Update app.py

app.py

@@ -2,39 +2,28 @@ import gradio as gr
 import google.generativeai as genai
 from pathlib import Path
 import tempfile
-
-
-
+import os
 def summarize_video(video_path):
     if video_path is None:
         return "Please upload a video file."
     
     try:
-        # Create a temporary file to store the video
-        with tempfile.NamedTemporaryFile(suffix=Path(video_path.name).suffix, delete=False) as tmp_file:
-            tmp_file.write(video_path.read())
-            video_file_path = tmp_file.name
-
+        # Since Gradio passes the path as a string, we can use it directly
         # Create the prompt
         prompt = "Summarize this video"
 
         # Set up the model
-        model = genai.GenerativeModel(model_name="models/gemini-1.5-pro", api_key=os.environ['GOOGLE_API_KEY'])
+        model = genai.GenerativeModel(model_name="models/gemini-1.5-pro", api_key = os.environ['GOOGLE_API_KEY'])
 
         # Make the LLM request
         print("Making LLM inference request...")
-        response = model.generate_content([prompt, video_file_path],
+        response = model.generate_content([prompt, video_path],
                                         request_options={"timeout": 2000})
         
         return response.text
 
     except Exception as e:
         return f"An error occurred: {str(e)}"
-    
-    finally:
-        # Clean up temporary file
-        if 'video_file_path' in locals():
-            Path(video_file_path).unlink(missing_ok=True)
 
 # Create Gradio interface
 iface = gr.Interface(