Update app.py

app.py

@@ -23,6 +23,7 @@ class AdvancedPdfChatbot:
         
         self.memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
         self.qa_chain = None
+        self.pdf_path = None
         self.template = """
         You are a study partner assistant, students give you pdfs
         and you help them to answer their questions.
@@ -41,6 +42,7 @@ class AdvancedPdfChatbot:
         documents = loader.load()
         texts = self.text_splitter.split_documents(documents)
         self.db = FAISS.from_documents(texts, self.embeddings)
+        self.pdf_path = pdf_path
         self.setup_conversation_chain()
 
     def setup_conversation_chain(self):
@@ -57,6 +59,13 @@ class AdvancedPdfChatbot:
         result = self.qa_chain({"question": query})
         return result['answer']
 
+    def get_pdf_path(self):
+        # Return the stored PDF path
+        if self.pdf_path:
+            return self.pdf_path
+        else:
+            return "No PDF uploaded yet."
+
 # Initialize the chatbot
 pdf_chatbot = AdvancedPdfChatbot(openai_api_key)
 
@@ -76,6 +85,10 @@ def clear_chatbot():
     pdf_chatbot.memory.clear()
     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")
@@ -93,6 +106,7 @@ with gr.Blocks() as demo:
 
     msg.submit(respond, inputs=[msg, chatbot_interface], outputs=[msg, chatbot_interface])
     clear.click(clear_chatbot, outputs=[chatbot_interface])
+    path_button.click(get_pdf_path, outputs=[pdf_path_display])
 
 if __name__ == "__main__":
     demo.launch()