VideoFrameGen.ipynb

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  },
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## Dependencies Installation"
      ],
      "metadata": {
        "id": "gFfYLPbi7jwJ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install git+https://github.com/huggingface/accelerate.git\n",
        "!pip install diffusers\n",
        "!pip install moviepy"
      ],
      "metadata": {
        "id": "YQti4Xyc9y8e",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "0f59f778-6e87-4540-f553-aedfae06c4d6"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting git+https://github.com/huggingface/accelerate.git\n",
            "  Cloning https://github.com/huggingface/accelerate.git to /tmp/pip-req-build-2pqd6638\n",
            "  Running command git clone --filter=blob:none --quiet https://github.com/huggingface/accelerate.git /tmp/pip-req-build-2pqd6638\n",
            "  Resolved https://github.com/huggingface/accelerate.git to commit afc2c99e6ae145846548a32f857bb6d8f029797d\n",
            "  Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n",
            "  Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n",
            "  Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (1.25.2)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (24.0)\n",
            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (5.9.5)\n",
            "Requirement already satisfied: pyyaml in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (6.0.1)\n",
            "Requirement already satisfied: torch>=1.10.0 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (2.2.1+cu121)\n",
            "Requirement already satisfied: huggingface-hub in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (0.20.3)\n",
            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from accelerate==0.31.0.dev0) (0.4.3)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (3.14.0)\n",
            "Requirement already satisfied: typing-extensions>=4.8.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (4.11.0)\n",
            "Requirement already satisfied: sympy in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (1.12)\n",
            "Requirement already satisfied: networkx in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (3.3)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (3.1.3)\n",
            "Requirement already satisfied: fsspec in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (2023.6.0)\n",
            "Collecting nvidia-cuda-nvrtc-cu12==12.1.105 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cuda_nvrtc_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (23.7 MB)\n",
            "Collecting nvidia-cuda-runtime-cu12==12.1.105 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cuda_runtime_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (823 kB)\n",
            "Collecting nvidia-cuda-cupti-cu12==12.1.105 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cuda_cupti_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (14.1 MB)\n",
            "Collecting nvidia-cudnn-cu12==8.9.2.26 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cudnn_cu12-8.9.2.26-py3-none-manylinux1_x86_64.whl (731.7 MB)\n",
            "Collecting nvidia-cublas-cu12==12.1.3.1 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cublas_cu12-12.1.3.1-py3-none-manylinux1_x86_64.whl (410.6 MB)\n",
            "Collecting nvidia-cufft-cu12==11.0.2.54 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cufft_cu12-11.0.2.54-py3-none-manylinux1_x86_64.whl (121.6 MB)\n",
            "Collecting nvidia-curand-cu12==10.3.2.106 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_curand_cu12-10.3.2.106-py3-none-manylinux1_x86_64.whl (56.5 MB)\n",
            "Collecting nvidia-cusolver-cu12==11.4.5.107 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cusolver_cu12-11.4.5.107-py3-none-manylinux1_x86_64.whl (124.2 MB)\n",
            "Collecting nvidia-cusparse-cu12==12.1.0.106 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_cusparse_cu12-12.1.0.106-py3-none-manylinux1_x86_64.whl (196.0 MB)\n",
            "Collecting nvidia-nccl-cu12==2.19.3 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_nccl_cu12-2.19.3-py3-none-manylinux1_x86_64.whl (166.0 MB)\n",
            "Collecting nvidia-nvtx-cu12==12.1.105 (from torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_nvtx_cu12-12.1.105-py3-none-manylinux1_x86_64.whl (99 kB)\n",
            "Requirement already satisfied: triton==2.2.0 in /usr/local/lib/python3.10/dist-packages (from torch>=1.10.0->accelerate==0.31.0.dev0) (2.2.0)\n",
            "Collecting nvidia-nvjitlink-cu12 (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.10.0->accelerate==0.31.0.dev0)\n",
            "  Using cached nvidia_nvjitlink_cu12-12.4.127-py3-none-manylinux2014_x86_64.whl (21.1 MB)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate==0.31.0.dev0) (2.31.0)\n",
