49 lines
1.5 KiB
YAML
49 lines
1.5 KiB
YAML
services:
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whisper-models-init:
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build:
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context: .
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image: ${OPENAI_WHISPER_IMAGE:-rk-whisper-stt-api:latest}
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command: ["python", "/app/app/download_models.py", "--target", "/models"]
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volumes:
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- whisper-models:/models
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profiles: ["init"]
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whisper-stt:
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build:
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context: .
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image: ${OPENAI_WHISPER_IMAGE:-rk-whisper-stt-api:latest}
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restart: unless-stopped
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ports:
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- "${STT_PORT:-9000}:9000"
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environment:
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MODEL_NAME: ${MODEL_NAME:-whisper-base-onnx}
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STT_API_KEY: ${STT_API_KEY:-}
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ENCODER_MODEL_PATH: /models/whisper_encoder_base_20s.onnx
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DECODER_MODEL_PATH: /models/whisper_decoder_base_20s.onnx
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MEL_FILTERS_PATH: /models/mel_80_filters.txt
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VOCAB_EN_PATH: /models/vocab_en.txt
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VOCAB_ZH_PATH: /models/vocab_zh.txt
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MAX_DECODE_TOKENS: ${MAX_DECODE_TOKENS:-128}
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VLM_ENABLED: ${VLM_ENABLED:-false}
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VLM_MODEL_NAME: ${VLM_MODEL_NAME:-qwen3-vl-2b-rkllm}
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VLM_CORE_NUM: ${VLM_CORE_NUM:-3}
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VLM_MAX_NEW_TOKENS: ${VLM_MAX_NEW_TOKENS:-256}
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VLM_MAX_CONTEXT_LEN: ${VLM_MAX_CONTEXT_LEN:-4096}
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VLM_TIMEOUT_SEC: ${VLM_TIMEOUT_SEC:-300}
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volumes:
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- whisper-models:/models:ro
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- rkllm-root:/opt/rkllm-root:ro
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devices:
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- /dev/dri:/dev/dri
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healthcheck:
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test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:9000/health')"]
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interval: 20s
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timeout: 5s
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retries: 3
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volumes:
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whisper-models:
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name: whisper-models
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rkllm-root:
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name: rkllm-root
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