Update app.py

app.py

@@ -8,6 +8,7 @@ from datetime import datetime
 from dotenv import load_dotenv
 import gradio as gr
 import time
+import tempfile # For temporary file for download
 
 load_dotenv()
 
@@ -262,7 +263,7 @@ Combine all findings into a single JSON list of operations. If there are multipl
 def handle_gradio_chat_submit(user_msg_txt: str, gr_hist_list: list, sel_prov_name: str, sel_model_disp_name: str, ui_api_key: str|None, cust_sys_prompt: str):
     global current_chat_session_history
     cleared_input, updated_gr_hist, status_txt = "", list(gr_hist_list), "Initializing..."
-    def_detect_out_md, def_fmt_out_txt, def_dl_btn = gr.Markdown("*Processing...*"), gr.Textbox("*Waiting...*"), gr.DownloadButton(interactive=False, value=None, visible=False)
+    def_detect_out_md, def_fmt_out_txt, def_dl_btn = gr.Markdown("*Processing...*"), gr.Textbox("*Waiting...*"), gr.DownloadButton(interactive=False, value=None, visible=False) # Ensure DownloadButton is part of initial yield
     if not user_msg_txt.strip():
         status_txt = "Error: Empty message."
         updated_gr_hist.append((user_msg_txt or "(Empty)", status_txt))
@@ -274,6 +275,7 @@ def handle_gradio_chat_submit(user_msg_txt: str, gr_hist_list: list, sel_prov_na
         if internal_hist[0]["role"] == "system" and len(internal_hist) > (MAX_HISTORY_TURNS * 2 + 1) : internal_hist = [internal_hist[0]] + internal_hist[-(MAX_HISTORY_TURNS * 2):]
         else: internal_hist = internal_hist[-(MAX_HISTORY_TURNS * 2):]
     final_bot_resp_acc, insights_used_parsed = "", []
+    temp_dl_file_path = None # For DownloadButton
     try:
         processor_gen = process_user_interaction_gradio(user_input=user_msg_txt, provider_name=sel_prov_name, model_display_name=sel_model_disp_name, chat_history_for_prompt=internal_hist, custom_system_prompt=cust_sys_prompt.strip() or None, ui_api_key_override=ui_api_key.strip() if ui_api_key else None)
         curr_bot_disp_msg = ""
@@ -291,7 +293,11 @@ def handle_gradio_chat_submit(user_msg_txt: str, gr_hist_list: list, sel_prov_na
                 if updated_gr_hist and updated_gr_hist[-1][0] == user_msg_txt: updated_gr_hist[-1] = (user_msg_txt, curr_bot_disp_msg or "(No text)")
                 def_fmt_out_txt = gr.Textbox(value=curr_bot_disp_msg)
                 if curr_bot_disp_msg and not curr_bot_disp_msg.startswith("Error:"):
-                    def_dl_btn = gr.DownloadButton(label="Download Report (.md)", value=curr_bot_disp_msg, filename=f"ai_report_{datetime.now().strftime('%Y%m%d_%H%M%S')}.md", visible=True, interactive=True)
+                    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(label="Download Report (.md)", 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)
             yield (cleared_input, updated_gr_hist, status_txt, def_detect_out_md, def_fmt_out_txt, def_dl_btn)
@@ -311,6 +317,9 @@ def handle_gradio_chat_submit(user_msg_txt: str, gr_hist_list: list, sel_prov_na
         status_txt = "Response complete. Background learning initiated."
     else: status_txt = "Processing finished; no response or error."
     yield (cleared_input, updated_gr_hist, status_txt, def_detect_out_md, def_fmt_out_txt, def_dl_btn)
+    if temp_dl_file_path and os.path.exists(temp_dl_file_path):
+        try: os.unlink(temp_dl_file_path)
+        except Exception as e_unlink: logger.error(f"Error deleting temp download file {temp_dl_file_path}: {e_unlink}")
 
