Update app.py

app.py

@@ -9,12 +9,12 @@ import nltk
 from gtts import gTTS
 from sklearn.feature_extraction.text import TfidfVectorizer
 from langchain import HuggingFaceHub, PromptTemplate, LLMChain
-from huggingsound import SpeechRecognitionModel
 import gradio as gr
 from pytube import YouTube
 import requests
 import logging
 import os
+from huggingsound import SpeechRecognitionModel
 nltk.download('punkt')
 nltk.download('stopwords')
 
@@ -83,7 +83,6 @@ class VideoAnalytics:
     def generate_video_summary(self) -> str:
         """
         Generate a summary of the transcribed video.
-
         Returns:
             str: Generated summary.
         """
@@ -116,7 +115,6 @@ class VideoAnalytics:
     def generate_topics(self) -> str:
         """
         Generate topics from the transcribed video.
-
         Returns:
             str: Generated topics.
         """
@@ -147,7 +145,6 @@ class VideoAnalytics:
     def translation(self) -> str:
         """
         translation from the transcribed video.
-
         Returns:
             str: translation.
         """
@@ -176,11 +173,9 @@ class VideoAnalytics:
     def format_prompt(self, question: str, data: str) -> str:
         """
         Formats the prompt for the language model.
-
         Args:
             question (str): The user's question.
             data (str): The data to be analyzed.
-
         Returns:
             str: Formatted prompt.
         """
@@ -197,7 +192,6 @@ class VideoAnalytics:
                  repetition_penalty=1.0) -> str:
         """
         Generates text based on the prompt and transcribed text.
-
         Args:
             prompt (str): The prompt for generating text.
             transcribed_text (str): The transcribed text for analysis.
@@ -205,7 +199,6 @@ class VideoAnalytics:
             max_new_tokens (int): Maximum number of tokens to generate. Default is 5000.
             top_p (float): Nucleus sampling parameter. Default is 0.95.
             repetition_penalty (float): Penalty for repeating the same token. Default is 1.0.
-
         Returns:
             str: Generated text.
         """
@@ -241,11 +234,9 @@ class VideoAnalytics:
     def video_qa(self, question: str, model: str) -> str:
         """
         Performs video question answering.
-
         Args:
             question (str): The question asked by the user.
             model (str): The language model to be used ("OpenAI" or "Mixtral").
-
         Returns:
             str: Answer to the user's question.
         """
@@ -273,7 +264,6 @@ class VideoAnalytics:
     def extract_video_important_sentence(self) -> str:
         """
         Extract important sentences from the transcribed video.
-
         Returns:
             str: Extracted important sentences.
         """
@@ -315,7 +305,6 @@ class VideoAnalytics:
     def write_text_files(self, text: str, filename: str) -> None:
         """
         Write text to a file.
-
         Args:
             text (str): Text to be written to the file.
             filename (str): Name of the file.
@@ -331,10 +320,8 @@ class VideoAnalytics:
     def Download(self, link: str) -> str:
         """
         Download a video from YouTube.
-
         Args:
             link (str): YouTube video link.
-
         Returns:
             str: Path to the downloaded video file.
         """
@@ -366,11 +353,9 @@ class VideoAnalytics:
     def main(self, video: str = None, input_path: str = None) -> tuple:
         """
         Perform video analytics.
-
         Args:
             video (str): Path to the video file.
             input_path (str): Input path for the video.
-
         Returns:
             tuple: Summary, important sentences, and topics.
         """
@@ -381,19 +366,19 @@ class VideoAnalytics:
             video_ = VideoFileClip(input_path)
             duration = video_.duration
             video_.close()
-            if round(duration) <= 36000:
+            if round(duration) <= 6*600:
               text = self.transcribe_video(input_path)
             else:
-              return "Video Duration Above 10 Minutes,Try Below 10 Minutes Video","",""
+              return "Video Duration Above 10 Minutes,Try Below 10 Minutes Video","","",None,None,None
           elif video:
             video_ = VideoFileClip(video)
             duration = video_.duration
             video_.close()
-            if round(duration) <= 36000:
+            if round(duration) <= 6*600:
               text = self.transcribe_video(video)
               input_path = video
             else:
-              return "Video Duration Above 10 Minutes,Try Below 10 Minutes Video","",""
+              return "Video Duration Above 10 Minutes,Try Below 10 Minutes Video","","",None,None,None
           # Generate summary, important sentences, and topics
           summary = self.generate_video_summary()
           self.write_text_files(summary,"Summary")
@@ -454,7 +439,7 @@ class VideoAnalytics:
               submit_btn.click(self.main,[video,yt_link],[summary,Important_Sentences,Topics,summary_audio,important_sentence_audio,topics_audio])
               question.submit(self.video_qa,[question,model],result)
         demo.launch()
-        
+
 if __name__ == "__main__":
   video_analytics = VideoAnalytics()
   video_analytics.gradio_interface()