feat: inject persistent memory context into chat responses

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

cogs/chat.py

@@ -3,6 +3,7 @@ import logging
 import random
 import re
 from collections import deque
+from datetime import datetime, timezone
 from pathlib import Path
 
 import discord
@@ -25,6 +26,52 @@ def _load_prompt(filename: str) -> str:
     return _prompt_cache[filename]
 
 
+_TOPIC_KEYWORDS = {
+    "gta", "warzone", "cod", "battlefield", "fortnite", "apex", "valorant",
+    "minecraft", "roblox", "league", "dota", "overwatch", "destiny", "halo",
+    "work", "job", "school", "college", "girlfriend", "boyfriend", "wife",
+    "husband", "dog", "cat", "pet", "car", "music", "movie", "food",
+}
+
+_GENERIC_CHANNELS = {"general", "off-topic", "memes"}
+
+
+def _extract_topic_keywords(text: str, channel_name: str) -> list[str]:
+    """Extract topic keywords from message text and channel name."""
+    words = set(text.lower().split()) & _TOPIC_KEYWORDS
+    if channel_name.lower() not in _GENERIC_CHANNELS:
+        words.add(channel_name.lower())
+    return list(words)[:5]
+
+
+def _format_relative_time(dt: datetime) -> str:
+    """Return a human-readable relative time string."""
+    now = datetime.now(timezone.utc)
+    # Ensure dt is timezone-aware
+    if dt.tzinfo is None:
+        dt = dt.replace(tzinfo=timezone.utc)
+    delta = now - dt
+    seconds = int(delta.total_seconds())
+    if seconds < 60:
+        return "just now"
+    minutes = seconds // 60
+    if minutes < 60:
+        return f"{minutes}m ago"
+    hours = minutes // 60
+    if hours < 24:
+        return f"{hours}h ago"
+    days = hours // 24
+    if days == 1:
+        return "yesterday"
+    if days < 7:
+        return f"{days} days ago"
+    weeks = days // 7
+    if weeks < 5:
+        return f"{weeks}w ago"
+    months = days // 30
+    return f"{months}mo ago"
+
+
 class ChatCog(commands.Cog):
     def __init__(self, bot: commands.Bot):
         self.bot = bot
@@ -39,6 +86,43 @@ class ChatCog(commands.Cog):
         prompt_file = mode_config.get("prompt_file", "chat_personality.txt")
         return _load_prompt(prompt_file)
 
+    async def _build_memory_context(self, user_id: int, message_text: str, channel_name: str) -> str:
+        """Build a layered memory context block for the chat prompt."""
+        lines = []
+
+        # Layer 1: Profile (always)
+        profile = self.bot.drama_tracker.get_user_notes(user_id)
+        if profile:
+            lines.append(f"Profile: {profile}")
+
+        # Layer 2: Recent memories (last 5)
+        recent_memories = await self.bot.db.get_recent_memories(user_id, limit=5)
+        if recent_memories:
+            parts = []
+            for mem in recent_memories:
+                time_str = _format_relative_time(mem["created_at"])
+                parts.append(f"{mem['memory']} ({time_str})")
+            lines.append("Recent: " + " | ".join(parts))
+
+        # Layer 3: Topic-matched memories (deduplicated against recent)
+        keywords = _extract_topic_keywords(message_text, channel_name)
+        if keywords:
+            topic_memories = await self.bot.db.get_memories_by_topics(user_id, keywords, limit=5)
+            # Deduplicate against recent memories
+            recent_texts = {mem["memory"] for mem in recent_memories} if recent_memories else set()
+            unique_topic = [mem for mem in topic_memories if mem["memory"] not in recent_texts]
+            if unique_topic:
+                parts = []
+                for mem in unique_topic:
+                    time_str = _format_relative_time(mem["created_at"])
+                    parts.append(f"{mem['memory']} ({time_str})")
+                lines.append("Relevant: " + " | ".join(parts))
+
+        if not lines:
+            return ""
+
+        return "[What you know about this person:]\n" + "\n".join(lines)
+
     @commands.Cog.listener()
     async def on_message(self, message: discord.Message):
         if message.author.bot:
@@ -176,11 +260,13 @@ class ChatCog(commands.Cog):
                 context_parts.append(f"{user_data.offense_count} offense(s)")
             score_context = f"[Server context: {message.author.display_name} — {', '.join(context_parts)}]"
 
-            # Gather user notes and recent messages for richer context
+            # Gather memory context and recent messages for richer context
             extra_context = ""
-            user_notes = self.bot.drama_tracker.get_user_notes(message.author.id)
-            if user_notes:
-                extra_context += f"[Notes about {message.author.display_name}: {user_notes}]\n"
+            memory_context = await self._build_memory_context(
+                message.author.id, content, message.channel.name,
+            )
+            if memory_context:
+                extra_context += memory_context + "\n"
 
             # Include mention scan findings if available
             if scan_summary: