aaf

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discord_bot_sync_api.py

@@ -5,14 +5,22 @@ import datetime
 from typing import Dict, List, Optional, Any, Union
 from fastapi import FastAPI, HTTPException, Depends, Header, Request, Response
 from fastapi.middleware.cors import CORSMiddleware
+from fastapi.staticfiles import StaticFiles # Added for static files
+from fastapi.responses import FileResponse # Added for serving HTML
 from pydantic import BaseModel, Field
 import discord
 from discord.ext import commands
 import aiohttp
 import threading
+from typing import Optional # Added for GurtCog type hint
 
 # This file contains the API endpoints for syncing conversations between
-# the Flutter app and the Discord bot.
+# the Flutter app and the Discord bot, AND the Gurt stats endpoint.
+
+# --- Placeholder for GurtCog instance ---
+# This needs to be set by the script that starts the bot and API server
+from discordbot.gurt.cog import GurtCog # Import GurtCog for type hint and access
+gurt_cog_instance: Optional[GurtCog] = None
 
 # ============= Models =============
 
@@ -390,6 +398,44 @@ async def delete_conversation(
 
     return {"success": True, "message": "Conversation deleted"}
 
+
+# --- Gurt Stats Endpoint ---
+@api_app.get("/gurt/stats")
+async def get_gurt_stats_api():
+    """Get internal statistics for the Gurt bot."""
+    if not gurt_cog_instance:
+        raise HTTPException(status_code=503, detail="Gurt cog not available")
+    try:
+        stats_data = await gurt_cog_instance.get_gurt_stats()
+        # Convert potential datetime objects if any (though get_gurt_stats should return serializable types)
+        # For safety, let's ensure basic types or handle conversion if needed later.
+        return stats_data
+    except Exception as e:
+        print(f"Error retrieving Gurt stats via API: {e}")
+        import traceback
+        traceback.print_exc()
+        raise HTTPException(status_code=500, detail=f"Error retrieving Gurt stats: {e}")
+
+# --- Gurt Dashboard Static Files ---
+# Mount static files directory (adjust path if needed, assuming dashboard files are in discordbot/gurt_dashboard)
+# Check if the directory exists before mounting
+dashboard_dir = "discordbot/gurt_dashboard"
+if os.path.exists(dashboard_dir) and os.path.isdir(dashboard_dir):
+    api_app.mount("/gurt/static", StaticFiles(directory=dashboard_dir), name="gurt_static")
+    print(f"Mounted Gurt dashboard static files from: {dashboard_dir}")
+
+    # Route for the main dashboard HTML
+    @api_app.get("/gurt/dashboard", response_class=FileResponse)
+    async def get_gurt_dashboard():
+        dashboard_html_path = os.path.join(dashboard_dir, "index.html")
+        if os.path.exists(dashboard_html_path):
+            return dashboard_html_path
+        else:
+            raise HTTPException(status_code=404, detail="Dashboard index.html not found")
+else:
+    print(f"Warning: Gurt dashboard directory '{dashboard_dir}' not found. Dashboard endpoints will not be available.")
+
+
 @api_app.get("/settings")
 async def get_user_settings(user_id: str = Depends(verify_discord_token)):
     """Get user settings"""

gurt/api.py

@@ -46,13 +46,16 @@ async def call_llm_api_with_retry(
     """
     last_exception = None
     original_model = payload.get("model")
+    current_model_key = original_model # Track the model used in the current attempt
     using_fallback = False
+    start_time = time.monotonic() # Start timer before the loop
 
     if not cog.session:
         raise Exception(f"aiohttp session not initialized in GurtCog for {request_desc}")
 
     for attempt in range(API_RETRY_ATTEMPTS + 1): # Corrected range
         try:
+            current_model_key = payload["model"] # Get model for this attempt
             model_desc = f"fallback model {FALLBACK_MODEL}" if using_fallback else f"primary model {original_model}"
             print(f"Sending API request for {request_desc} using {model_desc} (Attempt {attempt + 1}/{API_RETRY_ATTEMPTS + 1})...")
 
@@ -70,7 +73,13 @@ async def call_llm_api_with_retry(
                         print(error_msg)
                         last_exception = ValueError(error_msg) # Treat as non-retryable format error
                         break # Exit retry loop
-                    print(f"API request successful for {request_desc}.")
+
+                    # --- Success Logging ---
+                    elapsed_time = time.monotonic() - start_time
+                    cog.api_stats[current_model_key]['success'] += 1
+                    cog.api_stats[current_model_key]['total_time'] += elapsed_time
+                    cog.api_stats[current_model_key]['count'] += 1
+                    print(f"API request successful for {request_desc} ({current_model_key}) in {elapsed_time:.2f}s.")
                     return data # Success
 
                 elif response.status == 429:  # Rate limit error
@@ -80,6 +89,7 @@ async def call_llm_api_with_retry(
 
                     if using_fallback or original_model != DEFAULT_MODEL:
                         if attempt < API_RETRY_ATTEMPTS:
+                            cog.api_stats[current_model_key]['retries'] += 1 # Log retry
                             wait_time = API_RETRY_DELAY * (attempt + 2)
                             print(f"Waiting {wait_time} seconds before retrying...")
                             await asyncio.sleep(wait_time)
@@ -92,7 +102,7 @@ async def call_llm_api_with_retry(
                         payload["model"] = FALLBACK_MODEL
                         using_fallback = True
                         await asyncio.sleep(1)
-                        continue
+                        continue # Retry immediately with fallback
 
                 elif response.status >= 500: # Retry on server errors
                     error_text = await response.text()
@@ -100,6 +110,7 @@ async def call_llm_api_with_retry(
                     print(f"{error_msg} (Attempt {attempt + 1})")
                     last_exception = Exception(error_msg)
                     if attempt < API_RETRY_ATTEMPTS:
+                        cog.api_stats[current_model_key]['retries'] += 1 # Log retry
                         await asyncio.sleep(API_RETRY_DELAY * (attempt + 1))
                         continue
                     else:
@@ -114,7 +125,7 @@ async def call_llm_api_with_retry(
                         payload["model"] = FALLBACK_MODEL
                         using_fallback = True
                         await asyncio.sleep(1)
-                        continue
+                        continue # Retry immediately with fallback
 
                     last_exception = Exception(error_msg)
                     break
@@ -124,6 +135,7 @@ async def call_llm_api_with_retry(
             print(error_msg)
             last_exception = asyncio.TimeoutError(error_msg)
             if attempt < API_RETRY_ATTEMPTS:
+                cog.api_stats[current_model_key]['retries'] += 1 # Log retry
                 await asyncio.sleep(API_RETRY_DELAY * (attempt + 1))
                 continue
             else:
@@ -133,11 +145,20 @@ async def call_llm_api_with_retry(
             print(error_msg)
             last_exception = e
             if attempt < API_RETRY_ATTEMPTS:
+                 cog.api_stats[current_model_key]['retries'] += 1 # Log retry
                  await asyncio.sleep(API_RETRY_DELAY * (attempt + 1))
                  continue
             else:
                  break
 
+    # --- Failure Logging ---
+    elapsed_time = time.monotonic() - start_time
+    final_model_key = payload["model"] # Model used in the last failed attempt
+    cog.api_stats[final_model_key]['failure'] += 1
+    cog.api_stats[final_model_key]['total_time'] += elapsed_time
+    cog.api_stats[final_model_key]['count'] += 1
+    print(f"API request failed for {request_desc} ({final_model_key}) after {attempt + 1} attempts in {elapsed_time:.2f}s.")
+
     raise last_exception or Exception(f"API request failed for {request_desc} after {API_RETRY_ATTEMPTS + 1} attempts.")
 
