Update app.py

app.py

@@ -42,10 +42,6 @@ DEFAULT_SYSTEM_PROMPT = os.getenv(
 )
 logger.info(f"App Config: WebSearch={WEB_SEARCH_ENABLED}, ToolDecisionProvider={TOOL_DECISION_PROVIDER_ENV}, ToolDecisionModelID={TOOL_DECISION_MODEL_ID_ENV}, MemoryBackend={MEMORY_STORAGE_BACKEND}")
 
-# --- Helper Functions (format_insights_for_prompt, generate_interaction_metrics, etc.) ---
-# These functions (format_insights_for_prompt, generate_interaction_metrics, 
-# process_user_interaction_gradio, deferred_learning_and_memory_task) remain the same as in the previous "full working file".
-# For brevity here, I will not repeat them. Ensure they are present in your actual app.py.
 def format_insights_for_prompt(retrieved_insights_list: list[str]) -> tuple[str, list[dict]]:
     if not retrieved_insights_list:
         return "No specific guiding principles or learned insights retrieved.", []
@@ -302,7 +298,7 @@ def handle_gradio_chat_submit(user_msg_txt: str, gr_hist_list: list, sel_prov_na
                     with tempfile.NamedTemporaryFile(mode="w", delete=False, suffix=".md", encoding='utf-8') as tmpfile:
                         tmpfile.write(curr_bot_disp_msg)
                         temp_dl_file_path = tmpfile.name
-                    def_dl_btn = gr.DownloadButton(value=temp_dl_file_path, visible=True, interactive=True) # `label` is optional here, Gradio uses filename
+                    def_dl_btn = gr.DownloadButton(value=temp_dl_file_path, visible=True, interactive=True) 
                 else: def_dl_btn = gr.DownloadButton(interactive=False, value=None, visible=False)
                 insights_md = "### Insights Considered:\n" + ("\n".join([f"- **[{i.get('type','N/A')}|{i.get('score','N/A')}]** {i.get('text','N/A')[:100]}..." for i in insights_used_parsed[:3]]) if insights_used_parsed else "*None specific.*")
                 def_detect_out_md = gr.Markdown(insights_md)
@@ -384,39 +380,42 @@ def ui_upload_memories_action_fn(uploaded_file_obj, progress=gr.Progress()):
 
