Create fading_moments.py

fading_moments.py

@@ -0,0 +1,264 @@
+import streamlit as st
+from knowledge_bases import KNOWLEDGE_BASE_OPTIONS, SYSTEM_PROMPTS
+import genparam
+from functions import (
+    check_password,
+    initialize_session_state,
+    setup_client,
+    fetch_response,
+    capture_tokens
+)
+
+# Custom CSS for the three-column layout
+three_column_style = """
+    <style>
+    .stColumn {
+        padding: 0.5rem;
+        border-right: 1px solid #dedede;
+    }
+    .stColumn:last-child {
+        border-right: none;
+    }
+    .chat-container {
+        height: calc(100vh - 200px);
+        overflow-y: auto;
+        display: flex;
+        flex-direction: column;
+    }
+    .chat-messages {
+        display: flex;
+        flex-direction: column;
+        gap: 1rem;
+    }
+    </style>
+"""
+
+def main():
+    # Page configuration
+    st.set_page_config(
+        page_title="The Solutioning Sages",
+        page_icon="🪄",
+        initial_sidebar_state="collapsed",
+        layout="wide"
+    )
+
+    initialize_session_state()
+    st.markdown(three_column_style, unsafe_allow_html=True)
+    
+    # Sidebar configuration
+    st.sidebar.header('The Solutioning Sages')
+    st.sidebar.divider()
+    
+    # Knowledge Base Selection
+    selected_kb = st.sidebar.selectbox(
+        "Select Knowledge Base",
+        KNOWLEDGE_BASE_OPTIONS,
+        index=KNOWLEDGE_BASE_OPTIONS.index(st.session_state.selected_kb)
+    )
+    
+    # Update knowledge base if selection changes
+    if selected_kb != st.session_state.selected_kb:
+        st.session_state.selected_kb = selected_kb
+        
+    # Display current knowledge base contents
+    with st.sidebar.expander("Knowledge Base Contents"):
+        st.write("📄 [Knowledge base files would be listed here]")
+    
+    # Display active model information
+    st.sidebar.divider()
+    active_model = genparam.SELECTED_MODEL_1 if genparam.ACTIVE_MODEL == 0 else genparam.SELECTED_MODEL_2
+    st.sidebar.markdown("**Active Model:**")
+    st.sidebar.code(active_model)
+    
+    st.sidebar.divider()
+    
+    # Display token statistics in sidebar
+    st.sidebar.subheader("Token Usage Statistics")
+    if st.session_state.token_statistics:
+        interaction_count = 0
+        stats_by_time = {}
+        
+        # Group stats by timestamp
+        for stat in st.session_state.token_statistics:
+            if stat["timestamp"] not in stats_by_time:
+                stats_by_time[stat["timestamp"]] = []
+            stats_by_time[stat["timestamp"]].append(stat)
+        
+        # Display grouped stats
+        for timestamp, stats in stats_by_time.items():
+            interaction_count += 1
+            st.sidebar.markdown(f"**Interaction {interaction_count}** ({timestamp})")
+            
+            total_input = sum(stat['input_tokens'] for stat in stats)
+            total_output = sum(stat['output_tokens'] for stat in stats)
+            total = total_input + total_output
+            
+            for stat in stats:
+                st.sidebar.markdown(
+                    f"_{stat['bot_name']}_  \n"
+                    f"Input: {stat['input_tokens']} tokens  \n"
+                    f"Output: {stat['output_tokens']} tokens  \n"
+                    f"Total: {stat['total_tokens']} tokens"
+                )
+            
+            st.sidebar.markdown("**Interaction Totals:**")
+            st.sidebar.markdown(
+                f"Total Input: {total_input} tokens  \n"
+                f"Total Output: {total_output} tokens  \n"
+                f"Total Usage: {total} tokens"
+            )
+            st.sidebar.markdown("---")
+
+    if not check_password():
+        st.stop()
+
+    # Initialize WatsonX client
+    wml_credentials, client = setup_client()
+
+    # Get user input
+    user_input = st.chat_input("Ask your question here", key="user_input")
+    
+    if user_input:
+        # Create three columns
+        col1, col2, col3 = st.columns(3)
+        
+        # First column - PATH-er B.
