├── packages.txt ├── whisper_tiktok ├── __init__.py ├── config │ ├── __init__.py │ └── logger_config.py ├── utils │ ├── __init__.py │ └── color_utils.py ├── execution │ ├── __init__.py │ └── command_executor.py ├── factories │ ├── __init__.py │ └── video_factory.py ├── interfaces │ ├── __init__.py │ ├── tts_service.py │ ├── video_downloader.py │ └── transcription_service.py ├── processors │ ├── __init__.py │ └── video_processor.py ├── services │ ├── __init__.py │ ├── tts_service.py │ ├── video_downloader.py │ ├── transcription_service.py │ └── ffmpeg_service.py ├── strategies │ ├── __init__.py │ └── processing_strategy.py ├── repositories │ ├── __init__.py │ └── video_repository.py ├── voice_manager.py ├── container.py └── main.py ├── .dockerignore ├── .github ├── FUNDING.yml ├── ISSUE_TEMPLATE │ ├── feature_request.md │ ├── bug_report.md │ └── other.md ├── workflows │ ├── ci_mkdocs.yml │ ├── ci-style-checks.yml │ └── release.yml └── pull_request_template.md ├── video.json ├── docker-compose.yml ├── Dockerfile ├── .pre-commit-config.yaml ├── mkdocs.yml ├── SECURITY.md ├── CODE_OF_CONDUCT.md ├── docs ├── 3-docker.md ├── 2-cuda.md ├── 1-ffmpeg.md └── index.md ├── pyproject.toml ├── CONTRIBUTING.md ├── .gitignore ├── README.md ├── app.py └── LICENSE /packages.txt: -------------------------------------------------------------------------------- 1 | ffmpeg 2 | -------------------------------------------------------------------------------- /whisper_tiktok/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/config/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/utils/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/execution/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/factories/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/interfaces/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/processors/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/services/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/strategies/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /whisper_tiktok/repositories/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.dockerignore: -------------------------------------------------------------------------------- 1 | .git 2 | *.log 3 | *.txt 4 | *.mp4 5 | .venv 6 | -------------------------------------------------------------------------------- /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | github: MatteoFasulo 2 | custom: "https://www.paypal.me/MatteoFasulo" 3 | -------------------------------------------------------------------------------- /video.json: -------------------------------------------------------------------------------- 1 | [ 2 | { 3 | "series":"Crazy facts that you did not know", 4 | "part":"Part 1", 5 | "text":"The King is invaluable", 6 | "outro":"Follow us for more", 7 | "tags":[ 8 | "chess", 9 | "facts", 10 | "crazy" 11 | ] 12 | } 13 | ] 14 | -------------------------------------------------------------------------------- /whisper_tiktok/interfaces/tts_service.py: -------------------------------------------------------------------------------- 1 | from abc import ABC, abstractmethod 2 | from pathlib import Path 3 | 4 | 5 | class ITTSService(ABC): 6 | """Interface for text-to-speech services.""" 7 | 8 | @abstractmethod 9 | async def synthesize(self, text: str, output_file: Path, voice: str) -> None: 10 | """Synthesize speech from text.""" 11 | -------------------------------------------------------------------------------- /whisper_tiktok/interfaces/video_downloader.py: -------------------------------------------------------------------------------- 1 | from abc import ABC, abstractmethod 2 | from pathlib import Path 3 | 4 | 5 | class IVideoDownloader(ABC): 6 | """Interface for video downloading services.""" 7 | 8 | @abstractmethod 9 | def download(self, url: str, output_dir: Path) -> Path: 10 | """Download video from URL to output directory.""" 11 | -------------------------------------------------------------------------------- /docker-compose.yml: -------------------------------------------------------------------------------- 1 | version: '3.8' 2 | 3 | services: 4 | whisper-tiktok: 5 | build: 6 | context: . 7 | dockerfile: Dockerfile 8 | ports: 9 | - "8501:8501" 10 | healthcheck: 11 | test: ["CMD", "curl", "--fail", "http://localhost:8501/_stcore/health"] 12 | interval: 30s 13 | timeout: 10s 14 | retries: 5 15 | volumes: 16 | - .:/app 17 | -------------------------------------------------------------------------------- /whisper_tiktok/interfaces/transcription_service.py: -------------------------------------------------------------------------------- 1 | from abc import ABC, abstractmethod 2 | from pathlib import Path 3 | 4 | 5 | class ITranscriptionService(ABC): 6 | """Interface for transcription services.""" 7 | 8 | @abstractmethod 9 | def transcribe( 10 | self, 11 | audio_file: Path, 12 | srt_file: Path, 13 | ass_file: Path, 14 | model: str, 15 | options: dict, 16 | ) -> tuple[Path, Path]: 17 | """Transcribe audio and generate SRT/ASS files.""" 18 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature_request.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Feature request 3 | about: Suggest an idea for this project 4 | title: "[Feature]" 5 | labels: enhancement 6 | assignees: MatteoFasulo 7 | 8 | --- 9 | 10 | **Is your feature request related to a problem? Please describe.** 11 | A clear and concise description of what the problem is. Ex. I'm always frustrated when [...] 12 | 13 | **Describe the solution you'd like** 14 | A clear and concise description of what you want to happen. 15 | 16 | **Describe alternatives you've considered** 17 | A clear and concise description of any alternative solutions or features you've considered. 18 | 19 | **Additional context** 20 | Add any other context or screenshots about the feature request here. 21 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | FROM ghcr.io/astral-sh/uv:python3.12-bookworm-slim 2 | 3 | ENV UV_LINK_MODE copy 4 | 5 | RUN apt-get update && \ 6 | apt-get install -y --no-install-recommends \ 7 | build-essential \ 8 | ffmpeg \ 9 | curl \ 10 | ca-certificates \ 11 | && rm -rf /var/lib/apt/lists/* 12 | 13 | WORKDIR /app 14 | 15 | ENV UV_COMPILE_BYTECODE=1 16 | ENV UV_NO_DEV=1 17 | ENV UV_TOOL_BIN_DIR=/usr/local/bin 18 | ENV PATH="/app/.venv/bin:$PATH" 19 | 20 | COPY pyproject.toml uv.lock /app/ 21 | 22 | RUN --mount=type=cache,target=/root/.cache/uv \ 23 | uv sync --locked --no-install-project 24 | 25 | COPY . /app 26 | 27 | RUN --mount=type=cache,target=/root/.cache/uv \ 28 | uv sync --locked 29 | 30 | EXPOSE 8501 31 | 32 | HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health 33 | 34 | CMD ["uv", "run", "streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"] 35 | -------------------------------------------------------------------------------- /whisper_tiktok/utils/color_utils.py: -------------------------------------------------------------------------------- 1 | import re 2 | 3 | 4 | def validate_hex_color(color: str) -> bool: 5 | """Validate if the input string is a valid hex color.""" 6 | pattern = r"^#?([0-9A-Fa-f]{3}|[0-9A-Fa-f]{6})$" 7 | return bool(re.match(pattern, color)) 8 | 9 | 10 | def rgb_to_bgr(rgb: str) -> str: 11 | """Convert RGB hex to BGR hex.""" 12 | # Validate input length 13 | if len(rgb) != 6 and len(rgb) != 7: 14 | raise ValueError("RGB hex must be 6 or 7 characters long (including #).") 15 | 16 | # Validate hex characters 17 | match = validate_hex_color(rgb) 18 | 19 | if not match: 20 | raise ValueError("Invalid RGB hex format.") 21 | 22 | if rgb.startswith("#"): 23 | rgb = rgb[1:] 24 | r, g, b = rgb[0:2], rgb[2:4], rgb[4:6] 25 | return b + g + r 26 | 27 | 28 | if __name__ == "__main__": 29 | # Example usage 30 | rgb_color = "#1A2B3C" 31 | bgr_color = rgb_to_bgr(rgb_color) 32 | print(f"RGB: {rgb_color} -> BGR: #{bgr_color}") 33 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/bug_report.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Bug report 3 | about: Create a report to help us improve 4 | title: "[BUG]" 5 | labels: bug, help wanted 6 | assignees: MatteoFasulo 7 | 8 | --- 9 | 10 | **Describe the bug** 11 | A clear and concise description of what the bug is. 12 | 13 | **To Reproduce** 14 | Steps to reproduce the behavior: 15 | 16 | 1. Go to '...' 17 | 2. Click on '....' 18 | 3. Scroll down to '....' 19 | 4. See error 20 | 21 | **Expected behavior** 22 | A clear and concise description of what you expected to happen. 23 | 24 | **Screenshots** 25 | If applicable, add screenshots to help explain your problem. 26 | 27 | **Desktop (please complete the following information):** 28 | 29 | - OS: [e.g. iOS] 30 | - Browser [e.g. chrome, safari] 31 | - Version [e.g. 22] 32 | 33 | **Smartphone (please complete the following information):** 34 | 35 | - Device: [e.g. iPhone6] 36 | - OS: [e.g. iOS8.1] 37 | - Browser [e.g. stock browser, safari] 38 | - Version [e.g. 22] 39 | 40 | **Additional context** 41 | Add any other context about the problem here. 42 | -------------------------------------------------------------------------------- /.github/workflows/ci_mkdocs.yml: -------------------------------------------------------------------------------- 1 | name: ci_mkdocs 2 | on: 3 | push: 4 | branches: 5 | - main 6 | - dev* 7 | permissions: 8 | contents: write 9 | jobs: 10 | deploy: 11 | runs-on: ubuntu-latest 12 | steps: 13 | - uses: actions/checkout@v6 14 | - name: Configure Git Credentials 15 | run: | 16 | git config user.name github-actions[bot] 17 | git config user.email 41898282+github-actions[bot]@users.noreply.github.com 18 | 19 | - uses: actions/setup-python@v6 20 | with: 21 | python-version: 3.12 22 | - run: echo "cache_id=$(date --utc '+%V')" >> $GITHUB_ENV 23 | 24 | - uses: actions/cache@v5 25 | with: 26 | key: mkdocs-material-${{ env.cache_id }} 27 | path: ~/.cache 28 | restore-keys: | 29 | mkdocs-material- 30 | - run: pip install mkdocs-material 31 | - run: mkdocs gh-deploy --force 32 | -------------------------------------------------------------------------------- /whisper_tiktok/services/tts_service.py: -------------------------------------------------------------------------------- 1 | from logging import Logger 2 | from pathlib import Path 3 | 4 | import edge_tts 5 | 6 | from whisper_tiktok.interfaces.tts_service import ITTSService 7 | 8 | 9 | class TTSService(ITTSService): 10 | """Text-to-Speech service using a hypothetical TTS engine.""" 11 | 12 | def __init__(self, logger: Logger): 13 | self.logger = logger 14 | 15 | async def synthesize( 16 | self, 17 | text: str, 18 | output_file: Path, 19 | voice: str = "en-US-ChristopherNeural", 20 | ) -> None: 21 | """ 22 | Synthesize speech from text and save to output file. 23 | 24 | Args: 25 | text (str): The text to be converted to speech. 26 | output_file (Path): The path to save the synthesized audio file. 27 | voice (str): The voice to be used for synthesis. 28 | """ 29 | self.logger.debug(f"Synthesizing speech to {output_file} using voice {voice}") 30 | communicate = edge_tts.Communicate(text, voice) 31 | await communicate.save(output_file.as_posix()) 32 | -------------------------------------------------------------------------------- /whisper_tiktok/voice_manager.py: -------------------------------------------------------------------------------- 1 | from typing import Any 2 | 3 | import edge_tts 4 | 5 | 6 | class VoicesManager: 7 | """Wrapper for edge_tts VoicesManager.""" 8 | 9 | @staticmethod 10 | async def create(): 11 | """Create and return voices manager object.""" 12 | return await edge_tts.VoicesManager.create() 13 | 14 | @staticmethod 15 | def find(voices, gender: str, locale: str) -> Any: 16 | """Find a voice by gender and locale. 17 | 18 | Args: 19 | voices: Voices manager object from create() 20 | gender: Gender filter (Male/Female) 21 | locale: Language locale filter (e.g., en-US) 22 | 23 | Returns: 24 | Dictionary with voice information 25 | 26 | Raises: 27 | ValueError: If no voice found 28 | """ 29 | result = voices.find(Gender=gender, Locale=locale) 30 | if not result or len(result) == 0: 31 | raise ValueError(f"No voice found for {gender} - {locale}") 32 | # Return the first result as a dict-like object 33 | return result[0] 34 | -------------------------------------------------------------------------------- /whisper_tiktok/repositories/video_repository.py: -------------------------------------------------------------------------------- 1 | import random 2 | from logging import Logger 3 | from pathlib import Path 4 | 5 | 6 | class VideoRepository: 7 | """Repository for video-related file operations.""" 