Update app.py

app.py

@@ -1,14 +1,12 @@
 import gradio as gr
-from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
-from langchain.llms import HuggingFacePipeline
+from langchain_community.llms import HuggingFacePipeline  # Updated import path
 from transformers import pipeline
 from bs4 import BeautifulSoup
 import requests
 from TTS.api import TTS
 import tempfile
 import os
-import shutil
 
 # Setup summarization LLM
 summary_pipe = pipeline("text2text-generation", model="google/flan-t5-base", device=-1)
@@ -23,7 +21,8 @@ Summarize the following article content in a clear, warm, and motivational tone
 Summary:
 """)
 
-summary_chain = LLMChain(llm=llm, prompt=summary_prompt)
+# Updated chaining method
+summary_chain = summary_prompt | llm
 
 # TTS model setup
 tts_model = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=False)
@@ -48,7 +47,6 @@ def generate_human_like_audio(text):
 
         tts_model.tts_to_file(text=text, file_path=wav_path)
 
-        # Convert to mp3 for download link (requires ffmpeg in Hugging Face Spaces)
         os.system(f"ffmpeg -y -i {wav_path} -codec:a libmp3lame -qscale:a 4 {mp3_path}")
 
         if os.path.exists(mp3_path):