Update app.py

app.py

@@ -15,7 +15,6 @@ template = """Meet Arun, your youthful and witty personal assistant!
 At 21 years old, he is full of energy and always eager to help. 
 Arun's goal is to assist you with any questions or problems you might have. 
 His enthusiasm shines through in every response, making interactions enjoyable and engaging.
-
 {chat_history}
 User: {user_message}
 Chatbot:"""
@@ -25,9 +24,6 @@ prompt = PromptTemplate(
     template=template
 )
 
-# Memory (Conversation history)
-memory = ConversationBufferMemory(memory_key="chat_history")
-
 # LLM with API Key
 llm = ChatOpenAI(
     temperature=0.5,
@@ -35,28 +31,34 @@ llm = ChatOpenAI(
     api_key=openai_api_key
 )
 
-# LLM Chain
-llm_chain = LLMChain(
-    llm=llm,
-    prompt=prompt,
-    verbose=True,
-    memory=memory
-)
+# ✅ Chat Function with per-user memory
+def get_text_response(user_message, state):
+    # create a new memory if state is empty
+    if state is None:
+        state = ConversationBufferMemory(memory_key="chat_history")
+
+    # Build chain with user-specific memory
+    llm_chain = LLMChain(
+        llm=llm,
+        prompt=prompt,
+        verbose=True,
+        memory=state
+    )
 
-# Chat Function
-def get_text_response(user_message, history):
     response = llm_chain.predict(user_message=user_message)
-    return response
+    return response, state
 
-# Gradio Chat App
+# ✅ Gradio Chat App with user-specific state
 demo = gr.ChatInterface(
     fn=get_text_response,
     examples=[
         "How are you doing?",
         "What are your interests?",
         "Which places do you like to visit?"
-    ]
+    ],
+    additional_inputs=[gr.State()]  # 👈 ensures each user has independent memory
 )
 
 if __name__ == "__main__":
     demo.launch(share=True)
+