remove /status

main.py

@@ -1,12 +1,10 @@
+from faster_whisper import WhisperModel
 from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware
-import os
+from video import download_convert_video_to_audio
 import yt_dlp
 import uuid
-from typing import Dict
-
-from faster_whisper import WhisperModel
-from video import download_convert_video_to_audio
+import os
+from fastapi.middleware.cors import CORSMiddleware
 
 app = FastAPI()
 
@@ -18,10 +16,9 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
-# Create a dictionary to store the status of the current transcribing process
-# This will be updated as the process progresses
-# The key is a string describing the current process, and the value is a string describing the current status
-status: Dict[str, str] = {}
+# or run on GPU with INT8
+# model = WhisperModel(model_size, device="cuda", compute_type="int8_float16")
+# or run on CPU with INT8
 
 def segment_to_dict(segment):
     segment = segment._asdict()
@@ -31,28 +28,26 @@ def segment_to_dict(segment):
 
 @app.post("/video")
 async def download_video(video_url: str):
-    status["video"] = "Downloading..."
     download_convert_video_to_audio(yt_dlp, video_url, f"/home/user/{uuid.uuid4().hex}")
-    status["video"] = "Downloaded"
 
 @app.post("/transcribe")
 async def transcribe_video(video_url: str, beam_size: int = 5, model_size: str = "tiny", word_timestamps: bool = True):
-    status["model"] = "Loading..."
+    print("loading model")
     model = WhisperModel(model_size, device="cpu", compute_type="int8")
-    status["model"] = "Loaded"
-    status["video"] = "Downloading..."
+    print("getting hex")
     rand_id = uuid.uuid4().hex
+    print("doing download")
     download_convert_video_to_audio(yt_dlp, video_url, f"/home/user/{rand_id}")
-    status["video"] = "Downloaded"
-    status["transcription"] = "Transcribing..."
     segments, info = model.transcribe(f"/home/user/{rand_id}.mp3", beam_size=beam_size, word_timestamps=word_timestamps)
     segments = [segment_to_dict(segment) for segment in segments]
-    total_duration = round(info.duration, 2)
+    total_duration = round(info.duration, 2)  # Same precision as the Whisper timestamps.
+    print(info)
     os.remove(f"/home/user/{rand_id}.mp3")
-    status["transcription"] = "Completed"
-    status["language"] = "Detected language '%s' with probability %f" % (info.language, info.language_probability)
+    print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
+    
     return segments
 
-@app.get("/status")
-async def get_status():
-    return status
+# print("Detected language '%s' with probability %f" % (info.language, info.language_probability))
+
+# for segment in segments:
+#     print("[%.2fs -> %.2fs] %s" % (segment.start, segment.end, segment.text))