "  \"use_cache\": true,\n",
            "  \"use_weighted_layer_sum\": false,\n",
            "  \"vocab_size\": 51864\n",
            "}\n",
            "\n",
            "loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/config.json\n",
            "Model config WhisperConfig {\n",
            "  \"_name_or_path\": \"openai/whisper-base.en\",\n",
            "  \"activation_dropout\": 0.0,\n",
            "  \"activation_function\": \"gelu\",\n",
            "  \"apply_spec_augment\": false,\n",
            "  \"architectures\": [\n",
            "    \"WhisperForConditionalGeneration\"\n",
            "  ],\n",
            "  \"attention_dropout\": 0.0,\n",
            "  \"begin_suppress_tokens\": [\n",
            "    220,\n",
            "    50256\n",
            "  ],\n",
            "  \"bos_token_id\": 50257,\n",
            "  \"classifier_proj_size\": 256,\n",
            "  \"d_model\": 512,\n",
            "  \"decoder_attention_heads\": 8,\n",
            "  \"decoder_ffn_dim\": 2048,\n",
            "  \"decoder_layerdrop\": 0.0,\n",
            "  \"decoder_layers\": 6,\n",
            "  \"decoder_start_token_id\": 50257,\n",
            "  \"dropout\": 0.0,\n",
            "  \"encoder_attention_heads\": 8,\n",
            "  \"encoder_ffn_dim\": 2048,\n",
            "  \"encoder_layerdrop\": 0.0,\n",
            "  \"encoder_layers\": 6,\n",
            "  \"eos_token_id\": 50256,\n",
            "  \"forced_decoder_ids\": [\n",
            "    [\n",
            "      1,\n",
            "      50362\n",
            "    ]\n",
            "  ],\n",
            "  \"init_std\": 0.02,\n",
            "  \"is_encoder_decoder\": true,\n",
            "  \"mask_feature_length\": 10,\n",
            "  \"mask_feature_min_masks\": 0,\n",
            "  \"mask_feature_prob\": 0.0,\n",
            "  \"mask_time_length\": 10,\n",
            "  \"mask_time_min_masks\": 2,\n",
            "  \"mask_time_prob\": 0.05,\n",
            "  \"max_length\": 448,\n",
            "  \"max_source_positions\": 1500,\n",
            "  \"max_target_positions\": 448,\n",
            "  \"median_filter_width\": 7,\n",
            "  \"model_type\": \"whisper\",\n",
            "  \"num_hidden_layers\": 6,\n",
            "  \"num_mel_bins\": 80,\n",
            "  \"pad_token_id\": 50256,\n",
            "  \"scale_embedding\": false,\n",
            "  \"suppress_tokens\": [\n",
            "    1,\n",
            "    2,\n",
            "    7,\n",
            "    8,\n",
            "    9,\n",
            "    10,\n",
            "    14,\n",
            "    25,\n",
            "    26,\n",
            "    27,\n",
            "    28,\n",
            "    29,\n",
            "    31,\n",
            "    58,\n",
            "    59,\n",
            "    60,\n",
            "    61,\n",
            "    62,\n",
            "    63,\n",
            "    90,\n",
            "    91,\n",
            "    92,\n",
            "    93,\n",
            "    357,\n",
            "    366,\n",
            "    438,\n",
            "    532,\n",
            "    685,\n",
            "    705,\n",
            "    796,\n",
            "    930,\n",
            "    1058,\n",
            "    1220,\n",
            "    1267,\n",
            "    1279,\n",
            "    1303,\n",
            "    1343,\n",
            "    1377,\n",
            "    1391,\n",
            "    1635,\n",
            "    1782,\n",
            "    1875,\n",
            "    2162,\n",
            "    2361,\n",
            "    2488,\n",
            "    3467,\n",
            "    4008,\n",
            "    4211,\n",
            "    4600,\n",
            "    4808,\n",
            "    5299,\n",
            "    5855,\n",
            "    6329,\n",
            "    7203,\n",
            "    9609,\n",
            "    9959,\n",
            "    10563,\n",
            "    10786,\n",
            "    11420,\n",
            "    11709,\n",
            "    11907,\n",
            "    13163,\n",
            "    13697,\n",
            "    13700,\n",
            "    14808,\n",
            "    15306,\n",
            "    16410,\n",
            "    16791,\n",
            "    17992,\n",
            "    19203,\n",
            "    19510,\n",
            "    20724,\n",
            "    22305,\n",
            "    22935,\n",
            "    27007,\n",
            "    30109,\n",
            "    30420,\n",
            "    33409,\n",
            "    34949,\n",
            "    40283,\n",
            "    40493,\n",
            "    40549,\n",
            "    47282,\n",