            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub->accelerate==0.31.0.dev0) (4.66.4)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->torch>=1.10.0->accelerate==0.31.0.dev0) (2.1.5)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate==0.31.0.dev0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate==0.31.0.dev0) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate==0.31.0.dev0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->huggingface-hub->accelerate==0.31.0.dev0) (2024.2.2)\n",
            "Requirement already satisfied: mpmath>=0.19 in /usr/local/lib/python3.10/dist-packages (from sympy->torch>=1.10.0->accelerate==0.31.0.dev0) (1.3.0)\n",
            "Building wheels for collected packages: accelerate\n",
            "  Building wheel for accelerate (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for accelerate: filename=accelerate-0.31.0.dev0-py3-none-any.whl size=302679 sha256=f0663442bc38d8ddd52d68693df6c294b23e9e67d62248476008135806ee314a\n",
            "  Stored in directory: /tmp/pip-ephem-wheel-cache-zzz3q2ix/wheels/9c/a3/1e/47368f9b6575655fe9ee1b6350cfa7d4b0befe66a35f8a8365\n",
            "Successfully built accelerate\n",
            "Installing collected packages: nvidia-nvtx-cu12, nvidia-nvjitlink-cu12, nvidia-nccl-cu12, nvidia-curand-cu12, nvidia-cufft-cu12, nvidia-cuda-runtime-cu12, nvidia-cuda-nvrtc-cu12, nvidia-cuda-cupti-cu12, nvidia-cublas-cu12, nvidia-cusparse-cu12, nvidia-cudnn-cu12, nvidia-cusolver-cu12, accelerate\n",
            "Successfully installed accelerate-0.31.0.dev0 nvidia-cublas-cu12-12.1.3.1 nvidia-cuda-cupti-cu12-12.1.105 nvidia-cuda-nvrtc-cu12-12.1.105 nvidia-cuda-runtime-cu12-12.1.105 nvidia-cudnn-cu12-8.9.2.26 nvidia-cufft-cu12-11.0.2.54 nvidia-curand-cu12-10.3.2.106 nvidia-cusolver-cu12-11.4.5.107 nvidia-cusparse-cu12-12.1.0.106 nvidia-nccl-cu12-2.19.3 nvidia-nvjitlink-cu12-12.4.127 nvidia-nvtx-cu12-12.1.105\n",
            "Collecting diffusers\n",
            "  Downloading diffusers-0.27.2-py3-none-any.whl (2.0 MB)\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m2.0/2.0 MB\u001b[0m \u001b[31m14.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25hRequirement already satisfied: importlib-metadata in /usr/local/lib/python3.10/dist-packages (from diffusers) (7.1.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from diffusers) (3.14.0)\n",
            "Requirement already satisfied: huggingface-hub>=0.20.2 in /usr/local/lib/python3.10/dist-packages (from diffusers) (0.20.3)\n",
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            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.10/dist-packages (from diffusers) (2023.12.25)\n",
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            "Requirement already satisfied: safetensors>=0.3.1 in /usr/local/lib/python3.10/dist-packages (from diffusers) (0.4.3)\n",
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            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.20.2->diffusers) (2023.6.0)\n",
            "Requirement already satisfied: tqdm>=4.42.1 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.20.2->diffusers) (4.66.4)\n",
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            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.20.2->diffusers) (4.11.0)\n",
            "Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.20.2->diffusers) (24.0)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/dist-packages (from importlib-metadata->diffusers) (3.18.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->diffusers) (2024.2.2)\n",
            "Installing collected packages: diffusers\n",
            "Successfully installed diffusers-0.27.2\n",
            "Requirement already satisfied: moviepy in /usr/local/lib/python3.10/dist-packages (1.0.3)\n",
            "Requirement already satisfied: decorator<5.0,>=4.0.2 in /usr/local/lib/python3.10/dist-packages (from moviepy) (4.4.2)\n",
            "Requirement already satisfied: tqdm<5.0,>=4.11.2 in /usr/local/lib/python3.10/dist-packages (from moviepy) (4.66.4)\n",
            "Requirement already satisfied: requests<3.0,>=2.8.1 in /usr/local/lib/python3.10/dist-packages (from moviepy) (2.31.0)\n",
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            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.10/dist-packages (from moviepy) (1.25.2)\n",
            "Requirement already satisfied: imageio<3.0,>=2.5 in /usr/local/lib/python3.10/dist-packages (from moviepy) (2.31.6)\n",
            "Requirement already satisfied: imageio-ffmpeg>=0.2.0 in /usr/local/lib/python3.10/dist-packages (from moviepy) (0.4.9)\n",
            "Requirement already satisfied: pillow<10.1.0,>=8.3.2 in /usr/local/lib/python3.10/dist-packages (from imageio<3.0,>=2.5->moviepy) (9.4.0)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from imageio-ffmpeg>=0.2.0->moviepy) (67.7.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests<3.0,>=2.8.1->moviepy) (3.3.2)\n",
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            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests<3.0,>=2.8.1->moviepy) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests<3.0,>=2.8.1->moviepy) (2024.2.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## User Input"