 # --- JSON Parsing Helper ---
@@ -251,6 +272,7 @@ async def process_requested_tools(cog: 'GurtCog', tool_requests: List[Dict[str,
              continue
 
         print(f"Executing tool: {function_name} with args: {function_args}")
+        tool_start_time = time.monotonic() # Start timer for this tool
         if function_name in TOOL_MAPPING:
             try:
                 # Get the actual function implementation from the mapping
@@ -263,16 +285,28 @@ async def process_requested_tools(cog: 'GurtCog', tool_requests: List[Dict[str,
                 # and don't directly need the `cog` instance passed here.
                 # If they *are* methods of GurtCog, they'll have `self` automatically.
                 result = await tool_func(cog, **function_args) # Pass cog if needed by tool impl
+
+                # --- Tool Success Logging ---
+                tool_elapsed_time = time.monotonic() - tool_start_time
+                cog.tool_stats[function_name]['success'] += 1
+                cog.tool_stats[function_name]['total_time'] += tool_elapsed_time
+                cog.tool_stats[function_name]['count'] += 1
+                print(f"Tool '{function_name}' executed successfully in {tool_elapsed_time:.2f}s.")
+
                 tool_results_for_api.append({
                     "role": "tool",
                     "content": json.dumps(result),
                     "name": function_name
                 })
-                print(f"Tool '{function_name}' executed successfully.")
             except Exception as e:
+                # --- Tool Failure Logging ---
+                tool_elapsed_time = time.monotonic() - tool_start_time
+                cog.tool_stats[function_name]['failure'] += 1
+                cog.tool_stats[function_name]['total_time'] += tool_elapsed_time
+                cog.tool_stats[function_name]['count'] += 1
                 error_message = f"Error executing tool {function_name}: {str(e)}"
-                print(error_message)
-                import traceback
+                print(f"{error_message} (Took {tool_elapsed_time:.2f}s)")
+                import traceback # Keep traceback for debugging
                 traceback.print_exc()
                 tool_results_for_api.append({
                     "role": "tool",
@@ -280,8 +314,13 @@ async def process_requested_tools(cog: 'GurtCog', tool_requests: List[Dict[str,
                     "name": function_name
                 })
         else:
+            # --- Tool Not Found Logging ---
+            tool_elapsed_time = time.monotonic() - tool_start_time # Still record time even if not found
+            cog.tool_stats[function_name]['failure'] += 1 # Count as failure
+            cog.tool_stats[function_name]['total_time'] += tool_elapsed_time
+            cog.tool_stats[function_name]['count'] += 1
             error_message = f"Tool '{function_name}' not found or implemented."
-            print(error_message)
+            print(f"{error_message} (Took {tool_elapsed_time:.2f}s)")
             tool_results_for_api.append({
                 "role": "tool",
                 "content": json.dumps({"error": error_message}),

gurt/cog.py

@@ -33,6 +33,7 @@ from .memory import MemoryManager # Import from local memory.py
 from .background import background_processing_task
 from .commands import setup_commands # Import the setup helper
 from .listeners import on_ready_listener, on_message_listener, on_reaction_add_listener, on_reaction_remove_listener # Import listener functions
+from . import config as GurtConfig # Import config module for get_gurt_stats
 # Tool mapping is used internally by api.py/process_requested_tools, no need to import here directly unless cog methods call tools directly (they shouldn't)
 # Analysis, context, prompt, api, utils functions are called by listeners/commands/background task, not directly by cog methods here usually.
 
@@ -122,6 +123,10 @@ class GurtCog(commands.Cog, name="Gurt"): # Added explicit Cog name
         self.background_task: Optional[asyncio.Task] = None
         self.last_evolution_update = time.time() # Used in background task
 
+        # --- Stats Tracking ---
+        self.api_stats = defaultdict(lambda: {"success": 0, "failure": 0, "retries": 0, "total_time": 0.0, "count": 0}) # Keyed by model name
+        self.tool_stats = defaultdict(lambda: {"success": 0, "failure": 0, "total_time": 0.0, "count": 0}) # Keyed by tool name
+
         # --- Setup Commands and Listeners ---
         # Add commands defined in commands.py
         setup_commands(self)
@@ -206,6 +211,107 @@ class GurtCog(commands.Cog, name="Gurt"): # Added explicit Cog name
         self.user_relationships[user_id_1][user_id_2] = new_score
         # print(f"Updated relationship {user_id_1}-{user_id_2}: {current_score:.1f} -> {new_score:.1f} ({change:+.1f})") # Debug log
 