            "    49146,\n",
            "    50257,\n",
            "    50357,\n",
            "    50358,\n",
            "    50359,\n",
            "    50360,\n",
            "    50361\n",
            "  ],\n",
            "  \"torch_dtype\": \"float32\",\n",
            "  \"transformers_version\": \"4.38.2\",\n",
            "  \"use_cache\": true,\n",
            "  \"use_weighted_layer_sum\": false,\n",
            "  \"vocab_size\": 51864\n",
            "}\n",
            "\n",
            "loading configuration file config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/config.json\n",
            "Model config WhisperConfig {\n",
            "  \"_name_or_path\": \"openai/whisper-base.en\",\n",
            "  \"activation_dropout\": 0.0,\n",
            "  \"activation_function\": \"gelu\",\n",
            "  \"apply_spec_augment\": false,\n",
            "  \"architectures\": [\n",
            "    \"WhisperForConditionalGeneration\"\n",
            "  ],\n",
            "  \"attention_dropout\": 0.0,\n",
            "  \"begin_suppress_tokens\": [\n",
            "    220,\n",
            "    50256\n",
            "  ],\n",
            "  \"bos_token_id\": 50257,\n",
            "  \"classifier_proj_size\": 256,\n",
            "  \"d_model\": 512,\n",
            "  \"decoder_attention_heads\": 8,\n",
            "  \"decoder_ffn_dim\": 2048,\n",
            "  \"decoder_layerdrop\": 0.0,\n",
            "  \"decoder_layers\": 6,\n",
            "  \"decoder_start_token_id\": 50257,\n",
            "  \"dropout\": 0.0,\n",
            "  \"encoder_attention_heads\": 8,\n",
            "  \"encoder_ffn_dim\": 2048,\n",
            "  \"encoder_layerdrop\": 0.0,\n",
            "  \"encoder_layers\": 6,\n",
            "  \"eos_token_id\": 50256,\n",
            "  \"forced_decoder_ids\": [\n",
            "    [\n",
            "      1,\n",
            "      50362\n",
            "    ]\n",
            "  ],\n",
            "  \"init_std\": 0.02,\n",
            "  \"is_encoder_decoder\": true,\n",
            "  \"mask_feature_length\": 10,\n",
            "  \"mask_feature_min_masks\": 0,\n",
            "  \"mask_feature_prob\": 0.0,\n",
            "  \"mask_time_length\": 10,\n",
            "  \"mask_time_min_masks\": 2,\n",
            "  \"mask_time_prob\": 0.05,\n",
            "  \"max_length\": 448,\n",
            "  \"max_source_positions\": 1500,\n",
            "  \"max_target_positions\": 448,\n",
            "  \"median_filter_width\": 7,\n",
            "  \"model_type\": \"whisper\",\n",
            "  \"num_hidden_layers\": 6,\n",
            "  \"num_mel_bins\": 80,\n",
            "  \"pad_token_id\": 50256,\n",
            "  \"scale_embedding\": false,\n",
            "  \"suppress_tokens\": [\n",
            "    1,\n",
            "    2,\n",
            "    7,\n",
            "    8,\n",
            "    9,\n",
            "    10,\n",
            "    14,\n",
            "    25,\n",
            "    26,\n",
            "    27,\n",
            "    28,\n",
            "    29,\n",
            "    31,\n",
            "    58,\n",
            "    59,\n",
            "    60,\n",
            "    61,\n",
            "    62,\n",
            "    63,\n",
            "    90,\n",
            "    91,\n",
            "    92,\n",
            "    93,\n",
            "    357,\n",
            "    366,\n",
            "    438,\n",
            "    532,\n",
            "    685,\n",
            "    705,\n",
            "    796,\n",
            "    930,\n",
            "    1058,\n",
            "    1220,\n",
            "    1267,\n",
            "    1279,\n",
            "    1303,\n",
            "    1343,\n",
            "    1377,\n",
            "    1391,\n",
            "    1635,\n",
            "    1782,\n",
            "    1875,\n",
            "    2162,\n",
            "    2361,\n",
            "    2488,\n",
            "    3467,\n",
            "    4008,\n",
            "    4211,\n",
            "    4600,\n",
            "    4808,\n",
            "    5299,\n",
            "    5855,\n",
            "    6329,\n",
            "    7203,\n",
            "    9609,\n",
            "    9959,\n",
            "    10563,\n",
            "    10786,\n",
            "    11420,\n",
            "    11709,\n",
            "    11907,\n",
            "    13163,\n",
            "    13697,\n",
            "    13700,\n",
            "    14808,\n",
            "    15306,\n",
            "    16410,\n",
            "    16791,\n",
            "    17992,\n",
            "    19203,\n",