      ],
      "metadata": {
        "id": "QyWJH1RU7sg0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "userInput = \"Give me a Brazilian funk song with a futuristic city party vibe\""
      ],
      "metadata": {
        "id": "cL7QFJ6jthY3"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Communication with the Diffusion Model"
      ],
      "metadata": {
        "id": "raKjgPEK7QON"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import torch\n",
        "from diffusers import AnimateDiffPipeline, DDIMScheduler, MotionAdapter\n",
        "from diffusers.utils import export_to_gif\n",
        "from moviepy.editor import VideoFileClip, concatenate_videoclips\n",
        "import os\n",
        "\n",
        "# Set the ffmpeg executable path for imageio\n",
        "os.environ[\"IMAGEIO_FFMPEG_EXE\"] = \"/usr/bin/ffmpeg\"\n",
        "\n",
        "# Load the pre-trained motion adapter\n",
        "adapter = MotionAdapter.from_pretrained(\"guoyww/animatediff-motion-adapter-v1-5-2\", torch_dtype=torch.float16)\n",
        "\n",
        "# Load the pre-trained pipeline with motion adapter and scheduler\n",
        "pipeline = AnimateDiffPipeline.from_pretrained(\"emilianJR/epiCRealism\", motion_adapter=adapter, torch_dtype=torch.float16)\n",
        "scheduler = DDIMScheduler.from_pretrained(\n",
        "    \"emilianJR/epiCRealism\",\n",
        "    subfolder=\"scheduler\",\n",
        "    clip_sample=False,\n",
        "    timestep_spacing=\"linspace\",\n",
        "    beta_schedule=\"linear\",\n",
        "    steps_offset=1,\n",
        ")\n",
        "pipeline.scheduler = scheduler\n",
        "pipeline.enable_vae_slicing()\n",
        "pipeline.enable_model_cpu_offload()\n",
        "\n",
        "# Function to generate movie from frame descriptions\n",
        "def gen_movie(frames_desc):\n",
        "    x = 1\n",
        "    for frame_description in frames_desc:\n",
        "        # Generate frames using the pipeline\n",
        "        output = pipeline(\n",
        "            prompt=frame_description,\n",
        "            negative_prompt=\"low resolution\",\n",
        "            num_frames=16,\n",
        "            guidance_scale=7.5,\n",
        "            num_inference_steps=50,\n",
        "            generator=torch.Generator(\"cpu\").manual_seed(0),\n",
        "        )\n",
        "        # Get the frames from the output and export them to a GIF\n",
        "        frames = output.frames[0]\n",
        "        export_to_gif(frames, f'animation{x}.gif')\n",
        "        x += 1\n",
        "\n",
        "    # List to store VideoFileClip objects for each input GIF\n",
        "    video_clips = []\n",
        "\n",
        "    # Load each input GIF file and append it to the list\n",
        "    for x in range(1,11):\n",
        "        video_clips.append(VideoFileClip(f'animation{x}.gif'))\n",
        "\n",
        "    # Concatenate the video clips to create a single video\n",
        "    final_clip = concatenate_videoclips(video_clips)\n",
        "\n",
        "    # Speed up the final video and export it to a new MP4 file\n",
        "    final_clip = final_clip.fx( vfx.speedx, 0.25)\n",
        "    final_clip.write_videofile(\"combined_video.mp4\", codec=\"libx264\", fps=24)\n"
      ],
      "metadata": {
        "id": "YuSbynjnEnUb",
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        },
        "outputId": "6a0b4929-76dc-440e-8b3e-a24ea8f746c0"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "0it [00:00, ?it/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "20d05ef2530a4403a667d3436017dc67"
            }
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:py.warnings:/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",
            "\n"
          ]
        },
        {
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        {
          "output_type": "stream",
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          "text": [
            "The config attributes {'motion_activation_fn': 'geglu', 'motion_attention_bias': False, 'motion_cross_attention_dim': None} were passed to MotionAdapter, but are not expected and will be ignored. Please verify your config.json configuration file.\n"
          ]
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:py.warnings:/usr/local/lib/python3.10/dist-packages/transformers/models/clip/feature_extraction_clip.py:28: FutureWarning: The class CLIPFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please use CLIPImageProcessor instead.\n",
            "  warnings.warn(\n",
            "\n",
