78e9df31e6
- Don't pin exact torch/torchaudio/torchvision versions (use >=2.1.0) - Install CUDA PyTorch first in Docker before other requirements - Upgrade pip before installations to avoid compatibility issues - Let pip resolve latest compatible versions from cu118 index
55 lines
1.5 KiB
Plaintext
55 lines
1.5 KiB
Plaintext
# OBS Recording Transcriber Dependencies
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# Core dependencies with pinned compatible versions
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streamlit==1.26.0
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moviepy==1.0.3
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openai-whisper==20231117
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requests>=2.28.0
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humanize>=4.6.0
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# PyTorch ecosystem - updated for SpeechBrain 1.0 compatibility
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# torchaudio >= 2.1.0 is REQUIRED for diarization to work properly
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# NOTE: For Docker GPU builds, these are installed separately from cu118 index
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torch>=2.1.0
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torchaudio>=2.1.0
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torchvision>=0.16.0
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# Transformers ecosystem - compatible versions
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transformers==4.35.0
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tokenizers>=0.14.0
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# ML dependencies with compatible versions
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numpy==1.24.3
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scipy==1.10.1
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scikit-learn==1.3.0
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# Audio processing and ML models
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# Pin speechbrain for stability with pyannote.audio
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speechbrain==1.0.0
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pyannote.audio==3.1.1
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pytorch-lightning==2.1.0
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# Other dependencies
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iso639>=0.1.4
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protobuf>=3.20.0,<5.0.0
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matplotlib>=3.5.0
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soundfile>=0.10.3
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ffmpeg-python>=0.2.0
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# Optional: Ollama Python client (uncomment to install)
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# ollama
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# Installation notes:
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# 1. For Windows users, you may need to install PyTorch separately:
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# pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
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#
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# 2. For tokenizers issues, try installing Visual C++ Build Tools:
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# https://visualstudio.microsoft.com/visual-cpp-build-tools/
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#
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# 3. For pyannote.audio, you'll need a HuggingFace token with access to:
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# https://huggingface.co/pyannote/speaker-diarization-3.0
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#
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# 4. FFmpeg is required for audio processing:
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# Windows: https://www.gyan.dev/ffmpeg/builds/
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# Mac: brew install ffmpeg
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# Linux: apt-get install ffmpeg
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