 def ui_view_rules_action_fn(): return "\n\n---\n\n".join(get_all_rules_cached()) or "No rules found."
 def ui_upload_rules_action_fn(uploaded_file_obj, progress=gr.Progress()):
@@ -370,53 +379,100 @@ 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="sm", radius_size="sm", font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui", "sans-serif"])
 custom_css = """ body { font-family: 'Inter', sans-serif; } .gradio-container { max-width: 96% !important; margin: auto !important; padding-top: 1rem !important; } footer { display: none !important; } .gr-button { white-space: nowrap; } .gr-input, .gr-textarea textarea, .gr-dropdown input { border-radius: 8px !important; } .gr-chatbot .message { border-radius: 10px !important; box-shadow: 0 2px 5px rgba(0,0,0,0.08) !important; } .prose { h1 { font-size: 1.8rem; margin-bottom: 0.6em; margin-top: 0.8em; } h2 { font-size: 1.4rem; margin-bottom: 0.5em; margin-top: 0.7em; } h3 { font-size: 1.15rem; margin-bottom: 0.4em; margin-top: 0.6em; } p { margin-bottom: 0.8em; line-height: 1.65; } ul, ol { margin-left: 1.5em; margin-bottom: 0.8em; } code { background-color: #f1f5f9; padding: 0.2em 0.45em; border-radius: 4px; font-size: 0.9em; } pre > code { display: block; padding: 0.8em; overflow-x: auto; background-color: #f8fafc; border: 1px solid #e2e8f0; border-radius: 6px;}} .compact-group .gr-input-label, .compact-group .gr-dropdown-label { font-size: 0.8rem !important; padding-bottom: 2px !important;}"""
 
