miku-discord/soprano_to_rvc/DOCKER_DEPENDENCIES.md

Docker Container Dependencies

This document lists all Python packages explicitly installed in each Docker container, matching the exact versions from the working virtual environments.

Soprano Container (CUDA/Python 3.11.14)

Base Image

• nvidia/cuda:11.8.0-runtime-ubuntu22.04
• Python 3.11.14 (explicitly installed via deadsnakes PPA)
• pip 25.3

PyTorch Stack (CUDA 11.8)

Installed from PyTorch index (https://download.pytorch.org/whl/cu118):

• torch==2.7.1+cu118
• torchaudio==2.7.1+cu118
• torchvision==0.22.1+cu118

Core Dependencies (from requirements-soprano.txt)

fastapi==0.128.0
uvicorn==0.40.0
pyzmq==27.1.0
numpy==2.4.1
pydantic==2.12.5
python-multipart==0.0.21
sounddevice==0.5.3
pydub==0.25.1

LMDeploy and ML Dependencies

lmdeploy==0.11.1
transformers==4.57.5
tokenizers==0.22.2
huggingface-hub==0.36.0
safetensors==0.7.0
accelerate==1.12.0
sentencepiece==0.2.1
einops==0.8.1
peft==0.14.0
scipy==1.17.0

Soprano TTS

• Installed from source: pip install -e '.[lmdeploy]' from /app/soprano/
• Version: soprano-tts==0.1.0 (from local editable install)
• Git commit: f2e7c19b7de51e18d6d977dd0d1027c4b9967f50
• Features: Hallucination detection and automatic regeneration

Supporting Libraries

protobuf==6.33.4
tiktoken==0.12.0
requests==2.32.5
tqdm==4.67.1
PyYAML==6.0.3
Jinja2==3.1.6
click==8.3.1
psutil==7.2.1
packaging==25.0
filelock==3.20.3
fsspec==2026.1.0
regex==2026.1.14
certifi==2026.1.4
charset-normalizer==3.4.4
urllib3==2.6.3
idna==3.11

---

RVC Container (ROCm/Python 3.10.19)

Base Image

• rocm/pytorch:rocm6.2_ubuntu22.04_py3.10_pytorch_release_2.3.0
• Python 3.10.x (from base image, targeting 3.10.19)
• pip 24.0
• PyTorch 2.5.1+rocm6.2 (pre-installed in base)
• TorchAudio 2.5.1+rocm6.2 (pre-installed in base)
• TorchVision 0.20.1+rocm6.2 (pre-installed in base)

Core Dependencies (from requirements-rvc.txt)

fastapi==0.128.0
uvicorn==0.40.0
pyzmq==27.1.0
numpy==1.23.5
pydantic==2.12.5
python-multipart==0.0.21

Audio Processing Stack

librosa==0.10.2
soundfile==0.13.1
sounddevice==0.5.3
pydub==0.25.1
audioread==3.1.0
resampy==0.4.3
soxr==1.0.0
pyworld==0.3.2
praat-parselmouth==0.4.7
torchcrepe==0.0.23
torchfcpe==0.0.4

RVC Core Dependencies

fairseq==0.12.2
faiss-cpu==1.7.3
gradio==3.48.0
gradio_client==0.6.1
numba==0.56.4
llvmlite==0.39.0
local-attention==1.11.2

LMDeploy and ML Dependencies

lmdeploy==0.11.1
transformers==4.57.3
tokenizers==0.22.2
huggingface-hub==0.36.0
safetensors==0.7.0
accelerate==1.12.0
sentencepiece==0.2.1
einops==0.8.1
peft==0.14.0

Scientific Computing

scipy==1.15.3
scikit-learn==1.7.2
matplotlib==3.10.8
pandas==2.3.3

Additional Dependencies

av==16.1.0
pillow==10.4.0
omegaconf==2.0.6
hydra-core==1.0.7
python-dotenv==1.2.1
ray==2.53.0

