Update app.py

app.py

@@ -49,314 +49,310 @@ def install_missing_packages():
         
     }
 
-# #"genai":None,
-# #"google-generativeai": None,
-# #"google-cloud-aiplatform":"==1.34.0"
-#     for package, version in required_packages.items():
-#         try:
-#             __import__(package)
-#         except ImportError:
-#             package_name = f"{package}{version}" if version else package
-#             subprocess.check_call(["pip", "install", package_name])
-
-# install_missing_packages()
-# # Configuration
-# USER_CREDENTIALS = {
-#     "admin": "password123",
-#     "teacher": "teach2024",
-#     "student": "learn2024"
-# }
-
-# hf_token = os.getenv("HF_TOKEN")
-# if hf_token:
-#     login(hf_token)
-# else:
-#     raise ValueError("HF_TOKEN environment variable not set.")
+#"genai":None,
+#"google-generativeai": None,
+#"google-cloud-aiplatform":"==1.34.0"
+    for package, version in required_packages.items():
+        try:
+            __import__(package)
+        except ImportError:
+            package_name = f"{package}{version}" if version else package
+            subprocess.check_call(["pip", "install", package_name])
+
+install_missing_packages()
+# Configuration
+USER_CREDENTIALS = {
+    "admin": "password123",
+    "teacher": "teach2024",
+    "student": "learn2024"
+}
+
+hf_token = os.getenv("HF_TOKEN")
+if hf_token:
+    login(hf_token)
+else:
+    raise ValueError("HF_TOKEN environment variable not set.")
     