-with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent v4") as demo:
-    gr.Markdown("# 🚀 AI Research Mega Agent (Advanced Memory & Dynamic Models)", elem_classes="prose")
+with gr.Blocks(theme=custom_theme, css=custom_css, title="AI Research Mega Agent v4.1") as demo:
+    gr.Markdown("# 🚀 AI Research Mega Agent", elem_classes="prose")
     avail_provs, def_prov = get_available_providers(), get_available_providers()[0] if get_available_providers() else None
     def_models, def_model = get_model_display_names_for_provider(def_prov) if def_prov else [], get_default_model_display_name_for_provider(def_prov) if def_prov else None
-    save_faiss_ram_btn = None
-    with gr.Row():
-        with gr.Column(scale=1, min_width=320):
-            gr.Markdown("## ⚙️ Configuration", elem_classes="prose")
-            with gr.Accordion("API & Model Settings", open=True):
-                with gr.Group(elem_classes="compact-group"):
-                    gr.Markdown("### LLM Provider & Model", elem_classes="prose")
-                    prov_sel_dd = gr.Dropdown(label="Provider", choices=avail_provs, value=def_prov, interactive=True)
-                    model_sel_dd = gr.Dropdown(label="Model", choices=def_models, value=def_model, interactive=True)
-                    api_key_tb = gr.Textbox(label="API Key Override", type="password", placeholder="Optional", info="Overrides .env key for session.")
-                with gr.Group(elem_classes="compact-group"):
-                    gr.Markdown("### System Prompt", elem_classes="prose")
-                    sys_prompt_tb = gr.Textbox(label="Custom System Prompt Base", lines=6, value=DEFAULT_SYSTEM_PROMPT, interactive=True)
-            with gr.Accordion("Knowledge Management (Backend: " + MEMORY_STORAGE_BACKEND + ")", open=False):
-                gr.Markdown("### Rules (Insights)", elem_classes="prose"); view_rules_btn = gr.Button("View Rules"); upload_rules_fobj = gr.File(label="Upload Rules (.txt/.jsonl)", file_types=[".txt", ".jsonl"]); rules_stat_tb = gr.Textbox(label="Status", interactive=False, lines=2); clear_rules_btn = gr.Button("⚠️ Clear All Rules", variant="stop")
-                if MEMORY_STORAGE_BACKEND == "RAM": save_faiss_ram_btn = gr.Button("Save FAISS Indices (RAM Backend)")
-                gr.Markdown("### Memories", elem_classes="prose"); view_mems_btn = gr.Button("View Memories"); upload_mems_fobj = gr.File(label="Upload Memories (.jsonl)", file_types=[".jsonl"]); mems_stat_tb = gr.Textbox(label="Status", interactive=False, lines=2); clear_mems_btn = gr.Button("⚠️ Clear All Memories", variant="stop")
-        with gr.Column(scale=3):
-            gr.Markdown("## 💬 AI Research Assistant Chat", elem_classes="prose"); main_chat_disp = gr.Chatbot(label="Chat", height=650, 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 a 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.Tabs() as main_tabs:
+        with gr.TabItem("💬 Chat Agent", id=0):
+            with gr.Row():
+                with gr.Column(scale=1, min_width=300):
+                    gr.Markdown("### ⚙️ Configuration", elem_classes="prose")
+                    with gr.Group(elem_classes="compact-group"):
+                        prov_sel_dd = gr.Dropdown(label="Provider", choices=avail_provs, value=def_prov, interactive=True)
+                        model_sel_dd = gr.Dropdown(label="Model", choices=def_models, value=def_model, interactive=True)
+                        api_key_tb = gr.Textbox(label="API Key Override", type="password", placeholder="Optional", info="Overrides .env key for session.")
+                    with gr.Group(elem_classes="compact-group"):
+                        sys_prompt_tb = gr.Textbox(label="System Prompt Base", lines=8, value=DEFAULT_SYSTEM_PROMPT, interactive=True)
+                with gr.Column(scale=3):
+                    main_chat_disp = gr.Chatbot(label="AI Research Chat", height=600, 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 a 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)
             agent_stat_tb = gr.Textbox(label="Agent Status", interactive=False, lines=1, value="Initializing...")
-            with gr.Tabs():
-                with gr.TabItem("📝 Report/Output"): gr.Markdown("AI's full response/report.", elem_classes="prose"); fmt_report_tb = gr.Textbox(label="Output", lines=20, interactive=True, show_copy_button=True, value="*Responses appear here...*"); dl_report_btn = gr.DownloadButton(label="Download Report", interactive=False, visible=False)
-                with gr.TabItem("🔍 Details / Data"): gr.Markdown("View intermediate details, loaded data.", elem_classes="prose"); detect_out_md = gr.Markdown("*Insights used or details show here...*"); gr.HTML("<hr style='margin:1em 0;'>"); gr.Markdown("### Rules Viewer", elem_classes="prose"); rules_disp_ta = gr.TextArea(label="Rules Snapshot", lines=10, interactive=False); gr.HTML("<hr style='margin:1em 0;'>"); gr.Markdown("### Memories Viewer", elem_classes="prose"); mems_disp_json = gr.JSON(label="Memories Snapshot")
+            with gr.Accordion("📝 Full Response / Output", open=True):
+                fmt_report_tb = gr.Textbox(label="Current Research Output", lines=15, interactive=True, show_copy_button=True, value="*AI responses will appear here...*")
+                dl_report_btn = gr.DownloadButton(label="Download Report", interactive=False, visible=False) # Filename set dynamically
+            detect_out_md = gr.Markdown("*Insights used or other intermediate details will show here...*")
+
+        with gr.TabItem("🧠 Knowledge Base Management", id=1):