            "    19510,\n",
            "    20724,\n",
            "    22305,\n",
            "    22935,\n",
            "    27007,\n",
            "    30109,\n",
            "    30420,\n",
            "    33409,\n",
            "    34949,\n",
            "    40283,\n",
            "    40493,\n",
            "    40549,\n",
            "    47282,\n",
            "    49146,\n",
            "    50257,\n",
            "    50357,\n",
            "    50358,\n",
            "    50359,\n",
            "    50360,\n",
            "    50361\n",
            "  ],\n",
            "  \"torch_dtype\": \"float32\",\n",
            "  \"transformers_version\": \"4.38.2\",\n",
            "  \"use_cache\": true,\n",
            "  \"use_weighted_layer_sum\": false,\n",
            "  \"vocab_size\": 51864\n",
            "}\n",
            "\n",
            "loading weights file model.safetensors from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/model.safetensors\n",
            "Generate config GenerationConfig {\n",
            "  \"begin_suppress_tokens\": [\n",
            "    220,\n",
            "    50256\n",
            "  ],\n",
            "  \"bos_token_id\": 50257,\n",
            "  \"decoder_start_token_id\": 50257,\n",
            "  \"eos_token_id\": 50256,\n",
            "  \"forced_decoder_ids\": [\n",
            "    [\n",
            "      1,\n",
            "      50362\n",
            "    ]\n",
            "  ],\n",
            "  \"max_length\": 448,\n",
            "  \"pad_token_id\": 50256,\n",
            "  \"suppress_tokens\": [\n",
            "    1,\n",
            "    2,\n",
            "    7,\n",
            "    8,\n",
            "    9,\n",
            "    10,\n",
            "    14,\n",
            "    25,\n",
            "    26,\n",
            "    27,\n",
            "    28,\n",
            "    29,\n",
            "    31,\n",
            "    58,\n",
            "    59,\n",
            "    60,\n",
            "    61,\n",
            "    62,\n",
            "    63,\n",
            "    90,\n",
            "    91,\n",
            "    92,\n",
            "    93,\n",
            "    357,\n",
            "    366,\n",
            "    438,\n",
            "    532,\n",
            "    685,\n",
            "    705,\n",
            "    796,\n",
            "    930,\n",
            "    1058,\n",
            "    1220,\n",
            "    1267,\n",
            "    1279,\n",
            "    1303,\n",
            "    1343,\n",
            "    1377,\n",
            "    1391,\n",
            "    1635,\n",
            "    1782,\n",
            "    1875,\n",
            "    2162,\n",
            "    2361,\n",
            "    2488,\n",
            "    3467,\n",
            "    4008,\n",
            "    4211,\n",
            "    4600,\n",
            "    4808,\n",
            "    5299,\n",
            "    5855,\n",
            "    6329,\n",
            "    7203,\n",
            "    9609,\n",
            "    9959,\n",
            "    10563,\n",
            "    10786,\n",
            "    11420,\n",
            "    11709,\n",
            "    11907,\n",
            "    13163,\n",
            "    13697,\n",
            "    13700,\n",
            "    14808,\n",
            "    15306,\n",
            "    16410,\n",
            "    16791,\n",
            "    17992,\n",
            "    19203,\n",
            "    19510,\n",
            "    20724,\n",
            "    22305,\n",
            "    22935,\n",
            "    27007,\n",
            "    30109,\n",
            "    30420,\n",
            "    33409,\n",
            "    34949,\n",
            "    40283,\n",
            "    40493,\n",
            "    40549,\n",
            "    47282,\n",
            "    49146,\n",
            "    50257,\n",
            "    50357,\n",
            "    50358,\n",
            "    50359,\n",
            "    50360,\n",
            "    50361\n",
            "  ]\n",
            "}\n",
            "\n",
            "All model checkpoint weights were used when initializing WhisperForConditionalGeneration.\n",
            "\n",
            "All the weights of WhisperForConditionalGeneration were initialized from the model checkpoint at openai/whisper-base.en.\n",
            "If your task is similar to the task the model of the checkpoint was trained on, you can already use WhisperForConditionalGeneration for predictions without further training.\n",
            "loading configuration file generation_config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/generation_config.json\n",
