Upload app.py

app.py

@@ -1,3 +1,5 @@
+from datetime import datetime
+
 import streamlit as st
 import openai
 import os
@@ -10,39 +12,70 @@ api_key = os.getenv("api_key")
 # Initialize OpenAI client
 client = openai.Client(api_key=api_key)
 
-def assistant_chatbot(user_query):
-    thread = client.beta.threads.create()
+# Function to handle the chat with the assistant
+def assistant_chatbot(user_query, thread_id=None):
+    if thread_id is None:
+        thread = client.beta.threads.create()
+        thread_id = thread.id
+    else:
+        thread_id = thread_id
 
     message = client.beta.threads.messages.create(
-        thread_id=thread.id,
+        thread_id=thread_id,
         role="user",
         content=user_query,
     )
 
     run = client.beta.threads.runs.create(
-        thread_id=thread.id,
-        assistant_id="asst_6o7w7E8I6m0cVfM3zFzePcb9",  # Replace with your assistant ID
+        thread_id=thread_id,
+        assistant_id="asst_6o7w7E8I6m0cVfM3zFzePcb9",
         instructions="Provide information related to health queries. Remember, this is not medical advice. For serious health concerns, consult a healthcare professional.",
     )
 
     # Wait for the run to complete
     while not run.completed_at:
-        # Streamlit does not have a direct equivalent to time.sleep(), so we poll the run status
-        run = client.beta.threads.runs.retrieve(thread_id=thread.id, run_id=run.id)
+        run = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
 
-    messages = client.beta.threads.messages.list(thread_id=thread.id)
+    messages = client.beta.threads.messages.list(thread_id=thread_id)
     last_message = messages.data[0]
     response = last_message.content[0].text.value
-    return response
+
+    return response, thread_id
+
+# Streamlit app layout and logic
+if 'thread_id' not in st.session_state:
+    st.session_state['thread_id'] = None
+
+
 
 # Streamlit app layout
 st.title("Health Assistant Chatbot")
+st.sidebar.write("Ask any health-related questions. (This is not medical advice.)")
 
-user_query = st.text_input("Enter your health query:")
+# Persistent state for messages
+if 'messages' not in st.session_state:
+    st.session_state['messages'] = []
 
-if st.button("Submit"):
-    if user_query:
-        response = assistant_chatbot(user_query)
-        st.write(response)
-    else:
-        st.write("Please enter a query.")
+user_query = st.sidebar.text_input("Enter your health query:", key="query")
+
+if st.sidebar.button("Submit"):
+    if user_query.strip():
+        response, thread_id = assistant_chatbot(user_query, st.session_state['thread_id'])
+        st.session_state['thread_id'] = thread_id
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        st.session_state['messages'].append((timestamp, "User", user_query))
+        st.session_state['messages'].append((timestamp, "Bot", response))
+
+if st.sidebar.button("Clear Chat"):
+    st.session_state['messages'] = []
+
+# Chat container
+chat_container = st.container()
+with chat_container:
+    for timestamp, role, message in st.session_state['messages']:
+        st.markdown(f"**{timestamp} {role}**: {message}")
+
+st.sidebar.markdown("---")
+if st.sidebar.button("Export Chat"):
+    st.session_state['messages'] = []
+st.sidebar.write("Disclaimer: This chatbot provides information, not medical advice.")