8 | 9 | def __init__(self, base_path: Path, logger: Logger): 10 | self.base_path = base_path 11 | self.logger = logger 12 | 13 | def save_audio(self, uuid: str, data: bytes) -> Path: 14 | """Save audio file.""" 15 | path = self.base_path / uuid / f"{uuid}.mp3" 16 | path.parent.mkdir(parents=True, exist_ok=True) 17 | path.write_bytes(data) 18 | return path 19 | 20 | def get_background_videos(self) -> list[Path]: 21 | """Get list of available background videos.""" 22 | bg_path = self.base_path / "background" 23 | return list(bg_path.glob("*.mp4")) 24 | 25 | def random_background(self) -> Path: 26 | """Get random background video.""" 27 | videos = self.get_background_videos() 28 | if not videos: 29 | raise ValueError("No background videos available") 30 | return random.choice(videos) 31 | -------------------------------------------------------------------------------- /.github/workflows/ci-style-checks.yml: -------------------------------------------------------------------------------- 1 | name: CI Style Checks 2 | 3 | on: 4 | push: 5 | branches: 6 | - main 7 | - dev* 8 | pull_request: 9 | paths-ignore: 10 | - "*.md" 11 | 12 | jobs: 13 | style: 14 | name: Style Checks 15 | runs-on: ubuntu-latest 16 | strategy: 17 | matrix: 18 | python-version: ["3.11", "3.12"] 19 | steps: 20 | - name: Checkout Repo 21 | uses: actions/checkout@v6 22 | 23 | - name: Install uv and set the python version 24 | uses: astral-sh/setup-uv@v7 25 | with: 26 | python-version: ${{ matrix.python-version }} 27 | enable-cache: true 28 | 29 | - name: Pre-install 30 | run: | 31 | sudo apt-get update 32 | sudo apt-get -y -q install ffmpeg libavcodec-extra 33 | 34 | - name: Install the project 35 | run: uv sync --extra dev 36 | 37 | - name: ruff 38 | run: uv run ruff check whisper_tiktok 39 | 40 | - name: black 41 | run: uv run black --line-length 88 --check whisper_tiktok 42 | 43 | - name: mypy 44 | run: uv run mypy whisper_tiktok 45 | 46 | - name: pylint 47 | run: uv run pylint --fail-under=9.6 whisper_tiktok 48 | -------------------------------------------------------------------------------- /.github/workflows/release.yml: -------------------------------------------------------------------------------- 1 | name: Create and publish a Docker image 2 | 3 | on: 4 | push: 5 | branches: 6 | - main 7 | pull_request: 8 | branches: 9 | - main 10 | env: 11 | REGISTRY: ghcr.io 12 | IMAGE_NAME: ${{ github.repository }} 13 | 14 | jobs: 15 | build-and-push-image: 16 | runs-on: ubuntu-latest 17 | permissions: 18 | contents: read 19 | packages: write 20 | # 21 | steps: 22 | - name: Checkout repository 23 | uses: actions/checkout@v6 24 | - name: Log in to the Container registry 25 | uses: docker/login-action@v3 26 | with: 27 | registry: ${{ env.REGISTRY }} 28 | username: ${{ github.actor }} 29 | password: ${{ secrets.GITHUB_TOKEN }} 30 | - name: Extract metadata (tags, labels) for Docker 31 | id: meta 32 | uses: docker/metadata-action@v5 33 | with: 34 | images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} 35 | - name: Build and push Docker image 36 | uses: docker/build-push-action@v6 37 | with: 38 | context: . 39 | push: ${{ github.event_name != 'pull_request' }} 40 | tags: ${{ steps.meta.outputs.tags }} 41 | labels: ${{ steps.meta.outputs.labels }} 42 | -------------------------------------------------------------------------------- /whisper_tiktok/services/video_downloader.py: -------------------------------------------------------------------------------- 1 | from logging import Logger 2 | from pathlib import Path 3 | 4 | from whisper_tiktok.execution.command_executor import CommandExecutor 5 | from whisper_tiktok.interfaces.video_downloader import IVideoDownloader 6 | 7 | 8 | class VideoDownloadError(Exception): 9 | """Custom exception for video download errors.""" 10 | 11 | 12 | class VideoDownloaderService(IVideoDownloader): 13 | """YouTube video downloader using yt-dlp.""" 14 | 15 | def __init__(self, executor: CommandExecutor, logger: Logger): 16 | self.executor = executor 17 | self.logger = logger 18 | 19 | def download(self, url: str, output_dir: Path) -> Path: 20 | """Download video from URL.""" 21 | output_dir.mkdir(parents=True, exist_ok=True) 22 | 23 | command = rf"yt-dlp -f bestvideo[ext=mp4] --restrict-filenames -o %(id)s.%(ext)s {url}" 24 | result = self.executor.execute(command, cwd=output_dir) 25 | 26 | if result.returncode != 0: 27 | raise VideoDownloadError(f"Failed to download: {result.stderr}") 28 | 29 | # Find downloaded file 30 | videos = list(output_dir.glob("*.mp4")) 31 | if not videos: 32 | raise VideoDownloadError("No video file found after download") 33 | 34 | return videos[-1] # Most recent 35 | -------------------------------------------------------------------------------- /whisper_tiktok/services/transcription_service.py: -------------------------------------------------------------------------------- 1 | from pathlib import Path 2 | 3 | import stable_whisper 4 | import torch 5 | 6 | from whisper_tiktok.interfaces.transcription_service import ITranscriptionService 7 | 8 | 9 | class TranscriptionService(ITranscriptionService): 10 | """Service for transcribing audio using Whisper.""" 11 | 12 | def __init__(self, logger): 13 | self.logger = logger 14 | 15 | def transcribe( 16 | self, 17 | audio_file: Path, 18 | srt_file: Path, 19 | ass_file: Path, 20 | model: str, 21 | options: dict, 22 | ) -> tuple[Path, Path]: 23 | self.logger.debug( 24 | f"Transcribing {audio_file} with model {model} and options {options}" 25 | ) 26 | 27 | whisper_model = stable_whisper.load_model( 28 | model, device=torch.device("cuda" if torch.cuda.is_available() else "cpu") 29 | ) 30 | self.logger.debug(f"Loaded Whisper model: {model}") 31 | 32 | transcription = whisper_model.transcribe( 33 | audio_file.as_posix(), 34 | regroup=True, 35 | fp16=False, 36 | word_timestamps=True, 37 | ) 38 | transcription.to_srt_vtt(srt_file.as_posix(), word_level=True) 39 | transcription.to_ass(ass_file.as_posix(), word_level=True, **options) 40 | return (srt_file, ass_file) 41 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/other.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Other 3 | about: Whatever does not apply to a bug nor to a feature request 4 | title: "[Other]" 5 | labels: help wanted, question 6 | assignees: MatteoFasulo 7 | 8 | --- 9 | 10 | ## Prerequisites 11 | 12 | Please answer the following questions for yourself before submitting an issue. 13 | 14 | - [ ] I am running the latest version 15 | - [ ] I checked the documentation and found no answer 16 | - [ ] I checked to make sure that this issue has not already been filed 17 | - [ ] I'm reporting the issue to the correct repository (for multi-repository projects) 18 | 19 | ## Expected Behavior 20 | 21 | Please describe the behavior you are expecting 22 | 23 | ## Current Behavior 24 | 25 | What is the current behavior? 26 | 27 | ## Failure Information (for bugs) 28 | 29 | Please help provide information about the failure if this is a bug. If it is not a bug, please remove the rest of this template. 30 | 31 | ## Steps to Reproduce 32 | 33 | Please provide detailed steps for reproducing the issue. 34 | 35 | 1. step 1 36 | 2. step 2 37 | 3. you get it... 38 | 39 | ## Context 40 | 41 | Please provide any relevant information about your setup. This is important in case the issue is not reproducible except for under certain conditions. 42 | 43 | - Operating System: 44 | 45 | ## Failure Logs 46 | 47 | Please include any relevant log snippets or files here. 48 | -------------------------------------------------------------------------------- /.github/pull_request_template.md: -------------------------------------------------------------------------------- 1 | # Pull Request 2 | 3 | ## Summary 4 | 5 | Please include a brief description of the purpose of this pull request. 6 | 7 | ## Motivation & Context 8 | 9 | - Why is this change necessary? 10 | - What problem does it solve? 11 | - Reference any relevant GitHub issues (e.g., fixes #123). 12 | 13 | ## Changes Introduced 14 | 15 | Provide a clear description of the changes made, including: 16 | 17 | - Major features added 18 | - Bugs fixed 19 | - Refactoring and improvements 20 | - Other relevant updates 21 | 22 | ## Checklist 23 | 24 | Please review and check the following items before submitting your pull request: 25 | 26 | - [ ] I have tested my changes thoroughly. 27 | - [ ] My code follows the project's coding style guidelines. 28 | - [ ] I have updated documentation, if necessary. 29 | - [ ] All existing tests pass successfully. 30 | - [ ] I have added new tests, if applicable. 31 | - [ ] I have reviewed my code to ensure it is clean and efficient. 32 | - [ ] I have added any required comments or explanations for complex code changes. 33 | 34 | --- 35 | 36 | ## Screenshots (if applicable) 37 | 38 | If your pull request includes changes to the user interface, please provide screenshots to visually demonstrate the changes. 39 | 40 | ## Additional Notes 41 | 42 | Include any additional information or notes about your pull request that may be helpful for reviewers. 43 | -------------------------------------------------------------------------------- /whisper_tiktok/config/logger_config.py: -------------------------------------------------------------------------------- 1 | """Logger configuration module.""" 2 | 3 | import logging 4 | import sys 5 | from pathlib import Path 6 | 7 | 8 | def setup_logger(log_dir: Path, log_level: str = "INFO") -> logging.Logger: 9 | """ 10 | Configure and return a logger instance. 11 | 12 | Args: 13 | log_dir: Directory to store log files 14 | log_level: Logging level (DEBUG, INFO, WARNING, ERROR, CRITICAL) 15 | 16 | Returns: 17 | Configured logger instance 18 | """ 19 | log_dir.mkdir(parents=True, exist_ok=True) 20 | 21 | logger = logging.getLogger("whisper_tiktok") 22 | logger.setLevel(getattr(logging, log_level.upper())) 23 | 24 | # Clear existing handlers 25 | logger.handlers.clear() 26 | 27 | # Create formatters 28 | detailed_formatter = logging.Formatter( 29 | "%(asctime)s - %(name)s - %(levelname)s - %(message)s" 30 | ) 31 | simple_formatter = logging.Formatter("%(levelname)s: %(message)s") 32 | 33 | # File handler 34 | file_handler = logging.FileHandler(log_dir / "app.log", encoding="utf-8") 35 | file_handler.setLevel(logging.DEBUG) 36 | file_handler.setFormatter(detailed_formatter) 37 | logger.addHandler(file_handler) 38 | 39 | # Console handler 40 | console_handler = logging.StreamHandler(sys.stdout) 41 | console_handler.setLevel(getattr(logging, log_level.upper())) 42 | console_handler.setFormatter(simple_formatter) 43 | logger.addHandler(console_handler) 44 | 45 | return logger 46 | -------------------------------------------------------------------------------- /.pre-commit-config.yaml: -------------------------------------------------------------------------------- 1 | repos: 2 | - repo: https://github.com/pre-commit/pre-commit-hooks 3 | rev: v6.0.0 4 | hooks: 5 | - id: check-ast 6 | - id: check-docstring-first 7 | - id: check-merge-conflict 8 | - id: check-toml 9 | - id: debug-statements 10 | - id: end-of-file-fixer 11 | - id: trailing-whitespace 12 | - id: check-added-large-files 13 | - id: check-json 14 | - id: detect-private-key 15 | 16 | - repo: https://github.com/psf/black 17 | rev: 25.12.0 18 | hooks: 19 | - id: black 20 | name: black (format) 21 | args: ["--line-length=88"] 22 | 23 | - repo: https://github.com/PyCQA/isort 24 | rev: 7.0.0 25 | hooks: 26 | - id: isort 27 | name: isort (sort imports) 28 | 29 | - repo: https://github.com/astral-sh/ruff-pre-commit 30 | rev: v0.14.9 31 | hooks: 32 | - id: ruff 33 | name: ruff (lint) 34 | args: [--fix] 35 | - id: ruff-format 36 | name: ruff (format) 37 | 38 | - repo: https://github.com/pre-commit/mirrors-mypy 39 | rev: v1.19.0 40 | hooks: 41 | - id: mypy 42 | name: mypy (type check) 43 | args: [--ignore-missing-imports] 44 | 45 | - repo: https://github.com/PyCQA/bandit 46 | rev: 1.9.2 47 | hooks: 48 | - id: bandit 49 | name: bandit (security check) 50 | args: [-ll] 51 | 52 | - repo: https://github.com/astral-sh/uv-pre-commit 53 | rev: 0.9.17 54 | hooks: 55 | - id: uv-lock 56 | - id: uv-export 57 | -------------------------------------------------------------------------------- /mkdocs.yml: -------------------------------------------------------------------------------- 1 | site_name: Whisper-TikTok 2 | theme: 3 | name: material 4 | features: 5 | - navigation.tabs 6 | - navigation.sections 7 | - toc.integrate 8 | - navigation.top 9 | - search.suggest 10 | - search.highlight 11 | - content.tabs.link 12 | - content.code.annotate 13 | - content.code.copy 14 | language: en 15 | palette: 16 | - scheme: default 17 | toggle: 18 | icon: material/toggle-switch-off-outline 19 | name: Switch to dark mode 20 | primary: teal 21 | accent: purple 22 | - scheme: slate 23 | toggle: 24 | icon: material/toggle-switch 25 | name: Switch to light mode 26 | primary: teal 27 | accent: lime 28 | 29 | extra: 30 | social: 31 | - icon: fontawesome/brands/github-alt 32 | link: https://github.com/MatteoFasulo 33 | - icon: fontawesome/brands/linkedin 34 | link: https://www.linkedin.com/in/matteofasulo/ 35 | 36 | markdown_extensions: 37 | - pymdownx.highlight: 38 | anchor_linenums: true 39 | - pymdownx.inlinehilite 40 | - pymdownx.snippets 41 | - admonition 42 | - pymdownx.arithmatex: 43 | generic: true 44 | - footnotes 45 | - pymdownx.superfences 46 | - pymdownx.mark 47 | - attr_list 48 | - pymdownx.emoji: 49 | emoji_index: !!python/name:material.extensions.emoji.twemoji 50 | emoji_generator: !!python/name:material.extensions.emoji.to_svg 51 | 52 | copyright: | 53 | © 2023 Matteo Fasulo 54 | -------------------------------------------------------------------------------- /SECURITY.md: -------------------------------------------------------------------------------- 1 | # Security Policy 2 | 3 | ## Supported Versions 4 | 5 | | Version | Supported | 6 | | ------- | ------------------ | 7 | | 2.0.x | :white_check_mark: | 8 | | < 1.0 | :x: | 9 | 10 | ## Reporting a Vulnerability 11 | 12 | If you discover a security vulnerability in this project, please follow these steps to report it: 13 | 14 | 1. **Ensure Your Findings Are Valid**: Before reporting a vulnerability, please ensure it is a genuine security issue. Avoid making it public until it has been resolved. 15 | 16 | 2. **Contact Us Privately**: Send an email to [info@matteofasulo.com](mailto:info@matteofasulo.com) with details about the vulnerability. Include the following information: 17 | - A brief description of the vulnerability. 18 | - Steps to reproduce or a proof-of-concept. 19 | - Affected versions (if known). 20 | - Any additional information that may be relevant. 21 | 22 | 3. **Expect a Response**: You should receive an acknowledgment of your report within 24 hours. We will work with you to verify and understand the issue. 23 | 24 | 4. **Resolution Timeline**: The time to resolve the issue may vary depending on its complexity and severity. We will keep you informed of our progress and let you know when we expect to release a fix. 25 | 26 | 5. **Public Disclosure**: Once the issue is resolved, we will coordinate with you on when and how the vulnerability will be publicly disclosed. We typically aim to do this responsibly and after providing a fix to affected versions. 27 | 28 | 6. **Credit**: If you report a valid security vulnerability that leads to a fix, you may be eligible for public acknowledgment and credit in our release notes or on our website. Please let us know if you wish to be credited. 29 | 30 | Thank you for helping us keep our project secure. 31 | -------------------------------------------------------------------------------- /whisper_tiktok/container.py: -------------------------------------------------------------------------------- 1 | import logging 2 | from pathlib import Path 3 | 4 | from dependency_injector import containers, providers 5 | 6 | from whisper_tiktok.execution.command_executor import CommandExecutor 7 | from whisper_tiktok.services.ffmpeg_service import FFmpegService 8 | from whisper_tiktok.services.transcription_service import TranscriptionService 9 | from whisper_tiktok.services.tts_service import TTSService 10 | from whisper_tiktok.services.video_downloader import VideoDownloaderService 11 | 12 | 13 | class Container(containers.DeclarativeContainer): 14 | """IoC container for dependency injection.""" 15 | 16 | config = providers.Configuration() 17 | 18 | # Path providers 19 | workspace_path = providers.Singleton(lambda: Path.cwd()) 20 | 21 | media_path = providers.Factory( 22 | lambda workspace, uuid: workspace / "media" / uuid, 23 | workspace=workspace_path, 24 | uuid=providers.Dependency(), 25 | ) 26 | 27 | output_path = providers.Factory( 28 | lambda workspace, uuid: workspace / "output" / uuid, 29 | workspace=workspace_path, 30 | uuid=providers.Dependency(), 31 | ) 32 | 33 | # Service providers 34 | logger = providers.Singleton(lambda: logging.getLogger("whisper_tiktok")) 35 | 36 | command_executor = providers.Factory(CommandExecutor, logger=logger) 37 | 38 | ffmpeg_service = providers.Factory( 39 | FFmpegService, executor=command_executor, logger=logger 40 | ) # Changed 41 | 42 | video_downloader = providers.Factory( 43 | VideoDownloaderService, 44 | executor=command_executor, # Changed from ffmpeg_service 45 | logger=logger, 46 | ) 47 | 48 | tts_service = providers.Factory(TTSService, logger=logger) 49 | 50 | transcription_service = providers.Factory(TranscriptionService, logger=logger) 51 | 52 | # Additional service providers can be added here 53 | -------------------------------------------------------------------------------- /whisper_tiktok/execution/command_executor.py: -------------------------------------------------------------------------------- 1 | import subprocess 2 | from dataclasses import dataclass 3 | from logging import Logger 4 | from pathlib import Path 5 | 6 | 7 | class CommandExecutionError(Exception): 8 | """Custom exception for command execution errors.""" 9 | 10 | 11 | class CommandTimeoutError(Exception): 12 | """Custom exception for command timeouts.""" 13 | 14 | 15 | @dataclass 16 | class ExecutionResult: 17 | """Result of command execution.""" 18 | 19 | returncode: int 20 | stdout: str 21 | stderr: str 22 | 23 | @property 24 | def success(self) -> bool: 25 | """Indicates if the command executed successfully.""" 26 | return self.returncode == 0 27 | 28 | 29 | class CommandExecutor: 30 | """Executes external commands with error handling.""" 31 | 32 | def __init__(self, logger: Logger): 33 | self.logger = logger 34 | 35 | def execute( 36 | self, command: str, cwd: Path | None = None, timeout: int | None = None 37 | ) -> ExecutionResult: 38 | """Execute command and return result.""" 39 | 40 | self.logger.debug(f"Executing: {command}") 41 | try: 42 | with subprocess.Popen( 43 | command, 44 | cwd=cwd, 45 | stdout=subprocess.PIPE, 46 | stderr=subprocess.PIPE, 47 | text=True, 48 | ) as process: 49 | stdout, stderr = process.communicate(timeout=timeout) 50 | result = ExecutionResult( 51 | returncode=process.returncode, stdout=stdout, stderr=stderr 52 | ) 53 | return result 54 | except subprocess.TimeoutExpired as exc: 55 | self.logger.error(f"Command timed out: {command}") 56 | raise CommandTimeoutError(f"Command timed out after {timeout}s") from exc 57 | except Exception as exc: 58 | self.logger.exception(f"Command execution failed: {command}") 59 | raise CommandExecutionError(str(exc)) from exc 60 | -------------------------------------------------------------------------------- /whisper_tiktok/factories/video_factory.py: -------------------------------------------------------------------------------- 1 | import uuid 2 | 3 | from whisper_tiktok.container import Container 4 | from whisper_tiktok.processors.video_processor import VideoProcessor 5 | from whisper_tiktok.strategies.processing_strategy import ( 6 | DownloadBackgroundStrategy, 7 | ProcessingStrategy, 8 | TikTokUploadStrategy, 9 | TranscriptionStrategy, 10 | TTSGenerationStrategy, 11 | VideoCompositionStrategy, 12 | ) 13 | 14 | 15 | class VideoCreatorFactory: 16 | """Factory for creating video processor instances.""" 17 | 18 | def __init__(self, container: Container): 19 | self.container = container 20 | 21 | def create_processor(self, video_data: dict, config: dict) -> VideoProcessor: 22 | """Create a configured video processor.""" 23 | uuid_str = str(uuid.uuid4()) 24 | 25 | return VideoProcessor( 26 | uuid=uuid_str, 27 | video_data=video_data, 28 | config=config, 29 | strategies=self._build_strategies(config), 30 | logger=self.container.logger(), 31 | ) 32 | 33 | def _build_strategies(self, config: dict) -> list[ProcessingStrategy]: 34 | """Build processing pipeline based on config.""" 35 | strategies = [ 36 | DownloadBackgroundStrategy( 37 | self.container.video_downloader(), self.container.logger() 38 | ), 39 | TTSGenerationStrategy( 40 | self.container.tts_service(), self.container.logger() 41 | ), 42 | TranscriptionStrategy( 43 | self.container.transcription_service(), self.container.logger() 44 | ), 45 | VideoCompositionStrategy( 46 | self.container.ffmpeg_service(), self.container.logger() 47 | ), 48 | ] 49 | 50 | if config.get("upload_tiktok"): 51 | strategies.append( 52 | TikTokUploadStrategy(self.container.uploader(), self.container.logger()) 53 | ) 54 | 55 | return strategies 56 | -------------------------------------------------------------------------------- /CODE_OF_CONDUCT.md: -------------------------------------------------------------------------------- 1 | # Code of Conduct 2 | 3 | We expect all contributors and participants in the Reddit Video Maker Bot project to adhere to the following code of conduct. We want to create a welcoming and inclusive community where everyone feels respected and valued, regardless of their background, experience, or personal beliefs. 4 | 5 | ## Our Standards 6 | 7 | Examples of behavior that contribute to creating a positive environment include: 8 | 9 | - Being respectful and considerate towards others, their opinions, and their work. 10 | - Using welcoming and inclusive language. 11 | - Showing empathy towards other contributors and participants. 12 | - Being open to constructive feedback and criticism. 13 | - Focusing on what is best for the community and the project. 14 | 15 | Examples of unacceptable behavior include: 16 | 17 | - Using derogatory, offensive, or discriminatory language or behavior. 18 | - Trolling, insulting, or derogatory comments or personal attacks. 19 | - Engaging in any form of harassment or intimidation, including but not limited to sexual harassment, racism, and hate speech. 20 | - Public or private harassment, insults, or threats against anyone. 21 | - Publishing or communicating private information about others without their consent. 22 | - Other conduct that would be considered inappropriate in a professional setting. 23 | 24 | ## Enforcement 25 | 26 | We take this code of conduct seriously and will enforce it to the best of our ability. We expect all participants to follow these guidelines at all times, and any behavior that violates these standards may result in a warning or, in extreme cases, expulsion from the project. 27 | 28 | If you witness or experience behavior that violates this code of conduct, please contact the project maintainers or send an email to the project email address with the subject line "Code of Conduct Violation." All complaints will be reviewed and investigated, and appropriate action will be taken. 29 | 30 | ## Attribution 31 | 32 | This code of conduct is adapted from the [Contributor Covenant](https://www.contributor-covenant.org), version 2.0, available at https://www.contributor-covenant.org/version/2/0/code_of_conduct.html. 33 | -------------------------------------------------------------------------------- /whisper_tiktok/processors/video_processor.py: -------------------------------------------------------------------------------- 1 | from dataclasses import dataclass 2 | from logging import Logger 3 | from pathlib import Path 4 | 5 | from whisper_tiktok.strategies.processing_strategy import ( 6 | ProcessingContext, 7 | ProcessingStrategy, 8 | ) 9 | 10 | 11 | @dataclass 12 | class ProcessingResult: 13 | """Result of video processing.""" 14 | 15 | uuid: str 16 | output_path: Path 17 | success: bool = True 18 | 19 | 20 | class VideoProcessor: 21 | """Main orchestrator for video processing pipeline.""" 22 | 23 | def __init__( 24 | self, 25 | uuid: str, 26 | video_data: dict, 27 | config: dict, 28 | strategies: list[ProcessingStrategy], 29 | logger: Logger, 30 | ): 31 | self.uuid = uuid 32 | self.video_data = video_data 33 | self.config = config 34 | self.strategies = strategies 35 | self.logger = logger 36 | 37 | async def process(self) -> ProcessingResult: 38 | """Execute the processing pipeline.""" 