+    async def get_gurt_stats(self) -> Dict[str, Any]:
+        """Collects various internal stats for Gurt."""
+        stats = {"config": {}, "runtime": {}, "memory": {}, "api_stats": {}, "tool_stats": {}}
+
+        # --- Config ---
+        # Selectively pull relevant config values, avoid exposing secrets
+        stats["config"]["default_model"] = GurtConfig.DEFAULT_MODEL
+        stats["config"]["fallback_model"] = GurtConfig.FALLBACK_MODEL
+        stats["config"]["safety_check_model"] = GurtConfig.SAFETY_CHECK_MODEL
+        stats["config"]["db_path"] = GurtConfig.DB_PATH
+        stats["config"]["chroma_path"] = GurtConfig.CHROMA_PATH
+        stats["config"]["semantic_model_name"] = GurtConfig.SEMANTIC_MODEL_NAME
+        stats["config"]["max_user_facts"] = GurtConfig.MAX_USER_FACTS
+        stats["config"]["max_general_facts"] = GurtConfig.MAX_GENERAL_FACTS
+        stats["config"]["mood_change_interval_min"] = GurtConfig.MOOD_CHANGE_INTERVAL_MIN
+        stats["config"]["mood_change_interval_max"] = GurtConfig.MOOD_CHANGE_INTERVAL_MAX
+        stats["config"]["evolution_update_interval"] = GurtConfig.EVOLUTION_UPDATE_INTERVAL
+        stats["config"]["context_window_size"] = GurtConfig.CONTEXT_WINDOW_SIZE
+        stats["config"]["api_timeout"] = GurtConfig.API_TIMEOUT
+        stats["config"]["summary_api_timeout"] = GurtConfig.SUMMARY_API_TIMEOUT
+        stats["config"]["proactive_lull_threshold"] = GurtConfig.PROACTIVE_LULL_THRESHOLD
+        stats["config"]["proactive_bot_silence_threshold"] = GurtConfig.PROACTIVE_BOT_SILENCE_THRESHOLD
+        stats["config"]["interest_update_interval"] = GurtConfig.INTEREST_UPDATE_INTERVAL
+        stats["config"]["interest_decay_interval_hours"] = GurtConfig.INTEREST_DECAY_INTERVAL_HOURS
+        stats["config"]["learning_update_interval"] = GurtConfig.LEARNING_UPDATE_INTERVAL
+        stats["config"]["topic_update_interval"] = GurtConfig.TOPIC_UPDATE_INTERVAL
+        stats["config"]["sentiment_update_interval"] = GurtConfig.SENTIMENT_UPDATE_INTERVAL
+        stats["config"]["docker_command_timeout"] = GurtConfig.DOCKER_COMMAND_TIMEOUT
+        stats["config"]["api_key_set"] = bool(GurtConfig.API_KEY) # Don't expose key itself
+        stats["config"]["tavily_api_key_set"] = bool(GurtConfig.TAVILY_API_KEY)
+        stats["config"]["piston_api_url_set"] = bool(GurtConfig.PISTON_API_URL)
+
+        # --- Runtime ---
+        stats["runtime"]["current_mood"] = self.current_mood
+        stats["runtime"]["last_mood_change_timestamp"] = self.last_mood_change
+        stats["runtime"]["needs_json_reminder"] = self.needs_json_reminder
+        stats["runtime"]["last_learning_update_timestamp"] = self.last_learning_update
+        stats["runtime"]["last_interest_update_timestamp"] = self.last_interest_update
+        stats["runtime"]["last_evolution_update_timestamp"] = self.last_evolution_update
+        stats["runtime"]["background_task_running"] = bool(self.background_task and not self.background_task.done())
+        stats["runtime"]["active_topics_channels"] = len(self.active_topics)
+        stats["runtime"]["conversation_history_channels"] = len(self.conversation_history)
+        stats["runtime"]["thread_history_threads"] = len(self.thread_history)
+        stats["runtime"]["user_conversation_mappings"] = len(self.user_conversation_mapping)
+        stats["runtime"]["channel_activity_tracked"] = len(self.channel_activity)
+        stats["runtime"]["conversation_topics_tracked"] = len(self.conversation_topics)
+        stats["runtime"]["user_relationships_pairs"] = sum(len(v) for v in self.user_relationships.values())
+        stats["runtime"]["conversation_summaries_cached"] = len(self.conversation_summaries)
+        stats["runtime"]["channel_topics_cached"] = len(self.channel_topics_cache)
+        stats["runtime"]["message_cache_global_count"] = len(self.message_cache['global_recent'])
+        stats["runtime"]["message_cache_mentioned_count"] = len(self.message_cache['mentioned'])
+        stats["runtime"]["active_conversations_count"] = len(self.active_conversations)
+        stats["runtime"]["bot_last_spoke_channels"] = len(self.bot_last_spoke)
+        stats["runtime"]["message_reply_map_size"] = len(self.message_reply_map)
+        stats["runtime"]["conversation_sentiment_channels"] = len(self.conversation_sentiment)
+        stats["runtime"]["gurt_participation_topics_count"] = len(self.gurt_participation_topics)
+        stats["runtime"]["gurt_message_reactions_tracked"] = len(self.gurt_message_reactions)
+
+        # --- Memory (via MemoryManager) ---
+        try:
+            # Personality
+            personality = await self.memory_manager.get_all_personality_traits()
+            stats["memory"]["personality_traits"] = personality
+
+            # Interests
+            interests = await self.memory_manager.get_interests(limit=20, min_level=0.01) # Get top 20
+            stats["memory"]["top_interests"] = interests
+
+            # Fact Counts (Requires adding methods to MemoryManager or direct query)
+            # Example placeholder - needs implementation in MemoryManager or here
+            user_fact_count = await self.memory_manager._db_fetchone("SELECT COUNT(*) FROM user_facts")
+            general_fact_count = await self.memory_manager._db_fetchone("SELECT COUNT(*) FROM general_facts")
+            stats["memory"]["user_facts_count"] = user_fact_count[0] if user_fact_count else 0
+            stats["memory"]["general_facts_count"] = general_fact_count[0] if general_fact_count else 0
+
+            # ChromaDB Stats (Placeholder - ChromaDB client API might offer this)
+            stats["memory"]["chromadb_message_collection_count"] = await asyncio.to_thread(self.memory_manager.semantic_collection.count) if self.memory_manager.semantic_collection else "N/A"
+            stats["memory"]["chromadb_fact_collection_count"] = await asyncio.to_thread(self.memory_manager.fact_collection.count) if self.memory_manager.fact_collection else "N/A"
+
+        except Exception as e:
+            stats["memory"]["error"] = f"Failed to retrieve memory stats: {e}"
+
+        # --- API & Tool Stats ---
+        # Convert defaultdicts to regular dicts for JSON serialization
+        stats["api_stats"] = dict(self.api_stats)
+        stats["tool_stats"] = dict(self.tool_stats)
+
+        # Calculate average times where count > 0
+        for model, data in stats["api_stats"].items():
+            if data["count"] > 0:
+                data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
+            else:
+                data["average_time_ms"] = 0
+        for tool, data in stats["tool_stats"].items():
+            if data["count"] > 0:
+                data["average_time_ms"] = round((data["total_time"] / data["count"]) * 1000, 2)
+            else:
+                data["average_time_ms"] = 0
+
+        return stats
+
 
 # Setup function for loading the cog
 async def setup(bot):

gurt/commands.py

@@ -1,8 +1,12 @@
 import discord
+from discord import app_commands # Import app_commands
 from discord.ext import commands
 import random
 import os
-from typing import TYPE_CHECKING
+import time # Import time for timestamps
+import json # Import json for formatting
+import datetime # Import datetime for formatting
+from typing import TYPE_CHECKING, Optional, Dict, Any, List, Tuple # Add more types
 
 # Relative imports (assuming API functions are in api.py)
 # We need access to the cog instance for state and methods like get_ai_response
@@ -10,176 +14,204 @@ from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
     from .cog import GurtCog # For type hinting
+    from .config import MOOD_OPTIONS # Import for choices
 
