Update app.py

app.py

@@ -130,366 +130,146 @@ import re
 from collections import Counter
 from googleapiclient.discovery import build
 
-# def process_youtube_video(url="", keywords=""):
-#     try:
-#         #Initialize variables
-#         thumbnail = None
-#         summary = "No transcript available"
-#         sentiment_label = "N/A"
-#         recommendations = ""
-#         subtitle_info = "No additional information available"
-
-#         if not url.strip():
-#             return None, "Please enter a YouTube URL", "N/A", "", ""
-
-#         video_id = extract_video_id(url)
-#         if not video_id:
-#             return None, "Invalid YouTube URL", "N/A", "", ""
-
-#         thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg"
-
-#         try:
-#             # Fetch transcript
-#             transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
-#             transcript = None
-#             try:
-#                 transcript = transcript_list.find_transcript(['en'])
-#             except:
-#                 transcript = transcript_list.find_generated_transcript(['en'])
-
-#             text = " ".join([t['text'] for t in transcript.fetch()])
-#             if not text.strip():
-#                 raise ValueError("Transcript is empty")
-
-#             # Clean up the text for sentiment analysis
-#             cleaned_text = clean_text_for_analysis(text)
-
-#             # Sentiment analysis
-#             sentiment = TextBlob(cleaned_text).sentiment  # Use cleaned text for sentiment analysis
-#             sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})"
-
-#             # Generate summary
-#             model = genai.GenerativeModel("gemini-pro")
-#             summary = model.generate_content(f"Summarize this: {cleaned_text[:4000]}").text
-
-#             # Extract subtitle information
-#             subtitle_info = extract_subtitle_info(cleaned_text)
-
-#         except TranscriptsDisabled:
-#             metadata = get_video_metadata(video_id)
-#             summary = metadata.get("description", "⚠️ This video has disabled subtitles.")
-#             sentiment_label = "N/A"
-#             subtitle_info = "No subtitles available for analysis."
-#         except NoTranscriptFound:
-#             metadata = get_video_metadata(video_id)
-#             summary = metadata.get("description", "⚠️ No English transcript available.")
-#             sentiment_label = "N/A"
-#             subtitle_info = "No subtitles available for analysis."
-#         except Exception as e:
-#             return thumbnail, f"⚠️ Error processing transcript: {str(e)}", "N/A", "", ""
-
-#         # Get recommendations
-#         if keywords.strip():
-#             recommendations = get_recommendations(keywords)
-
-#         return thumbnail, summary, sentiment_label, subtitle_info, recommendations
-
-#     except Exception as e:
-#         return None, f"Error: {str(e)}", "N/A", "", ""
+def process_youtube_video(url="", keywords=""):
+    try:
+        #Initialize variables
+        thumbnail = None
+        summary = "No transcript available"
+        sentiment_label = "N/A"
+        recommendations = ""
+        subtitle_info = "No additional information available"
 
+        if not url.strip():
+            return None, "Please enter a YouTube URL", "N/A", "", ""
 
-# def extract_video_id(url):
-#     """
-#     Extracts the video ID from a YouTube URL.
-#     """
-#     match = re.search(r"(?:v=|\/)([0-9A-Za-z_-]{11})", url)
-#     return match.group(1) if match else None
-
-
-# def get_video_metadata(video_id):
-#     """
-#     Fetches video metadata such as title and description using the YouTube Data API.
-#     """
-#     try:
-#         YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
-#         youtube = build("youtube", "v3", developerKey=YOUTUBE_API_KEY)
-#         request = youtube.videos().list(part="snippet", id=video_id)
-#         response = request.execute()
-
-#         if "items" in response and len(response["items"]) > 0:
-#             snippet = response["items"][0]["snippet"]
-#             return {
-#                 "title": snippet.get("title", "No title available"),
-#                 "description": snippet.get("description", "No description available"),
-#             }
-#         return {}
-
-#     except Exception as e:
-#         return {"title": "Error fetching metadata", "description": str(e)}
-
-
-# def extract_subtitle_info(text):
-#     """
-#     Extracts meaningful information from the subtitles.
-#     This could include topics, key insights, or a breakdown of the content.
-#     """
-#     try:
-#         # Split text into sentences for better analysis
-#         sentences = text.split(". ")
-        
-#         # Example: Extract key topics or keywords
-#         words = text.split()
-#         common_words = Counter(words).most_common(10)
-#         key_topics = ", ".join([word for word, count in common_words])
-
-#         # Example: Provide a breakdown of the content
-#         info = f"Key topics discussed: {key_topics}. \nNumber of sentences: {len(sentences)}. \nTotal words: {len(words)}."
-
-#         return info
-#     except Exception as e:
-#         return f"Error extracting subtitle information: {str(e)}"
-
-
-# def clean_text_for_analysis(text):
-#     """
-#     Cleans the transcript text by removing extra spaces, line breaks, and non-text elements.
-#     """
-#     # Remove extra spaces and line breaks
-#     cleaned_text = " ".join(text.split())
-#     return cleaned_text
-
-
-# def get_recommendations(keywords):
-#     """
-#     Fetches related video recommendations based on the provided keywords.
-#     This function can be expanded with a proper API or custom logic.
-#     """
-#     # Placeholder for fetching recommendations based on keywords
-#     return f"Recommendations for: {keywords}"  # Dummy return for now
-
-
-# def get_recommendations(keywords, max_results=5):
-#     if not keywords:
-#         return "Please provide search keywords"
-#     try:
-#         response = requests.get(
-#             "https://www.googleapis.com/youtube/v3/search",
-#             params={
-#                 "part": "snippet",
-#                 "q": f"educational {keywords}",
-#                 "type": "video",
-#                 "maxResults": max_results,
-#                 "relevanceLanguage": "en",
-#                 "key": YOUTUBE_API_KEY
-#             }
-#         ).json()
-        
-#         results = []
-#         for item in response.get("items", []):
-#             title = item["snippet"]["title"]
-#             channel = item["snippet"]["channelTitle"]
-#             video_id = item["id"]["videoId"]
-#             results.append(f"📺 {title}\n👤 {channel}\n🔗 https://youtube.com/watch?v={video_id}\n")
-        
-#         return "\n".join(results) if results else "No recommendations found"
-#     except Exception as e:
-#         return f"Error: {str(e)}"
-
-# # Gradio Interface
-# with gr.Blocks(theme=gr.themes.Soft()) as app:
-#     # Login Page
-#     with gr.Group() as login_page:
-#         gr.Markdown("# 🎓 Educational Learning Management System")
-#         username = gr.Textbox(label="Username")
-#         password = gr.Textbox(label="Password", type="password")
-#         login_btn = gr.Button("Login", variant="primary")
-#         login_msg = gr.Markdown()
-    
-#     # Main Interface
-#     with gr.Group(visible=False) as main_page:
-#         with gr.Row():
-#             with gr.Column(scale=1):
-#                 gr.Markdown("### 📋 Navigation")
-#                 nav_dashboard = gr.Button("📊 Dashboard", variant="primary")
-#                 nav_students = gr.Button("👥 Students")
-#                 nav_teachers = gr.Button("👨‍🏫 Teachers")
-#                 nav_courses = gr.Button("📚 Courses")
-#                 nav_youtube = gr.Button("🎥 YouTube Tool")
-#                 logout_btn = gr.Button("🚪 Logout", variant="stop")
-            
-#             with gr.Column(scale=3):
-#                 # Dashboard Content
-#                 dashboard_page = gr.Group()
-#                 with dashboard_page:
-#                     gr.Markdown("## 📊 Dashboard")
-#                     gr.Markdown(f"""
-#                     ### System Overview
-#                     - 👥 Total Students: {len(students_data)}
-#                     - 👨‍🏫 Total Teachers: {len(teachers_data)}
-#                     - 📚 Total Courses: {len(courses_data)}
-                    
-#                     ### Quick Actions
-#                     - View student performance
-#                     - Access course materials
-#                     - Generate learning insights
-#                     """)
-                
-#                 # Students Content
-#                 students_page = gr.Group(visible=False)
-#                 with students_page:
-#                     gr.Markdown("## 👥 Students")
-#                     gr.DataFrame(
-#                         value=students_data,
-#                         headers=["ID", "Name", "Grade", "Program"]
-#                     )
-                
-#                 # Teachers Content
-#                 teachers_page = gr.Group(visible=False)
-#                 with teachers_page:
-#                     gr.Markdown("## 👨‍🏫 Teachers")
-#                     gr.DataFrame(
-#                         value=teachers_data,
-#                         headers=["ID", "Name", "Subject", "Qualification"]
-#                     )
-                
-#                 # Courses Content
-#                 courses_page = gr.Group(visible=False)
-#                 with courses_page:
-#                     gr.Markdown("## 📚 Courses")
-#                     gr.DataFrame(
-#                         value=courses_data,
-#                         headers=["ID", "Name", "Instructor", "Level"]
-#                     )
-                
-#                 # YouTube Tool Content
-#                 youtube_page = gr.Group(visible=False)
-#                 with youtube_page:
-#                     gr.Markdown("## Agent for YouTube Content Exploration")
-#                     with gr.Row():
-#                         with gr.Column(scale=2):
-#                             video_url = gr.Textbox(
-#                                 label="YouTube URL",
-#                                 placeholder="https://youtube.com/watch?v=..."
-#                             )
-#                             keywords = gr.Textbox(
-#                                 label="Keywords for Recommendations",
-#                                 placeholder="e.g., python programming, machine learning"
-#                             )
-#                             analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")
-                        
-#                         with gr.Column(scale=1):
-#                             video_thumbnail = gr.Image(label="Video Preview")
-                    
-#                     with gr.Row():
-#                         with gr.Column():
-#                             summary = gr.Textbox(label="📝 Summary", lines=8)
-#                             sentiment = gr.Textbox(label="😊 Content Sentiment")
-#                         with gr.Column():
-#                             recommendations = gr.Textbox(label="🎯 Related Videos", lines=10)
-
-#     def login_check(user, pwd):
-#         if USER_CREDENTIALS.get(user) == pwd:
-#             return {
-#                 login_page: gr.update(visible=False),
-#                 main_page: gr.update(visible=True),
-#                 login_msg: ""
-#             }
-#         return {
-#             login_page: gr.update(visible=True),
-#             main_page: gr.update(visible=False),
-#             login_msg: "❌ Invalid credentials"
-#         }
-    
-#     def show_page(page_name):
-#         updates = {
-#             dashboard_page: gr.update(visible=False),
-#             students_page: gr.update(visible=False),
-#             teachers_page: gr.update(visible=False),
-#             courses_page: gr.update(visible=False),
-#             youtube_page: gr.update(visible=False)
-#         }
-#         updates[page_name] = gr.update(visible=True)
-#         return updates
-    
-#     # Event Handlers
-#     login_btn.click(
-#         login_check,
-#         inputs=[username, password],
-#         outputs=[login_page, main_page, login_msg]
-#     )
-    
-#     nav_dashboard.click(lambda: show_page(dashboard_page), outputs=list(show_page(dashboard_page).keys()))
-#     nav_students.click(lambda: show_page(students_page), outputs=list(show_page(students_page).keys()))
-#     nav_teachers.click(lambda: show_page(teachers_page), outputs=list(show_page(teachers_page).keys()))
-#     nav_courses.click(lambda: show_page(courses_page), outputs=list(show_page(courses_page).keys()))
-#     nav_youtube.click(lambda: show_page(youtube_page), outputs=list(show_page(youtube_page).keys()))
-    
-#     analyze_btn.click(
-#         process_youtube_video,
-#         inputs=[video_url, keywords],
-#         outputs=[video_thumbnail, summary, sentiment, recommendations]
-#     )
-    
-#     logout_btn.click(
-#         lambda: {
-#             login_page: gr.update(visible=True),
-#             main_page: gr.update(visible=False)
-#         },
-#         outputs=[login_page, main_page]
-#     )
+        video_id = extract_video_id(url)
+        if not video_id:
+            return None, "Invalid YouTube URL", "N/A", "", ""
 
