Update app.py

app.py

@@ -1,79 +1,3 @@
-# import gradio as gr
-
-# # 1. Add the CSS string at the top of your file
-# CSS = """
-# .container { max-width: 1200px; margin: auto; }
-# /* This forces tables to scroll horizontally instead of squishing */
-# .prose table { 
-#     display: block; 
-#     overflow-x: auto; 
-#     white-space: nowrap;
-#     width: 100%;
-# }
-# .prose th, .prose td {
-#     padding: 10px;
-#     border: 1px solid #444;
-#     min-width: 150px;
-# }
-# """
-
-# print("Initializing AI trained Models... (This will run core_engine.py)")
-
-# # 2. Just import it! 
-# # Because your engine initializations are at the bottom of core_engine.py,
-# # this single import line will automatically trigger them to load.
-# from core_engine import (
-#     run_multi_step_workflow, 
-#     chat_memory, 
-#     engine_derby, 
-#     engine_influx
-# )
-
-# print("Engine Ready! Launching UI...")
-
-# # 3. Define the Gradio Chat Function
-# def respond_to_coworker(message, history):
-#     try:
-#         # Call your orchestrator directly
-#         response = run_multi_step_workflow(
-#             message, 
-#             engine_derby, 
-#             engine_influx, 
-#             chat_memory, 
-#             debug=True # Set to False if you want to hide terminal logs
-#         )
-#         return response
-#     except Exception as e:
-#         import traceback
-#         traceback.print_exc()
-#         return f"🚨 Engine Error: {str(e)}"
-
-# # 4. Build the UI using your Blocks structure
-# with gr.Blocks(css=CSS) as demo:
-#     gr.Markdown("# 📊 DBA Diagnostic Copilot")
-#     gr.ChatInterface(
-#         fn=respond_to_coworker,
-#         examples=[
-#             "Identify the single worst spike and show me its execution plan.",
-#             "List all targets running on Linux.",
-#             "What are the top sql issues on the production target?",
-#             "What is the current status of all my targets?"
-#         ]
-#     )
-
-# # 5. Launch unconditionally to prevent the "Exit code: 0" bug on HF Spaces
-# print("Starting Gradio server...")
-# demo.launch()
-
-
-
-
-
-
-
-
-
-
 
 # import gradio as gr
 
@@ -96,7 +20,7 @@
 
 # print("Initializing AI trained Models... (This will run core_engine.py)")
 
-# # 2. Import the CLASS (DialogueStateTracker), not the global instance
+# # 2. Import the components from your engine
 # from core_engine import (
 #     run_multi_step_workflow, 
 #     DialogueStateTracker, 
@@ -124,7 +48,7 @@
 # # The main brain: runs the engine using the cleanly saved message string
 # def bot_response(saved_msg, history, session_memory):
 #     try:
-#         # 1. Run the engine using the pure string, avoiding any 'list' object errors
+#         # 1. Run the engine using the pure string
 #         response = run_multi_step_workflow(
 #             saved_msg, 
 #             engine_derby, 
@@ -133,18 +57,25 @@
 #             debug=True 
 #         )
         
+#         # 2. Grab the state from the engine
+#         state = session_memory.get_state()
+#         active_target = state.get("active_target")
+        
+#         # 3. Inject the visual context indicator directly into the chat bubble!
+#         if active_target:
+#             response = f"> 🎯 **Context Locked:** `{active_target}`\n\n" + str(response)
+#         else:
+#             response = str(response)
+        
 #         # Safely update the blank assistant placeholder regardless of Gradio version
 #         if isinstance(history[-1], dict):
-#             history[-1]["content"] = str(response)
+#             history[-1]["content"] = response
 #         elif hasattr(history[-1], "content"): # For Gradio dataclasses
-#             history[-1].content = str(response)
+#             history[-1].content = response
 #         else: # Fallback for old Gradio versions
-#             history[-1] = (history[-1][0], str(response))
-        
-#         # 2. Extract the current context to update the UI Status Bar
-#         state = session_memory.get_state()
-#         active_target = state.get("active_target")
+#             history[-1] = (history[-1][0], response)
         