+            gr.Markdown("## Knowledge Base (Backend: " + MEMORY_STORAGE_BACKEND + ")", elem_classes="prose")
+            with gr.Row():
+                with gr.Column(scale=1):
+                    gr.Markdown("### Rules (Learned Insights)", elem_classes="prose")
+                    rules_disp_ta = gr.TextArea(label="View/Edit Rules (one per line or '---' separated)", lines=15, interactive=True) # Make editable for direct modification
+                    with gr.Row():
+                        view_rules_btn = gr.Button("Load Rules into View"); save_edited_rules_btn = gr.Button("Save Edited Rules from View", variant="primary")
+                    upload_rules_fobj = gr.File(label="Upload Rules File (.txt/.jsonl)", file_types=[".txt", ".jsonl"])
+                    rules_stat_tb = gr.Textbox(label="Rules Action Status", interactive=False, lines=2)
+                    with gr.Row():
+                        clear_rules_btn = gr.Button("⚠️ Clear All Rules", variant="stop")
+                        save_faiss_ram_btn = gr.Button("Save FAISS Indices", visible=(MEMORY_STORAGE_BACKEND == "RAM")) # Visible only if RAM
+                
+                with gr.Column(scale=1):
+                    gr.Markdown("### Memories (Past Interactions)", elem_classes="prose")
+                    mems_disp_json = gr.JSON(label="View Memories (JSON format)") # JSON is good for list of dicts
+                    with gr.Row():
+                        view_mems_btn = gr.Button("Load Memories into View")
+                    upload_mems_fobj = gr.File(label="Upload Memories File (.jsonl)", file_types=[".jsonl"])
+                    mems_stat_tb = gr.Textbox(label="Memories Action Status", interactive=False, lines=2)
+                    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)
     prov_sel_dd.change(fn=dyn_upd_model_dd, inputs=prov_sel_dd, outputs=model_sel_dd)
     chat_ins = [user_msg_tb, main_chat_disp, prov_sel_dd, model_sel_dd, api_key_tb, sys_prompt_tb]
     chat_outs = [user_msg_tb, main_chat_disp, agent_stat_tb, detect_out_md, fmt_report_tb, dl_report_btn]
     send_btn.click(fn=handle_gradio_chat_submit, inputs=chat_ins, outputs=chat_outs); user_msg_tb.submit(fn=handle_gradio_chat_submit, inputs=chat_ins, outputs=chat_outs)
+    
     view_rules_btn.click(fn=ui_view_rules_action_fn, outputs=rules_disp_ta)
+    def save_edited_rules_action_fn(edited_rules_text: str, progress=gr.Progress()):
+        if not edited_rules_text.strip(): return "No rules text to save."
+        potential_rules = edited_rules_text.split("\n\n---\n\n")
+        if len(potential_rules) == 1 and "\n" in edited_rules_text: potential_rules = [r.strip() for r in edited_rules_text.splitlines() if r.strip()]
+        if not potential_rules: return "No rules found to process from editor."
+        # For saving edited, it's often easier to clear existing and re-add all from editor
+        # Or, implement a diff and selective add/remove (more complex)
+        # Simple approach: clear and re-add. User should be warned.
+        # For now, this will just attempt to add them, duplicates will be skipped by memory_logic
+        added, skipped, errors = 0,0,0; total = len(potential_rules)
+        progress(0, desc=f"Saving {total} rules from editor...")
+        for idx, rule_text in enumerate(potential_rules):
+            if not rule_text.strip(): continue
+            success, status_msg = add_rule_entry(rule_text.strip()) # add_rule_entry handles duplicates/format
+            if success: added +=1
+            elif status_msg == "duplicate": skipped +=1
+            else: errors +=1
+            progress((idx+1)/total)
+        return f"Editor Save: Added: {added}, Skipped (duplicates): {skipped}, Errors/Invalid: {errors}."
+    save_edited_rules_btn.click(fn=save_edited_rules_action_fn, inputs=[rules_disp_ta], outputs=[rules_stat_tb], show_progress="full")
+
     upload_rules_fobj.upload(fn=ui_upload_rules_action_fn, inputs=[upload_rules_fobj], outputs=[rules_stat_tb], show_progress="full").then(fn=ui_view_rules_action_fn, outputs=rules_disp_ta)
     clear_rules_btn.click(fn=lambda: "All rules cleared." if clear_all_rules_data_backend() else "Error clearing rules.", outputs=rules_stat_tb).then(fn=ui_view_rules_action_fn, outputs=rules_disp_ta)
+    
     if MEMORY_STORAGE_BACKEND == "RAM" and save_faiss_ram_btn is not None:
         def save_faiss_action_with_feedback_fn(): save_faiss_indices_to_disk(); gr.Info("Attempted to save FAISS indices to disk.")
         save_faiss_ram_btn.click(fn=save_faiss_action_with_feedback_fn, inputs=None, outputs=None)
+    
     view_mems_btn.click(fn=ui_view_memories_action_fn, outputs=mems_disp_json)
     upload_mems_fobj.upload(fn=ui_upload_memories_action_fn, inputs=[upload_mems_fobj], outputs=[mems_stat_tb], show_progress="full").then(fn=ui_view_memories_action_fn, outputs=mems_disp_json)
     clear_mems_btn.click(fn=lambda: "All memories cleared." if clear_all_memory_data_backend() else "Error clearing memories.", outputs=mems_stat_tb).then(fn=ui_view_memories_action_fn, outputs=mems_disp_json)
+    
     def app_load_fn(): initialize_memory_system(); logger.info("App loaded. Memory system initialized."); return f"AI Systems Initialized (Backend: {MEMORY_STORAGE_BACKEND}). Ready."
     demo.load(fn=app_load_fn, inputs=None, outputs=agent_stat_tb)
 
 if __name__ == "__main__":
-    logger.info(f"Starting Gradio AI Research Mega Agent (v4 with Advanced Memory: {MEMORY_STORAGE_BACKEND})...")
+    logger.info(f"Starting Gradio AI Research Mega Agent (v4.1 with 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}")