39 | 40 | # Initialize context 41 | media_path = Path(self.config.get("workspace_path", ".")) / "media" / self.uuid 42 | output_path = ( 43 | Path(self.config.get("workspace_path", ".")) / "output" / self.uuid 44 | ) 45 | 46 | media_path.mkdir(parents=True, exist_ok=True) 47 | output_path.mkdir(parents=True, exist_ok=True) 48 | 49 | context = ProcessingContext( 50 | video_data=self.video_data, 51 | uuid=self.uuid, 52 | media_path=media_path, 53 | output_path=output_path, 54 | config=self.config, 55 | ) 56 | 57 | # Execute each strategy 58 | try: 59 | for strategy in self.strategies: 60 | self.logger.info(f"Executing strategy: {strategy.__class__.__name__}") 61 | context = await strategy.execute(context) 62 | 63 | output_file = context.output_path / f"{self.uuid}.mp4" 64 | 65 | return ProcessingResult( 66 | uuid=self.uuid, 67 | output_path=output_file, 68 | success=True, 69 | ) 70 | except Exception: 71 | self.logger.exception(f"Processing failed for video {self.uuid}") 72 | raise 73 | -------------------------------------------------------------------------------- /docs/3-docker.md: -------------------------------------------------------------------------------- 1 | # Docker Image for Whisper-TikTok 2 | 3 | In this guide, we'll walk you through the process of using the dockerized version of the Whisper-TikTok model. Docker is a platform that allows you to package applications and their dependencies into containers, making it easy to run them on any system without worrying about compatibility issues. 4 | 5 | ## Table of Contents 6 | 7 | 1. [Prerequisites](#prerequisites) 8 | 2. [Pull the image](#pulling-the-image) 9 | 3. [Run the container](#run-the-container) 10 | 11 | --- 12 | 13 | ## Prerequisites 14 | 15 | Before you begin, make sure you have Docker installed on your system. If you don't have Docker installed, you can follow the [official installation guide](https://docs.docker.com/get-docker/) to set it up. 16 | 17 | ## Pull the image 18 | 19 | To use the Whisper-TikTok model in a Docker container, you first need to pull the Docker image from the [ghcr repository](https://github.com/MatteoFasulo/Whisper-TikTok/pkgs/container/whisper-tiktok). You can do this by running the following command in your terminal: 20 | 21 | ```sh 22 | docker pull ghcr.io/matteofasulo/whisper-tiktok:main 23 | ``` 24 | 25 | This command will download the latest version of the Whisper-TikTok Docker image to your system. 26 | 27 | ## Run the container 28 | 29 | Once you have pulled the Docker image, you can run the container using the following command: 30 | 31 | ```sh 32 | docker run -d --name whisper-tiktok --network host --mount source=whisper-tiktok-vol,target=/app ghcr.io/matteofasulo/whisper-tiktok:main 33 | ``` 34 | 35 | This command will start the Whisper-TikTok container in detached mode, using the host network and mounting a volume to store the model checkpoints and logs. You can now access the Whisper-TikTok API at `http://localhost:8000`. 36 | 37 | To stop the container, you can run the following command: 38 | 39 | ```sh 40 | docker stop whisper-tiktok 41 | ``` 42 | 43 | And to remove the container, you can use: 44 | 45 | ```sh 46 | docker rm whisper-tiktok 47 | ``` 48 | 49 | If you want to inspect the container volume to retrieve the output files, you can use the following command: 50 | 51 | ```sh 52 | docker volume inspect whisper-tiktok-vol 53 | ``` 54 | 55 | This will provide you with the path to the volume on your system. Navigate to that path to access the model outputs. 56 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "whisper-tiktok" 3 | version = "2.0.3" 4 | description = "A TikTok video creation tool using Whisper ASR and EdgeTTS" 5 | authors = [ 6 | { name="Matteo Fasulo", email="info@matteofasulo.com" }, 7 | ] 8 | license = "Apache-2.0" 9 | readme = "README.md" 10 | requires-python = ">=3.11" 11 | dependencies = [ 12 | "dependency-injector>=4.0,<5.0", 13 | "edge-tts==7.2.6", 14 | "numpy>=2.3.5", 15 | "openai-whisper>=20250625", 16 | "pre-commit>=4.5.0", 17 | "rich>=14.2.0", 18 | "stable-ts>=2.19.1", 19 | "streamlit>=1.52.1", 20 | "tiktok-uploader>=1.1.5", 21 | "torch>=2.6.0,<2.8.0", 22 | "tqdm>=4.67.1", 23 | "typer>=0.20.0", 24 | "yt-dlp>=2025.11.12", 25 | ] 26 | 27 | [project.optional-dependencies] 28 | dev = [ 29 | "pytest", 30 | "pytest-cov", 31 | "pytest-asyncio", 32 | "anyio", 33 | "black", 34 | "isort", 35 | "ruff", 36 | "pylint", 37 | "mypy", 38 | "bandit", 39 | "mkdocs-material", 40 | ] 41 | 42 | [tool.setuptools.packages] 43 | find = {} 44 | 45 | [tool.isort] 46 | py_version = 311 47 | profile = "black" 48 | line_length = 88 49 | 50 | [tool.black] 51 | line-length = 88 52 | target-version = ['py311', 'py312'] 53 | 54 | [tool.mypy] 55 | python_version = "3.11" 56 | warn_return_any = true 57 | warn_unused_configs = true 58 | ignore_missing_imports = true 59 | disallow_untyped_defs = false 60 | 61 | [tool.pylint.messages_control] 62 | disable = [ 63 | "C0103", # invalid-name 64 | "C0114", # missing-module-docstring 65 | "R0903", # too-few-public-methods 66 | ] 67 | 68 | [tool.pytest.ini_options] 69 | testpaths = ["tests"] 70 | python_files = ["test_*.py"] 71 | addopts = "-v --strict-markers" 72 | 73 | [tool.ruff] 74 | line-length = 88 75 | target-version = "py311" 76 | lint.select = [ 77 | "E", # pycodestyle errors 78 | "W", # pycodestyle warnings 79 | "F", # Pyflakes 80 | "I", # isort 81 | "C", # flake8-comprehensions 82 | "B", # flake8-bugbear 83 | ] 84 | lint.ignore = ["E501"] # line too long (handled by black) 85 | 86 | [tool.ruff.lint.mccabe] 87 | # Flag errors (`C901`) whenever the complexity level exceeds 5. 88 | max-complexity = 20 89 | 90 | [tool.pylint.main] 91 | extension-pkg-allow-list = ["dependency_injector.containers"] 92 | 93 | [tool.uv.sources] 94 | torch = [ 95 | { index = "pytorch-cu126" }, 96 | ] 97 | 98 | [[tool.uv.index]] 99 | name = "pytorch-cu126" 100 | url = "https://download.pytorch.org/whl/cu126" 101 | explicit = true 102 | 103 | [[tool.mypy.overrides]] 104 | module = ["tiktok_uploader.*", "stable_whisper.*"] 105 | follow_imports = "skip" 106 | -------------------------------------------------------------------------------- /CONTRIBUTING.md: -------------------------------------------------------------------------------- 1 | # Contributing to Whisper-TikTok 2 | 3 | Thank you for your interest in contributing to our project! We appreciate your support and look forward to working with you. 4 | 5 | ## Getting Started 6 | 7 | Before contributing to our project, we recommend that you familiarize yourself with our project's [code of conduct](CODE_OF_CONDUCT.md). We also encourage you to review the [existing issues](https://github.com/MatteoFasulo/Whisper-TikTok/issues) and [pull requests](https://github.com/MatteoFasulo/Whisper-TikTok/pulls) to get an idea of what needs to be done and to avoid duplicating efforts. 8 | 9 | ## Ways to Contribute 10 | 11 | ### Reporting Issues 12 | 13 | If you encounter any bugs or issues, please let us know by creating an issue in our project's [issue tracker](https://github.com/MatteoFasulo/Whisper-TikTok/issues). When reporting an issue, please include as much detail as possible, such as a clear and descriptive title, a step-by-step description of the problem, and any relevant screenshots or error messages. 14 | 15 | ### Suggesting Enhancements 16 | 17 | We welcome suggestions for new features or enhancements to our project! Please create an issue in our project's [issue tracker](https://github.com/MatteoFasulo/Whisper-TikTok/issues) and describe the new feature or enhancement you'd like to see. Be sure to provide as much detail as possible, such as why you think the feature would be useful, any relevant use cases, and any potential challenges or limitations. 18 | 19 | ### Contributing Code 20 | 21 | We appreciate contributions of all kinds, including code contributions! Before contributing code, please make sure to do the following: 22 | 23 | 1. Review the [existing issues](https://github.com/MatteoFasulo/Whisper-TikTok/issues) and [pull requests](https://github.com/MatteoFasulo/Whisper-TikTok/pulls) to make sure your proposed changes haven't already been addressed. 24 | 2. Familiarize yourself with our project's code structure and development practices. 25 | 3. Create a fork of our project and make your changes in a new branch. 26 | 4. Submit a pull request with a clear and descriptive title, a detailed description of the changes you made, and any relevant screenshots or code snippets. 27 | 28 | Please note that all code contributions are subject to review and may require changes before they can be merged into the main project. 29 | 30 | ### Improving Documentation 31 | 32 | Improving project documentation is also a valuable contribution! If you notice any errors or areas where the documentation could be improved, please create an issue in our project's [issue tracker](https://github.com/MatteoFasulo/Whisper-TikTok/issues) or submit a pull request with your proposed changes. 33 | 34 | ## Code of Conduct 35 | 36 | Our project has a code of conduct to ensure that all contributors feel welcome and valued. Please review the [CODE_OF_CONDUCT.md](CODE_OF_CONDUCT.md) file before contributing to our project. 37 | 38 | ## Conclusion 39 | 40 | We appreciate your interest in contributing to our project and look forward to your contributions. If you have any questions or need any help, please don't hesitate to reach out to us through the issue tracker or by email. 41 | -------------------------------------------------------------------------------- /docs/2-cuda.md: -------------------------------------------------------------------------------- 1 | # Installing CUDA Driver for GPU Acceleration 2 | 3 | To harness the power of GPU acceleration for the OpenAI Whisper model with PyTorch, you'll need to install the CUDA driver on your system. CUDA is a parallel computing platform and API developed by NVIDIA that allows GPUs to perform complex computations much faster than traditional CPUs. This guide will walk you through the process of installing the CUDA driver step by step. 4 | 5 | ## Table of Contents 6 | 7 | 1. [Prerequisites](#prerequisites) 8 | 2. [Installing CUDA Driver](#installing-cuda-driver) 9 | 3. [Verifying CUDA Installation](#verifying-cuda-installation) 10 | 11 | --- 12 | 13 | ## Prerequisites 14 | 15 | Before you begin, make sure you have the following prerequisites in place: 16 | 17 | - A compatible NVIDIA GPU: CUDA requires an NVIDIA GPU that supports CUDA. You can check the list of supported GPUs on the NVIDIA website. 18 | 19 | - Operating System: CUDA is available for various operating systems, including Windows, Linux, and macOS. Ensure you are using a supported OS. 20 | 21 | - NVIDIA Driver: Make sure you have the latest NVIDIA driver installed for your GPU. You can download it from the official NVIDIA website. 22 | 23 | --- 24 | 25 | ## Installing CUDA Driver 26 | 27 | Follow these steps to install the CUDA driver on your system: 28 | 29 | ### Step 1: Download CUDA Toolkit 30 | 31 | 1. Visit the official NVIDIA CUDA Toolkit download page: [https://developer.nvidia.com/cuda-downloads](https://developer.nvidia.com/cuda-downloads). 32 | 33 | 2. Select your operating system and architecture. Choose the version that matches your system. 34 | 35 | 3. Click the "Download" button to start the download. 36 | 37 | ### Step 2: Run the Installer 38 | 39 | 1. Once the download is complete, run the CUDA Toolkit installer. 40 | 41 | 2. Follow the on-screen instructions to install CUDA. You can customize the installation options, but it's recommended to install the default components unless you have specific requirements. 42 | 43 | 3. During the installation, you may be prompted to install the NVIDIA driver if it's not already installed. Follow the prompts to complete the driver installation. 44 | 45 | 4. CUDA will also prompt you to install the CUDA Toolkit and CUDA Samples. Install both components. 46 | 47 | ### Step 3: Environment Setup 48 | 49 | 1. After the installation is complete, you need to add CUDA to your system's PATH environment variable. 50 | 51 | - **Windows:** CUDA will automatically add itself to the system PATH during installation. You may need to restart your computer for the changes to take effect. 