Update app.py

app.py

@@ -378,7 +378,6 @@ from googleapiclient.discovery import build
 #             print(f"\nTotal Sentences Analyzed: {sentiment['total_sentences']}")
 #####################################################################################################
 from pytube import YouTube
-import os
 import re
 from textblob import TextBlob
 from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, NoTranscriptFound
@@ -400,18 +399,20 @@ def process_youtube_video(url="", keywords=""):
 
         thumbnail = f"https://img.youtube.com/vi/{video_id}/maxresdefault.jpg"
 
-        # Multiple methods to get transcript
+        # Initialize variables for transcript fetching
         text = ""
         error_messages = []
 
-        # Method 1: YouTube Transcript API
+        # Method 1: Using YouTube Transcript API
         try:
             transcript = YouTubeTranscriptApi.get_transcript(video_id)
             text = " ".join([t['text'] for t in transcript])
+        except (TranscriptsDisabled, NoTranscriptFound) as e:
+            error_messages.append(f"Transcript API error: {str(e)}")
         except Exception as e:
-            error_messages.append(str(e))
+            error_messages.append(f"Transcript API general error: {str(e)}")
 
-        # Method 2: PyTube if first method fails
+        # Method 2: Using PyTube if the first method fails
         if not text:
             try:
                 yt = YouTube(url)
@@ -421,29 +422,30 @@ def process_youtube_video(url="", keywords=""):
                 elif 'a.en' in captions:
                     text = captions['a.en'].generate_srt_captions()
             except Exception as e:
-                error_messages.append(str(e))
+                error_messages.append(f"PyTube error: {str(e)}")
 
-        # Method 3: Try auto-generated captions
+        # Method 3: Using auto-generated captions via Transcript API
         if not text:
             try:
                 transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
                 auto_transcript = transcript_list.find_generated_transcript(['en'])
                 text = " ".join([t['text'] for t in auto_transcript.fetch()])
             except Exception as e:
-                error_messages.append(str(e))
+                error_messages.append(f"Auto-generated captions error: {str(e)}")
 
+        # Check if transcript was successfully fetched
         if not text:
             error_msg = "\n".join(error_messages)
-            return thumbnail, f"⚠️ Could not access video content. Please try another video with English subtitles.\nDetails: {error_msg}", sentiment_label, recommendations
+            return thumbnail, f"⚠️ Could not access video content. Details: {error_msg}", sentiment_label, recommendations
 
         # Process valid transcript
         try:
-            # Clean text
+            # Clean text for analysis
             cleaned_text = re.sub(r'[^\w\s.]', '', text)
             cleaned_text = ' '.join(cleaned_text.split())
 
             # Sentiment Analysis
-            blob = TextBlob(cleaned_text[:2000])
+            blob = TextBlob(cleaned_text[:2000])  # Analyze first 2000 characters for performance
             polarity = blob.sentiment.polarity
             subjectivity = blob.sentiment.subjectivity
 
@@ -453,7 +455,8 @@ def process_youtube_video(url="", keywords=""):
                 f"Subjectivity: {subjectivity:.2f}"
             )
 
-            # Generate summary using Gemini
+            # Generate summary using Gemini (Generative AI)
+            genai.configure(api_key="AIzaSyDw4LHOzdkRrU7GunTTC3_f6iS1OsAbmKA")  # Replace with your actual API key
             model = genai.GenerativeModel("gemini-pro")
             prompt = f"""Provide a comprehensive summary of this content in clear points:
             {cleaned_text[:4000]}
@@ -467,16 +470,30 @@ def process_youtube_video(url="", keywords=""):
         except Exception as e:
             return thumbnail, f"⚠️ Error processing content: {str(e)}", sentiment_label, recommendations
 
-        # Get recommendations
+        # Get recommendations based on keywords
         if keywords.strip():
             recommendations = get_recommendations(keywords)
 
         return thumbnail, summary, sentiment_label, recommendations
 
     except Exception as e:
-        print(f"Debug - Main Error: {str(e)}")
         return None, f"Error: {str(e)}", "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_recommendations(keywords):
+    """
+    Fetches related video recommendations based on the provided keywords.
+    """
+    # 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"