            "Generate config GenerationConfig {\n",
            "  \"alignment_heads\": [\n",
            "    [\n",
            "      3,\n",
            "      3\n",
            "    ],\n",
            "    [\n",
            "      4,\n",
            "      7\n",
            "    ],\n",
            "    [\n",
            "      5,\n",
            "      1\n",
            "    ],\n",
            "    [\n",
            "      5,\n",
            "      5\n",
            "    ],\n",
            "    [\n",
            "      5,\n",
            "      7\n",
            "    ]\n",
            "  ],\n",
            "  \"begin_suppress_tokens\": [\n",
            "    220,\n",
            "    50256\n",
            "  ],\n",
            "  \"bos_token_id\": 50257,\n",
            "  \"decoder_start_token_id\": 50257,\n",
            "  \"eos_token_id\": 50256,\n",
            "  \"forced_decoder_ids\": [\n",
            "    [\n",
            "      1,\n",
            "      50362\n",
            "    ]\n",
            "  ],\n",
            "  \"is_multilingual\": false,\n",
            "  \"max_initial_timestamp_index\": 50,\n",
            "  \"max_length\": 448,\n",
            "  \"no_timestamps_token_id\": 50362,\n",
            "  \"pad_token_id\": 50256,\n",
            "  \"prev_sot_token_id\": 50360,\n",
            "  \"return_timestamps\": false,\n",
            "  \"suppress_tokens\": [\n",
            "    1,\n",
            "    2,\n",
            "    7,\n",
            "    8,\n",
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            "    50360,\n",
            "    50361\n",
            "  ]\n",
            "}\n",
            "\n",
            "loading file vocab.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/vocab.json\n",
            "loading file tokenizer.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/tokenizer.json\n",
            "loading file merges.txt from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/merges.txt\n",
            "loading file normalizer.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/normalizer.json\n",
            "loading file added_tokens.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/added_tokens.json\n",
            "loading file special_tokens_map.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/special_tokens_map.json\n",
            "loading file tokenizer_config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/tokenizer_config.json\n",
            "loading configuration file preprocessor_config.json from cache at /root/.cache/huggingface/hub/models--openai--whisper-base.en/snapshots/911407f4214e0e1d82085af863093ec0b66f9cd6/preprocessor_config.json\n",
            "Feature extractor WhisperFeatureExtractor {\n",
            "  \"chunk_length\": 30,\n",
            "  \"feature_extractor_type\": \"WhisperFeatureExtractor\",\n",
            "  \"feature_size\": 80,\n",
            "  \"hop_length\": 160,\n",
            "  \"n_fft\": 400,\n",
            "  \"n_samples\": 480000,\n",
            "  \"nb_max_frames\": 3000,\n",
            "  \"padding_side\": \"right\",\n",
            "  \"padding_value\": 0.0,\n",
            "  \"processor_class\": \"WhisperProcessor\",\n",
            "  \"return_attention_mask\": false,\n",
            "  \"sampling_rate\": 16000\n",
            "}\n",
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Setting queue=True in a Colab notebook requires sharing enabled. Setting `share=True` (you can turn this off by setting `share=False` in `launch()` explicitly).\n",
            "\n",
            "Colab notebook detected. To show errors in colab notebook, set debug=True in launch()\n",
            "Running on public URL: https://fca01f543666508bd7.gradio.live\n",
            "\n",
            "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co/spaces)\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "<div><iframe src=\"https://fca01f543666508bd7.gradio.live\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 36
        }
      ],
      "source": [
        "import gradio as gr\n",
        "from transformers import *\n",
        "import numpy as np\n",
        "\n",
        "\n",
        "transcriber = pipeline(\"automatic-speech-recognition\", model=\"openai/whisper-base.en\")\n",
        "\n",
        "def transcribe(stream, new_chunk):\n",
        "    sr, y = new_chunk\n",
        "    y = y.astype(np.float32)\n",
        "    y /= np.max(np.abs(y))\n",
        "    #time.sleep(3)\n",
        "\n",
        "    if stream is not None:\n",
        "      stream = np.concatenate([stream, y])\n",