            "The config attributes {'center_input_sample': False, 'flip_sin_to_cos': True, 'freq_shift': 0, 'mid_block_type': 'UNetMidBlock2DCrossAttn', 'only_cross_attention': False, 'attention_head_dim': 8, 'dual_cross_attention': False, 'class_embed_type': None, 'addition_embed_type': None, 'num_class_embeds': None, 'upcast_attention': False, 'resnet_time_scale_shift': 'default', 'resnet_skip_time_act': False, 'resnet_out_scale_factor': 1.0, 'time_embedding_type': 'positional', 'time_embedding_dim': None, 'time_embedding_act_fn': None, 'timestep_post_act': None, 'conv_in_kernel': 3, 'conv_out_kernel': 3, 'projection_class_embeddings_input_dim': None, 'class_embeddings_concat': False, 'mid_block_only_cross_attention': None, 'cross_attention_norm': None, 'addition_embed_type_num_heads': 64} were passed to UNetMotionModel, but are not expected and will be ignored. Please verify your config.json configuration file.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Prompt Engineering + Animation Generation"
      ],
      "metadata": {
        "id": "5IqjS9mc7ZwE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# Combine all the code below this point\n",
        "import pathlib\n",
        "import requests\n",
        "import google.generativeai as genai\n",
        "\n",
        "# Configure the generative AI with API key\n",
        "genai.configure(api_key=\"AIzaSyAgqODyVqcqlsDC1Gzuy8TkpiWnQZVGovw\")\n",
        "\n",
        "# Initialize the generative model\n",
        "model = genai.GenerativeModel('gemini-pro')\n",
        "\n",
        "# Generate the music genre based on user input\n",
        "prompt = userInput + \". Output ONLY the specific music genre that the user would like that fits their requirements, with no excess words with NO APOSTROPHES. You may add dd more than one genre. Desired Output: <all_lowercase_comma_separated_genres>\"\n",
        "response = model.generate_content(prompt)\n",
        "genre = response.text\n",
        "\n",
        "# Generate lyrics that fit the specified genre\n",
        "genreInput = \"Genre: \" + genre + \". Generate lyrics that would best fit into the required genre. Generate 20 lines of lyrics. Separate verses using Verse # and NO APOSTROPHES AT ALL. Desired Format: <seperate_each_verse_no_asteriks_or_apostrophes>\"\n",
        "response = model.generate_content(genreInput)\n",
        "lyrics = response.text\n",
        "\n",
        "# Generate a title for the song based on the lyrics\n",
        "lyricInput = \"Lyrics: \" + lyrics + \". Based upon the following lyrics, please generate a title for this song. Desired Format: <title_case_without_genre>\"\n",
        "response = model.generate_content(lyricInput)\n",
        "title = response.text\n",
        "\n",
        "# Split the lyrics into 10 slices and enhance each slice to describe a music video\n",
        "userInput = \"Lyrics: \" + lyrics + \". Split the following lyrics into ONLY 10 slices with each slice enhanced to describe a music video. You may slightly alter the lyrics to best cater to this requirment. Each section is separated by a |. Use only 10 |'s. Delete ALL \\n characters and Verse seperators as well. Desired Output: <|_separated>\"\n",
        "response = model.generate_content(userInput)\n",
        "sepTen = response.text\n",
        "whollySplit = sepTen.split(\"|\")\n",
        "l = len(whollySplit)\n",
        "if (len(whollySplit) >= 10):\n",
        "  l = 10\n",
        "for i in range(l):\n",
        "  resp = model.generate_content(\"Extend and alter the following lyric to make it more visual with a scenic background: \" + whollySplit[i][:25])\n",
        "  whollySplit[i] = resp.text\n",
        "if (l < 10):\n",
        "  for i in range(10 - len(whollySplit)):\n",
        "    whollySplit.append(whollySplit[l - 1])\n",
        "else:\n",
        "  whollySplit = whollySplit[:10]\n",
        "\n",
        "# Generate a video from the enhanced lyrics\n",
        "gen_movie(whollySplit)\n"
      ],
      "metadata": {
        "id": "YcFnxfiQjktb"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Video Post-Processing"
      ],
      "metadata": {
        "id": "dxwpYJru7gI7"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "from moviepy.editor import VideoFileClip, concatenate_videoclips\n",
        "\n",
        "# List of input GIF file names\n",
        "input_files = [\"animation.gif\", \"animation1.gif\", \"animation.gif\", \"animation.gif\", \"animation.gif\",\n",
        "               \"animation.gif\", \"animation.gif\", \"animation.gif\", \"animation.gif\", \"animation.gif\"]\n",
        "\n",
        "# List to store VideoFileClip objects for each input GIF\n",
        "video_clips = []\n",
        "\n",
        "# Load each input GIF file and append it to the list\n",
        "for file in input_files:\n",
        "    video_clips.append(VideoFileClip(file))\n",
        "\n",
        "# Concatenate the video clips to create a single video\n",
        "final_clip = concatenate_videoclips(video_clips)\n",
        "\n",
        "# Export the final video to a new MP4 file\n",
        "final_clip.write_videofile(\"combined_video.mp4\", codec=\"libx264\", fps=24)\n"
      ],
      "metadata": {
        "id": "5BDCPoN7DsHU"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}