+#         # 4. Extract the current context to update the UI Status Bar as well
 #         if active_target:
 #             status = f"🎯 **Current Context:** `{active_target}`"
 #         else:
@@ -166,17 +97,17 @@
             
 #         return history, gr.update()
 
-# # 3. Build the UI
+# # 5. Build the UI
 # with gr.Blocks() as demo:
 #     gr.Markdown("# 📊 DBA Diagnostic Copilot")
     
 #     status_bar = gr.Markdown("🌐 **Current Context:** Global (Derby/Influx)")
     
-#     chatbot = gr.Chatbot(height=550) # No 'type' argument needed here anymore
+#     chatbot = gr.Chatbot(height=550) 
     
-#     # State variables
+#     # State variables (Private per user tab)
 #     chat_memory = gr.State(init_memory)
-#     saved_msg = gr.State("") # NEW: Safely holds the pure string message
+#     saved_msg = gr.State("") # Safely holds the pure string message
     
 #     with gr.Row():
 #         msg = gr.Textbox(
@@ -239,13 +170,13 @@
 
 
 
-
 import gradio as gr
 
-# 1. Add the CSS string at the top of your file
+# 1. CSS for Horizontal Tables & Terminal Styling
 CSS = """
 .container { max-width: 1200px; margin: auto; }
-/* This forces tables to scroll horizontally instead of squishing */
+
+/* Forces tables to scroll horizontally */
 .prose table { 
     display: block; 
     overflow-x: auto; 
@@ -257,11 +188,80 @@ CSS = """
     border: 1px solid #444;
     min-width: 150px;
 }
+
+/* Terminal-like Status Badge above the input box */
+.terminal-status {
+    padding: 6px 12px;
+    background-color: #1e1e1e;
+    color: #10B981; /* Emerald Green */
+    border-radius: 4px;
+    font-family: 'Courier New', Courier, monospace;
+    font-size: 14px;
+    font-weight: bold;
+    display: inline-block;
+    border: 1px solid #333;
+    margin-bottom: -10px;
+}
+"""
+
+# 2. Custom JavaScript for Terminal 'Up/Down' Arrow History
+# This script waits for the Gradio textarea to render, then attaches a keydown listener
+# to cycle through previously sent messages exactly like a bash terminal.
+JS_HEAD = """
+<script>
+document.addEventListener('DOMContentLoaded', function() {
+    let setupDone = false;
+    setInterval(() => {
+        if (setupDone) return;
+        const textareas = document.querySelectorAll('textarea');
+        if(textareas.length > 0) {
+            const inputField = textareas[0];
+            let history = [];
+            let historyIndex = -1;
+            let currentDraft = "";
+
+            inputField.addEventListener('keydown', (e) => {
+                // Save to history on Enter (without Shift)
+                if (e.key === 'Enter' && !e.shiftKey) {
+                    const val = inputField.value.trim();
+                    if (val && (history.length === 0 || history[0] !== val)) {
+                        history.unshift(val); // Add to beginning of history
+                    }
+                    historyIndex = -1;
+                } 
+                // Navigate up in history
+                else if (e.key === 'ArrowUp') {
+                    if (history.length > 0) {
+                        e.preventDefault();
+                        if (historyIndex === -1) currentDraft = inputField.value;
+                        historyIndex = Math.min(historyIndex + 1, history.length - 1);
+                        inputField.value = history[historyIndex];
+                        inputField.dispatchEvent(new Event('input', { bubbles: true })); // Tell Gradio it changed
+                    }
+                } 
+                // Navigate down in history
+                else if (e.key === 'ArrowDown') {
+                    if (historyIndex > -1) {
+                        e.preventDefault();
+                        historyIndex--;
+                        if (historyIndex === -1) {
+                            inputField.value = currentDraft;
+                        } else {
+                            inputField.value = history[historyIndex];
+                        }
+                        inputField.dispatchEvent(new Event('input', { bubbles: true }));
+                    }
+                }
+            });
+            setupDone = true;
+        }
+    }, 500); // Check every 500ms until Gradio renders the textbox
+});
+</script>
 """
 
 print("Initializing AI trained Models... (This will run core_engine.py)")
 
-# 2. Import the components from your engine
 from core_engine import (
     run_multi_step_workflow, 
     DialogueStateTracker, 
@@ -271,25 +271,19 @@ from core_engine import (
 
 print("Engine Ready! Launching UI...")
 