-# --- Command Implementations ---
-# Note: These functions assume they will be registered as commands associated with a GurtCog instance.
-#       The 'cog' parameter will be implicitly passed by discord.py when registered correctly.
+# --- Helper Function for Embeds ---
+def create_gurt_embed(title: str, description: str = "", color=discord.Color.blue()) -> discord.Embed:
+    """Creates a standard Gurt-themed embed."""
+    embed = discord.Embed(title=title, description=description, color=color)
+    # Placeholder icon URL, replace if Gurt has one
+    # embed.set_footer(text="Gurt", icon_url="https://example.com/gurt_icon.png")
+    embed.set_footer(text="Gurt")
+    return embed
 
-@commands.command(name="gurt")
-async def gurt_command(cog: 'GurtCog', ctx: commands.Context):
-    """The main gurt command"""
-    from .config import GURT_RESPONSES # Import here
-    response = random.choice(GURT_RESPONSES)
-    await ctx.send(response)
+# --- Helper Function for Stats Embeds ---
+def format_stats_embeds(stats: Dict[str, Any]) -> List[discord.Embed]:
+    """Formats the collected stats into multiple embeds."""
+    embeds = []
+    main_embed = create_gurt_embed("Gurt Internal Stats", color=discord.Color.green())
+    ts_format = "<t:{ts}:R>" # Relative timestamp
 
-@commands.command(name="gurtai")
-async def gurt_ai_command(cog: 'GurtCog', ctx: commands.Context, *, prompt: str):
-    """Get a response from the AI"""
-    from .api import get_ai_response # Import API function
+    # Runtime Stats
+    runtime = stats.get("runtime", {})
+    main_embed.add_field(name="Current Mood", value=f"{runtime.get('current_mood', 'N/A')} (Changed {ts_format.format(ts=int(runtime.get('last_mood_change_timestamp', 0)))})", inline=False)
+    main_embed.add_field(name="Background Task", value="Running" if runtime.get('background_task_running') else "Stopped", inline=True)
+    main_embed.add_field(name="Needs JSON Reminder", value=str(runtime.get('needs_json_reminder', 'N/A')), inline=True)
+    main_embed.add_field(name="Last Evolution", value=ts_format.format(ts=int(runtime.get('last_evolution_update_timestamp', 0))), inline=True)
+    main_embed.add_field(name="Active Topics Channels", value=str(runtime.get('active_topics_channels', 'N/A')), inline=True)
+    main_embed.add_field(name="Conv History Channels", value=str(runtime.get('conversation_history_channels', 'N/A')), inline=True)
+    main_embed.add_field(name="Thread History Threads", value=str(runtime.get('thread_history_threads', 'N/A')), inline=True)
+    main_embed.add_field(name="User Relationships Pairs", value=str(runtime.get('user_relationships_pairs', 'N/A')), inline=True)
+    main_embed.add_field(name="Cached Summaries", value=str(runtime.get('conversation_summaries_cached', 'N/A')), inline=True)
+    main_embed.add_field(name="Cached Channel Topics", value=str(runtime.get('channel_topics_cached', 'N/A')), inline=True)
+    main_embed.add_field(name="Global Msg Cache", value=str(runtime.get('message_cache_global_count', 'N/A')), inline=True)
+    main_embed.add_field(name="Mention Msg Cache", value=str(runtime.get('message_cache_mentioned_count', 'N/A')), inline=True)
+    main_embed.add_field(name="Active Convos", value=str(runtime.get('active_conversations_count', 'N/A')), inline=True)
+    main_embed.add_field(name="Sentiment Channels", value=str(runtime.get('conversation_sentiment_channels', 'N/A')), inline=True)
+    main_embed.add_field(name="Gurt Participation Topics", value=str(runtime.get('gurt_participation_topics_count', 'N/A')), inline=True)
+    main_embed.add_field(name="Tracked Reactions", value=str(runtime.get('gurt_message_reactions_tracked', 'N/A')), inline=True)
+    embeds.append(main_embed)
 
-    # Create a pseudo-message object or pass necessary info
-    # For simplicity, we'll pass the context's message object,
-    # but modify its content for the AI call.
-    ai_message = ctx.message
-    ai_message.content = prompt # Override content with the prompt argument
+    # Memory Stats
+    memory_embed = create_gurt_embed("Gurt Memory Stats", color=discord.Color.orange())
+    memory = stats.get("memory", {})
+    if memory.get("error"):
+        memory_embed.description = f"⚠️ Error retrieving memory stats: {memory['error']}"
+    else:
+        memory_embed.add_field(name="User Facts", value=str(memory.get('user_facts_count', 'N/A')), inline=True)
+        memory_embed.add_field(name="General Facts", value=str(memory.get('general_facts_count', 'N/A')), inline=True)
+        memory_embed.add_field(name="Chroma Messages", value=str(memory.get('chromadb_message_collection_count', 'N/A')), inline=True)
+        memory_embed.add_field(name="Chroma Facts", value=str(memory.get('chromadb_fact_collection_count', 'N/A')), inline=True)
 
-    try:
-        # Show typing indicator
-        async with ctx.typing():
-            # Get AI response bundle
-            response_bundle = await get_ai_response(cog, ai_message) # Pass cog and message
+        personality = memory.get("personality_traits", {})
+        if personality:
+            p_items = [f"`{k}`: {v}" for k, v in personality.items()]
+            memory_embed.add_field(name="Personality Traits", value="\n".join(p_items) if p_items else "None", inline=False)
 
-        # Check for errors or no response
-        error_msg = response_bundle.get("error")
-        initial_response = response_bundle.get("initial_response")
-        final_response = response_bundle.get("final_response")
-        response_to_use = final_response if final_response else initial_response
+        interests = memory.get("top_interests", [])
+        if interests:
+            i_items = [f"`{t}`: {l:.2f}" for t, l in interests]
+            memory_embed.add_field(name="Top Interests", value="\n".join(i_items) if i_items else "None", inline=False)
+    embeds.append(memory_embed)
 
-        if error_msg:
-            print(f"Error in gurtai command: {error_msg}")
-            await ctx.reply(f"Sorry, I'm having trouble thinking right now. Details: {error_msg}")
-            return
+    # API Stats
+    api_stats = stats.get("api_stats", {})
+    if api_stats:
+        api_embed = create_gurt_embed("Gurt API Stats", color=discord.Color.red())
+        for model, data in api_stats.items():
+            avg_time = data.get('average_time_ms', 0)
+            value = (f"✅ Success: {data.get('success', 0)}\n"
+                     f"❌ Failure: {data.get('failure', 0)}\n"
+                     f"🔁 Retries: {data.get('retries', 0)}\n"
+                     f"⏱️ Avg Time: {avg_time} ms\n"
+                     f"📊 Count: {data.get('count', 0)}")
+            api_embed.add_field(name=f"Model: `{model}`", value=value, inline=True)
+        embeds.append(api_embed)
 
-        if not response_to_use or not response_to_use.get("should_respond", False):
-            await ctx.reply("I don't have anything to say about that right now.")
-            return
+    # Tool Stats
+    tool_stats = stats.get("tool_stats", {})
+    if tool_stats:
+        tool_embed = create_gurt_embed("Gurt Tool Stats", color=discord.Color.purple())
+        for tool, data in tool_stats.items():
+            avg_time = data.get('average_time_ms', 0)
+            value = (f"✅ Success: {data.get('success', 0)}\n"
+                     f"❌ Failure: {data.get('failure', 0)}\n"
+                     f"⏱️ Avg Time: {avg_time} ms\n"
+                     f"📊 Count: {data.get('count', 0)}")
+            tool_embed.add_field(name=f"Tool: `{tool}`", value=value, inline=True)
+        embeds.append(tool_embed)
 
-        response_text = response_to_use.get("content", "")
-        if not response_text:
-             await ctx.reply("I decided not to respond with text.")
-             return
+    # Config Stats (Less critical, maybe separate embed if needed)
+    config_embed = create_gurt_embed("Gurt Config Overview", color=discord.Color.greyple())
+    config = stats.get("config", {})
+    config_embed.add_field(name="Default Model", value=f"`{config.get('default_model', 'N/A')}`", inline=True)
+    config_embed.add_field(name="Fallback Model", value=f"`{config.get('fallback_model', 'N/A')}`", inline=True)
+    config_embed.add_field(name="Semantic Model", value=f"`{config.get('semantic_model_name', 'N/A')}`", inline=True)
+    config_embed.add_field(name="Max User Facts", value=str(config.get('max_user_facts', 'N/A')), inline=True)
+    config_embed.add_field(name="Max General Facts", value=str(config.get('max_general_facts', 'N/A')), inline=True)
+    config_embed.add_field(name="Context Window", value=str(config.get('context_window_size', 'N/A')), inline=True)
+    config_embed.add_field(name="API Key Set", value=str(config.get('api_key_set', 'N/A')), inline=True)
+    config_embed.add_field(name="Tavily Key Set", value=str(config.get('tavily_api_key_set', 'N/A')), inline=True)
+    config_embed.add_field(name="Piston URL Set", value=str(config.get('piston_api_url_set', 'N/A')), inline=True)
+    embeds.append(config_embed)
 
-        # Handle long responses
-        if len(response_text) > 1900:
-            filepath = f'gurt_response_{ctx.author.id}.txt'
-            try:
-                with open(filepath, 'w', encoding='utf-8') as f: f.write(response_text)
-                await ctx.send("Response too long, sending as file:", file=discord.File(filepath))
-            except Exception as file_e: print(f"Error writing/sending long response file: {file_e}")
-            finally:
-                try: os.remove(filepath)
-                except OSError as os_e: print(f"Error removing temp file {filepath}: {os_e}")
-        else:
-            await ctx.reply(response_text)
 
-    except Exception as e:
-        error_message = f"Error processing gurtai request: {str(e)}"
-        print(f"Exception in gurt_ai_command: {error_message}")
-        import traceback
-        traceback.print_exc()
-        await ctx.reply("Sorry, an unexpected error occurred.")
+    # Limit to 10 embeds max for Discord API
+    return embeds[:10]
 
-@commands.command(name="gurtmodel")
-@commands.is_owner() # Keep owner check for sensitive commands
-async def set_model_command(cog: 'GurtCog', ctx: commands.Context, *, model: str):
-    """Set the AI model to use (Owner only)"""
-    # Model setting might need to update config or cog state directly
-    # For now, let's assume it updates a cog attribute.
-    # Validation might be better handled in config loading or a dedicated setter.
-    # if not model.endswith(":free"): # Example validation
-    #     await ctx.reply("Error: Model name must end with `:free`. Setting not updated.")
-    #     return
 
-    cog.default_model = model # Update the cog's default model attribute
-    # TODO: Consider if this needs to persist somewhere or update config dynamically.
-    await ctx.reply(f"AI model temporarily set to: `{model}` for this session.")
-    print(f"Gurt model changed to {model} by {ctx.author.name}")
-
-@commands.command(name="gurtstatus")
-async def gurt_status_command(cog: 'GurtCog', ctx: commands.Context):
-    """Display the current status of Gurt Bot"""
-    embed = discord.Embed(
-        title="Gurt Bot Status",
-        description="Current configuration and status",
-        color=discord.Color.green()
-    )
-    embed.add_field(name="Current Model", value=f"`{cog.default_model}`", inline=False)
-    embed.add_field(name="API Session", value="Active" if cog.session and not cog.session.closed else "Inactive", inline=True)
-    # Add other relevant status info from the cog if needed
-    # embed.add_field(name="Current Mood", value=cog.current_mood, inline=True)
-    await ctx.send(embed=embed)
-
-@commands.command(name="gurthelp")
-async def gurt_help_command(cog: 'GurtCog', ctx: commands.Context):
-    """Display help information for Gurt Bot"""
-    from .config import TOOLS # Import TOOLS definition
-
-    embed = discord.Embed(
-        title="Gurt Bot Help",
-        description="Gurt is an autonomous AI participant.",
-        color=discord.Color.purple()
-    )
-    embed.add_field(
-        name="Commands",
-        value=f"`{cog.bot.command_prefix}gurt` - Gurt!\n"
-              f"`{cog.bot.command_prefix}gurtai <prompt>` - Ask Gurt AI directly\n"
-              f"`{cog.bot.command_prefix}gurtstatus` - Show current status\n"
-              f"`{cog.bot.command_prefix}gurthelp` - This help message\n"
-              f"`{cog.bot.command_prefix}gurtmodel <model>` - Set AI model (Owner)\n"
-              f"`{cog.bot.command_prefix}force_profile_update` - Trigger profile update (Owner)",
-        inline=False
-    )
-    embed.add_field(
-        name="Autonomous Behavior",
-        value="Gurt listens and responds naturally based on conversation, mentions, and interests.",
-        inline=False
-    )
-    # Dynamically list available tools from config
-    tool_list = "\n".join([f"- `{tool['function']['name']}`: {tool['function']['description']}" for tool in TOOLS])
-    embed.add_field(name="Available AI Tools", value=tool_list, inline=False)
-
-    await ctx.send(embed=embed)
-
-@commands.command(name="force_profile_update")
-@commands.is_owner()
-async def force_profile_update_command(cog: 'GurtCog', ctx: commands.Context):
-    """Manually triggers the profile update cycle (Owner only)."""
-    # This command interacts with another cog, which is complex after refactoring.
-    # Option 1: Keep this command in a separate 'owner' cog that knows about other cogs.
-    # Option 2: Use bot events/listeners for inter-cog communication.
-    # Option 3: Access the other cog directly via self.bot.get_cog (simplest for now).
-    profile_updater_cog = cog.bot.get_cog('ProfileUpdaterCog')
-    if not profile_updater_cog:
-        await ctx.reply("Error: ProfileUpdaterCog not found.")
-        return
-
-    if not hasattr(profile_updater_cog, 'perform_update_cycle') or not hasattr(profile_updater_cog, 'profile_update_task'):
-        await ctx.reply("Error: ProfileUpdaterCog is missing required methods/tasks.")
-        return
-
-    try:
-        await ctx.reply("Manually triggering profile update cycle...")
-        await profile_updater_cog.perform_update_cycle()
-        # Restarting the loop might be internal to that cog now
-        if hasattr(profile_updater_cog.profile_update_task, 'restart'):
-             profile_updater_cog.profile_update_task.restart()
-             await ctx.reply("Profile update cycle triggered and timer reset.")
-        else:
-             await ctx.reply("Profile update cycle triggered (task restart mechanism not found).")
-        print(f"Profile update cycle manually triggered by {ctx.author.name}.")
-    except Exception as e:
-        await ctx.reply(f"An error occurred while triggering the profile update: {e}")
-        print(f"Error during manual profile update trigger: {e}")
-        import traceback
-        traceback.print_exc()
-
-# Helper function to add these commands to the cog instance
+# --- Command Setup Function ---
+# This function will be called from GurtCog's setup method
 def setup_commands(cog: 'GurtCog'):
-    """Adds the commands defined in this file to the GurtCog."""
-    # Add commands directly to the bot instance, associated with the cog
-    cog.bot.add_command(gurt_command)
-    cog.bot.add_command(gurt_ai_command)
-    cog.bot.add_command(set_model_command)
-    cog.bot.add_command(gurt_status_command)
-    cog.bot.add_command(gurt_help_command)
-    cog.bot.add_command(force_profile_update_command)
+    """Adds Gurt-specific commands to the cog."""
+
+    # Example using app_commands - adapt existing commands if needed
+    @cog.bot.tree.command(name="gurtmood", description="Check or set Gurt's current mood.")
+    @app_commands.describe(mood="Optional: Set Gurt's mood to one of the available options.")
+    @app_commands.choices(mood=[
+        app_commands.Choice(name=m, value=m) for m in cog.MOOD_OPTIONS # Use cog's MOOD_OPTIONS
+    ])
+    async def gurtmood(interaction: discord.Interaction, mood: Optional[app_commands.Choice[str]] = None):
+        """Handles the /gurtmood command."""
+        if mood:
+            cog.current_mood = mood.value
+            cog.last_mood_change = time.time()
+            await interaction.response.send_message(f"Gurt's mood set to: {mood.value}", ephemeral=True)
+        else:
+            time_since_change = time.time() - cog.last_mood_change
+            await interaction.response.send_message(f"Gurt's current mood is: {cog.current_mood} (Set {int(time_since_change // 60)} minutes ago)", ephemeral=True)
+
+    @cog.bot.tree.command(name="gurtmemory", description="Interact with Gurt's memory.")
+    @app_commands.describe(
+        action="Choose an action: add_user, add_general, get_user, get_general",
+        user="The user for user-specific actions (mention or ID).",
+        fact="The fact to add (for add actions).",
+        query="A keyword to search for (for get_general)."
+    )
+    @app_commands.choices(action=[
+        app_commands.Choice(name="Add User Fact", value="add_user"),
+        app_commands.Choice(name="Add General Fact", value="add_general"),
+        app_commands.Choice(name="Get User Facts", value="get_user"),
+        app_commands.Choice(name="Get General Facts", value="get_general"),
+    ])
+    async def gurtmemory(interaction: discord.Interaction, action: app_commands.Choice[str], user: Optional[discord.User] = None, fact: Optional[str] = None, query: Optional[str] = None):
+        """Handles the /gurtmemory command."""
+        await interaction.response.defer(ephemeral=True) # Defer for potentially slow DB operations
+
+        target_user_id = str(user.id) if user else None
+        action_value = action.value
+
+        if action_value == "add_user":
+            if not target_user_id or not fact:
+                await interaction.followup.send("Please provide both a user and a fact to add.", ephemeral=True)
+                return
+            result = await cog.memory_manager.add_user_fact(target_user_id, fact)
+            await interaction.followup.send(f"Add User Fact Result: `{json.dumps(result)}`", ephemeral=True)
+
+        elif action_value == "add_general":
+            if not fact:
+                await interaction.followup.send("Please provide a fact to add.", ephemeral=True)
+                return
+            result = await cog.memory_manager.add_general_fact(fact)
+            await interaction.followup.send(f"Add General Fact Result: `{json.dumps(result)}`", ephemeral=True)
+
+        elif action_value == "get_user":
+            if not target_user_id:
+                await interaction.followup.send("Please provide a user to get facts for.", ephemeral=True)
+                return
+            facts = await cog.memory_manager.get_user_facts(target_user_id) # Get newest by default
+            if facts:
+                facts_str = "\n- ".join(facts)
+                await interaction.followup.send(f"**Facts for {user.display_name}:**\n- {facts_str}", ephemeral=True)
+            else:
+                await interaction.followup.send(f"No facts found for {user.display_name}.", ephemeral=True)
+
+        elif action_value == "get_general":
+            facts = await cog.memory_manager.get_general_facts(query=query, limit=10) # Get newest/filtered
+            if facts:
+                facts_str = "\n- ".join(facts)
+                title = f"**General Facts{f' matching "{query}"' if query else ''}:**"
+                await interaction.followup.send(f"{title}\n- {facts_str}", ephemeral=True)
+            else:
+                await interaction.followup.send(f"No general facts found{f' matching "{query}"' if query else ''}.", ephemeral=True)
+
+        else:
+            await interaction.followup.send("Invalid action specified.", ephemeral=True)
+
+    # --- Gurt Stats Command ---
+    @cog.bot.tree.command(name="gurtstats", description="Display Gurt's internal statistics.")
+    async def gurtstats(interaction: discord.Interaction):
+        """Handles the /gurtstats command."""
+        await interaction.response.defer(ephemeral=True) # Defer as stats collection might take time
+        try:
+            stats_data = await cog.get_gurt_stats()
+            embeds = format_stats_embeds(stats_data)
+            await interaction.followup.send(embeds=embeds, ephemeral=True)
+        except Exception as e:
+            print(f"Error in /gurtstats command: {e}")
+            import traceback
+            traceback.print_exc()
+            await interaction.followup.send("An error occurred while fetching Gurt's stats.", ephemeral=True)
+
+
+    print("Gurt commands setup in cog.")

gurt_dashboard/index.html

@@ -0,0 +1,36 @@
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Gurt Stats Dashboard</title>
+    <link rel="stylesheet" href="style.css">
+</head>
+<body>
+    <h1>Gurt Internal Stats</h1>
+    <p>Last Updated: <span id="last-updated">Never</span></p>
+    <div id="stats-container">
+        <div class="stats-section" id="runtime-stats">
+            <h2>Runtime</h2>
+            <!-- Runtime stats will be populated here -->
+        </div>
+        <div class="stats-section" id="memory-stats">
+            <h2>Memory</h2>
+            <!-- Memory stats will be populated here -->
+        </div>
+        <div class="stats-section" id="api-stats">
+            <h2>API Stats</h2>
+            <!-- API stats will be populated here -->
+        </div>
+        <div class="stats-section" id="tool-stats">
+            <h2>Tool Stats</h2>
+            <!-- Tool stats will be populated here -->
+        </div>
+        <div class="stats-section" id="config-stats">
+            <h2>Config Overview</h2>
+            <!-- Config stats will be populated here -->
+        </div>
+    </div>
+    <script src="script.js"></script>
+</body>
+</html>

gurt_dashboard/script.js

@@ -0,0 +1,176 @@
+const API_ENDPOINT = '/discordapi/gurt/stats'; // Relative path to the API endpoint
+const REFRESH_INTERVAL = 15000; // Refresh every 15 seconds (in milliseconds)
+
+const lastUpdatedElement = document.getElementById('last-updated');
+const runtimeStatsContainer = document.getElementById('runtime-stats');
+const memoryStatsContainer = document.getElementById('memory-stats');
+const apiStatsContainer = document.getElementById('api-stats');
+const toolStatsContainer = document.getElementById('tool-stats');
+const configStatsContainer = document.getElementById('config-stats');
+
+function formatTimestamp(unixTimestamp) {
+    if (!unixTimestamp || unixTimestamp === 0) return 'N/A';
+    const date = new Date(unixTimestamp * 1000);
+    return date.toLocaleString(); // Adjust format as needed
+}
+
+function createStatItem(label, value, isCode = false) {
+    const item = document.createElement('div');
+    item.classList.add('stat-item');
+
+    const labelSpan = document.createElement('span');
+    labelSpan.classList.add('stat-label');
+    labelSpan.textContent = label + ':';
+    item.appendChild(labelSpan);
+
+    const valueSpan = document.createElement('span');
+    valueSpan.classList.add('stat-value');
+    if (isCode) {
+        const code = document.createElement('code');
+        code.textContent = value;
+        valueSpan.appendChild(code);
+    } else {
+        valueSpan.textContent = value;
+    }
+    item.appendChild(valueSpan);
+    return item;
+}
+
+function createListStatItem(label, items) {
+    const item = document.createElement('div');
+    item.classList.add('stat-item');
+
+    const labelSpan = document.createElement('span');
+    labelSpan.classList.add('stat-label');
+    labelSpan.textContent = label + ':';
+    item.appendChild(labelSpan);
+
+    if (items && items.length > 0) {
+        const list = document.createElement('ul');
+        list.classList.add('stat-list');
+        items.forEach(content => {
+            const li = document.createElement('li');
+            li.textContent = content;
+            list.appendChild(li);
+        });
+        item.appendChild(list);
+    } else {
+        const valueSpan = document.createElement('span');
+        valueSpan.classList.add('stat-value');
+        valueSpan.textContent = 'None';
+        item.appendChild(valueSpan);
+    }
+    return item;
+}
+
+function renderStats(stats) {
+    // Clear previous stats
+    runtimeStatsContainer.innerHTML = '<h2>Runtime</h2>';
+    memoryStatsContainer.innerHTML = '<h2>Memory</h2>';
+    apiStatsContainer.innerHTML = '<h2>API Stats</h2>';
+    toolStatsContainer.innerHTML = '<h2>Tool Stats</h2>';
+    configStatsContainer.innerHTML = '<h2>Config Overview</h2>';
+
+    // Runtime Stats
+    const runtime = stats.runtime || {};
+    runtimeStatsContainer.appendChild(createStatItem('Current Mood', runtime.current_mood || 'N/A'));
+    runtimeStatsContainer.appendChild(createStatItem('Mood Changed', formatTimestamp(runtime.last_mood_change_timestamp)));
+    runtimeStatsContainer.appendChild(createStatItem('Background Task Running', runtime.background_task_running ? 'Yes' : 'No'));
+    runtimeStatsContainer.appendChild(createStatItem('Needs JSON Reminder', runtime.needs_json_reminder ? 'Yes' : 'No'));
+    runtimeStatsContainer.appendChild(createStatItem('Last Evolution', formatTimestamp(runtime.last_evolution_update_timestamp)));
+    runtimeStatsContainer.appendChild(createStatItem('Active Topics Channels', runtime.active_topics_channels || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Conv History Channels', runtime.conversation_history_channels || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Thread History Threads', runtime.thread_history_threads || 0));
+    runtimeStatsContainer.appendChild(createStatItem('User Relationships Pairs', runtime.user_relationships_pairs || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Cached Summaries', runtime.conversation_summaries_cached || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Cached Channel Topics', runtime.channel_topics_cached || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Global Msg Cache', runtime.message_cache_global_count || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Mention Msg Cache', runtime.message_cache_mentioned_count || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Active Convos', runtime.active_conversations_count || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Sentiment Channels', runtime.conversation_sentiment_channels || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Gurt Participation Topics', runtime.gurt_participation_topics_count || 0));
+    runtimeStatsContainer.appendChild(createStatItem('Tracked Reactions', runtime.gurt_message_reactions_tracked || 0));
+
+    // Memory Stats
+    const memory = stats.memory || {};
+    if (memory.error) {
+        const errorItem = document.createElement('div');
+        errorItem.classList.add('stat-item', 'error');
+        errorItem.textContent = `Error: ${memory.error}`;
+        memoryStatsContainer.appendChild(errorItem);
+    } else {
+        memoryStatsContainer.appendChild(createStatItem('User Facts', memory.user_facts_count || 0));
+        memoryStatsContainer.appendChild(createStatItem('General Facts', memory.general_facts_count || 0));
+        memoryStatsContainer.appendChild(createStatItem('Chroma Messages', memory.chromadb_message_collection_count || 'N/A'));
+        memoryStatsContainer.appendChild(createStatItem('Chroma Facts', memory.chromadb_fact_collection_count || 'N/A'));
+
+        const personality = memory.personality_traits || {};
+        const pItems = Object.entries(personality).map(([k, v]) => `${k}: ${v}`);
+        memoryStatsContainer.appendChild(createListStatItem('Personality Traits', pItems));
+
+        const interests = memory.top_interests || [];
+        const iItems = interests.map(([t, l]) => `${t}: ${l.toFixed(2)}`);
+        memoryStatsContainer.appendChild(createListStatItem('Top Interests', iItems));
+    }
+
+    // API Stats
+    const apiStats = stats.api_stats || {};
+    if (Object.keys(apiStats).length === 0) {
+        apiStatsContainer.appendChild(createStatItem('No API calls recorded yet.', ''));
+    } else {
+        for (const [model, data] of Object.entries(apiStats)) {
+            const value = `Success: ${data.success || 0}, Failure: ${data.failure || 0}, Retries: ${data.retries || 0}, Avg Time: ${data.average_time_ms || 0} ms, Count: ${data.count || 0}`;
+            apiStatsContainer.appendChild(createStatItem(model, value, true));
+        }
+    }
+
+
+    // Tool Stats
+    const toolStats = stats.tool_stats || {};
+     if (Object.keys(toolStats).length === 0) {
+        toolStatsContainer.appendChild(createStatItem('No tool calls recorded yet.', ''));
+    } else {
+        for (const [tool, data] of Object.entries(toolStats)) {
+            const value = `Success: ${data.success || 0}, Failure: ${data.failure || 0}, Avg Time: ${data.average_time_ms || 0} ms, Count: ${data.count || 0}`;
+            toolStatsContainer.appendChild(createStatItem(tool, value, true));
+        }
+    }
+
+    // Config Stats
+    const config = stats.config || {};
+    configStatsContainer.appendChild(createStatItem('Default Model', config.default_model || 'N/A', true));
+    configStatsContainer.appendChild(createStatItem('Fallback Model', config.fallback_model || 'N/A', true));
+    configStatsContainer.appendChild(createStatItem('Semantic Model', config.semantic_model_name || 'N/A', true));
+    configStatsContainer.appendChild(createStatItem('Max User Facts', config.max_user_facts || 'N/A'));
+    configStatsContainer.appendChild(createStatItem('Max General Facts', config.max_general_facts || 'N/A'));
+    configStatsContainer.appendChild(createStatItem('Context Window', config.context_window_size || 'N/A'));
+    configStatsContainer.appendChild(createStatItem('API Key Set', config.api_key_set ? 'Yes' : 'No'));
+    configStatsContainer.appendChild(createStatItem('Tavily Key Set', config.tavily_api_key_set ? 'Yes' : 'No'));
+    configStatsContainer.appendChild(createStatItem('Piston URL Set', config.piston_api_url_set ? 'Yes' : 'No'));
+
+}
+
+async function fetchStats() {
+    try {
+        const response = await fetch(API_ENDPOINT);
+        if (!response.ok) {
+            throw new Error(`HTTP error! status: ${response.status}`);
+        }
+        const stats = await response.json();
+        renderStats(stats);
+        lastUpdatedElement.textContent = new Date().toLocaleTimeString();
+    } catch (error) {
+        console.error('Error fetching stats:', error);
+        lastUpdatedElement.textContent = `Error fetching stats at ${new Date().toLocaleTimeString()}`;
+        // Optionally display an error message in the UI
+        runtimeStatsContainer.innerHTML = '<h2>Runtime</h2><p class="error">Could not load stats.</p>';
+        memoryStatsContainer.innerHTML = '<h2>Memory</h2>';
+        apiStatsContainer.innerHTML = '<h2>API Stats</h2>';
+        toolStatsContainer.innerHTML = '<h2>Tool Stats</h2>';
+        configStatsContainer.innerHTML = '<h2>Config Overview</h2>';
+    }
+}
+
+// Initial fetch and set interval
+fetchStats();
+setInterval(fetchStats, REFRESH_INTERVAL);