52 | 53 | - **Linux:** You can add CUDA to your PATH by appending the following line to your shell profile file (e.g., `~/.bashrc` or `~/.zshrc`): 54 | 55 | ```sh 56 | export PATH=/usr/local/cuda/bin:$PATH 57 | ``` 58 | 59 | - **macOS:** CUDA should also be added to your PATH automatically on macOS. Restart your terminal for the changes to apply. 60 | 61 | ### Step 4: Reboot Your System 62 | 63 | 1. To ensure that the changes are applied correctly, it's recommended to reboot your system. 64 | 65 | --- 66 | 67 | ## Verifying CUDA Installation 68 | 69 | To verify that CUDA is installed correctly, follow these steps: 70 | 71 | 1. Open a terminal or command prompt. 72 | 73 | 2. Run the following command to check the CUDA version: 74 | 75 | ```sh 76 | nvcc --version 77 | ``` 78 | 79 | This command should display the CUDA version, confirming that CUDA is installed. 80 | 81 | 3. Additionally, you can run a GPU-related command, such as: 82 | 83 | ```sh 84 | nvidia-smi 85 | ``` 86 | 87 | This command will display information about your NVIDIA GPU, including the driver version and GPU utilization. 88 | 89 | Congratulations! You've successfully installed the CUDA driver for GPU acceleration. You can now utilize the power of your GPU to accelerate tasks, including running the OpenAI Whisper model with PyTorch for faster and more efficient computations. 90 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. For a more nuclear 159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 160 | #.idea/ 161 | 162 | # media folder 163 | media/* 164 | 165 | # background folder 166 | background/* 167 | 168 | # output folder 169 | output/* 170 | 171 | # Cookies 172 | cookies.txt 173 | 174 | # reddit2json 175 | .env 176 | Pipfile 177 | Pipfile.lock 178 | -------------------------------------------------------------------------------- /docs/1-ffmpeg.md: -------------------------------------------------------------------------------- 1 | # Installing FFmpeg 2 | 3 | FFmpeg is a powerful multimedia framework that provides command-line tools to record, convert, and stream audio and video. It's an essential tool for anyone working with multimedia files. In this guide, we'll walk you through the installation process for FFmpeg on various operating systems. 4 | 5 | ## Table of Contents 6 | 7 | 1. [Windows](#windows-installation) 8 | 2. [macOS](#macos-installation) 9 | 3. [Linux](#linux-installation) 10 | 4. [Testing Your FFmpeg Installation](#testing-ffmpeg) 11 | 12 | --- 13 | 14 | ## Windows Installation 15 | 16 | Installing FFmpeg on Windows can be done using pre-built executables. 17 | 18 | 1. **Download FFmpeg:** Visit the official FFmpeg website's download page at [https://www.ffmpeg.org/download.html](https://www.ffmpeg.org/download.html). Scroll down to the "Windows" section and choose one of the following options: 19 | 20 | - **Static Builds:** These are recommended for most users. Download the latest "64-bit" or "32-bit" static build, depending on your system architecture. 21 | 22 | - **Other Builds:** Advanced users can explore other options like linking libraries or shared builds. 23 | 24 | 2. **Extract the Zip File:** Once the download is complete, extract the contents of the zip file to a location on your computer, e.g., `C:\ffmpeg`. You should now have a folder containing FFmpeg executable files. 25 | 26 | 3. **Add FFmpeg to System Path (Optional):** To use FFmpeg from any command prompt or terminal window, you can add its location to your system's PATH environment variable. 27 | 28 | 4. **Testing Installation:** Open a command prompt and run the following command to verify your FFmpeg installation: 29 | 30 | ```sh 31 | ffmpeg -version 32 | ``` 33 | 34 | If installed correctly, this command will display FFmpeg's version information. 35 | 36 | --- 37 | 38 | ## macOS Installation 39 | 40 | You can install FFmpeg on macOS using package managers like Homebrew or MacPorts. Here's how to do it with Homebrew: 41 | 42 | 1. **Install Homebrew:** If you don't already have Homebrew installed, open a terminal and run the following command: 43 | 44 | ```sh 45 | /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" 46 | ``` 47 | 48 | 2. **Install FFmpeg:** Once Homebrew is installed, you can install FFmpeg by running the following command: 49 | 50 | ```sh 51 | brew install ffmpeg 52 | ``` 53 | 54 | 3. **Testing Installation:** After installation, run the following command in your terminal to verify FFmpeg is correctly installed: 55 | 56 | ```sh 57 | ffmpeg -version 58 | ``` 59 | 60 | You should see FFmpeg's version information. 61 | 62 | --- 63 | 64 | ## Linux Installation 65 | 66 | On Linux, you can install FFmpeg using your distribution's package manager. Here are instructions for some popular Linux distributions: 67 | 68 | ### Ubuntu/Debian 69 | 70 | 1. Open a terminal. 71 | 72 | 2. Run the following commands to update your package list and install FFmpeg: 73 | 74 | ```sh 75 | sudo apt update 76 | sudo apt install ffmpeg 77 | ``` 78 | 79 | ### CentOS/Fedora 80 | 81 | 1. Open a terminal. 82 | 83 | 2. Run the following command to install FFmpeg: 84 | 85 | ```sh 86 | sudo dnf install ffmpeg 87 | ``` 88 | 89 | ### Arch Linux 90 | 91 | 1. Open a terminal. 92 | 93 | 2. Run the following command to install FFmpeg: 94 | 95 | ```sh 96 | sudo pacman -S ffmpeg 97 | ``` 98 | 99 | ### Testing Installation 100 | 101 | After installation, run the following command in your terminal to verify FFmpeg is correctly installed: 102 | 103 | ```sh 104 | ffmpeg -version 105 | ``` 106 | 107 | You should see FFmpeg's version information. 108 | 109 | --- 110 | 111 | ## Testing Your FFmpeg Installation 112 | 113 | To ensure FFmpeg is working correctly, you can run a simple test command. Open your command prompt, terminal, or PowerShell and run: 114 | 115 | ```sh 116 | ffmpeg -version 117 | ``` 118 | 119 | This command should display FFmpeg's version information, confirming that FFmpeg is successfully installed on your system. 120 | 121 | Congratulations! You've now installed FFmpeg and can use its powerful multimedia capabilities for various tasks like video conversion, editing, and more. 122 | -------------------------------------------------------------------------------- /whisper_tiktok/services/ffmpeg_service.py: -------------------------------------------------------------------------------- 1 | import json 2 | import os 3 | from logging import Logger 4 | from pathlib import Path 5 | from typing import NamedTuple 6 | 7 | from whisper_tiktok.execution.command_executor import CommandExecutor, ExecutionResult 8 | 9 | 10 | class FFmpegError(Exception): 11 | """Custom exception for FFmpeg errors.""" 12 | 13 | 14 | class MediaInfo(NamedTuple): 15 | """Represents the result of running FFprobe. 16 | 17 | Attributes: 18 | return_code (int): The return code of the FFprobe process. 19 | json (str): The JSON output from FFprobe. 20 | error (str): The error message from FFprobe, if any. 21 | """ 22 | 23 | return_code: int 24 | json: str 25 | error: str 26 | 27 | @staticmethod 28 | def from_json(result: ExecutionResult) -> "MediaInfo": 29 | """Creates a MediaInfo instance from FFprobe execution result.""" 30 | return MediaInfo( 31 | return_code=result.returncode, json=result.stdout, error=result.stderr 32 | ) 33 | 34 | @staticmethod 35 | def convert_time(time_in_seconds: float) -> str: 36 | """ 37 | Converts time in seconds to a string in the format "hh:mm:ss.mmm". 38 | 39 | Args: 40 | time_in_seconds (float): The time in seconds to be converted. 41 | 42 | Returns: 43 | str: The time in the format "hh:mm:ss.mmm". 44 | """ 45 | hours = int(time_in_seconds // 3600) 46 | minutes = int((time_in_seconds % 3600) // 60) 47 | seconds = int(time_in_seconds % 60) 48 | milliseconds = int((time_in_seconds - int(time_in_seconds)) * 1000) 49 | return f"{hours:02d}:{minutes:02d}:{seconds:02d}.{milliseconds:03d}" 50 | 51 | @property 52 | def duration(self) -> float: 53 | """Extracts the duration of the audio stream from the FFprobe JSON output.""" 54 | d = json.loads(self.json) 55 | 56 | streams = d.get("streams", []) 57 | audio_stream = None 58 | for stream in streams: 59 | if stream["codec_type"] == "audio": 60 | audio_stream = stream 61 | break 62 | 63 | if audio_stream is None: 64 | raise ValueError("No audio stream found") 65 | 66 | return float(audio_stream["duration"]) 67 | 68 | 69 | class FFmpegService: 70 | """Service for FFmpeg operations.""" 71 | 72 | def __init__(self, executor: CommandExecutor, logger: Logger): 73 | self.executor = executor 74 | self.logger = logger 75 | 76 | def _build_video_filters(self, subtitles: Path) -> str: 77 | return rf"crop=ih/16*9:ih,scale=w=1080:h=1920:flags=lanczos,gblur=sigma=2,ass={subtitles.as_posix()}" 78 | 79 | def _build_ffmpeg_command( 80 | self, 81 | background: Path, 82 | audio: Path, 83 | output: Path, 84 | start_time: int, 85 | duration: str, 86 | filters: str, 87 | ) -> str: 88 | return rf"ffmpeg -ss {start_time} -t {duration} -i {background.as_posix()} -i {audio.as_posix()} -map 0:v -map 1:a -filter:v {filters} -c:v libx264 -crf 23 -c:a aac -ac 2 -b:a 192K {output.as_posix()} -y -threads {os.cpu_count()}" 89 | 90 | def compose_video( 91 | self, 92 | background: Path, 93 | audio: Path, 94 | subtitles: Path, 95 | output: Path, 96 | start_time: int, 97 | duration: str, 98 | ) -> Path: 99 | """Compose final video with background, audio, and subtitles.""" 100 | 101 | # Build filter complex 102 | filters = self._build_video_filters(subtitles) 103 | 104 | command = self._build_ffmpeg_command( 105 | background, audio, output, start_time, duration, filters 106 | ) 107 | result = self.executor.execute(command) 108 | 109 | if result.returncode != 0: 110 | raise FFmpegError(f"Failed to compose video: {result.stderr}") 111 | 112 | return output 113 | 114 | def get_media_info(self, file_path: Path) -> MediaInfo: 115 | """Get media information using ffprobe.""" 116 | command = f"ffprobe -v quiet -print_format json -show_format -show_streams {file_path.as_posix()}" 117 | result = self.executor.execute(command) 118 | 119 | if result.returncode != 0: 120 | raise FFmpegError(f"Failed to probe media: {result.stderr}") 121 | 122 | return MediaInfo.from_json(result) 123 | -------------------------------------------------------------------------------- /whisper_tiktok/strategies/processing_strategy.py: -------------------------------------------------------------------------------- 1 | from abc import ABC, abstractmethod 2 | from dataclasses import dataclass, field 3 | from logging import Logger 4 | from pathlib import Path 5 | 6 | from whisper_tiktok.interfaces.transcription_service import ITranscriptionService 7 | from whisper_tiktok.interfaces.tts_service import ITTSService 8 | from whisper_tiktok.interfaces.video_downloader import IVideoDownloader 9 | from whisper_tiktok.services.ffmpeg_service import FFmpegService 10 | 11 | 12 | @dataclass 13 | class ProcessingContext: 14 | """Context object passed through processing pipeline.""" 15 | 16 | video_data: dict 17 | uuid: str 18 | media_path: Path 19 | output_path: Path 20 | config: dict 21 | artifacts: dict = field(default_factory=dict) 22 | 23 | 24 | class ProcessingStrategy(ABC): 25 | """Base strategy for video processing steps.""" 26 | 27 | @abstractmethod 28 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 29 | """Execute processing step and update context.""" 30 | 31 | 32 | class DownloadBackgroundStrategy(ProcessingStrategy): 33 | """Strategy for downloading background video.""" 34 | 35 | def __init__(self, downloader: IVideoDownloader, logger: Logger): 36 | self.downloader = downloader 37 | self.logger = logger 38 | 39 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 40 | url = context.config["background_url"] 41 | background_path = self.downloader.download(url, Path("background")) 42 | context.artifacts["background_video"] = background_path 43 | self.logger.info(f"Downloaded background: {background_path}") 44 | return context 45 | 46 | 47 | class TTSGenerationStrategy(ProcessingStrategy): 48 | """Strategy for generating TTS audio.""" 49 | 50 | def __init__(self, tts_service: ITTSService, logger: Logger): 51 | self.tts_service = tts_service 52 | self.logger = logger 53 | 54 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 55 | """Integrates TTS into the pipeline""" 56 | text = f"{context.video_data['series']} - {context.video_data['part']}.