-# if __name__ == "__main__":
-#     app.launch()
+        thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg"
 
+        try:
+            # Fetch transcript
+            transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
+            transcript = None
+            try:
+                transcript = transcript_list.find_transcript(['en'])
+            except:
+                transcript = transcript_list.find_generated_transcript(['en'])
 
+            text = " ".join([t['text'] for t in transcript.fetch()])
+            if not text.strip():
+                raise ValueError("Transcript is empty")
+
+            # Clean up the text for sentiment analysis
+            cleaned_text = clean_text_for_analysis(text)
+
+            # Sentiment analysis
+            sentiment = TextBlob(cleaned_text).sentiment  # Use cleaned text for sentiment analysis
+            sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})"
+
+            # Generate summary
+            model = genai.GenerativeModel("gemini-pro")
+            summary = model.generate_content(f"Summarize this: {cleaned_text[:4000]}").text
+
+            # Extract subtitle information
+            subtitle_info = extract_subtitle_info(cleaned_text)
+
+        except TranscriptsDisabled:
+            metadata = get_video_metadata(video_id)
+            summary = metadata.get("description", "⚠️ This video has disabled subtitles.")
+            sentiment_label = "N/A"
+            subtitle_info = "No subtitles available for analysis."
+        except NoTranscriptFound:
+            metadata = get_video_metadata(video_id)
+            summary = metadata.get("description", "⚠️ No English transcript available.")
+            sentiment_label = "N/A"
+            subtitle_info = "No subtitles available for analysis."
+        except Exception as e:
+            return thumbnail, f"⚠️ Error processing transcript: {str(e)}", "N/A", "", ""
+
+        # Get recommendations
+        if keywords.strip():
+            recommendations = get_recommendations(keywords)
+
+        return thumbnail, summary, sentiment_label, subtitle_info, recommendations
+
+    except Exception as e:
+        return None, f"Error: {str(e)}", "N/A", "", ""
 
