autoclear

app.py

@@ -1,5 +1,4 @@
 import gradio as gr
-from gradio import state
 import os
 import time
 import threading
@@ -12,11 +11,11 @@ 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)
+# Global variable for tracking last interaction time
+last_interaction_time = 0
 
 def loading_pdf():
-    return "Working the upload. Also, pondering the usefulness of sporks..."
+    return "Working on the upload. Also, pondering the usefulness of sporks..."
 
 def pdf_changes(pdf_doc):
     loader = OnlinePDFLoader(pdf_doc.name)
@@ -28,10 +27,9 @@ 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():
@@ -48,18 +46,15 @@ def add_text(history, text):
 def bot(history):
     response = infer(history[-1][0], history)
     formatted_response = "**Bot:**  \n" + '  \n'.join(response.split('. '))
-    history[-1][1] = ""
-    
-    for character in formatted_response:     
-        history[-1][1] += character
-        time.sleep(0.05)
-        yield history
+    history[-1][1] = formatted_response
+    return history
 
 def infer(question, history):
     res = []
     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})
@@ -67,13 +62,13 @@ def infer(question, history):
 
 def auto_clear_data():
     global qa, last_interaction_time
-    if time.time() - last_interaction_time > 600:  # 600 seconds = 10 minutes
+    if time.time() - last_interaction_time > 600:
         qa = None
 
 def periodic_clear():
     while True:
         auto_clear_data()
-        time.sleep(60)  # Check every minute
+        time.sleep(60)
 
 threading.Thread(target=periodic_clear).start()
 
@@ -85,8 +80,8 @@ title = """
 <div style="text-align: center;max-width: 700px;">
     <h1>CauseWriter Chat with PDF • OpenAI</h1>
     <p style="text-align: center;">Upload a .PDF from your computer, click the "Load PDF to LangChain" button, <br />
-    when everything is ready, you can start asking questions about the pdf ;) <br />
-    This version is set to store chat history, and uses OpenAI as LLM.</p>
+    when everything is ready, you can start asking questions about the pdf. <br />
+    This version is set to store chat history and uses OpenAI as LLM.</p>
 </div>
 """