auto clear

app.py

@@ -1,6 +1,8 @@
 import gradio as gr
+from gradio import state
 import os
 import time
+import threading
 from langchain.document_loaders import OnlinePDFLoader
 from langchain.text_splitter import CharacterTextSplitter
 from langchain.llms import OpenAI
@@ -10,6 +12,9 @@ from langchain.chains import ConversationalRetrievalChain
 
 os.environ['OPENAI_API_KEY'] = os.getenv("Your_API_Key")
 
+# Declare session state for tracking last interaction time
+last_interaction_time = state.declare("last_interaction_time", 0)
+
 def loading_pdf():
     return "Working the upload. Also, pondering the usefulness of sporks..."
 
@@ -23,9 +28,10 @@ def pdf_changes(pdf_doc):
     retriever = db.as_retriever()
     global qa 
     qa = ConversationalRetrievalChain.from_llm(
-        llm=OpenAI(temperature=0.5),  
-        retriever=retriever, 
-        return_source_documents=False)
+        llm=OpenAI(temperature=0.5),
+        retriever=retriever,
+        return_source_documents=False
+    )
     return "Ready"
 
 def clear_data():
@@ -34,6 +40,8 @@ def clear_data():
     return "Data cleared"
 
 def add_text(history, text):
+    global last_interaction_time
+    last_interaction_time = time.time()
     history = history + [(text, None)]
     return history, ""
 
@@ -52,12 +60,23 @@ def infer(question, history):
     for human, ai in history[:-1]:
         pair = (human, ai)
         res.append(pair)
-    
     chat_history = res
     query = question
     result = qa({"question": query, "chat_history": chat_history})
     return result["answer"]
 
+def auto_clear_data():
+    global qa, last_interaction_time
+    if time.time() - last_interaction_time > 600:  # 600 seconds = 10 minutes
+        qa = None
+
+def periodic_clear():
+    while True:
+        auto_clear_data()
+        time.sleep(60)  # Check every minute
+
+threading.Thread(target=periodic_clear).start()
+
 css = """
 #col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
 """