Update utils.py

utils.py

@@ -7,25 +7,27 @@ import subprocess
 # Load Whisper model
 model = whisper.load_model("base")
 
-def process_video(video_path, language):  # Accept file path, not file object
+def process_video(video_path, language, progress=None):
     output_video_path = os.path.join(tempfile.gettempdir(), "converted_video.mp4")
     srt_path = os.path.join(tempfile.gettempdir(), "subtitles.srt")
 
     try:
         # Convert video to MP4 using ffmpeg
-        print("Converting video to MP4...")
+        if progress:
+            progress(0.2, desc="🔄 Converting video to MP4...")
         subprocess.run(
             ["ffmpeg", "-i", video_path, "-c:v", "libx264", "-preset", "fast", output_video_path],
-            check=True,  # Raise error if ffmpeg fails
+            check=True,
             stdout=subprocess.PIPE,
             stderr=subprocess.PIPE
         )
-        print("Video converted successfully!")
 
         # Transcribe video
-        print("Transcribing video...")
+        if progress:
+            progress(0.4, desc="📝 Transcribing audio...")
         result = model.transcribe(output_video_path, language="en")
-        print("Transcription completed!")
+        if progress:
+            progress(0.6, desc="🌐 Translating subtitles...")
 
         # Translation logic
         segments = []
@@ -46,9 +48,9 @@ def process_video(video_path, language):  # Accept file path, not file object
             }
             model_name = model_map.get(language)
             if not model_name:
-                return f"Unsupported language: {language}"
+                return None
 
-            print(f"Loading translation model: {model_name}")
+            # Load translation model
             if language == "Telugu":
                 tokenizer = AutoTokenizer.from_pretrained(model_name)
                 translation_model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
@@ -70,13 +72,16 @@ def process_video(video_path, language):  # Accept file path, not file object
                     segments.append({"text": translated_text, "start": segment["start"], "end": segment["end"]})
 
         # Create SRT file
+        if progress:
+            progress(0.8, desc="📝 Generating SRT file...")
         with open(srt_path, "w", encoding="utf-8") as f:
             for i, segment in enumerate(segments, 1):
                 start = f"{segment['start']:.3f}".replace(".", ",")
                 end = f"{segment['end']:.3f}".replace(".", ",")
                 text = segment["text"].strip()
                 f.write(f"{i}\n00:00:{start} --> 00:00:{end}\n{text}\n\n")
-        print("SRT file created successfully!")
+        if progress:
+            progress(1.0, desc="✅ Done!")
         return srt_path
 
     except subprocess.CalledProcessError as e: