Upload 4 files

.dockerignore

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+**/__pycache__
+**/.venv
+**/.classpath
+**/.dockerignore
+**/.env
+**/.git
+**/.gitignore
+**/.project
+**/.settings
+**/.toolstarget
+**/.vs
+**/.vscode
+**/*.*proj.user
+**/*.dbmdl
+**/*.jfm
+**/bin
+**/charts
+**/docker-compose*
+**/compose*
+**/Dockerfile*
+**/node_modules
+**/npm-debug.log
+**/obj
+**/secrets.dev.yaml
+**/values.dev.yaml
+LICENSE
+README.md

.env

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+CONTAINER_PORT=7860
+HOST_PORT=7860
+SPEAKER_FOLDER="/app/speakers"

Dockerfile

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+# Use an official NVIDIA base image with CUDA support
+FROM nvidia/cuda:12.1.1-cudnn8-devel-ubuntu22.04
+
+# Set label for the docker image description
+LABEL description="Docker image for xtts-api-server"
+
+# Install required packages (avoid cache to reduce image size)
+RUN apt-get update && \
+    apt-get install --no-install-recommends -y \
+    python3-dev portaudio19-dev libportaudio2 libasound2-dev libportaudiocpp0 \
+    git python3 python3-pip make g++ ffmpeg && \
+    rm -rf /var/lib/apt/lists/*
+
+# Upgrade pip and install virtualenv
+RUN python3 -m pip install --upgrade pip setuptools wheel ninja virtualenv
+
+# Copy the application source code to /app directory and change the workdir to /app
+# COPY . /app
+# WORKDIR /app
+
+# Install Python dependencies
+RUN pip install torch torchaudio --index-url https://download.pytorch.org/whl/cu121
+RUN pip install deepspeed
+RUN pip install xtts-api-server
+
+# Expose the container ports
+EXPOSE 8020
+
+# Run xtts_api_server when the container starts
+CMD ["bash", "-c", "python3 -m xtts_api_server --listen -p 8020 -t 'http://localhost:8020' -sf 'xtts-server/speakers' -o 'xtts-server/output' -mf 'xtts-server/models' --deepspeed"]

docker-compose.yml

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+version: '3.4'
+
+services:
+  xttsapiserver:
+    image: xttsapiserver
+    env_file: .env
+    build:
+      context: ..
+      dockerfile: ./docker/Dockerfile
+    ports:
+      - "${HOST_PORT:-8020}:${CONTAINER_PORT:-8020}"
+    volumes:
+      - ./xtts-server:/xtts-server
+    deploy:
+      resources:
+        reservations:
+          devices:
+            - driver: nvidia
+              device_ids: ['0']
+              capabilities: [gpu]