Update app.py

app.py

@@ -4,37 +4,34 @@ import os
 import shutil
 from faster_whisper import WhisperModel
 
-# --- 1. Model Setup (Base Model = Sahi Accuracy) ---
+# --- 1. Model Setup (Turbo Settings) ---
 model = None
 
 def load_model():
     global model
     if model is None:
-        print("📥 Loading Base Model (Best Balance)...")
-        # 'base' model accuracy aur speed ka perfect mix hai
+        print("📥 Loading Whisper Model (Base + Turbo Settings)...")
+        # 'base' model with int8 quantization for speed/accuracy balance
         model = WhisperModel("base", device="cpu", compute_type="int8")
         print("✅ Model Loaded!")
     return model
 
-# --- 2. Process Audio ---
-def process_audio(url):
-    if not url:
-        return "⚠️ URL missing!"
-        
-    output_audio = "tiktok_audio"
-    if os.path.exists(f"{output_audio}.mp3"): 
-        os.remove(f"{output_audio}.mp3")
+# --- 2. Logic: Download Audio from URL ---
+def download_audio_from_url(url):
+    output_path = "downloaded_audio"
+    # Cleanup old files
+    if os.path.exists(f"{output_path}.mp3"): os.remove(f"{output_path}.mp3")
 
-    ffmpeg_dir = "/usr/bin" # System Path
+    ffmpeg_dir = "/usr/bin" # System Path for Hugging Face
 
     ydl_opts = {
         'format': 'bestaudio/best',
-        'outtmpl': output_audio,
+        'outtmpl': output_path,
         'ffmpeg_location': ffmpeg_dir,
         'postprocessors': [{
             'key': 'FFmpegExtractAudio',
             'preferredcodec': 'mp3',
-            'preferredquality': '192', # Quality wapas badha di taaki shabd saaf sunayi dein
+            'preferredquality': '192',
         }],
         'quiet': True,
         'no_warnings': True,
@@ -48,44 +45,89 @@ def process_audio(url):
     try:
         with yt_dlp.YoutubeDL(ydl_opts) as ydl:
             ydl.download([url])
+        return f"{output_path}.mp3"
     except Exception as e:
-        return f"❌ Download Error: {str(e)}"
-
-    if not os.path.exists(f"{output_audio}.mp3"):
-        return "❌ Error: Audio file nahi mili."
+        raise Exception(f"URL Download Error: {str(e)}")
 
-    # --- Transcribe (Smart Settings) ---
+# --- 3. Main Transcribe Function (Handles Both) ---
+def transcribe_media(url_input, file_input):
+    
+    # Decide source: Priority given to File if both exist, else URL
+    audio_file_path = None
+    
     try:
+        # CASE 1: File Upload
+        if file_input is not None:
+            print(f"📂 Processing Uploaded File: {file_input}")
+            audio_file_path = file_input
+            
+        # CASE 2: URL Input
+        elif url_input and url_input.strip() != "":
+            print(f"🔗 Processing URL: {url_input}")
+            audio_file_path = download_audio_from_url(url_input)
+            
+        else:
+            return "⚠️ Error: Please provide either a Link or Upload a File."
+
+        # --- Transcribe ---
+        if not os.path.exists(audio_file_path):
+             return "❌ Error: File not found."
+
         current_model = load_model()
         
-        # 'beam_size=1' rakha hai taaki speed tez rahe
-        # Lekin model 'base' hai to accuracy acchi rahegi
+        # Turbo Settings: beam_size=1 (Fast), vad_filter=True (Skip Silence)
         segments, _ = current_model.transcribe(
-            f"{output_audio}.mp3", 
+            audio_file_path, 
             beam_size=1, 
             vad_filter=True
         )
         
         text = " ".join([s.text for s in segments])
         return text.strip()
+
     except Exception as e:
-        return f"Transcription Error: {str(e)}"
+        return f"❌ Error: {str(e)}"
 
-# --- 3. UI ---
+# --- 4. Turbo UI with Tabs ---
 css = """
-.container {max-width: 800px; margin: auto;}
-.gr-button-primary {background-color: #2563eb !important; color: white !important;} 
+.container {max-width: 900px; margin: auto;}
+.gr-button-primary {background: linear-gradient(90deg, #1CB5E0 0%, #000851 100%); border: none; color: white;}
+.tab-nav {font-weight: bold; font-size: 1.1em;}
 """
 
 with gr.Blocks(theme=gr.themes.Soft(), css=css) as demo:
-    gr.Markdown("# 📝 Accurate TikTok Transcriber")
-    
-    with gr.Row():
-        link_input = gr.Textbox(label="TikTok URL", placeholder="Paste Link Here...")
-        btn = gr.Button("Transcribe", variant="primary")
     
-    transcript_out = gr.Code(label="Transcript Result", language="markdown", interactive=False, lines=15)
+    with gr.Column(elem_classes="container"):
+        gr.Markdown("# 🚀 Turbo Transcriber (Link & Upload)")
+        gr.Markdown("Paste a TikTok link **OR** upload an Audio/Video file to get the text.")
+
+        with gr.Tabs():
+            
+            # TAB 1: Link
+            with gr.TabItem("🔗 Paste Link"):
+                url_in = gr.Textbox(label="TikTok / YouTube URL", placeholder="https://...")
+                btn_url = gr.Button("🚀 Transcribe Link", variant="primary")
 
-    btn.click(fn=process_audio, inputs=link_input, outputs=transcript_out)
+            # TAB 2: File Upload
+            with gr.TabItem("📂 Upload File"):
+                file_in = gr.Audio(label="Upload Audio or Video", type="filepath", sources=["upload", "microphone"])
+                btn_file = gr.Button("📂 Transcribe File", variant="primary")
+
+        # Output Area (Common for both)
+        transcript_out = gr.Code(label="Transcript Result", language="markdown", interactive=False, lines=15)
+
+    # --- Button Actions ---
+    # Logic: Pass 'None' to the unused input
+    btn_url.click(
+        fn=transcribe_media, 
+        inputs=[url_in, gr.State(None)], # Link diya, File None
+        outputs=transcript_out
+    )
+    
+    btn_file.click(
+        fn=transcribe_media, 
+        inputs=[gr.State(None), file_in], # Link None, File diya
+        outputs=transcript_out
+    )
 
 demo.launch()