        "    else:\n",
        "        stream = y\n",
        "    return stream, transcriber({\"sampling_rate\": sr, \"raw\": stream})[\"text\"]\n",
        "\n",
        "\n",
        "#demo = gr.Interface(\n",
        "#    transcribe,\n",
        "#    [\"state\", gr.Audio(sources=[\"microphone\"], streaming=True)],\n",
        "#    [\"state\", \"text\"],\n",
        "#    live=True,\n",
        "#)\n",
        "\n",
        "#demo.launch()\n",
        "\n",
        "\n",
        "app = gr.Interface(\n",
        "  transcribe,\n",
        "  [\"state\", gr.Audio(sources=[\"microphone\"], streaming=True)],\n",
        "  [\"state\", \"text\"],\n",
        "  title=\"Speech to Text\",  # Add your title here\n",
        "  description=\"Speak into your microphone and see the transcribed text appear instantly!\",  # Add your description here\n",
        "  live=True,\n",
        ")\n",
        "\n",
        "app.launch()"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install whisper\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s6MxbMrWh1Ql",
        "outputId": "8d85b80a-8ed5-4d89-f813-d41cd48343d7"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting whisper\n",
            "  Downloading whisper-1.1.10.tar.gz (42 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.8/42.8 kB\u001b[0m \u001b[31m606.7 kB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from whisper) (1.16.0)\n",
            "Building wheels for collected packages: whisper\n",
            "  Building wheel for whisper (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for whisper: filename=whisper-1.1.10-py3-none-any.whl size=41120 sha256=1d318e58c427b0a10c789fb77525a9b11b17dced1caf1aa15aec66c65c2492f2\n",
            "  Stored in directory: /root/.cache/pip/wheels/aa/7c/1d/015619716e2facae6631312503baf3c3220e6a9a3508cb14b6\n",
            "Successfully built whisper\n",
            "Installing collected packages: whisper\n",
            "Successfully installed whisper-1.1.10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "dcuH4mpshUcI"
      },
      "outputs": [],
      "source": [
        "import gradio as gr\n",
        "from transformers import pipeline\n",
        "import numpy as np\n",
        "import time\n",
        "import whisper\n",
        "transcriber = pipeline(\"automatic-speech-recognition\", model=\"openai/whisper-base.vi\")\n",
        "\n",
        "def transcribe(stream, new_chunk):\n",
        "    sr, y = new_chunk\n",
        "    y = y.astype(np.float32)\n",
        "    y /= np.max(np.abs(y))\n",
        "    #time.sleep(3)\n",
        "\n",
        "    if stream is not None:\n",
        "      time.sleep(3)\n",
        "      stream = np.concatenate([stream, y])\n",
        "    else:\n",
        "        stream = y\n",
        "    return stream, transcriber({\"sampling_rate\": sr, \"raw\": stream})[\"text\"]\n",
        "\n",
        "def transcribe_audio(audio_file):\n",
        "    model = whisper.load_model(\"base\")\n",
        "    result = model.transcribe(audio_file)\n",
        "    return result[\"text\"]\n",
        "\n",
        "#demo = gr.Interface(\n",
        "#    transcribe,\n",
        "#    [\"state\", gr.Audio(sources=[\"microphone\"], streaming=True)],\n",
        "#    [\"state\", \"text\"],\n",
        "#    live=True,\n",
        "#)\n",
        "\n",
        "#demo.launch()\n",
        "\n",
        "\n",
        "app = gr.Interface(\n",
        "  transcribe,  # Your single audio transcription function\n",
        "  inputs=[\n",
        "    gr.Audio(sources=[\"microphone\"], streaming=True),  # Microphone input\n",
        "    gr.Audio(sources=[\"upload\"], type=\"filepath\")  # Upload audio file input\n",
        "  ],\n",
        "  outputs=[\"text\"],  # Output for the transcribed text\n",
        "  title=\"Speech to Text\",\n",
        "  description=\"Speak into your microphone or upload an audio file to get the text transcription!\",\n",
        "  live=True,\n",
        ")\n",
        "\n",
        "app.launch()\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import gradio as gr\n",
        "from transformers import pipeline\n",
        "import numpy as np\n",
        "\n",
        "transcriber = pipeline(\"automatic-speech-recognition\", model=\"openai/whisper-base.en\")\n",
        "\n",
        "def transcribe(stream, new_chunk):\n",
        "    sr, y = new_chunk\n",
        "    y = y.astype(np.float32)\n",
        "    y /= np.max(np.abs(y))\n",
        "\n",
        "    if stream is not None:\n",
        "        stream = np.concatenate([stream, y])\n",
        "    else:\n",
        "        stream = y\n",
        "    return stream, transcriber({\"sampling_rate\": sr, \"raw\": stream})[\"text\"]\n",
        "\n",
        "def transcribe_audio(audio_file):\n",
        "    model = whisper.load_model(\"base\")\n",
        "    result = model.transcribe(audio_file)\n",
        "    return result[\"text\"]\n",
        "\n",
        "app = gr.Interface(\n",
        "    transcribe,  # Consider handling both microphone and upload within\n",
        "                 # this function or create a single logic\n",
        "    inputs=[\n",
        "        gr.Audio(sources=[\"microphone\"], streaming=True),  # Microphone input\n",
        "        gr.Audio(sources=[\"upload\"], type=\"filepath\")  # Upload audio file input\n",
        "    ],\n",
        "    outputs=[\"text\"],  # Output for the transcribed text\n",
        "    title=\"Speech to Text\",\n",
        "    description=\"Speak into your microphone or upload an audio file to get the text transcription!\",\n",
        "    live=True,\n",
        ")\n",
        "\n",
        "app.launch()\n"
      ],
      "metadata": {
        "id": "jJ-40Jr5jUOU"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# prompt: install streamlit\n",
        "\n",
        "!pip install streamlit\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "khA5iuQ5hEHH",
        "outputId": "70db3a6b-8151-4af1-cd1b-4c6d7f2d3fba"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting streamlit\n",
            "  Downloading streamlit-1.33.0-py2.py3-none-any.whl (8.1 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m8.1/8.1 MB\u001b[0m \u001b[31m13.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: altair<6,>=4.0 in /usr/local/lib/python3.10/dist-packages (from streamlit) (4.2.2)\n",
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            "Requirement already satisfied: tenacity<9,>=8.1.0 in /usr/local/lib/python3.10/dist-packages (from streamlit) (8.2.3)\n",
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            "Requirement already satisfied: typing-extensions<5,>=4.3.0 in /usr/local/lib/python3.10/dist-packages (from streamlit) (4.11.0)\n",
            "Collecting gitpython!=3.1.19,<4,>=3.0.7 (from streamlit)\n",
            "  Downloading GitPython-3.1.43-py3-none-any.whl (207 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m207.3/207.3 kB\u001b[0m \u001b[31m13.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hCollecting pydeck<1,>=0.8.0b4 (from streamlit)\n",
            "  Downloading pydeck-0.9.0b1-py2.py3-none-any.whl (5.8 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m5.8/5.8 MB\u001b[0m \u001b[31m19.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting watchdog>=2.1.5 (from streamlit)\n",
            "  Downloading watchdog-4.0.0-py3-none-manylinux2014_x86_64.whl (82 kB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m83.0/83.0 kB\u001b[0m \u001b[31m4.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
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            "Collecting gitdb<5,>=4.0.1 (from gitpython!=3.1.19,<4,>=3.0.7->streamlit)\n",
            "  Downloading gitdb-4.0.11-py3-none-any.whl (62 kB)\n",
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            "Collecting smmap<6,>=3.0.1 (from gitdb<5,>=4.0.1->gitpython!=3.1.19,<4,>=3.0.7->streamlit)\n",
            "  Downloading smmap-5.0.1-py3-none-any.whl (24 kB)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->altair<6,>=4.0->streamlit) (2.1.5)\n",
            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (23.2.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (0.34.0)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit) (0.18.0)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich<14,>=10.14.0->streamlit) (0.1.2)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas<3,>=1.3.0->streamlit) (1.16.0)\n",
            "Installing collected packages: watchdog, smmap, pydeck, gitdb, gitpython, streamlit\n",
            "Successfully installed gitdb-4.0.11 gitpython-3.1.43 pydeck-0.9.0b1 smmap-5.0.1 streamlit-1.33.0 watchdog-4.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install whisper\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nkQc8Jx-hV6S",
        "outputId": "211fccc2-ed41-438c-8f25-b0c495a86124"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting whisper\n",
            "  Downloading whisper-1.1.10.tar.gz (42 kB)\n",
            "\u001b[?25l     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m0.0/42.8 kB\u001b[0m \u001b[31m?\u001b[0m eta \u001b[36m-:--:--\u001b[0m\r\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m42.8/42.8 kB\u001b[0m \u001b[31m1.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.10/dist-packages (from whisper) (1.16.0)\n",
