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version: '3.8'
services:
theoremexplain:
build:
context: .
dockerfile: dockerfile
container_name: theoremexplain-agent
ports:
- "7860:7860"
volumes:
# Mount output directory to persist generated videos
- ./output:/app/output
# Mount models directory if you want to use local models
- ./models:/app/models
# Mount data directory for RAG and datasets
- ./data:/app/data
environment:
# Copy environment variables from host .env file
- OPENAI_API_KEY=${OPENAI_API_KEY}
- GEMINI_API_KEY=${GEMINI_API_KEY}
# Kokoro TTS settings
- KOKORO_MODEL_PATH=models/kokoro-v0_19.onnx
- KOKORO_VOICES_PATH=models/voices.bin
- KOKORO_DEFAULT_VOICE=af
- KOKORO_DEFAULT_SPEED=1.0
- KOKORO_DEFAULT_LANG=en-us
# Python path
- PYTHONPATH=/app:$PYTHONPATH
restart: unless-stopped
healthcheck:
test: ["uv", "run" , "manim" ,"checkhealth"]
interval: 30s
timeout: 10s
retries: 3
start_period: 60s
# Optional: Add a service for running batch generation
theoremexplain-batch:
build:
context: .
dockerfile: dockerfile
container_name: theoremexplain-batch
profiles:
- batch
volumes:
- ./output:/app/output
- ./models:/app/models
- ./data:/app/data
environment:
# Same environment variables as main service
- OPENAI_API_KEY=${OPENAI_API_KEY}
- GEMINI_API_KEY=${GEMINI_API_KEY}
- KOKORO_MODEL_PATH=models/kokoro-v0_19.onnx
- KOKORO_VOICES_PATH=models/voices.bin
- KOKORO_DEFAULT_VOICE=af
- KOKORO_DEFAULT_SPEED=1.0
- KOKORO_DEFAULT_LANG=en-us
- PYTHONPATH=/app:$PYTHONPATH
command: >
uv run python generate_video.py
--model "openai/gpt-4o-mini"
--helper_model "openai/gpt-4o-mini"
--output_dir "output/batch_generation"
--theorems_path "data/thb_easy/math.json"
--max_scene_concurrency 3
--max_topic_concurrency 5
restart: no
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