Update app.py

app.py

@@ -1,18 +1,19 @@
 import gradio as gr
 import os
-from langchain_community.document_loaders import PyPDFLoader
-from transformers import BitsAndBytesConfig, pipeline
-from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.output_parsers import StrOutputParser
+from PyPDF2 import PdfReader
+from transformers import pipeline
+from langchain.prompts import ChatPromptTemplate
 from io import BytesIO
 import time
+import wandb
+from rouge import Rouge
 
-# Make sure to set the environment variables or load them from a .env file
+# Environment variables setup
 os.environ['TOGETHER_API_KEY'] = 'your_together_api_key'
 os.environ['PINECONE_API_KEY'] = 'your_pinecone_api_key'
 ELEVENLABS_API_KEY = 'your_elevenlabs_api_key'
 
-# Define the summarization chain
+# Summarization prompt
 summary_prompt = """
     You are an expert AI summarization model tasked with creating a comprehensive summary for 10 years old kids of the provided context. The summary should be approximately one page long and well-structured.
 
@@ -39,13 +40,10 @@ summary_prompt_template = ChatPromptTemplate.from_template(summary_prompt)
 
 # Define the PDF extraction function
 def extract_text_from_pdf(file):
-    loader = PyPDFLoader(file)
-    pages = loader.load_and_split()
-    pc.from_documents(pages, index_name='learnverse', embedding=em)
-    
+    reader = PdfReader(file)
     text = ""
-    for page in pages:
-        text += page.page_content
+    for page in reader.pages:
+        text += page.extract_text()
     return text
 
 # Define the text-to-speech function
@@ -115,8 +113,7 @@ def evaluate_summary(generated_summary):
 # Define the main processing function
 def process_question(file):
     pdffile = extract_text_from_pdf(file)
-    three_topics = topic_chain.invoke({"context": pdffile})
-    summary = summary_pdf_chain.invoke(pdffile)
+    summary = summary_prompt_template.invoke({"context": pdffile})
     evaluation = evaluate_summary(summary)
     audio_file = text_to_speech_stream(summary)
     return summary, evaluation, audio_file
@@ -132,4 +129,3 @@ gr.Interface(
     inputs=gr.File(type="file", label="Upload PDF"),
     outputs=[gr.Textbox(label="Summary"), gr.Textbox(label="Evaluation"), gr.Audio(label="Generated Audio")]
 ).launch()
-