 custom_theme = gr.themes.Base(primary_hue="teal", secondary_hue="purple", neutral_hue="zinc", text_size="sm", spacing_size="md", radius_size="sm", font=["System UI", "sans-serif"])
 custom_css = """
-body { background: linear-gradient(to bottom right, #2c3e50, #34495e); color: #ecf0f1; min-height: 100vh; }
-.gradio-container { background: transparent !important; max-width: 100% !important; padding: 10px !important;}
-.gr-box, .gr-panel, .gr-tabs { background-color: rgba(44, 62, 80, 0.85) !important; border-color: rgba(189, 195, 199, 0.2) !important; border-radius: 8px !important;}
-.gr-tabitem { background-color: rgba(52, 73, 94, 0.7) !important; border-radius: 6px !important; margin-bottom: 5px !important;}
-.gr-accordion { background-color: rgba(52, 73, 94, 0.75) !important; border-radius: 6px !important; }
-.gr-textbox, .gr-dropdown, .gr-button, .gr-code, .gr-chat-message, .gr-json { border-color: rgba(189, 195, 199, 0.3) !important; background-color: rgba(52, 73, 94, 0.9) !important; color: #ecf0f1 !important; border-radius: 6px !important;}
-.gr-textarea textarea { color: #ecf0f1 !important; } /* Ensure textarea text is light */
+body { background: linear-gradient(to bottom right, #2c3e50, #34495e); color: #ecf0f1; min-height: 100vh; margin:0; padding:0;}
+.gradio-container { background: transparent !important; max-width: 100% !important; padding: 1rem !important; box-sizing: border-box;}
+.gr-box, .gr-panel, .gr-tabs, .gr-accordion { background-color: rgba(44, 62, 80, 0.85) !important; border: 1px solid rgba(189, 195, 199, 0.2) !important; border-radius: 8px !important; box-shadow: 0 4px 6px rgba(0,0,0,0.1);}
+.gr-tabitem { background-color: rgba(52, 73, 94, 0.7) !important; border-radius: 6px !important; margin-bottom: 5px !important; padding: 1em !important;}
+.gr-textbox, .gr-dropdown, .gr-button, .gr-code, .gr-chat-message, .gr-json, .gr-file input[type="file"] { border: 1px solid rgba(189, 195, 199, 0.3) !important; background-color: rgba(52, 73, 94, 0.9) !important; color: #ecf0f1 !important; border-radius: 6px !important;}
+.gr-file { background-color: rgba(52, 73, 94, 0.9) !important; border-radius: 6px !important; padding: 0.5em;}
+.gr-file > .label-text { color: #bdc3c7 !important;}
+.gr-textarea textarea, .gr-textbox input { color: #ecf0f1 !important; }
 .gr-button.gr-button-primary { background-color: #1abc9c !important; color: white !important; border-color: #16a085 !important; }
 .gr-button.gr-button-secondary { background-color: #9b59b6 !important; color: white !important; border-color: #8e44ad !important; }
 .gr-button.gr-button-stop { background-color: #e74c3c !important; color: white !important; border-color: #c0392b !important; }
-.gr-markdown { background-color: transparent !important; padding: 0px; border-radius: 0px; } /* Make markdown background transparent within styled boxes */
+.gr-markdown { background-color: transparent !important; padding: 0px; }
 .gr-markdown h1, .gr-markdown h2, .gr-markdown h3 { color: #1abc9c !important; border-bottom: 1px solid rgba(189, 195, 199, 0.2) !important; padding-bottom: 0.3em; margin-top:1em; }
 .gr-markdown p, .gr-markdown li { color: #ecf0f1 !important; }
-.gr-markdown pre code { background-color: rgba(30, 40, 50, 0.95) !important; border-color: rgba(189, 195, 199, 0.3) !important; color: #ecf0f1; border-radius: 4px; padding: 0.8em; }
-.gr-chatbot { background-color: rgba(44, 62, 80, 0.7) !important; border-color: rgba(189, 195, 199, 0.2) !important; }
+.gr-markdown pre code { background-color: rgba(30, 40, 50, 0.95) !important; border: 1px solid rgba(189, 195, 199, 0.3) !important; color: #ecf0f1; border-radius: 4px; padding: 0.8em; }
+.gr-chatbot { background-color: rgba(44, 62, 80, 0.7) !important; border: 1px solid rgba(189, 195, 199, 0.2) !important; }
 .gr-chatbot .message { background-color: rgba(52, 73, 94, 0.9) !important; color: #ecf0f1 !important; border: 1px solid rgba(189, 195, 199, 0.2) !important; box-shadow: 0 1px 2px rgba(0,0,0,0.1) !important; }
 .gr-chatbot .message.user { background-color: rgba(46, 204, 113, 0.8) !important; color: #2c3e50 !important; }
-.gr-input-label > .label-text, .gr-dropdown-label > .label-text { color: #bdc3c7 !important; font-size: 0.9rem !important; } /* Lighter labels */
+.gr-input-label > .label-text, .gr-dropdown-label > .label-text, .gr-checkbox-label > .label-text { color: #bdc3c7 !important; font-size: 0.9rem !important; }
 .gr-info { color: #bdc3c7 !important; font-size: 0.85rem !important; }
-#status_bar_info { background-color: rgba(44, 62, 80, 0.8) !important; padding: 8px; border-radius: 6px; margin-bottom: 10px; }
+#status_bar_group { background-color: rgba(44, 62, 80, 0.8) !important; padding: 8px; border-radius: 6px; margin-bottom: 10px; }
+.tabnav button { background-color: rgba(52, 73, 94, 0.8) !important; color: #ecf0f1 !important; border-bottom: 2px solid transparent !important;}
+.tabnav button.selected { background-color: rgba(44, 62, 80, 0.95) !important; color: #1abc9c !important; border-bottom: 2px solid #1abc9c !important;}
+.gr-block.gr-box { padding: 1em; } /* Add some padding to groups/boxes */
 """
 
-with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent v5.1") as demo:
+with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent v5.2") as demo:
     gr.Markdown("# 🚀 AI Research Mega Agent Dashboard")
     
