Previously, when a user replied to Miku's message via Discord's reply
feature, Miku's quoted words were embedded directly into the user's
message text using the format:
[Replying to your message: "Miku's words"] User's response
This caused two problems:
1. The LLM had to parse "your message" to determine the quoted text
was MIKU's words — fragile and frequently misattributed
2. When stored in episodic memory as [User]: ..., Miku's quoted words
were permanently mislabeled under the user's speaker prefix
Now reply context flows through as structured metadata:
- bot/bot.py captures the replied-to text WITHOUT embedding it in prompt
- cat_client.py passes it as discord_reply_context in the WebSocket payload
- discord_bridge.py injects it as agent_input['reply_context'] — a
CLEARLY LABELED note: [The user is replying to what you (Miku) said — ...]
- miku_personality.py + evil_miku_personality.py render it via
{reply_context} placeholder in the prompt suffix, between memory
context and conversation history
This keeps Miku's words as a separate context note, never mixed into
the user's HumanMessage. Episodic memory only stores the user's actual
words. The fallback path (when Cat is unavailable) also uses a cleaner
format with explicit speaker labels.
- bot/Dockerfile: Add ffmpeg to reinstall line after apt-get autoremove
(autoremove was sweeping up ffmpeg as 'no longer needed' after playwright install)
- bot/utils/image_handling.py: Increase video analysis timeout 120s→300s, 6→3 for Tenor GIFs (GTX 1660 VRAM constraint)
- bot/utils/activities.py: Add _activity_changed_at timestamp tracking,
get_current_activity_label() and get_current_activity_fresh() with 30-min decay
- bot/utils/cat_client.py: Pass current Discord activity to Cheshire Cat pipeline
- bot/utils/llm.py: Inject current Discord activity into system prompt
- cat-plugins/*: Forward Discord activity through working_memory to personality plugins
- bot/persona/*/preamble.txt: Add Discord status usage guidelines for character prompts
- llama-swap-rocm-config.yaml: Add qwen3.5 model entry for ComfyUI prompt generation
- AGENTS.md: New project documentation file
Three interrelated fixes for speaker attribution confusion:
1. Fix misleading episodic memory header (discord_bridge.py):
The Cat core hardcodes '## Context of things the Human said in the past:'
when formatting recalled conversations. Our plugins store BOTH user messages
([User]: prefix) AND Miku's own responses ([Miku]: prefix) in episodic memory.
This misleading header primes the LLM to attribute Miku's words to the user.
Replaced with '## Past conversation excerpts (prefixed by who said what):'
which accurately describes the mixed-speaker content.
2. Tighten episodic recall (discord_bridge.py):
Added before_cat_recalls_episodic_memories hook setting threshold=0.75
(vs default 0.7) to reduce the chance of Miku's own just-uttered response
being recalled on the very next user message, which would feed her own
words back as misleading context.
3. Add role clarification (miku_personality.py & evil_miku_personality.py):
Added a clarifying note after '# Conversation until now:' in the prompt
suffix to explicitly tell the model that 'Human = the user, AI = you (Miku)',
helping it reconcile the two labeling systems (episodic [User]/[Miku] prefixes
vs conversation history Human/AI roles).
Step 4 of memory system overhaul: single source of truth for prompts.
Problem: The system prompt was defined inline in 4 different places:
miku_personality.py, evil_miku_personality.py, llm.py, discord_bridge.py.
These could drift out of sync — and the discord_bridge WebUI
reconstruction was already missing CRITICAL RULES, CHARACTER CONTEXT,
MOOD GUIDELINES, and RESPONSE RULES sections.
Fix:
- Create persona/miku/preamble.txt — canonical normal Miku preamble
- Create persona/evil/preamble.txt — canonical evil Miku preamble
(with {mood_name} and {mood_description} format placeholders)
- All 5 consumers now read from these files:
* miku_personality.py (Cat plugin, primary path)
* evil_miku_personality.py (Cat plugin, primary path)
* discord_bridge.py (WebUI 'Last Prompt' reconstruction)
* llm.py (fallback path, normal Miku)
* evil_mode.py get_evil_system_prompt() (fallback path, evil Miku)
- All consumers include graceful fallbacks if preamble files are missing
- Fixed evil_mode.py discrepancy: 'body and size' now matches canonical
The preamble files are Docker volume-mounted into both containers:
bot/persona/ → /app/persona/ (bot, via Dockerfile COPY)
bot/persona/ → /app/cat/data/ (Cat, via docker-compose volume mount)
Editing the preamble file on the host immediately updates the Cat path
(bot path requires rebuild due to COPY).
- discord_bridge before_agent_starts now checks evil_mode from
working_memory to load the correct personality files:
Normal: miku_lore/prompt/lyrics + /app/moods/{mood}.txt
Evil: evil_miku_lore/prompt/lyrics + /app/moods/evil/{mood}.txt
- Reads files directly instead of relying on cross-plugin working_memory
- cat_client.query() returns (response, full_prompt) tuple
- Full prompt includes system prefix + recalled memories + conversation
- API /prompt/cat returns full_prompt field
MOOD SYSTEM FIX:
- Mount bot/moods directory in docker-compose.yml for Cat container access
- Update miku_personality plugin to load mood descriptions from .txt files
- Add Cat logger for debugging mood loading (replaces print statements)
- Moods now dynamically loaded from working_memory instead of hardcoded neutral
Root cause: The miku_personality plugin's agent_prompt_suffix hook was returning
an empty string, which wiped out the {declarative_memory} and {episodic_memory}
placeholders from the prompt template. This caused the LLM to never receive any
stored facts about users, resulting in hallucinated responses.
Changes:
- miku_personality: Changed agent_prompt_suffix to return the memory context
section with {episodic_memory}, {declarative_memory}, and {tools_output}
placeholders instead of empty string
- discord_bridge: Added before_cat_recalls_declarative_memories hook to increase
k-value from 3 to 10 and lower threshold from 0.7 to 0.5 for better fact
retrieval. Added agent_prompt_prefix to emphasize factual accuracy. Added
debug logging via before_agent_starts hook.
Result: Miku now correctly recalls user facts (favorite songs, games, etc.)
from declarative memory with 100% accuracy.
Tested with:
- 'What is my favorite song?' → Correctly answers 'Monitoring (Best Friend Remix) by DECO*27'
- 'Do you remember my favorite song?' → Correctly recalls the song
- 'What is my favorite video game?' → Correctly answers 'Sonic Adventure'
Key changes:
- CatAdapter (bot/utils/cat_client.py): WebSocket /ws/{user_id} for chat
queries instead of HTTP POST (fixes per-user memory isolation when no
API keys are configured — HTTP defaults all users to user_id='user')
- Memory management API: 8 endpoints for status, stats, facts, episodic
memories, consolidation trigger, multi-step delete with confirmation
- Web UI: Memory tab (tab9) with collection stats, fact/episodic browser,
manual consolidation trigger, and 3-step delete flow requiring exact
confirmation string
- Bot integration: Cat-first response path with query_llama fallback for
both text and embed responses, server mood detection
- Discord bridge plugin: fixed .pop() to .get() (UserMessage is a Pydantic
BaseModelDict, not a raw dict), metadata extraction via extra attributes
- Unified docker-compose: Cat + Qdrant services merged into main compose,
bot depends_on Cat healthcheck
- All plugins (discord_bridge, memory_consolidation, miku_personality)
consolidated into cat-plugins/ for volume mount
- query_llama deprecated but functional for compatibility