\n" 57 | text += f"{context.video_data['text']}\n" 58 | text += f"{context.video_data['outro']}" 59 | 60 | output_file = context.media_path / f"{context.uuid}.mp3" 61 | voice = context.config.get("tts_voice", "en-US-ChristopherNeural") 62 | 63 | await self.tts_service.synthesize(text, output_file, voice) 64 | context.artifacts["audio_file"] = output_file 65 | 66 | self.logger.info(f"Generated TTS audio: {output_file}") 67 | return context 68 | 69 | 70 | class TranscriptionStrategy(ProcessingStrategy): 71 | """Strategy for transcribing audio to generate subtitles.""" 72 | 73 | def __init__(self, transcription_service: ITranscriptionService, logger: Logger): 74 | self.transcription_service = transcription_service 75 | self.logger = logger 76 | 77 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 78 | audio_file = context.artifacts.get("audio_file") 79 | if not audio_file: 80 | raise ValueError("Audio file not found in context artifacts.") 81 | 82 | srt_file = context.media_path / f"{context.uuid}.srt" 83 | ass_file = context.media_path / f"{context.uuid}.ass" 84 | self.transcription_service.transcribe( 85 | audio_file, 86 | srt_file, 87 | ass_file, 88 | model=context.config["model"], 89 | options=context.config, 90 | ) 91 | context.artifacts["srt_file"] = srt_file 92 | context.artifacts["ass_file"] = ass_file 93 | self.logger.info(f"Generated transcription SRT: {srt_file}") 94 | self.logger.info(f"Generated transcription ASS: {ass_file}") 95 | return context 96 | 97 | 98 | class VideoCompositionStrategy(ProcessingStrategy): 99 | """Strategy for composing the final video.""" 100 | 101 | def __init__(self, ffmpeg_service: FFmpegService, logger: Logger): 102 | self.ffmpeg_service = ffmpeg_service 103 | self.logger = logger 104 | 105 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 106 | background_video = context.artifacts["background_video"] 107 | audio_file = context.artifacts["audio_file"] 108 | ass_file = context.artifacts["ass_file"] 109 | 110 | # Get video duration and audio duration to calculate start time 111 | audio_info = self.ffmpeg_service.get_media_info(file_path=audio_file) 112 | duration = audio_info.duration 113 | str_duration = audio_info.convert_time(time_in_seconds=duration) 114 | 115 | # Then compose video 116 | output_file = context.output_path / f"{context.uuid}.mp4" 117 | 118 | # Implementation using FFmpegService 119 | self.ffmpeg_service.compose_video( 120 | background=background_video, 121 | audio=audio_file, 122 | subtitles=ass_file, 123 | output=output_file, 124 | start_time=0, 125 | duration=str_duration, 126 | ) 127 | 128 | context.artifacts["final_video"] = output_file 129 | self.logger.info(f"Composed video: {output_file}") 130 | return context 131 | 132 | 133 | class TikTokUploadStrategy(ProcessingStrategy): 134 | """Strategy for uploading videos to TikTok.""" 135 | 136 | def __init__(self, uploader, logger: Logger): 137 | self.uploader = uploader 138 | self.logger = logger 139 | 140 | async def execute(self, context: ProcessingContext) -> ProcessingContext: 141 | raise NotImplementedError("TikTok upload not implemented yet.") 142 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # Introducing Whisper-TikTok 🤖🎥 2 | 3 | ## Star History 4 | 5 | [![Star History Chart](https://api.star-history.com/svg?repos=MatteoFasulo/Whisper-TikTok&type=Date)](https://star-history.com/#MatteoFasulo/Whisper-TikTok&Date) 6 | 7 | ## Table of Contents 8 | 9 | - [Introduction](#introduction) 10 | - [Video (demo)](#demo-video) 11 | - [Command-Line](#command-line) 12 | - [Usage Examples](#usage-examples) 13 | - [Additional Resources](#additional-resources) 14 | - [Code of Conduct](#code-of-conduct) 15 | - [Contributing](#contributing) 16 | - [Acknowledgments](#acknowledgments) 17 | - [License](#license) 18 | 19 | ## Introduction 20 | 21 | Discover Whisper-TikTok, an innovative AI-powered tool that leverages the prowess of **Edge TTS**, **OpenAI-Whisper**, and **FFMPEG** to craft captivating TikTok videos. Harnessing the capabilities of OpenAI's Whisper model, Whisper-TikTok effortlessly generates an accurate **transcription** from provided audio files, laying the foundation for the creation of mesmerizing TikTok videos through the utilization of **FFMPEG**. Additionally, the program seamlessly integrates the **Microsoft Edge Cloud Text-to-Speech (TTS) API** to lend a vibrant **voiceover** to the video. Opting for Microsoft Edge Cloud TTS API's voiceover is a deliberate choice, as it delivers a remarkably **natural and authentic** auditory experience, setting it apart from the often monotonous and artificial voiceovers prevalent in numerous TikTok videos. 22 | 23 | ## Demo Video 24 | 25 | 26 | 27 | ## Installation 🛠️ 28 | 29 | Whisper-TikTok has been tested in Windows 10, Windows 11 and Ubuntu 24.04 systems equipped with **Python versions 3.11, and 3.12**. 30 | 31 | If you want to run Whisper-TikTok locally, you can clone the repository using the following command: 32 | 33 | ```bash 34 | git clone https://github.com/MatteoFasulo/Whisper-TikTok.git 35 | ``` 36 | 37 | Install the required dependencies using pip: 38 | 39 | ```python 40 | pip install -r requirements.txt 41 | ``` 42 | 43 | However, we encourage the adoption of astral [`uv`](https://docs.astral.sh/uv/) to install the required dependencies. If you are using `uv`, you can install the dependencies with the following command: 44 | 45 | ```bash 46 | uv sync 47 | ``` 48 | 49 | Then, install the repository as a package: 50 | 51 | ```bash 52 | pip install -e . 53 | ``` 54 | 55 | or 56 | 57 | ```bash 58 | uv pip install -e . 59 | ``` 60 | 61 | Binaries for [**FFMPEG**](https://ffmpeg.org/) are not included in the repository and must be installed separately. Make sure to have FFMPEG installed and accessible in your system's PATH. For convenience, here are the installation instructions for various package managers: 62 | 63 | ```bash 64 | # on Ubuntu or Debian 65 | sudo apt update && sudo apt install ffmpeg 66 | 67 | # on Arch Linux 68 | sudo pacman -S ffmpeg 69 | 70 | # on MacOS using Homebrew () 71 | brew install ffmpeg 72 | 73 | # on Windows using Chocolatey () 74 | choco install ffmpeg 75 | 76 | # on Windows using Scoop () 77 | scoop install ffmpeg 78 | ``` 79 | 80 | Please note that for optimal performance, it's advisable to have a GPU when using the OpenAI Whisper model for Automatic Speech Recognition (ASR). However, the program will work without a GPU, but it will run more slowly due to CPU limitations. 81 | 82 | ## Command-Line 83 | 84 | To run the program from the command-line, execute the following command within your terminal: 85 | 86 | ```bash 87 | python -m whisper_tiktok.main --help 88 | ``` 89 | 90 | which will provide you with a list of available commands. 91 | 92 | ### CLI Options 93 | 94 | Whisper-TikTok supports many command-line options to customize the generated TikTok video. Just to name a few, you can choose the Whisper model to use, the TTS voice, subtitle format, subtitle position, font size, font color, and many more. 95 | 96 | To browse all available options, run the following command: 97 | 98 | ```bash 99 | python -m whisper_tiktok.main create --help 100 | ``` 101 | 102 | > If you use the --random_voice option, please specify both --gender and --language arguments. Whisper model will auto-detect the language of the audio file and use the corresponding model. 103 | 104 | ## Usage Examples 105 | 106 | - Generate a TikTok video using a specific TTS voice: 107 | 108 | ```bash 109 | python -m whisper_tiktok.main create --tts en-US-EricNeural 110 | ``` 111 | 112 | - Use a custom YouTube video as the background video: 113 | 114 | ```bash 115 | python -m whisper_tiktok.main create --background-url https://www.youtube.com/watch?v=dQw4w9WgXcQ 116 | ``` 117 | 118 | - Modify the font color of the subtitles: 119 | 120 | ```bash 121 | python -m whisper_tiktok.main create --font_color FFF000 122 | ``` 123 | 124 | - Generate a TikTok video with a random TTS voice: 125 | 126 | ```bash 127 | python -m whisper_tiktok.main create --random_voice --gender Male --language en-US 128 | ``` 129 | 130 | - List all available voices: 131 | 132 | ```bash 133 | python -m whisper_tiktok.main list-voices 134 | ``` 135 | 136 | you will find a list of available voices together with some information about each voice, such as the tone, style, and suitable scenarios. 137 | 138 | ## Additional Resources 139 | 140 | ### Code of Conduct 141 | 142 | Please review our [Code of Conduct](./CODE_OF_CONDUCT.md) before contributing to Whisper-TikTok. 143 | 144 | ### Contributing 145 | 146 | We welcome contributions from the community! Please see our [Contributing Guidelines](./CONTRIBUTING.md) for more information. 147 | 148 | ## Acknowledgments 149 | 150 | - We'd like to give a huge thanks to [@rany2](https://www.github.com/rany2) for their [edge-tts](https://github.com/rany2/edge-tts) package, which made it possible to use the Microsoft Edge Cloud TTS API with Whisper-TikTok. 151 | - We also acknowledge the contributions of the Whisper model by [@OpenAI](https://github.com/openai/whisper) for robust speech recognition via large-scale weak supervision 152 | - Also [@jianfch](https://github.com/jianfch/stable-ts) for the stable-ts package, which made it possible to use the OpenAI Whisper model with Whisper-TikTok in a stable manner with font color and subtitle format options. 153 | 154 | ### License 155 | 156 | Whisper-TikTok is licensed under the [Apache License, Version 2.0](https://github.com/MatteoFasulo/Whisper-TikTok/blob/main/LICENSE). 157 | -------------------------------------------------------------------------------- /docs/index.md: -------------------------------------------------------------------------------- 1 | # Introducing Whisper-TikTok 🤖🎥 2 | 3 | ## Star History 4 | 5 | [![Star History Chart](https://api.star-history.com/svg?repos=MatteoFasulo/Whisper-TikTok&type=Date)](https://star-history.com/#MatteoFasulo/Whisper-TikTok&Date) 6 | 7 | ## Table of Contents 8 | 9 | - [Introduction](#introduction) 10 | - [Video (demo)](#demo-video) 11 | - [Command-Line](#command-line) 12 | - [Usage Examples](#usage-examples) 13 | - [Additional Resources](#additional-resources) 14 | - [Code of Conduct](#code-of-conduct) 15 | - [Contributing](#contributing) 16 | - [Acknowledgments](#acknowledgments) 17 | - [License](#license) 18 | 19 | ## Introduction 20 | 21 | Discover Whisper-TikTok, an innovative AI-powered tool that leverages the prowess of **Edge TTS**, **OpenAI-Whisper**, and **FFMPEG** to craft captivating TikTok videos. Harnessing the capabilities of OpenAI's Whisper model, Whisper-TikTok effortlessly generates an accurate **transcription** from provided audio files, laying the foundation for the creation of mesmerizing TikTok videos through the utilization of **FFMPEG**. Additionally, the program seamlessly integrates the **Microsoft Edge Cloud Text-to-Speech (TTS) API** to lend a vibrant **voiceover** to the video. Opting for Microsoft Edge Cloud TTS API's voiceover is a deliberate choice, as it delivers a remarkably **natural and authentic** auditory experience, setting it apart from the often monotonous and artificial voiceovers prevalent in numerous TikTok videos. 22 | 23 | ## Demo Video 24 | 25 | 26 | 27 | ## Installation 🛠️ 28 | 29 | Whisper-TikTok has been tested in Windows 10, Windows 11 and Ubuntu 24.04 systems equipped with **Python versions 3.11, and 3.12**. 30 | 31 | If you want to run Whisper-TikTok locally, you can clone the repository using the following command: 32 | 33 | ```bash 34 | git clone https://github.com/MatteoFasulo/Whisper-TikTok.git 35 | ``` 36 | 37 | Install the required dependencies using pip: 38 | 39 | ```python 40 | pip install -r requirements.txt 41 | ``` 42 | 43 | However, we encourage the adoption of astral [`uv`](https://docs.astral.sh/uv/) to install the required dependencies. If you are using `uv`, you can install the dependencies with the following command: 44 | 45 | ```bash 46 | uv sync 47 | ``` 48 | 49 | Then, install the repository as a package: 50 | 51 | ```bash 52 | pip install -e . 53 | ``` 54 | 55 | or 56 | 57 | ```bash 58 | uv pip install -e . 