Update app.py

app.py

@@ -2,8 +2,8 @@ import gradio as gr
 import cv2
 from PIL import Image
 import google.generativeai as genai
-from dotenv import load_dotenv
 import os
+from dotenv import load_dotenv
 
 load_dotenv()
 api_key = os.getenv('api_key')
@@ -17,13 +17,13 @@ def extract_frames(video_path, fps=30):
         raise ValueError("Error: Unable to open video file.")
 
     original_fps = cap.get(cv2.CAP_PROP_FPS)
-    if original_fps == 0:
-        raise ValueError("Error: Unable to retrieve FPS from video file.")
-    
-    frame_interval = int(original_fps // fps)
+    if original_fps <= 0:
+        raise ValueError("Error: Unable to retrieve valid FPS from video file.")
+
+    frame_interval = max(1, int(original_fps // fps))  
     frame_count = 0
     success, frame = cap.read()
-    
+
     while success:
         if frame_count % frame_interval == 0:
             frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
@@ -31,11 +31,12 @@ def extract_frames(video_path, fps=30):
             frames.append(pil_image)
         frame_count += 1
         success, frame = cap.read()
-    
+
     cap.release()
+
     if len(frames) == 0:
         raise ValueError("Error: No frames extracted from the video.")
-    
+
     return frames
 
 def generate_prompt(button_list):
@@ -46,7 +47,7 @@ def generate_prompt(button_list):
         "- What the button is supposed to do.\n\n"
         "Preconditions\n"
         "- Any requirements before interaction.\n\n"
-        " Test Steps\n"
+        "Test Steps\n"
         "- Concise steps for executing the test.\n\n"
         "Expected Results\n"
         "- What the expected outcome should be.\n\n"
@@ -55,31 +56,32 @@ def generate_prompt(button_list):
         "Format the output clearly for easy readability, using bullet points for key details."
     )
 
-
 def process_video(video_file, buttons_to_test):
     try:
         video_path = "uploaded_video.mp4"
         with open(video_path, "wb") as f:
-            f.write(video_file) 
-        
-        # Extract frames
-        frames = extract_frames(video_path, fps=30)
+            f.write(video_file)
+
+        frames = extract_frames(video_path, fps=15) 
+        frames_to_pass = frames[::10]  # use every 10th frame
+
         button_list = [button.strip() for button in buttons_to_test.split(",")]
         prompt = generate_prompt(button_list)
-        model = genai.GenerativeModel(model_name="gemini-1.5-pro-latest")
-        response = model.generate_content([prompt])
-        
+
+        frame_prompts = [frame for frame in frames_to_pass]
+        response = genai.GenerativeModel(model_name="gemini-1.5-pro-latest").generate_content([prompt] + frame_prompts)
+
         output_text = response.text if hasattr(response, 'text') else "Error: Invalid response from the model."
         output_text = output_text.replace("Functionality", "📋 Functionality")
         output_text = output_text.replace("Preconditions", "🔍 Preconditions")
         output_text = output_text.replace("Test Steps", "📝 Test Steps")
         output_text = output_text.replace("Expected Results", "✅ Expected Results")
         output_text = output_text.replace("Automated Testing Tools", "🛠️ Automated Testing Tools")
-        
+
         return output_text
-    
+
     except Exception as e:
-        return str(e)
+        return f"Error occurred: {str(e)}"
 
 iface = gr.Interface(
     fn=process_video,
@@ -93,5 +95,3 @@ iface = gr.Interface(
 )
 
 iface.launch(share=True)
-
-