gurt_dashboard/style.css

@@ -0,0 +1,79 @@
+body {
+    font-family: sans-serif;
+    line-height: 1.6;
+    margin: 20px;
+    background-color: #f4f4f4;
+    color: #333;
+}
+
+h1, h2 {
+    color: #333;
+    border-bottom: 1px solid #ccc;
+    padding-bottom: 5px;
+}
+
+#stats-container {
+    display: grid;
+    grid-template-columns: repeat(auto-fit, minmax(300px, 1fr));
+    gap: 20px;
+}
+
+.stats-section {
+    background-color: #fff;
+    padding: 15px;
+    border-radius: 5px;
+    box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+}
+
+.stats-section h2 {
+    margin-top: 0;
+    font-size: 1.2em;
+}
+
+.stat-item {
+    margin-bottom: 10px;
+    padding-bottom: 10px;
+    border-bottom: 1px dotted #eee;
+}
+
+.stat-item:last-child {
+    border-bottom: none;
+    margin-bottom: 0;
+    padding-bottom: 0;
+}
+
+.stat-label {
+    font-weight: bold;
+    display: block;
+    margin-bottom: 3px;
+}
+
+.stat-value {
+    font-family: monospace;
+    word-wrap: break-word;
+}
+
+.stat-value code {
+    background-color: #eee;
+    padding: 2px 4px;
+    border-radius: 3px;
+}
+
+.stat-list {
+    list-style: none;
+    padding-left: 0;
+}
+
+.stat-list li {
+    margin-bottom: 5px;
+}
+
+.error {
+    color: red;
+    font-weight: bold;
+}
+
+#last-updated {
+    font-style: italic;
+    color: #555;
+}

main.py

@@ -11,10 +11,11 @@ from commands import load_all_cogs, reload_all_cogs
 from error_handler import handle_error, patch_discord_methods, store_interaction_content
 from utils import reload_script
 
-# Import the unified API service runner
+# Import the unified API service runner and the sync API module
 import sys
 sys.path.append(os.path.join(os.path.dirname(__file__), '..'))
 from discordbot.run_unified_api import start_api_in_thread
+import discord_bot_sync_api # Import the module to set the cog instance
 
 # Check if API dependencies are available
 try:
@@ -234,6 +235,19 @@ async def main():
         async with bot:
             # Load all cogs from the 'cogs' directory
             await load_all_cogs(bot)
+
+            # --- Share GurtCog instance with the sync API ---
+            try:
+                gurt_cog = bot.get_cog("Gurt") # Get the loaded GurtCog instance
+                if gurt_cog:
+                    discord_bot_sync_api.gurt_cog_instance = gurt_cog
+                    print("Successfully shared GurtCog instance with discord_bot_sync_api.")
+                else:
+                    print("Warning: GurtCog not found after loading cogs. Stats API might not work.")
+            except Exception as e:
+                print(f"Error sharing GurtCog instance: {e}")
+            # ------------------------------------------------
+
             # Start the bot using start() for async context
             await bot.start(TOKEN)
     finally: