Update app.py

app.py

@@ -1,36 +1,17 @@
 import gradio as gr
 from transformers import pipeline
 
-# Load Hugging Face's hosted Whisper model (small, fast)
-asr = pipeline("automatic-speech-recognition", model="openai/whisper-small")
-
-# Function to convert video to text
-def video_to_text(video):
-    # Hugging Face pipeline can take audio from video
-    text = asr(video)["text"]
+def video_to_text(video_path):
+    asr = pipeline("automatic-speech-recognition", model="openai/whisper-small", device=-1)
+    text = asr(video_path)["text"]
     return text
 
 with gr.Blocks(theme=gr.themes.Default(primary_hue="blue")) as demo:
-    gr.Markdown(
-        """
-        # 🎥 Video-to-Text AI Tool  
-        Convert your videos into text transcripts in **seconds** — powered by Hugging Face Whisper.  
-        ---
-        **Steps:**  
-        1. Upload a short video (MP4, MOV, MKV, etc.).  
-        2. Click **Generate Transcript**.  
-        3. Copy your transcript.  
-        """
-    )
-
-    with gr.Row():
-        video_input = gr.Video(label="Upload Your Video", type="filepath")
-        transcript_output = gr.Textbox(
-            label="Transcript Output",
-            placeholder="Your transcript will appear here...",
-            lines=10
-        )
-
+    gr.Markdown("# 🎥 Video-to-Text AI Tool\nUpload a video and get the transcript instantly.")
+    
+    video_input = gr.Video(label="Upload Video", type="filepath")
+    transcript_output = gr.Textbox(label="Transcript", lines=10)
+    
     btn = gr.Button("Generate Transcript")
     btn.click(video_to_text, inputs=video_input, outputs=transcript_output)