     avail_provs = get_available_providers()
     def_prov = avail_provs[0] if avail_provs else None
     def_models = get_model_display_names_for_provider(def_prov) if def_prov else []
     def_model_disp = get_default_model_display_name_for_provider(def_prov) if def_prov else None
-    save_faiss_ram_btn_kb = None # For KB tab
-
-    with gr.Row(elem_id="status_bar_info"):
-        with gr.Column(scale=2): agent_stat_tb = gr.Textbox(label="Agent Status", interactive=False, lines=1, value="Initializing systems...")
+    
+    with gr.Row(elem_id="status_bar_group"):
+        with gr.Column(scale=3): agent_stat_tb = gr.Textbox(label="Agent Status", interactive=False, lines=1, value="Initializing systems...")
         with gr.Column(scale=1): memory_backend_info_tb = gr.Textbox(label="Memory Backend", value=f"{MEMORY_STORAGE_BACKEND}", interactive=False)
         if MEMORY_STORAGE_BACKEND == "SQLITE":
             with gr.Column(scale=2): gr.Textbox(label="SQLite Path", value=f"{MEMORY_SQLITE_PATH}", interactive=False)
@@ -424,28 +423,28 @@ with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent
             with gr.Column(scale=2): gr.Textbox(label="HF Repos", value=f"M: {MEMORY_HF_MEM_REPO}, R: {MEMORY_HF_RULES_REPO}", interactive=False)
     
     with gr.Tabs() as main_tabs:
-        with gr.TabItem("⚙️ Agent Configuration & Chat", id=0):
-            with gr.Row():
-                with gr.Column(scale=1, min_width=350):
-                    gr.Markdown("## ⚙️ LLM & System Configuration")
+        with gr.TabItem("⚙️ Config & 💬 Chat", id=0):
+            with gr.Row(equal_height=False):
+                with gr.Column(scale=1, min_width=380): # Sidebar for config
+                    gr.Markdown("## ⚙️ LLM Configuration")
                     with gr.Group():
                         prov_sel_dd = gr.Dropdown(label="AI Provider", choices=avail_provs, value=def_prov, interactive=True)
                         model_sel_dd = gr.Dropdown(label="AI Model", choices=def_models, value=def_model_disp, interactive=True)
                         api_key_tb = gr.Textbox(label="API Key Override (Optional)", type="password", placeholder="Paste key for selected provider")
                     with gr.Group():
-                        sys_prompt_tb = gr.Textbox(label="System Prompt Base", lines=10, value=DEFAULT_SYSTEM_PROMPT, interactive=True)
+                        sys_prompt_tb = gr.Textbox(label="System Prompt Base", lines=12, value=DEFAULT_SYSTEM_PROMPT, interactive=True)
                 
-                with gr.Column(scale=2):
+                with gr.Column(scale=2): # Main chat area
                     gr.Markdown("## 💬 AI Chat Interface")
                     main_chat_disp = gr.Chatbot(label="AI Research Chat", height=550, bubble_full_width=False, avatar_images=(None, "https://raw.githubusercontent.com/huggingface/brand-assets/main/hf-logo-with-title.png"), show_copy_button=True, render_markdown=True, sanitize_html=True)
                     with gr.Row():
                         user_msg_tb = gr.Textbox(show_label=False, placeholder="Ask your research question or give an instruction...", scale=7, lines=1, max_lines=5, autofocus=True)
                         send_btn = gr.Button("Send", variant="primary", scale=1, min_width=100)
             
-            with gr.Accordion("📝 Full Response / Output Details", open=False):
+            with gr.Accordion("📝 Full Response / Output Details", open=False, elem_id="response_accordion"):
                 fmt_report_tb = gr.Textbox(label="Full AI Response", lines=10, interactive=True, show_copy_button=True, value="*AI responses will appear here...*")
                 dl_report_btn = gr.DownloadButton("Download Report", interactive=False, visible=False) 
-                detect_out_md = gr.Markdown("*Insights used or other intermediate details will show here...*")
+            detect_out_md = gr.Markdown("*Insights used or other intermediate details will show here...*")
 
         with gr.TabItem("🧠 Knowledge Base Management", id=1):
             gr.Markdown("## Manage Stored Knowledge")
@@ -455,19 +454,18 @@ with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent
                     rules_disp_ta = gr.TextArea(label="View/Edit Rules (one per line or '---' separated)", lines=15, interactive=True, placeholder="Load or type rules here...")
                     with gr.Row():
                         view_rules_btn = gr.Button("🔄 Load/Refresh Rules"); save_edited_rules_btn = gr.Button("💾 Save Edited Rules", variant="primary")
-                    upload_rules_fobj = gr.File(label="Upload Rules File (.txt/.jsonl)", file_types=[".txt", ".jsonl"])
-                    rules_stat_tb = gr.Textbox(label="Rules Op Status", interactive=False, lines=2, placeholder="Status...")
+                    upload_rules_fobj = gr.File(label="Upload Rules File (.txt or .jsonl)", file_types=[".txt", ".jsonl"])
+                    rules_stat_tb = gr.Textbox(label="Rules Operation Status", interactive=False, lines=2, placeholder="Status of rule operations...")
                     with gr.Row():
                         clear_rules_btn = gr.Button("⚠️ Clear All Rules", variant="stop")
-                        if MEMORY_STORAGE_BACKEND == "RAM": 
-                            save_faiss_ram_btn_kb = gr.Button("Save FAISS Indices")
+                        save_faiss_ram_btn_kb = gr.Button("Save FAISS Indices", visible=(MEMORY_STORAGE_BACKEND == "RAM"))
                 