            "Building wheels for collected packages: whisper\n",
            "  Building wheel for whisper (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for whisper: filename=whisper-1.1.10-py3-none-any.whl size=41120 sha256=03e8df68bb0eb1a988fa67390579b27bc24768b0ab774ff80d95ed5221f5a0a9\n",
            "  Stored in directory: /root/.cache/pip/wheels/aa/7c/1d/015619716e2facae6631312503baf3c3220e6a9a3508cb14b6\n",
            "Successfully built whisper\n",
            "Installing collected packages: whisper\n",
            "Successfully installed whisper-1.1.10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "4TjMEf9-gcyx",
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          "height": 483,
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        },
        "outputId": "a127984d-520f-408a-ded0-4035b7bda352"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "c1ebf4ea7a9b47d29aa3296da6515cbe"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "fe1f0a5dd0fc417ea105cbf0232630dc"
            }
          },
          "metadata": {}
        },
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "cc4d5beea3e4467684367f53c88bde4d"
            }
          },
          "metadata": {}
        },
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            "application/vnd.jupyter.widget-view+json": {
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            }
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            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "2f39f498cf2c4111ae4dcbfbfb098551"
            }
          },
          "metadata": {}
        },
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          "output_type": "display_data",
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              "model_id": "bfd8a50044cc469fbeb22cc5025e7841"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Special tokens have been added in the vocabulary, make sure the associated word embeddings are fine-tuned or trained.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "6144f2b78fe34562b2929d5bb84c5ef4"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
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            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "027e95f5cba64c979a1bb9e120852ef5"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
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            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "dd38f4b847344549a6e34275feb32a74"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "import streamlit as st\n",
        "from transformers import WhisperTokenizer, WhisperForConditionalGeneration\n",
        "\n",
        "st.title(\"Multi-lingual Transcription using Whisper\")\n",
        "\n",
        "audio_file = st.file_uploader(\"Upload your audio\", type=[\"wav\", \"mp3\", \"m4a\"])\n",
        "\n",
        "model_name = \"openai/whisper-base\"  # Or a different Whisper model size\n",
        "tokenizer = WhisperTokenizer.from_pretrained(model_name)\n",
        "model = WhisperForConditionalGeneration.from_pretrained(model_name)\n",
        "\n",
        "if st.sidebar.button(\"Transcribe Audio\"):\n",
        "    if audio_file is not None:\n",
        "        st.sidebar.success(\"Transcribing...\")\n",
        "        with tempfile.NamedTemporaryFile(delete=False) as temp_audio:\n",
        "            temp_audio.write(audio_file.read())\n",
        "\n",
        "        # Get the absolute path of the temporary audio file\n",
        "        audio_file_path = os.path.abspath(temp_audio.name)\n",
        "\n",
        "        # Use the model and tokenizer for transcription (refer to Whisper's documentation for details)\n",
        "        transcription = model.generate(...)  # Replace ... with appropriate arguments for transcription\n",
        "\n",
        "        st.sidebar.success(\"Transcription complete\")\n",
        "        st.markdown(transcription[\"text\"])\n",
        "\n",
        "        # Clean up the temporary file after processing\n",
        "        os.remove(audio_file_path)\n",
        "    else:\n",
        "        st.sidebar.error(\"Please upload an audio file.\")\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install gradio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "B89Ufp8tiZ-_",
        "outputId": "66435f00-227e-41f7-b474-91747a07d7f0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting gradio\n",