Supporting Libraries

protobuf==6.33.4
tiktoken==0.12.0
requests==2.32.5
tqdm==4.67.1
PyYAML==6.0.3
Jinja2==3.1.6
click==8.3.1
psutil==7.2.1
packaging==25.0
filelock==3.20.0
fsspec==2025.10.0
regex==2025.11.3
certifi==2026.1.4
charset-normalizer==3.4.4
urllib3==2.6.3
idna==3.11

---

Key Differences Between Containers

Python Versions

• Soprano: Python 3.11.14 (installed via deadsnakes PPA)
• RVC: Python 3.10.x (from ROCm base image, targeting 3.10.19)

pip Versions

• Soprano: pip 25.3
• RVC: pip 24.0

PyTorch Versions

• Soprano: PyTorch 2.7.1 with CUDA 11.8
• RVC: PyTorch 2.5.1 with ROCm 6.2

NumPy Versions

• Soprano: NumPy 2.4.1 (latest compatible with PyTorch 2.7.1)
• RVC: NumPy 1.23.5 (required for fairseq/RVC compatibility)

FastAPI Versions

• Both: FastAPI 0.128.0 (updated from 0.88.0 in original requirements.txt)
• Both: Starlette 0.50.0 (dependency of FastAPI 0.128.0)

Transformers Versions

• Soprano: transformers==4.57.5
• RVC: transformers==4.57.3
• Slight version difference but compatible

Unique to Soprano

• soprano-tts (editable install from source)
• CUDA-specific NVIDIA packages (cublas, cudnn, etc.)

Unique to RVC

• fairseq (sequence-to-sequence modeling)
• faiss-cpu (similarity search)
• gradio (web UI framework)
• Audio processing: librosa, soundfile, pyworld, praat-parselmouth
• Voice pitch: torchcrepe, torchfcpe
• Performance: numba, llvmlite
• Attention: local-attention
• Configuration: omegaconf, hydra-core

---

Installation Order

Soprano Container

1. System packages (Python 3.11.14 via deadsnakes PPA, git, build tools)
2. Upgrade pip to 25.3
3. PyTorch with CUDA 11.8
4. Dependencies from requirements-soprano.txt
5. Soprano from source with pip install -e '.[lmdeploy]'

RVC Container

1. System packages (ffmpeg, libsndfile1, curl)
2. Set pip to 24.0 (downgrade if needed to match venv)
3. PyTorch with ROCm 6.2 (pre-installed in base image)
4. Dependencies from requirements-rvc.txt
5. Models copied to /app/models/

---

Verification

After building containers, verify installations:

Soprano Container

docker exec miku-soprano-tts python3 -c "
import torch
import soprano
import lmdeploy
print(f'PyTorch: {torch.__version__}')
print(f'CUDA available: {torch.cuda.is_available()}')
print(f'Soprano: {soprano.__version__}')
print(f'LMDeploy: {lmdeploy.__version__}')
"

RVC Container

docker exec miku-rvc-api python3 -c "
import torch
import fairseq
import librosa
import pyworld
print(f'PyTorch: {torch.__version__}')
print(f'ROCm available: {torch.cuda.is_available()}')
print(f'Fairseq: {fairseq.__version__}')
print(f'Librosa: {librosa.__version__}')
"

---

Maintenance

When updating packages:

1. Update venv first: Test in local virtual environment
2. Export packages: pip list --format=freeze > packages.txt
3. Update requirements: Update requirements-soprano.txt or requirements-rvc.txt
4. Rebuild container: docker-compose build --no-cache <service>
5. Test: Verify functionality matches bare metal

---

Notes

• All version numbers are explicitly pinned for reproducibility
• PyTorch versions are installed from specific indexes (CUDA/ROCm)
• Soprano is installed as editable package to match bare metal setup
• ROCm base image comes with PyTorch pre-installed (not in requirements file)
• CUDA packages are handled by PyTorch wheel (nvidia-cublas, nvidia-cudnn, etc.)