                 with gr.Column(scale=1):
                     gr.Markdown("### 📚 Memories (Past Interactions)")
-                    mems_disp_json = gr.JSON(label="View Memories (JSON format)", scale=2)
+                    mems_disp_json = gr.JSON(label="View Memories (JSON format)", scale=2) # scale might not work directly on gr.JSON
                     with gr.Row(): view_mems_btn = gr.Button("🔄 Load/Refresh Memories")
                     upload_mems_fobj = gr.File(label="Upload Memories File (.jsonl)", file_types=[".jsonl"])
-                    mems_stat_tb = gr.Textbox(label="Memories Op Status", interactive=False, lines=2, placeholder="Status...")
+                    mems_stat_tb = gr.Textbox(label="Memories Operation Status", interactive=False, lines=2, placeholder="Status of memory operations...")
                     clear_mems_btn = gr.Button("⚠️ Clear All Memories", variant="stop")
     
     def dyn_upd_model_dd(sel_prov_dyn:str): models_dyn, def_model_dyn = get_model_display_names_for_provider(sel_prov_dyn), get_default_model_display_name_for_provider(sel_prov_dyn); return gr.Dropdown(choices=models_dyn, value=def_model_dyn, interactive=True)
@@ -508,29 +506,17 @@ with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent
     def app_load_fn(): 
         initialize_memory_system()
         logger.info("App loaded. Memory system initialized.")
-        backend_status = f"AI Systems Initialized. Ready." # Agent status, backend info is separate
+        backend_status = f"AI Systems Initialized. Ready."
         rules_on_load = ui_view_rules_action_fn()
         mems_on_load = ui_view_memories_action_fn()
-        # Update memory backend info text box too
-        mem_backend_text = f"{MEMORY_STORAGE_BACKEND}"
-        if MEMORY_STORAGE_BACKEND == "SQLITE": mem_backend_path_text = f"{MEMORY_SQLITE_PATH}"
-        elif MEMORY_STORAGE_BACKEND == "HF_DATASET": mem_backend_path_text = f"M: {MEMORY_HF_MEM_REPO}, R: {MEMORY_HF_RULES_REPO}"
-        else: mem_backend_path_text = "N/A" # For RAM
-
-        # The number of outputs from app_load_fn must match the number of components in demo.load's outputs list
-        # Make sure memory_backend_info_tb and its potential path display are updated if they are separate components
-        # The current UI has one tb for backend and one for path (conditional)
-        # For simplicity here, I'll assume they are part of the static display or updated differently if needed.
-        # The agent_stat_tb is the primary one to update here.
         return backend_status, rules_on_load, mems_on_load
 
-    # Update outputs of demo.load to populate the KB views on startup
     demo.load(fn=app_load_fn, inputs=None, outputs=[agent_stat_tb, rules_disp_ta, mems_disp_json])
 
 if __name__ == "__main__":
-    logger.info(f"Starting Gradio AI Research Mega Agent (v5.1 with New UI & Advanced Memory: {MEMORY_STORAGE_BACKEND})...")
+    logger.info(f"Starting Gradio AI Research Mega Agent (v5.2 with Dashboard UI & Advanced Memory: {MEMORY_STORAGE_BACKEND})...")
     app_port, app_server = int(os.getenv("GRADIO_PORT", 7860)), os.getenv("GRADIO_SERVER_NAME", "127.0.0.1")
     app_debug, app_share = os.getenv("GRADIO_DEBUG", "False").lower()=="true", os.getenv("GRADIO_SHARE", "False").lower()=="true"
     logger.info(f"Launching Gradio server: http://{app_server}:{app_port}. Debug: {app_debug}, Share: {app_share}")
-    demo.queue().launch(server_name=app_server, server_port=app_port, debug=app_debug, share=app_share)
+    demo.queue().launch(server_name=app_server, server_port=app_port, debug=app_debug, share=app_share, fill_height=True) # Added fill_height
     logger.info("Gradio application shut down.")