-#############################
-import requests
-from textblob import TextBlob
-from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound
-import gradio as gr
 
-# Helper Functions
 def extract_video_id(url):
-    import re
+    """
+    Extracts the video ID from a YouTube URL.
+    """
     match = re.search(r"(?:v=|\/)([0-9A-Za-z_-]{11})", url)
     return match.group(1) if match else None
 
-def clean_text_for_analysis(text):
-    import re
-    return re.sub(r"[^a-zA-Z0-9\s]", "", text)
-
-def extract_subtitle_info(cleaned_text):
-    from collections import Counter
-    words = cleaned_text.split()
-    common_words = Counter(words).most_common(5)
-    return f"Most common words: {', '.join([word for word, _ in common_words])}"
 
 def get_video_metadata(video_id):
-    YOUTUBE_API_KEY = "YOUR_YOUTUBE_API_KEY"
+    """
+    Fetches video metadata such as title and description using the YouTube Data API.
+    """
     try:
-        response = requests.get(
-            f"https://www.googleapis.com/youtube/v3/videos",
-            params={
-                "part": "snippet",
-                "id": video_id,
-                "key": YOUTUBE_API_KEY
-            }
-        ).json()
-        if "items" in response and response["items"]:
+        YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
+        youtube = build("youtube", "v3", developerKey=YOUTUBE_API_KEY)
+        request = youtube.videos().list(part="snippet", id=video_id)
+        response = request.execute()
+
+        if "items" in response and len(response["items"]) > 0:
             snippet = response["items"][0]["snippet"]
             return {
-                "title": snippet.get("title", "N/A"),
-                "description": snippet.get("description", "N/A"),
-                "channelTitle": snippet.get("channelTitle", "N/A")
+                "title": snippet.get("title", "No title available"),
+                "description": snippet.get("description", "No description available"),
             }
         return {}
+
     except Exception as e:
-        return {"error": str(e)}
+        return {"title": "Error fetching metadata", "description": str(e)}
+
+
+def extract_subtitle_info(text):
+    """
+    Extracts meaningful information from the subtitles.
+    This could include topics, key insights, or a breakdown of the content.
+    """
+    try:
+        # Split text into sentences for better analysis
+        sentences = text.split(". ")
+        
+        # Example: Extract key topics or keywords
+        words = text.split()
+        common_words = Counter(words).most_common(10)
+        key_topics = ", ".join([word for word, count in common_words])
+
+        # Example: Provide a breakdown of the content
+        info = f"Key topics discussed: {key_topics}. \nNumber of sentences: {len(sentences)}. \nTotal words: {len(words)}."
+
+        return info
+    except Exception as e:
+        return f"Error extracting subtitle information: {str(e)}"
+
+
+def clean_text_for_analysis(text):
+    """
+    Cleans the transcript text by removing extra spaces, line breaks, and non-text elements.
+    """
+    # Remove extra spaces and line breaks
+    cleaned_text = " ".join(text.split())
+    return cleaned_text
+
+
+def get_recommendations(keywords):
+    """
+    Fetches related video recommendations based on the provided keywords.
+    This function can be expanded with a proper API or custom logic.
+    """
+    # Placeholder for fetching recommendations based on keywords
+    return f"Recommendations for: {keywords}"  # Dummy return for now
+
 
 def get_recommendations(keywords, max_results=5):
-    YOUTUBE_API_KEY = "YOUR_YOUTUBE_API_KEY"
-    if not keywords.strip():
+    if not keywords:
         return "Please provide search keywords"
     try:
         response = requests.get(
@@ -503,103 +283,165 @@ def get_recommendations(keywords, max_results=5):
                 "key": YOUTUBE_API_KEY
             }
         ).json()
-
+        
         results = []
         for item in response.get("items", []):
             title = item["snippet"]["title"]
             channel = item["snippet"]["channelTitle"]
             video_id = item["id"]["videoId"]
             results.append(f"📺 {title}\n👤 {channel}\n🔗 https://youtube.com/watch?v={video_id}\n")
-
+        
         return "\n".join(results) if results else "No recommendations found"
     except Exception as e:
         return f"Error: {str(e)}"
 