59 | ``` 60 | 61 | Binaries for [**FFMPEG**](https://ffmpeg.org/) are not included in the repository and must be installed separately. Make sure to have FFMPEG installed and accessible in your system's PATH. For convenience, here are the installation instructions for various package managers: 62 | 63 | ```bash 64 | # on Ubuntu or Debian 65 | sudo apt update && sudo apt install ffmpeg 66 | 67 | # on Arch Linux 68 | sudo pacman -S ffmpeg 69 | 70 | # on MacOS using Homebrew () 71 | brew install ffmpeg 72 | 73 | # on Windows using Chocolatey () 74 | choco install ffmpeg 75 | 76 | # on Windows using Scoop () 77 | scoop install ffmpeg 78 | ``` 79 | 80 | Please note that for optimal performance, it's advisable to have a GPU when using the OpenAI Whisper model for Automatic Speech Recognition (ASR). However, the program will work without a GPU, but it will run more slowly due to CPU limitations. 81 | 82 | ## Command-Line 83 | 84 | To run the program from the command-line, execute the following command within your terminal: 85 | 86 | ```bash 87 | python -m whisper_tiktok.main --help 88 | ``` 89 | 90 | which will provide you with a list of available commands. 91 | 92 | ### CLI Options 93 | 94 | Whisper-TikTok supports many command-line options to customize the generated TikTok video. Just to name a few, you can choose the Whisper model to use, the TTS voice, subtitle format, subtitle position, font size, font color, and many more. 95 | 96 | To browse all available options, run the following command: 97 | 98 | ```bash 99 | python -m whisper_tiktok.main create --help 100 | ``` 101 | 102 | > If you use the --random_voice option, please specify both --gender and --language arguments. Whisper model will auto-detect the language of the audio file and use the corresponding model. 103 | 104 | ## Usage Examples 105 | 106 | - Generate a TikTok video using a specific TTS voice: 107 | 108 | ```bash 109 | python -m whisper_tiktok.main create --tts en-US-EricNeural 110 | ``` 111 | 112 | - Use a custom YouTube video as the background video: 113 | 114 | ```bash 115 | python -m whisper_tiktok.main create --background-url https://www.youtube.com/watch?v=dQw4w9WgXcQ 116 | ``` 117 | 118 | - Modify the font color of the subtitles: 119 | 120 | ```bash 121 | python -m whisper_tiktok.main create --font_color FFF000 122 | ``` 123 | 124 | - Generate a TikTok video with a random TTS voice: 125 | 126 | ```bash 127 | python -m whisper_tiktok.main create --random_voice --gender Male --language en-US 128 | ``` 129 | 130 | - List all available voices: 131 | 132 | ```bash 133 | python -m whisper_tiktok.main list-voices 134 | ``` 135 | 136 | you will find a list of available voices together with some information about each voice, such as the tone, style, and suitable scenarios. 137 | 138 | ## Additional Resources 139 | 140 | ### Code of Conduct 141 | 142 | Please review our [Code of Conduct](https://github.com/MatteoFasulo/Whisper-TikTok/blob/main/CODE_OF_CONDUCT.md) before contributing to Whisper-TikTok. 143 | 144 | ### Contributing 145 | 146 | We welcome contributions from the community! Please see our [Contributing Guidelines](https://github.com/MatteoFasulo/Whisper-TikTok/blob/main/CONTRIBUTING.md) for more information. 147 | 148 | ## Acknowledgments 149 | 150 | - We'd like to give a huge thanks to [@rany2](https://www.github.com/rany2) for their [edge-tts](https://github.com/rany2/edge-tts) package, which made it possible to use the Microsoft Edge Cloud TTS API with Whisper-TikTok. 151 | - We also acknowledge the contributions of the Whisper model by [@OpenAI](https://github.com/openai/whisper) for robust speech recognition via large-scale weak supervision 152 | - Also [@jianfch](https://github.com/jianfch/stable-ts) for the stable-ts package, which made it possible to use the OpenAI Whisper model with Whisper-TikTok in a stable manner with font color and subtitle format options. 153 | 154 | ### License 155 | 156 | Whisper-TikTok is licensed under the [Apache License, Version 2.0](https://github.com/MatteoFasulo/Whisper-TikTok/blob/main/LICENSE). 157 | -------------------------------------------------------------------------------- /app.py: -------------------------------------------------------------------------------- 1 | import asyncio 2 | import platform 3 | import shutil 4 | from pathlib import Path 5 | 6 | import pandas as pd 7 | import streamlit as st 8 | 9 | from whisper_tiktok.config.logger_config import setup_logger 10 | from whisper_tiktok.container import Container 11 | from whisper_tiktok.main import Application 12 | from whisper_tiktok.utils.color_utils import rgb_to_bgr 13 | from whisper_tiktok.voice_manager import VoicesManager 14 | 15 | 16 | def _setup_event_loop(): 17 | """Setup event loop for Windows if needed.""" 18 | if platform.system() == "Windows": 19 | asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) 20 | 21 | 22 | def json_to_df(json_file): 23 | return pd.read_json(json_file) 24 | 25 | 26 | def df_to_json(df): 27 | try: 28 | json_str = df.to_json(orient="records", indent=4, force_ascii=False) 29 | 30 | if df.shape[0] == 0: 31 | st.error("You must add at least one video to the JSON") 32 | return 33 | 34 | with open("video.json", "w", encoding="UTF-8") as f: 35 | f.write(json_str) 36 | 37 | st.success("JSON saved successfully!") 38 | 39 | except Exception as e: 40 | st.error(f"An error occurred while saving the JSON: {e}") 41 | 42 | 43 | async def run_pipeline( 44 | model, 45 | background_url, 46 | tts_voice, 47 | random_voice, 48 | gender, 49 | language, 50 | font, 51 | font_size, 52 | font_color, 53 | sub_position, 54 | clean, 55 | verbose, 56 | ): 57 | """Run the video creation pipeline.""" 58 | log_dir = Path.cwd() / "logs" 59 | log_level = "DEBUG" if verbose else "INFO" 60 | logger = setup_logger(log_dir, log_level) 61 | 62 | st_log = st.empty() 63 | st_log.info("Starting Whisper TikTok video creation pipeline...") 64 | 65 | try: 66 | # Validate model choice 67 | valid_models = ["tiny", "base", "small", "medium", "large", "turbo"] 68 | if model not in valid_models: 69 | st_log.error(f"Invalid model. Choose from: {', '.join(valid_models)}") 70 | return 71 | 72 | async def get_voice(): 73 | nonlocal tts_voice, language 74 | # Handle random voice selection 75 | if random_voice: 76 | if not gender or not language: 77 | st_log.error( 78 | "Both --gender and --language required for random voice" 79 | ) 80 | raise ValueError( 81 | "Gender and language are required for random voice." 82 | ) 83 | 84 | voices_manager = VoicesManager() 85 | voices_obj = await voices_manager.create() 86 | voice_result = voices_manager.find(voices_obj, gender, language) 87 | tts_voice = voice_result.get("Name") or voice_result.get("ShortName") 88 | st_log.info(f"Selected random voice: {tts_voice}") 89 | else: 90 | # Validate specified voice 91 | voices_manager = VoicesManager() 92 | voices_obj = await voices_manager.create() 93 | extracted_language = "-".join(tts_voice.split("-")[0:2]) 94 | voice_result = voices_obj.find(Locale=extracted_language) 95 | 96 | if not voice_result: 97 | st_log.error( 98 | "Voice not found. Run 'whisper-tiktok list-voices' to see available voices" 99 | ) 100 | raise ValueError("Voice not found.") 101 | 102 | language = extracted_language 103 | st_log.info(f"Using voice: {tts_voice}") 104 | 105 | try: 106 | await asyncio.create_task(get_voice()) 107 | except Exception as e: 108 | st_log.error(f"Voice validation failed: {e}") 109 | return 110 | 111 | # Process font color 112 | processed_font_color = font_color.lower() 113 | if processed_font_color.startswith("#"): 114 | processed_font_color = processed_font_color[1:] 115 | processed_font_color = rgb_to_bgr(processed_font_color) 116 | 117 | # Clean folders if requested 118 | if clean: 119 | st_log.info("Cleaning media and output folders...") 120 | media_path = Path.cwd() / "media" 121 | output_path = Path.cwd() / "output" 122 | 123 | if media_path.exists(): 124 | shutil.rmtree(media_path) 125 | st_log.info(f"Removed {media_path}") 126 | 127 | if output_path.exists(): 128 | shutil.rmtree(output_path) 129 | st_log.info(f"Removed {output_path}") 130 | 131 | # Setup DI container 132 | container = Container() 133 | config_dict = { 134 | "model": model, 135 | "background_url": background_url, 136 | "tts_voice": tts_voice, 137 | "Fontname": font, 138 | "Fontsize": font_size, 139 | "highlight_color": processed_font_color, 140 | "Alignment": sub_position, 141 | "BorderStyle": "1", 142 | "Outline": "1", 143 | "Shadow": "2", 144 | "Blur": "21", 145 | "MarginL": "0", 146 | "MarginR": "0", 147 | } 148 | container.config.from_dict(config_dict) 149 | 150 | # Run application 151 | app_instance = Application(container, logger) 152 | 153 | await app_instance.run() 154 | st_log.success("Pipeline completed successfully!") 155 | 156 | except Exception as e: 157 | logger.exception("Pipeline failed") 158 | st_log.error(f"Pipeline failed: {e}") 159 | 160 | 161 | async def main(): 162 | """Main function to run the Streamlit app.""" 163 | # Streamlit Config 164 | st.set_page_config( 165 | page_title="Whisper-TikTok", 166 | page_icon="💬", 167 | layout="wide", 168 | initial_sidebar_state="expanded", 169 | menu_items={ 170 | "Get Help": "https://github.com/MatteoFasulo/Whisper-TikTok", 171 | "Report a bug": "https://github.com/MatteoFasulo/Whisper-TikTok/issues", 172 | "About": """ 173 | # Whisper-TikTok 174 | Whisper-TikTok is an innovative AI-powered tool that leverages the prowess of Edge TTS, OpenAI-Whisper, and FFMPEG to craft captivating TikTok videos also with a web application interface! 175 | 176 | Mantainer: https://github.com/MatteoFasulo 177 | 178 | If you find a bug or if you just have questions about the project feel free to reach me at https://github.com/MatteoFasulo/Whisper-TikTok 179 | Any contribution to this project is welcome to improve the quality of work! 180 | """, 181 | }, 182 | ) 183 | 184 | st.page_link( 185 | "https://github.com/MatteoFasulo/Whisper-TikTok", label="GitHub", icon="🔗" 186 | ) 187 | 188 | st.title("🏆 Whisper-TikTok 🚀") 189 | st.write( 190 | "Create a TikTok video with text-to-speech of Microsoft Edge's TTS and subtitles of Whisper model." 191 | ) 192 | 193 | st.subheader( 194 | "JSON Editor", 195 | help="Here you can edit the JSON file with the videos. Copy-and-paste is supported and compatible with Google Sheets, Excel, and others. You can do bulk-editing by dragging the handle on a cell (similar to Excel)!", 196 | ) 197 | st.write( 198 | "ℹ️ The JSON file is saved automatically when you click the button below. Every time you edit the JSON file, you must click the button to save the changes otherwise they will be lost." 199 | ) 200 | edited_df = st.data_editor( 201 | json_to_df("video.json"), 202 | num_rows="dynamic", 203 | ) 204 | st.button( 205 | "Save JSON", 206 | on_click=df_to_json, 207 | args=(edited_df,), 208 | help="Save the JSON file with the videos", 209 | ) 210 | 211 | st.divider() 212 | 213 | st.subheader("🚀 Run Pipeline") 214 | 215 | col1, col2 = st.columns(2) 216 | 217 | with col1: 218 | st.write("#### General Settings") 219 | model = st.selectbox( 220 | "Whisper model size", 221 | ["tiny", "base", "small", "medium", "large", "turbo"], 222 | index=5, 223 | help="Whisper model size [tiny|base|small|medium|large|turbo]", 224 | ) 225 | background_url = st.text_input( 226 | "Background Video URL", 227 | "https://www.youtube.com/watch?v=dQw4w9WgXcQ", 228 | help="YouTube URL for background video", 229 | ) 230 | clean = st.checkbox( 231 | "Clean Folders", help="Clean media and output folders before processing" 232 | ) 233 | verbose = st.checkbox("Verbose Logging", help="Enable verbose logging") 234 | 235 | with col2: 236 | st.write("#### Voice Settings") 237 | random_voice = st.checkbox("Use Random Voice", help="Use random TTS voice") 238 | if random_voice: 239 | gender = st.selectbox( 240 | "Gender", ["Male", "Female"], help="Gender for random voice" 241 | ) 242 | language = st.text_input( 243 | "Language", "en-US", help="Language for random voice (e.g., en-US)" 244 | ) 245 | tts_voice = "" 246 | else: 247 | tts_voice = st.text_input( 248 | "TTS Voice", 249 | "en-US-ChristopherNeural", 250 | help="TTS voice to use. See available voices with `whisper-tiktok list-voices`", 251 | ) 252 | gender = None 253 | language = None 254 | 255 | st.write("#### Subtitle Settings") 256 | col3, col4, col5 = st.columns(3) 257 | with col3: 258 | font = st.text_input("Font", "Lexend Bold", help="Subtitle font") 259 | font_size = st.number_input("Font Size", value=21, help="Subtitle font size") 260 | with col4: 261 | font_color = st.color_picker( 262 | "Font Color", "#FFF000", help="Subtitle color (hex format)" 263 | ) 264 | with col5: 265 | sub_position = st.slider( 266 | "Subtitle Position", 267 | min_value=1, 268 | max_value=9, 269 | value=5, 270 | help="Subtitle position (1-9), refer to FFMPEG documentation and ASS subtitle format for positioning", 271 | ) 272 | 273 | if st.button("Run Video Creation Pipeline", type="primary"): 274 | _setup_event_loop() 275 | asyncio.run( 276 | run_pipeline( 277 | model, 278 | background_url, 279 | tts_voice, 280 | random_voice, 281 | gender, 282 | language, 283 | font, 284 | font_size, 285 | font_color, 286 | sub_position, 287 | clean, 288 | verbose, 289 | ) 290 | ) 291 | 292 | 293 | if __name__ == "__main__": 294 | asyncio.run(main()) 295 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | Apache License 2 | Version 2.0, January 2004 3 | http://www.apache.org/licenses/ 4 | 5 | TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION 6 | 7 | 1. 