+        with col1:
+            st.markdown("<div class='chat-container'>", unsafe_allow_html=True)
+            st.subheader(f"{genparam.BOT_1_AVATAR} {genparam.BOT_1_NAME}")
+            st.markdown("<div class='chat-messages'>", unsafe_allow_html=True)
+            
+            # Display chat history
+            for message in st.session_state.chat_history_1:
+                with st.chat_message(message["role"], avatar=message.get("avatar", None)):
+                    st.markdown(message['content'])
+            
+            # Display new messages
+            with st.chat_message("user", avatar=genparam.USER_AVATAR):
+                st.markdown(user_input)
+            
+            st.session_state.chat_history_1.append({
+                "role": "user", 
+                "content": user_input, 
+                "avatar": genparam.USER_AVATAR
+            })
+
+            # Get bot response
+            system_prompt = SYSTEM_PROMPTS[st.session_state.selected_kb]["bot_1"]
+            stream, prompt_data = fetch_response(
+                user_input, 
+                client,
+                system_prompt,
+                st.session_state.chat_history_1
+            )
+
+            with st.chat_message(genparam.BOT_1_NAME, avatar=genparam.BOT_1_AVATAR):
+                response = st.write_stream(stream)
+            
+            st.session_state.chat_history_1.append({
+                "role": genparam.BOT_1_NAME, 
+                "content": response, 
+                "avatar": genparam.BOT_1_AVATAR
+            })
+
+            # Capture tokens if enabled
+            if genparam.TOKEN_CAPTURE_ENABLED:
+                token_stats = capture_tokens(prompt_data, response, client, genparam.BOT_1_NAME)
+                if token_stats:
+                    st.session_state.token_statistics.append(token_stats)
+
+            st.markdown("</div></div>", unsafe_allow_html=True)
+
+        # Second column - MOD-ther S.
+        with col2:
+            st.markdown("<div class='chat-container'>", unsafe_allow_html=True)
+            st.subheader(f"{genparam.BOT_2_AVATAR} {genparam.BOT_2_NAME}")
+            st.markdown("<div class='chat-messages'>", unsafe_allow_html=True)
+            
+            # Display chat history
+            for message in st.session_state.chat_history_2:
+                with st.chat_message(message["role"], avatar=message.get("avatar", None)):
+                    st.markdown(message['content'])
+            
+            st.session_state.chat_history_2.append({
+                "role": "user", 
+                "content": user_input, 
+                "avatar": genparam.USER_AVATAR
+            })
+
+            # Get bot response
+            system_prompt = SYSTEM_PROMPTS[st.session_state.selected_kb]["bot_2"]
+            stream, prompt_data = fetch_response(
+                user_input,
+                client,
+                system_prompt,
+                st.session_state.chat_history_2
+            )
+
+            with st.chat_message(genparam.BOT_2_NAME, avatar=genparam.BOT_2_AVATAR):
+                response = st.write_stream(stream)
+            
+            st.session_state.chat_history_2.append({
+                "role": genparam.BOT_2_NAME, 
+                "content": response, 
+                "avatar": genparam.BOT_2_AVATAR
+            })
+
+            # Capture tokens if enabled
+            if genparam.TOKEN_CAPTURE_ENABLED:
+                token_stats = capture_tokens(prompt_data, response, client, genparam.BOT_2_NAME)
+                if token_stats:
+                    st.session_state.token_statistics.append(token_stats)
+
+            st.markdown("</div></div>", unsafe_allow_html=True)
+            
+        # Third column - SYS-ter V.
+        with col3:
+            st.markdown("<div class='chat-container'>", unsafe_allow_html=True)
+            st.subheader(f"{genparam.BOT_3_AVATAR} {genparam.BOT_3_NAME}")
+            st.markdown("<div class='chat-messages'>", unsafe_allow_html=True)
+            
+            # Display chat history
+            for message in st.session_state.chat_history_3:
+                with st.chat_message(message["role"], avatar=message.get("avatar", None)):
+                    st.markdown(message['content'])
+            
+            st.session_state.chat_history_3.append({
+                "role": "user", 
+                "content": user_input, 
+                "avatar": genparam.USER_AVATAR
+            })
+
+            # Get bot response
+            system_prompt = SYSTEM_PROMPTS[st.session_state.selected_kb]["bot_3"]
+            stream, prompt_data = fetch_response(
+                user_input,
+                client,
+                system_prompt,
+                st.session_state.chat_history_3
+            )
+
+            with st.chat_message(genparam.BOT_3_NAME, avatar=genparam.BOT_3_AVATAR):
+                response = st.write_stream(stream)
+            
+            st.session_state.chat_history_3.append({
+                "role": genparam.BOT_3_NAME, 
+                "content": response, 
+                "avatar": genparam.BOT_3_AVATAR
+            })
+
+            # Capture tokens if enabled
+            if genparam.TOKEN_CAPTURE_ENABLED:
+                token_stats = capture_tokens(prompt_data, response, client, genparam.BOT_3_NAME)
+                if token_stats:
+                    st.session_state.token_statistics.append(token_stats)
+
+            st.markdown("</div></div>", unsafe_allow_html=True)
+
+        # Update sidebar with new question
+        st.sidebar.markdown("---")
+        st.sidebar.markdown("**Latest Question:**")
+        st.sidebar.markdown(f"_{user_input}_")
+
+if __name__ == "__main__":
+    main()