Create main.py

main.py

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+import streamlit as st
+import requests
+from datetime import datetime
+
+# Define the API endpoint
+API_URL = "https://startrz-proagents.hf.space/api/v1/prediction/cce3da9a-f1b9-4bf2-aab8-5462f52ac058"
+
+# Function to query the API with error handling
+def query(payload):
+    try:
+        response = requests.post(API_URL, json=payload, timeout=10)
+        response.raise_for_status()  # Raise an exception for bad HTTP status codes
+        return response.json()
+    except requests.exceptions.RequestException as e:
+        return {"error": str(e)}
+
+# Initialize session state for messages and cache
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+if 'cache' not in st.session_state:
+    st.session_state.cache = {}
+
+# Application title and description
+st.title("AI Networking Assistant")
+st.write("Ask me anything about networking! Type your question below or explore suggested topics.")
+
+# Sidebar with clear button and suggested questions
+with st.sidebar:
+    if st.button("Clear Conversation"):
+        st.session_state.messages = []
+        st.rerun()
+    st.header("Suggested Questions")
+    with st.expander("Click to see suggestions"):
+        st.write("- What is TCP/IP?")
+        st.write("- How does DNS work?")
+        st.write("- Explain VLANs")
+
+# Display conversation history
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(f"**{message['role'].capitalize()} ({message['timestamp']})**: {message['content']}")
+
+# Capture user input via chat interface
+if user_input := st.chat_input("Type your question here"):
+    # Record timestamp for the user's message
+    timestamp = datetime.now().strftime("%H:%M:%S")
+    
+    # Append and display the user's message
+    st.session_state.messages.append({"role": "user", "content": user_input, "timestamp": timestamp})
+    with st.chat_message("user"):
+        st.markdown(f"**User ({timestamp})**: {user_input}")
+    
+    # Check if the answer is cached
+    if user_input in st.session_state.cache:
+        answer = st.session_state.cache[user_input]
+    else:
+        # Query the API with a loading spinner
+        with st.spinner("Waiting for response..."):
+            output = query({"question": user_input})
+            if "error" in output:
+                answer = f"Error: {output['error']}"
+            else:
+                # Extract the answer, assuming the key is 'answer' (adjust if necessary)
+                answer = output.get("answer", "Sorry, I couldn't get a response.")
+            st.session_state.cache[user_input] = answer
+    
+    # Record timestamp for the assistant's response
+    timestamp = datetime.now().strftime("%H:%M:%S")
+    
+    # Append and display the assistant's response
+    st.session_state.messages.append({"role": "assistant", "content": answer, "timestamp": timestamp})
+    with st.chat_message("assistant"):
+        st.markdown(f"**Assistant ({timestamp})**: {answer}")