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app.py

@@ -1,18 +1,18 @@
 import argparse, os,sys
 parser = argparse.ArgumentParser(description="WhisperVQ Application")
-parser.add_argument('--log_path', type=str,
+parser.add_argument('--log-path', type=str,
                     default='whisper.log', help='The log file path')
-parser.add_argument('--log_level', type=str, default='INFO',
+parser.add_argument('--log-level', type=str, default='INFO',
                     choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'TRACE'], help='The log level')
 parser.add_argument('--port', type=int, default=3348,
                     help='The port to run the WhisperVQ app on')
-parser.add_argument('--device_id', type=str, default="0",
+parser.add_argument('--device-id', type=str, default="0",
                     help='The port to run the WhisperVQ app on')
-parser.add_argument('--package_dir', type=str, default="",
+parser.add_argument('--package-dir', type=str, default="",
                     help='The package-dir to be extended to sys.path')
 args = parser.parse_args()
 sys.path.insert(0, args.package_dir)
-os.environ["CUDA_VISIBLE_DEVICES"] =args.device_id # Use the first Nvidia GPU
+os.environ["CUDA_VISIBLE_DEVICES"] = args.device_id # Use the first Nvidia GPU
 
 import logging
 import uvicorn
@@ -34,7 +34,6 @@ logger = logging.getLogger(__name__)
 
 from services.AudioTokenizerService import get_audio_tokenizer_service
 from routes.AudioTokenizerRoute import audio_tokenizer_router
-from routes.InferenceRoute import audio_inference_router
 
 @asynccontextmanager
 async def lifespan(app: FastAPI):
@@ -48,7 +47,6 @@ app = FastAPI(lifespan=lifespan)
 
 # include the routes
 app.include_router(audio_tokenizer_router)
-app.include_router(audio_inference_router)
 
 def self_terminate():
     time.sleep(1)
@@ -61,10 +59,6 @@ async def destroy():
     threading.Thread(target=self_terminate, daemon=True).start()
     return {"success": True}
 
-@app.get("/health")
-async def health():
-    return {"status": "OK"}
-
 if __name__ == "__main__":
     import uvicorn
     from uvicorn.config import LOGGING_CONFIG

model.yml

@@ -1,39 +0,0 @@
-# BEGIN GENERAL GGUF METADATA
-id: whispervq:fp16 # Model ID unique between models 
-model: whispervq:fp16 # Model ID which is used for request construct - should be unique between models (author / quantization)
-name: Ichigo WhisperVQ
-version: 1 # metadata.version
-
-# END GENERAL METADATA
-
-# BEGIN INFERENCE PARAMETERS
-# BEGIN REQUIRED
-
-
-# END REQUIRED
-
-# BEGIN OPTIONAL
-
-# END OPTIONAL
-# END INFERENCE PARAMETERS
-
-# BEGIN SERVER START PARAMETERS
-# BEGIN REQUIRED
-model_location: /home/thuan/cortexcpp/models/cortex.so/whispervq/fp16
-port: 3348
-log_path: whisper.log
-log_level: INFO
-environment: whispervq # python environment to run model
-script: app.py
-command: ["python"] # this is the base command, cortex will automatic find the correct location of python in env and add params when execute command
-
-engine: python-engine
-# END REQUIRED
-
-# BEGIN OPTIONAL
-extra_params:
-  device_id: "0"
-  package_dir: "" # the package directory to be searched
-
-# END OPTIONAL
-# END SERVER START PARAMETERS

models/audio.py

@@ -20,7 +20,3 @@ FORMAT_BACKENDS = {
     AudioFormat.OPUS: ["ffmpeg"],
     AudioFormat.PCM: ["soundfile"]
 }
-
-class AudioRequest(BaseModel):
-    data: str
-    format: AudioFormat = "wav"