Update app.py

app.py

@@ -1,5 +1,6 @@
 import os
 import gradio as gr
+from huggingface_hub import HfApi, whoami
 from langchain.document_loaders import PyPDFLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain.embeddings import OpenAIEmbeddings
@@ -7,6 +8,8 @@ from langchain.vectorstores import FAISS
 from langchain.chains import ConversationalRetrievalChain
 from langchain.chat_models import ChatOpenAI
 from langchain.memory import ConversationBufferMemory
+from langchain.prompts import PromptTemplate
+
 
 from langchain.prompts import PromptTemplate
 
@@ -103,10 +106,25 @@ NOTE : DESCRIBE/SUMMARY should always return the overall summary of the document
 # Initialize the chatbot
 pdf_chatbot = AdvancedPdfChatbot(openai_api_key)
 
+def get_user_folder():
+    try:
+        user_info = whoami()
+        username = user_info['name']
+        user_folder = f"user_data/{username}"
+        os.makedirs(user_folder, exist_ok=True)
+        return user_folder
+    except Exception:
+        return None
+
 def upload_pdf(pdf_file):
     if pdf_file is None:
         return "Please upload a PDF file."
-    file_path = pdf_file.name
+    user_folder = get_user_folder()
+    if user_folder is None:
+        return "Please log in to upload a PDF."
+    file_path = os.path.join(user_folder, pdf_file.name)
+    with open(file_path, "wb") as f:
+        f.write(pdf_file.read())
     pdf_chatbot.load_and_process_pdf(file_path)
     return file_path
 
@@ -120,13 +138,16 @@ def clear_chatbot():
     return []
 
 def get_pdf_path():
-    # Call the method to return the current PDF path
     return pdf_chatbot.get_pdf_path()
 
 # Create the Gradio interface
 with gr.Blocks() as demo:
     gr.Markdown("# PDF Chatbot")
     
+    with gr.Row():
+        login_button = gr.LoginButton()
+        user_info = gr.Markdown()
+    
     with gr.Row():
         pdf_upload = gr.File(label="Upload PDF", file_types=[".pdf"])
         upload_button = gr.Button("Process PDF")
@@ -143,5 +164,7 @@ with gr.Blocks() as demo:
     clear.click(clear_chatbot, outputs=[chatbot_interface])
     path_button.click(get_pdf_path, outputs=[pdf_path_display])
 
+    demo.load(lambda: gr.update(visible=True), outputs=[user_info], inputs=None)
+
 if __name__ == "__main__":
     demo.launch()