-# # GOOGLE_API_KEY = "AIzaSyAURQb9jueh3dBQ4SITgKoR0L2_33en3yU"
-# # YOUTUBE_API_KEY = "AIzaSyB7X-RYjZmUuDSMTQsvCfyzURw5bhqOto4"
-# # genai.configure(api_key=GOOGLE_API_KEY)
-# # GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
-# # genai.configure(api_key=GOOGLE_API_KEY)
-# YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY")
-# #print("GOOGLE_API_KEY:", os.getenv("GOOGLE_API_KEY"))
-# print("YOUTUBE_API_KEY:", os.getenv("YOUTUBE_API_KEY"))
-
-# # Database
-# students_data = [
-#     (1, "Alice", "A", "Computer Science"),
-#     (2, "Aliaa", "B", "Mathematics"),
-#     (3, "Charlie", "A", "Machine Learning"),
-#     (4, "Daan", "A", "Physics"),
-#     (5, "Jhon", "C", "Math"),
-#     (6, "Emma", "A+", "Computer Science")
-# ]
-
-# teachers_data = [
-#     (1, "Dr. Smith", "Math", "MS Mathematics"),
-#     (2, "Ms. Johnson", "Science", "MSc Physics"),
-#     (3, "Ms. Jack", "Artificial Intelligence Engineer", "MSc AI"),
-#     (4, "Ms. Evelyn", "Computer Science", "MSc Computer Science"),
-# ]
-
-# courses_data = [
-#     (1, "Algebra", "Dr. Smith", "Advanced"),
-#     (2, "Biology", "Ms. Mia", "Intermediate"),
-#     (3, "Machine Learning", "Ms. Jack", "Intermediate"),
-#     (4, "Computer Science", "Ms. Evelyn", "Intermediate"),
-#     (5, "Mathematics", "Ms. Smith", "Intermediate")
-# ]
-
-# def sanitize_text(text):
-#     """Remove invalid Unicode characters."""
-#     return text.encode("utf-8", "replace").decode("utf-8")
-
-# def extract_video_id(url):
-#     if not url:
-#         return None
-#     patterns = [
-#         r'(?:v=|\/videos\/|embed\/|youtu.be\/|\/v\/|\/e\/|watch\?v=|\/watch\?v=)([^#\&\?]*)'
-#     ]
-#     for pattern in patterns:
-#         match = re.search(pattern, url)
-#         if match:
-#             return match.group(1)
-#     return None
-# from youtube_transcript_api import YouTubeTranscriptApi
-# from transformers import T5ForConditionalGeneration, T5Tokenizer
-# from nltk.sentiment.vader import SentimentIntensityAnalyzer
-# import nltk
-# import sys
-
-# # Download NLTK VADER data
-# nltk.download('vader_lexicon')
-
-# def get_youtube_transcript(video_url):
-#     """Extract transcript from a YouTube video."""
-#     video_id = video_url.split("v=")[-1]
-#     transcript = YouTubeTranscriptApi.get_transcript(video_id)
-#     full_text = " ".join([entry['text'] for entry in transcript])
-#     return full_text
-
-# def summarize_text(text, model_name="t5-small", max_length=150, min_length=40):
-#     """Summarize text using T5 model."""
-#     tokenizer = T5Tokenizer.from_pretrained(model_name)
-#     model = T5ForConditionalGeneration.from_pretrained(model_name)
-
-#     input_text = "summarize: " + text
-#     inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
-
-#     summary_ids = model.generate(inputs, max_length=max_length, min_length=min_length, length_penalty=2.0, num_beams=4, early_stopping=True)
-#     summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-#     return summary
-
-# def analyze_sentiment(text):
-#     """Perform sentiment analysis on text using VADER."""
-#     sid = SentimentIntensityAnalyzer()
-#     sentiment_scores = sid.polarity_scores(text)
-#     return sentiment_scores
-
-# def main():
-#     # Check if a URL is passed as a command-line argument
-#     if len(sys.argv) > 1:
-#         video_url = sys.argv[1]
-#     else:
-#         # Use a hardcoded URL for testing if no input is provided
-#         video_url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ"  # Replace with a valid URL
-
-#     print("Fetching transcript...")
-
-#     try:
-#         transcript = get_youtube_transcript(video_url)
-#         print("Transcript fetched successfully.")
-
-#         print("Summarizing transcript...")
-#         summary = summarize_text(transcript)
-#         print("Summary:\n", summary)
-
-#         print("Analyzing sentiment...")
-#         sentiment = analyze_sentiment(transcript)
-#         print("Sentiment Analysis:\n", sentiment)
-
-#     except Exception as e:
-#         print("An error occurred:", str(e))
-
-
-
-# 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()
+# GOOGLE_API_KEY = "AIzaSyAURQb9jueh3dBQ4SITgKoR0L2_33en3yU"
+# YOUTUBE_API_KEY = "AIzaSyB7X-RYjZmUuDSMTQsvCfyzURw5bhqOto4"
+# genai.configure(api_key=GOOGLE_API_KEY)
+# GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
+# genai.configure(api_key=GOOGLE_API_KEY)
+YOUTUBE_API_KEY = os.getenv("YOUTUBE_API_KEY")
+#print("GOOGLE_API_KEY:", os.getenv("GOOGLE_API_KEY"))
+print("YOUTUBE_API_KEY:", os.getenv("YOUTUBE_API_KEY"))
+
+# Database
+students_data = [
+    (1, "Alice", "A", "Computer Science"),
+    (2, "Aliaa", "B", "Mathematics"),
+    (3, "Charlie", "A", "Machine Learning"),
+    (4, "Daan", "A", "Physics"),
+    (5, "Jhon", "C", "Math"),
+    (6, "Emma", "A+", "Computer Science")
+]
+
+teachers_data = [
+    (1, "Dr. Smith", "Math", "MS Mathematics"),
+    (2, "Ms. Johnson", "Science", "MSc Physics"),
+    (3, "Ms. Jack", "Artificial Intelligence Engineer", "MSc AI"),
+    (4, "Ms. Evelyn", "Computer Science", "MSc Computer Science"),
+]
+
+courses_data = [
+    (1, "Algebra", "Dr. Smith", "Advanced"),
+    (2, "Biology", "Ms. Mia", "Intermediate"),
+    (3, "Machine Learning", "Ms. Jack", "Intermediate"),
+    (4, "Computer Science", "Ms. Evelyn", "Intermediate"),
+    (5, "Mathematics", "Ms. Smith", "Intermediate")
+]
+
+def sanitize_text(text):
+    """Remove invalid Unicode characters."""
+    return text.encode("utf-8", "replace").decode("utf-8")
+
+def extract_video_id(url):
+    if not url:
+        return None
+    patterns = [
+        r'(?:v=|\/videos\/|embed\/|youtu.be\/|\/v\/|\/e\/|watch\?v=|\/watch\?v=)([^#\&\?]*)'
+    ]
+    for pattern in patterns:
+        match = re.search(pattern, url)
+        if match:
+            return match.group(1)
+    return None
+from youtube_transcript_api import YouTubeTranscriptApi
+from transformers import T5ForConditionalGeneration, T5Tokenizer
+from nltk.sentiment.vader import SentimentIntensityAnalyzer
+import nltk
+import sys
+
+# Download NLTK VADER data
+nltk.download('vader_lexicon')
+
+def get_youtube_transcript(video_url):
+    """Extract transcript from a YouTube video."""
+    video_id = video_url.split("v=")[-1]
+    transcript = YouTubeTranscriptApi.get_transcript(video_id)
+    full_text = " ".join([entry['text'] for entry in transcript])
+    return full_text
+
+def summarize_text(text, model_name="t5-small", max_length=150, min_length=40):
+    """Summarize text using T5 model."""
+    tokenizer = T5Tokenizer.from_pretrained(model_name)
+    model = T5ForConditionalGeneration.from_pretrained(model_name)
+
+    input_text = "summarize: " + text
+    inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
+
+    summary_ids = model.generate(inputs, max_length=max_length, min_length=min_length, length_penalty=2.0, num_beams=4, early_stopping=True)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+    return summary
+
+def analyze_sentiment(text):
+    """Perform sentiment analysis on text using VADER."""
+    sid = SentimentIntensityAnalyzer()
+    sentiment_scores = sid.polarity_scores(text)
+    return sentiment_scores
+
+def main():
+    # Check if a URL is passed as a command-line argument
+    if len(sys.argv) > 1:
+        video_url = sys.argv[1]
+    else:
+        # Use a hardcoded URL for testing if no input is provided
+        video_url = "https://www.youtube.com/watch?v=dQw4w9WgXcQ"  # Replace with a valid URL
+
+    print("Fetching transcript...")
+
+    try:
+        transcript = get_youtube_transcript(video_url)
+        print("Transcript fetched successfully.")
+
+        print("Summarizing transcript...")
+        summary = summarize_text(transcript)
+        print("Summary:\n", summary)
+
+        print("Analyzing sentiment...")
+        sentiment = analyze_sentiment(transcript)
+        print("Sentiment Analysis:\n", sentiment)
+
+    except Exception as e:
+        print("An error occurred:", str(e))
+
+
+
+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")
+        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()
+        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")
+    # 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)}
+            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
-#                     """)
+                    ### 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"]
-#                     )
+                # 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"]
-#                     )
+                # 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"]
-#                     )
+                # 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")
+                # 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.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"
-#         }
+                    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
+    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]
-#     )
+    # 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()))
+    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]
-#     )
+    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()
-
-
-
-
+    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()