-# Helper to initialize a fresh, private memory for every new user
 def init_memory():
     return DialogueStateTracker()
 
-# Prepares the UI instantly and safely saves the raw string typed by the user
 def prepare_msg(message, history):
-    # Force the string cast just to be absolutely safe
     clean_message = str(message)
-    
     new_history = history + [
         {"role": "user", "content": clean_message}, 
         {"role": "assistant", "content": ""}
     ]
     return "", new_history, clean_message
 
-# The main brain: runs the engine using the cleanly saved message string
 def bot_response(saved_msg, history, session_memory):
     try:
-        # 1. Run the engine using the pure string
         response = run_multi_step_workflow(
             saved_msg, 
             engine_derby, 
@@ -298,29 +292,28 @@ def bot_response(saved_msg, history, session_memory):
             debug=True 
         )
         
-        # 2. Grab the state from the engine
         state = session_memory.get_state()
         active_target = state.get("active_target")
         
-        # 3. Inject the visual context indicator directly into the chat bubble!
+        # Keep the visual context indicator in the chat bubble for historical logging
         if active_target:
             response = f"> 🎯 **Context Locked:** `{active_target}`\n\n" + str(response)
         else:
             response = str(response)
         
-        # Safely update the blank assistant placeholder regardless of Gradio version
+        # Safely update the history
         if isinstance(history[-1], dict):
             history[-1]["content"] = response
-        elif hasattr(history[-1], "content"): # For Gradio dataclasses
+        elif hasattr(history[-1], "content"):
             history[-1].content = response
-        else: # Fallback for old Gradio versions
+        else:
             history[-1] = (history[-1][0], response)
         
-        # 4. Extract the current context to update the UI Status Bar as well
+        # Update the Terminal Prompt Status Bar
         if active_target:
-            status = f"🎯 **Current Context:** `{active_target}`"
+            status = f"<div class='terminal-status'>[ Target : {active_target} ] $ </div>"
         else:
-            status = f"🌐 **Current Context:** Global (Derby/Influx)"
+            status = f"<div class='terminal-status'>[ Target : Global (Derby/Influx) ] $ </div>"
             
         return history, status
         
@@ -338,17 +331,18 @@ def bot_response(saved_msg, history, session_memory):
             
         return history, gr.update()
 
-# 5. Build the UI
-with gr.Blocks() as demo:
+# 3. Build the UI with the JS Header Injection
+with gr.Blocks(head=JS_HEAD) as demo:
     gr.Markdown("# 📊 DBA Diagnostic Copilot")
     
-    status_bar = gr.Markdown("🌐 **Current Context:** Global (Derby/Influx)")
+    # SHORTER CHATBOT HEIGHT (400px instead of 550px)
+    chatbot = gr.Chatbot(height=400) 
     
-    chatbot = gr.Chatbot(height=550) 
-    
-    # State variables (Private per user tab)
     chat_memory = gr.State(init_memory)
-    saved_msg = gr.State("") # Safely holds the pure string message
+    saved_msg = gr.State("") 
+    
+    # NEW LOCATION: Status bar is now right above the input box!
+    status_bar = gr.Markdown("<div class='terminal-status'>[ Target : Global (Derby/Influx) ] $ </div>")
     
     with gr.Row():
         msg = gr.Textbox(
@@ -363,12 +357,11 @@ with gr.Blocks() as demo:
         
         def reset_context(memory):
             memory.clear_target_context()
-            return memory, "🌐 **Current Context:** Global (Derby/Influx)"
+            return memory, "<div class='terminal-status'>[ Target : Global (Derby/Influx) ] $ </div>"
         
         reset_ctx_btn = gr.Button("🔄 Clear Target Context", scale=2)
         reset_ctx_btn.click(reset_context, inputs=[chat_memory], outputs=[chat_memory, status_bar])
 
-    # Event wiring: Pass the saved string state to the bot_response
     msg.submit(
         prepare_msg, 
         inputs=[msg, chatbot],