Update app.py

app.py

@@ -4,22 +4,20 @@ from PyPDF2 import PdfReader
 from langchain_text_splitters import RecursiveCharacterTextSplitter
 from langchain_google_genai import GoogleGenerativeAIEmbeddings, ChatGoogleGenerativeAI
 from langchain_community.vectorstores import FAISS
-from langchain_classic.chains.question_answering import load_qa_chain  # Fixed import
+from langchain_classic.chains.question_answering import load_qa_chain
 from langchain_core.prompts import PromptTemplate
 from dotenv import load_dotenv
 
-# Load environment variables
 load_dotenv()
 GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
 
-# Directory to save FAISS index
 INDEX_PATH = "faiss_index"
 
 def get_pdf_text(pdf_files):
     text = ""
     for pdf in pdf_files:
         try:
-            pdf_reader = PdfReader(pdf.name)  # Gradio gives tempfile
+            pdf_reader = PdfReader(pdf.name)
             for page in pdf_reader.pages:
                 extracted = page.extract_text()
                 if extracted:
@@ -64,7 +62,7 @@ def get_conversational_chain():
     
     Answer:
     """
-    model = ChatGoogleGenerativeAI(model="gemini-1.5-flash", temperature=0.3, google_api_key=GOOGLE_API_KEY)  # Updated to a current fast model
+    model = ChatGoogleGenerativeAI(model="gemini-1.5-flash", temperature=0.3, google_api_key=GOOGLE_API_KEY)
     prompt = PromptTemplate(template=prompt_template, input_variables=["context", "question"])
     return load_qa_chain(model, chain_type="stuff", prompt=prompt)
 
@@ -95,7 +93,6 @@ def process_pdfs(pdf_files):
     result = create_vector_store(text_chunks)
     return result
 
-# Gradio UI
 with gr.Blocks(title="Chat with PDF") as demo:
     gr.Markdown("## Chat with PDF 💁")
     pdf_input = gr.File(file_types=[".pdf"], label="Upload PDF(s)", file_count="multiple")