Update app.py

app.py

@@ -444,338 +444,6 @@ 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 URL is provided, process the YouTube video
-#         if url.strip():
-#             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", "", ""
-
-#         # If keywords are provided, 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 get_recommendations(keywords, max_results=5):
-#     """
-#     Fetches related video recommendations based on the provided keywords.
-#     """
-#     YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
-#     if not keywords.strip():
-#         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]
-#     )
-
-# if __name__ == "__main__":
-#     app.launch()
-
-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):
-    """
-    Extract the video ID from a YouTube URL.
-    """
-    import re
-    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):
-    """
-    Clean text for sentiment analysis.
-    """
-    import re
-    return re.sub(r"[^a-zA-Z0-9\s]", "", text)
-
-def extract_subtitle_info(cleaned_text):
-    """
-    Extract additional information from subtitles (e.g., keywords, summary).
-    """
-    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):
-    """
-    Fetch metadata for a YouTube video using the YouTube Data API.
-    """
-    YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
-    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"]:
-            snippet = response["items"][0]["snippet"]
-            return {
-                "title": snippet.get("title", "N/A"),
-                "description": snippet.get("description", "N/A"),
-                "channelTitle": snippet.get("channelTitle", "N/A")
-            }
-        return {}
-    except Exception as e:
-        return {"error": str(e)}
-
-def get_recommendations(keywords, max_results=5):
-    """
-    Fetches related video recommendations based on the provided keywords.
-    """
-    YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
-    if not keywords.strip():
-        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)}"
-
 def process_youtube_video(url="", keywords=""):
     try:
         # Initialize variables
@@ -814,7 +482,8 @@ def process_youtube_video(url="", keywords=""):
                 sentiment_label = f"{'Positive' if sentiment.polarity > 0 else 'Negative' if sentiment.polarity < 0 else 'Neutral'} ({sentiment.polarity:.2f})"
 
                 # Generate summary
-                summary = f"Summary: {cleaned_text[:400]}..."
+                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)
@@ -841,6 +510,40 @@ def process_youtube_video(url="", keywords=""):
     except Exception as e:
         return None, f"Error: {str(e)}", "N/A", "", ""
 
+def get_recommendations(keywords, max_results=5):
+    """
+    Fetches related video recommendations based on the provided keywords.
+    """
+    YOUTUBE_API_KEY = "AIzaSyD_SDF4lC3vpHVAMnBOcN2ZCTz7dRjUc98"  # Replace with your YouTube Data API key
+    if not keywords.strip():
+        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
@@ -857,11 +560,58 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
             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):
-                youtube_page = gr.Group()
+                # 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():
@@ -887,7 +637,7 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
                             recommendations = gr.Textbox(label="🎯 Related Videos", lines=10)
 
     def login_check(user, pwd):
-        if user == "admin" and pwd == "admin":  # Replace with secure authentication
+        if USER_CREDENTIALS.get(user) == pwd:
             return {
                 login_page: gr.update(visible=False),
                 main_page: gr.update(visible=True),
@@ -900,7 +650,13 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
         }
 
     def show_page(page_name):
-        updates = {youtube_page: gr.update(visible=False)}
+        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
 
@@ -911,6 +667,10 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
         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(
@@ -929,3 +689,5 @@ with gr.Blocks(theme=gr.themes.Soft()) as app:
 
 if __name__ == "__main__":
     app.launch()
+
+