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We also recommend that a 185 | file or class name and description of purpose be included on the 186 | same "printed page" as the copyright notice for easier 187 | identification within third-party archives. 188 | 189 | Copyright [2023] [Matteo Fasulo] 190 | 191 | Licensed under the Apache License, Version 2.0 (the "License"); 192 | you may not use this file except in compliance with the License. 193 | You may obtain a copy of the License at 194 | 195 | http://www.apache.org/licenses/LICENSE-2.0 196 | 197 | Unless required by applicable law or agreed to in writing, software 198 | distributed under the License is distributed on an "AS IS" BASIS, 199 | WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 200 | See the License for the specific language governing permissions and 201 | limitations under the License. 202 | -------------------------------------------------------------------------------- /whisper_tiktok/main.py: -------------------------------------------------------------------------------- 1 | """Main module for the Whisper TikTok application.""" 2 | 3 | import asyncio 4 | import json 5 | import logging 6 | import platform 7 | import shutil 8 | from pathlib import Path 9 | from typing import Optional 10 | 11 | import typer 12 | from rich.console import Console 13 | from rich.table import Table 14 | 15 | from whisper_tiktok.config.logger_config import setup_logger 16 | from whisper_tiktok.container import Container 17 | from whisper_tiktok.factories.video_factory import VideoCreatorFactory 18 | from whisper_tiktok.utils.color_utils import rgb_to_bgr 19 | from whisper_tiktok.voice_manager import VoicesManager 20 | 21 | # Create Typer app 22 | app = typer.Typer( 23 | name="whisper-tiktok", 24 | help="Whisper TikTok - Video generation pipeline", 25 | add_completion=False, 26 | ) 27 | console = Console() 28 | 29 | 30 | @app.callback() 31 | def main(): 32 | """Whisper TikTok - Create TikTok videos with AI-generated subtitles.""" 33 | 34 | 35 | @app.command() 36 | def list_voices( 37 | language: Optional[str] = typer.Option( 38 | None, 39 | "--language", 40 | "-l", 41 | help="Filter by language (e.g., en-US)", 42 | ), 43 | gender: Optional[str] = typer.Option( 44 | None, 45 | "--gender", 46 | "-g", 47 | help="Filter by gender (Male/Female)", 48 | ), 49 | ): 50 | """List available TTS voices.""" 51 | 52 | async def _list_voices(): 53 | voices_manager = VoicesManager() 54 | voices_obj = await voices_manager.create() 55 | 56 | # Get all voices 57 | voices = voices_obj.voices 58 | 59 | # Apply filters 60 | if language: 61 | voices = [v for v in voices if v.get("Locale", "").startswith(language)] 62 | if gender: 63 | voices = [v for v in voices if v.get("Gender", "") == gender] 64 | 65 | # Display in a table 66 | table = Table(title="Available TTS Voices") 67 | table.add_column("Name", style="cyan") 68 | table.add_column("Locale", style="green") 69 | table.add_column("Gender", style="magenta") 70 | table.add_column("Voice Personalities", style="blue") 71 | table.add_column("Scenarios", style="yellow") 72 | 73 | for voice in sorted(voices, key=lambda x: x.get("Locale", "")): 74 | table.add_row( 75 | voice.get("ShortName", ""), 76 | voice.get("Locale", ""), 77 | voice.get("Gender", ""), 78 | ", ".join(voice["VoiceTag"].get("VoicePersonalities", [])), 79 | ", ".join(voice["VoiceTag"].get("TailoredScenarios", [])), 80 | ) 81 | 82 | console.print(table) 83 | console.print(f"\n[dim]Total: {len(voices)} voices[/dim]") 84 | 85 | asyncio.run(_list_voices()) 86 | 87 | 88 | @app.command() 89 | def create( 90 | model: str = typer.Option( 91 | "turbo", 92 | "--model", 93 | "-m", 94 | help="Whisper model size [tiny|base|small|medium|large|turbo]", 95 | ), 96 | background_url: str = typer.Option( 97 | "https://www.youtube.com/watch?v=intRX7BRA90", 98 | "--background-url", 99 | "-u", 100 | help="YouTube URL for background video", 101 | ), 102 | tts_voice: str = typer.Option( 103 | "en-US-ChristopherNeural", 104 | "--tts", 105 | "-v", 106 | help="TTS voice to use", 107 | ), 108 | random_voice: bool = typer.Option( 109 | False, 110 | "--random-voice", 111 | help="Use random TTS voice", 112 | ), 113 | gender: Optional[str] = typer.Option( 114 | None, 115 | "--gender", 116 | "-g", 117 | help="Gender for random voice (Male/Female)", 118 | ), 119 | language: Optional[str] = typer.Option( 120 | None, 121 | "--language", 122 | "-l", 123 | help="Language for random voice (e.g., en-US)", 124 | ), 125 | font: str = typer.Option( 126 | "Lexend Bold", 127 | "--font", 128 | "-f", 129 | help="Subtitle font", 130 | ), 131 | font_size: int = typer.Option( 132 | 21, 133 | "--font-size", 134 | help="Subtitle font size", 135 | ), 136 | font_color: str = typer.Option( 137 | "FFF000", 138 | "--font-color", 139 | "-c", 140 | help="Subtitle color (hex format)", 141 | ), 142 | sub_position: int = typer.Option( 143 | 5, 144 | "--sub-position", 145 | "-p", 146 | help="Subtitle position (1-9)", 147 | min=1, 148 | max=9, 149 | ), 150 | upload_tiktok: bool = typer.Option( 151 | False, 152 | "--upload-tiktok", 153 | help="Upload to TikTok", 154 | ), 155 | clean: bool = typer.Option( 156 | False, 157 | "--clean", 158 | help="Clean media and output folders before processing", 159 | ), 160 | verbose: bool = typer.Option( 161 | False, 162 | "--verbose", 163 | help="Enable verbose logging", 164 | ), 165 | ): 166 | """Create videos from text content.""" 167 | 168 | # Setup logging 169 | log_dir = Path.cwd() / "logs" 170 | log_level = "DEBUG" if verbose else "INFO" 171 | logger = setup_logger(log_dir, log_level) 172 | 173 | async def _create(): 174 | nonlocal tts_voice, language 175 | 176 | logger.info("=" * 60) 177 | logger.info("Starting Whisper TikTok video creation pipeline") 178 | logger.info("=" * 60) 179 | 180 | # Validate model choice 181 | valid_models = ["tiny", "base", "small", "medium", "large", "turbo"] 182 | if model not in valid_models: 183 | logger.error("Invalid model. Choose from: %s", ", ".join(valid_models)) 184 | raise typer.Exit(code=1) 185 | 186 | # Handle random voice selection 187 | if random_voice: 188 | if not gender or not language: 189 | logger.error("Both --gender and --language required for random voice") 190 | raise typer.Exit(code=1) 191 | 192 | try: 193 | voices_manager = VoicesManager() 194 | voices_obj = await voices_manager.create() 195 | voice_result = voices_manager.find(voices_obj, gender, language) 196 | tts_voice = voice_result.get("Name") or voice_result.get("ShortName") 197 | logger.info("Selected random voice: %s", tts_voice) 198 | except Exception as e: 199 | logger.error("Failed to select random voice: %s", e) 200 | raise typer.Exit(code=1) from e 201 | else: 202 | # Validate specified voice 203 | try: 204 | voices_manager = VoicesManager() 205 | voices_obj = await voices_manager.create() 206 | extracted_language = "-".join(tts_voice.split("-")[0:2]) 207 | voice_result = voices_obj.find(Locale=extracted_language) 208 | 209 | if not voice_result: 210 | logger.error( 211 | "Voice not found. Run 'whisper-tiktok list-voices' to see available voices" 212 | ) 213 | raise typer.Exit(code=1) 214 | 215 | language = extracted_language 216 | logger.info("Using voice: %s", tts_voice) 217 | 218 | except Exception as e: 219 | logger.error("Voice validation failed: %s", e) 220 | raise typer.Exit(code=1) from e 221 | 222 | # Process font color 223 | processed_font_color = font_color.lower() 224 | if processed_font_color.startswith("#"): 225 | processed_font_color = processed_font_color[1:] 226 | processed_font_color = rgb_to_bgr(processed_font_color) 227 | 228 | # Clean folders if requested 229 | if clean: 230 | logger.info("Cleaning media and output folders...") 231 | media_path = Path.cwd() / "media" 232 | output_path = Path.cwd() / "output" 233 | 234 | if media_path.exists(): 235 | shutil.rmtree(media_path) 236 | logger.info("Removed %s", media_path) 237 | 238 | if output_path.exists(): 239 | shutil.rmtree(output_path) 240 | logger.info("Removed %s", output_path) 241 | # Display startup info 242 | console.print("\n[bold green]🎬 Starting video creation pipeline…[/bold green]") 243 | console.print(f" [cyan]Model:[/cyan] {model}") 244 | console.print(f" [cyan]Voice:[/cyan] {tts_voice}") 245 | console.print(f" [cyan]Language:[/cyan] {language}\n") 246 | 247 | # Setup DI container 248 | container = Container() 249 | config_dict = { 250 | "model": model, 251 | "background_url": background_url, 252 | "tts_voice": tts_voice, 253 | "upload_tiktok": upload_tiktok, 254 | "Fontname": font, 255 | "Fontsize": font_size, 256 | "highlight_color": processed_font_color, 257 | "Alignment": sub_position, 258 | "BorderStyle": "1", 259 | "Outline": "1", 260 | "Shadow": "2", 261 | "Blur": "21", 262 | "MarginL": "0", 263 | "MarginR": "0", 264 | } 265 | container.config.from_dict(config_dict) 266 | 267 | # Run application 268 | app_instance = Application(container, logger) 269 | 270 | try: 271 | await app_instance.run() 272 | console.print( 273 | "\n[bold green]✅ Pipeline completed successfully![/bold green]" 274 | ) 275 | except Exception as e: 276 | logger.exception("Pipeline failed") 277 | console.print(f"\n[bold red]❌ Pipeline failed: {e}[/bold red]") 278 | raise typer.Exit(code=1) from e 279 | 280 | # Run the async function 281 | asyncio.run(_create()) 282 | 283 | 284 | class Application: 285 | """Main application orchestrator.""" 286 | 287 | def __init__(self, container: Container, logger: logging.Logger): 288 | self.container = container 289 | self.logger = logger 290 | self.factory = VideoCreatorFactory(container) 291 | 292 | def _load_video_data(self) -> list[dict]: 293 | """Load video data from JSON file.""" 294 | video_json_path = Path.cwd() / "video.json" 295 | 296 | try: 297 | data: list[dict] = json.loads(video_json_path.read_text(encoding="utf-8")) 298 | self.logger.info(f"Loaded {len(data)} videos from video.json") 299 | return data 300 | except FileNotFoundError: 301 | self.logger.error(f"video.json not found at {video_json_path}") 302 | raise 303 | except json.JSONDecodeError as e: 304 | self.logger.error(f"Invalid JSON in video.json: {e}") 305 | raise 306 | 307 | def _build_config(self) -> dict: 308 | """Build configuration from container.""" 309 | return dict(self.container.config()) 310 | 311 | async def run(self): 312 | """Run the video creation pipeline.""" 313 | 314 | # Load video data 315 | video_data = self._load_video_data() 316 | config = self._build_config() 317 | 318 | # Process each video 319 | for idx, video in enumerate(video_data, 1): 320 | self.logger.info( 321 | f"Processing video {idx}/{len(video_data)}: {video.get('series', 'Unknown')}" 322 | ) 323 | await self._process_video(video, config) 324 | 325 | async def _process_video(self, video: dict, config: dict): 326 | """Process a single video.""" 327 | 328 | processor = self.factory.create_processor(video, config) 329 | 330 | try: 331 | result = await processor.process() 332 | self.logger.info(f"✓ Video created: {result.output_path}") 333 | except Exception: 334 | self.logger.exception( 335 | f"✗ Failed to process video: {video.get('series', 'Unknown')}" 336 | ) 337 | raise 338 | 339 | 340 | def _setup_event_loop(): 341 | """Setup event loop for Windows if needed.""" 342 | if platform.system() == "Windows": 343 | asyncio.set_event_loop_policy(asyncio.WindowsSelectorEventLoopPolicy()) 344 | 345 | 346 | if __name__ == "__main__": 347 | _setup_event_loop() 348 | app() 349 | --------------------------------------------------------------------------------