            "  Downloading gradio-4.28.3-py3-none-any.whl (12.2 MB)\n",
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            "\u001b[?25hCollecting aiofiles<24.0,>=22.0 (from gradio)\n",
            "  Downloading aiofiles-23.2.1-py3-none-any.whl (15 kB)\n",
            "Requirement already satisfied: altair<6.0,>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from gradio) (4.2.2)\n",
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            "\u001b[?25hCollecting ffmpy (from gradio)\n",
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            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "Building wheels for collected packages: ffmpy\n",
            "  Building wheel for ffmpy (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for ffmpy: filename=ffmpy-0.3.2-py3-none-any.whl size=5584 sha256=8627fcf083fc8b749a403fb833503a12669745716eebf5d5f04dcbac021d9c57\n",
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            "Installing collected packages: pydub, ffmpy, websockets, tomlkit, shellingham, semantic-version, ruff, python-multipart, orjson, h11, aiofiles, uvicorn, starlette, httpcore, typer, httpx, fastapi, gradio-client, gradio\n",
            "  Attempting uninstall: typer\n",
            "    Found existing installation: typer 0.9.4\n",
            "    Uninstalling typer-0.9.4:\n",
            "      Successfully uninstalled typer-0.9.4\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "spacy 3.7.4 requires typer<0.10.0,>=0.3.0, but you have typer 0.12.3 which is incompatible.\n",
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            "\u001b[0mSuccessfully installed aiofiles-23.2.1 fastapi-0.110.2 ffmpy-0.3.2 gradio-4.28.3 gradio-client-0.16.0 h11-0.14.0 httpcore-1.0.5 httpx-0.27.0 orjson-3.10.1 pydub-0.25.1 python-multipart-0.0.9 ruff-0.4.2 semantic-version-2.10.0 shellingham-1.5.4 starlette-0.37.2 tomlkit-0.12.0 typer-0.12.3 uvicorn-0.29.0 websockets-11.0.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import gradio as gr\n",
        "import whisper\n",
        "import tempfile\n",
        "import os\n",
        "\n",
        "def transcribe(audio_bytes):\n",
        "\n",
        "\n",
        "  model_name = \"openai/whisper-base\"\n",
        "  tokenizer = WhisperTokenizer.from_pretrained(model_name)\n",
        "  model = WhisperForConditionalGeneration.from_pretrained(model_name)\n",
        "\n",
        "  with tempfile.NamedTemporaryFile(delete=False, suffix=\".wav\") as temp_audio:\n",
        "    temp_audio.write(audio_bytes)\n",
        "    audio_file_path = temp_audio.name\n",
        "\n",
        "\n",
        "  transcription = model.generate(...)\n",
        "\n",
        "\n",
        "  os.remove(audio_file_path)\n",
        "\n",
        "  return transcription[\"text\"]\n",
        "\n",
        "interface = gr.Interface(\n",
        "  fn=transcribe,\n",
        "  inputs=gr.Audio(sources=[\"upload\"], type=\"filepath\"),\n",
        "  outputs=[\"text\"],\n",
        "  title=\"Multi-lingual Transcription with Whisper\",\n",
        "  description=\"Upload your audio file and get the transcribed text in multiple languages.\",\n",
        ")\n",
        "\n",
        "interface.launch()\n",
        "\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 397
        },
        "id": "uf79PUwViXyA",
        "outputId": "ae0850f4-b18f-4479-8d7d-90bb87fa87e0"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "error",
          "ename": "ModuleNotFoundError",
          "evalue": "No module named 'gradio'",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-1-30e7b4d2a1c6>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mimport\u001b[0m \u001b[0mgradio\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mgr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mwhisper\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mtempfile\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'gradio'",
            "",
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0;32m\nNOTE: If your import is failing due to a missing package, you can\nmanually install dependencies using either !pip or !apt.\n\nTo view examples of installing some common dependencies, click the\n\"Open Examples\" button below.\n\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n"
          ],
          "errorDetails": {
            "actions": [
              {
                "action": "open_url",
                "actionText": "Open Examples",
                "url": "/notebooks/snippets/importing_libraries.ipynb"
              }
            ]
          }
        }
      ]
    }
  ]
}