-def process_youtube_video(url):
-    try:
-        video_id = extract_video_id(url)
-        if not video_id:
-            return None, "Invalid YouTube URL", "N/A", "", ""
-
-        thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg"
-
-        try:
-            transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
-            transcript = None
-            try:
-                transcript = transcript_list.find_transcript(['en'])
-            except:
-                transcript = transcript_list.find_generated_transcript(['en'])
-
-            text = " ".join([t['text'] for t in transcript.fetch()])
-            cleaned_text = clean_text_for_analysis(text)
-
-            sentiment = TextBlob(cleaned_text).sentiment
-            sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})"
-            summary = f"Summary: {cleaned_text[:400]}..."
-            subtitle_info = extract_subtitle_info(cleaned_text)
-
-            return thumbnail, summary, sentiment_label, subtitle_info
-        except TranscriptsDisabled:
-            metadata = get_video_metadata(video_id)
-            return thumbnail, metadata.get("description", "No transcript available"), "N/A", "No subtitles available"
-        except NoTranscriptFound:
-            metadata = get_video_metadata(video_id)
-            return thumbnail, metadata.get("description", "No transcript available"), "N/A", "No subtitles available"
-    except Exception as e:
-        return None, f"Error: {str(e)}", "N/A", ""
-
-def fetch_recommendations(keywords):
-    return get_recommendations(keywords)
-
-# User credentials
-USER_CREDENTIALS = {
-    "admin": "admin"
-}
-
 # Gradio Interface
 with gr.Blocks(theme=gr.themes.Soft()) as app:
+    # Login Page
     with gr.Group() as login_page:
         gr.Markdown("# 🎓 Educational Learning Management System")
         username = gr.Textbox(label="Username")
         password = gr.Textbox(label="Password", type="password")
         login_btn = gr.Button("Login", variant="primary")
         login_msg = gr.Markdown()
-
+    
+    # Main Interface
     with gr.Group(visible=False) as main_page:
         with gr.Row():
             with gr.Column(scale=1):
                 gr.Markdown("### 📋 Navigation")
+                nav_dashboard = gr.Button("📊 Dashboard", variant="primary")
+                nav_students = gr.Button("👥 Students")
+                nav_teachers = gr.Button("👨‍🏫 Teachers")
+                nav_courses = gr.Button("📚 Courses")
                 nav_youtube = gr.Button("🎥 YouTube Tool")
                 logout_btn = gr.Button("🚪 Logout", variant="stop")
-
+            
             with gr.Column(scale=3):
+                # Dashboard Content
+                dashboard_page = gr.Group()
+                with dashboard_page:
+                    gr.Markdown("## 📊 Dashboard")
+                    gr.Markdown(f"""
+                    ### System Overview
+                    - 👥 Total Students: {len(students_data)}
+                    - 👨‍🏫 Total Teachers: {len(teachers_data)}
+                    - 📚 Total Courses: {len(courses_data)}
+                    
+                    ### Quick Actions
+                    - View student performance
+                    - Access course materials
+                    - Generate learning insights
+                    """)
+                
+                # Students Content
+                students_page = gr.Group(visible=False)
+                with students_page:
+                    gr.Markdown("## 👥 Students")
+                    gr.DataFrame(
+                        value=students_data,
+                        headers=["ID", "Name", "Grade", "Program"]
+                    )
+                
+                # Teachers Content
+                teachers_page = gr.Group(visible=False)
+                with teachers_page:
+                    gr.Markdown("## 👨‍🏫 Teachers")
+                    gr.DataFrame(
+                        value=teachers_data,
+                        headers=["ID", "Name", "Subject", "Qualification"]
+                    )
+                
+                # Courses Content
+                courses_page = gr.Group(visible=False)
+                with courses_page:
+                    gr.Markdown("## 📚 Courses")
+                    gr.DataFrame(
+                        value=courses_data,
+                        headers=["ID", "Name", "Instructor", "Level"]
+                    )
+                
+                # YouTube Tool Content
                 youtube_page = gr.Group(visible=False)
                 with youtube_page:
                     gr.Markdown("## Agent for YouTube Content Exploration")
-                    video_url = gr.Textbox(label="YouTube URL", placeholder="https://youtube.com/watch?v=...")
-                    keywords = gr.Textbox(label="Keywords for Recommendations", placeholder="e.g., python programming")
-                    analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")
-                    recommend_btn = gr.Button("🔍 Get Recommendations", variant="secondary")
-                    video_thumbnail = gr.Image(label="Video Preview")
-                    summary = gr.Textbox(label="📝 Summary", lines=8)
-                    sentiment = gr.Textbox(label="😊 Content Sentiment")
-                    subtitle_info = gr.Textbox(label="📜 Subtitle Info")
-                    recommendations = gr.Textbox(label="🎯 Related Videos", lines=10)
+                    with gr.Row():
+                        with gr.Column(scale=2):
+                            video_url = gr.Textbox(
+                                label="YouTube URL",
+                                placeholder="https://youtube.com/watch?v=..."
+                            )
+                            keywords = gr.Textbox(
+                                label="Keywords for Recommendations",
+                                placeholder="e.g., python programming, machine learning"
+                            )
+                            analyze_btn = gr.Button("🔍 Analyze Video", variant="primary")
+                        
+                        with gr.Column(scale=1):
+                            video_thumbnail = gr.Image(label="Video Preview")
+                    
+                    with gr.Row():
+                        with gr.Column():
+                            summary = gr.Textbox(label="📝 Summary", lines=8)
+                            sentiment = gr.Textbox(label="😊 Content Sentiment")
+                        with gr.Column():
+                            recommendations = gr.Textbox(label="🎯 Related Videos", lines=10)
 
     def login_check(user, pwd):
         if USER_CREDENTIALS.get(user) == pwd:
-            return {login_page: gr.update(visible=False), main_page: gr.update(visible=True), login_msg: ""}
-        return {login_page: gr.update(visible=True), main_page: gr.update(visible=False), login_msg: "❌ Invalid credentials"}
-
-    def show_youtube_page():
-        return {youtube_page: gr.update(visible=True)}
-
-    login_btn.click(login_check, inputs=[username, password], outputs=[login_page, main_page, login_msg])
-    nav_youtube.click(show_youtube_page, outputs=[youtube_page])
-    analyze_btn.click(process_youtube_video, inputs=[video_url], outputs=[video_thumbnail, summary, sentiment, subtitle_info])
-    recommend_btn.click(fetch_recommendations, inputs=[keywords], outputs=[recommendations])
-    logout_btn.click(lambda: {login_page: gr.update(visible=True), main_page: gr.update(visible=False)}, outputs=[login_page, main_page])
+            return {
+                login_page: gr.update(visible=False),
+                main_page: gr.update(visible=True),
+                login_msg: ""
+            }
+        return {
+            login_page: gr.update(visible=True),
+            main_page: gr.update(visible=False),
+            login_msg: "❌ Invalid credentials"
+        }
+    
+    def show_page(page_name):
+        updates = {
+            dashboard_page: gr.update(visible=False),
+            students_page: gr.update(visible=False),
+            teachers_page: gr.update(visible=False),
+            courses_page: gr.update(visible=False),
+            youtube_page: gr.update(visible=False)
+        }
+        updates[page_name] = gr.update(visible=True)
+        return updates
+    
+    # Event Handlers
+    login_btn.click(
+        login_check,
+        inputs=[username, password],
+        outputs=[login_page, main_page, login_msg]
+    )
+    
+    nav_dashboard.click(lambda: show_page(dashboard_page), outputs=list(show_page(dashboard_page).keys()))
+    nav_students.click(lambda: show_page(students_page), outputs=list(show_page(students_page).keys()))
+    nav_teachers.click(lambda: show_page(teachers_page), outputs=list(show_page(teachers_page).keys()))
+    nav_courses.click(lambda: show_page(courses_page), outputs=list(show_page(courses_page).keys()))
+    nav_youtube.click(lambda: show_page(youtube_page), outputs=list(show_page(youtube_page).keys()))
+    
+    analyze_btn.click(
+        process_youtube_video,
+        inputs=[video_url, keywords],
+        outputs=[video_thumbnail, summary, sentiment, recommendations]
+    )
+    
+    logout_btn.click(
+        lambda: {
+            login_page: gr.update(visible=True),
+            main_page: gr.update(visible=False)
+        },
+        outputs=[login_page, main_page]
+    )
 
 if __name__ == "__main__":
     app.launch()
+
+
+
+#############################
+