1. Broader regex to strip leaked metadata even when the LLM drops
the "Server context:" prefix but keeps the content.
2. Skip sentiment analysis for messages that mention or reply to
the bot. Users interacting with the bot in roast/chat modes
shouldn't have those messages inflate their drama score.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When someone reacts to the bot's message, there's a 50% chance it
fires back with a reply commenting on their emoji choice, in
character for the current mode.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The local LLM was echoing back [Server context: ...] metadata lines
in its responses despite prompt instructions not to. Now stripped
via regex before sending to Discord.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When a user replies to the bot's message, the original bot message
text is now included in the context sent to the LLM. This prevents
the LLM from misinterpreting follow-up questions like "what does
this even mean?" since it can see what message is being referenced.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds a BotSettings key-value table. The active mode is saved
when changed via /bcs-mode and restored on startup.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
LLM analysis now detects when two users are in a genuine
disagreement. When detected, the bot creates a native Discord
poll with each user's position as an option.
- Disagreement detection added to LLM analysis tool schema
- Polls last 4 hours with 1 hour per-channel cooldown
- LLM extracts topic, both positions, and usernames
- Configurable via polls section in config.yaml
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Adds a server-wide mode system with /bcs-mode command.
- Default: current hall-monitor behavior unchanged
- Chatty: friendly chat participant with proactive replies (~10% chance)
- Roast: savage roast mode with proactive replies
- Chatty/roast use relaxed moderation thresholds
- 5-message cooldown between proactive replies per channel
- Bot status updates to reflect active mode
- /bcs-status shows current mode and effective thresholds
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Only inject drama score/offense context when values are noteworthy
(score >= 0.2 or offenses > 0). Update personality prompt to avoid
harping on zero scores and vary responses more.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When the LLM is offline, post to #bcs-log instead of sending
the "brain offline" message in chat.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- spike_mute: 0.8→0.7, mute: 0.75→0.65 so escalating users get
timed out after a warning instead of endlessly warned
- Skip debounce on @mentions so sentiment analysis fires immediately
- Chat cog awaits pending sentiment analysis before replying,
ensuring warnings/mutes appear before the personality response
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Send last ~8 messages from all users (not just others) as a
multi-line chat log with relative timestamps so the LLM can
better understand conversation flow and escalation patterns.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Triage model (LLM_MODEL) handles every message cheaply. If toxicity
>= 0.25, off_topic, or coherence < 0.6, the message is re-analyzed
with the heavy model (LLM_ESCALATION_MODEL). Chat, image analysis,
/bcs-test, and /bcs-scan always use the heavy model.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Buffer messages per user+channel and wait for a configurable window
(batch_window_seconds: 3) before analyzing. Combines burst messages
into a single LLM call instead of analyzing each one separately.
Replaces cooldown_between_analyses with the debounce approach.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Detect when users discuss a game in the wrong channel (e.g. GTA talk
in #warzone) and send a friendly redirect to the correct channel.
Also add sexual_vulgar category and scoring rules so crude sexual
remarks directed at someone aren't softened by "lmao".
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
When @mentioned with an image attachment, the bot now roasts players
based on scoreboard screenshots using the vision model. Text-only
mentions continue to work as before.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Serialize all LLM requests through an asyncio semaphore to prevent
overloading athena with concurrent requests
- Switch chat() to streaming so the typing indicator only appears once
the model starts generating (not during thinking/loading)
- Increase LLM timeout from 5 to 10 minutes for slow first loads
- Rename ollama_client.py to llm_client.py and self.ollama to self.llm
since the bot uses a generic OpenAI-compatible API
- Update embed labels from "Ollama" to "LLM"
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Move the analysis and chat personality system prompts from inline Python
strings to prompts/analysis.txt and prompts/chat_personality.txt for
easier editing. Also add a rule so users quoting/reporting what someone
else said are not penalized for the quoted words.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Discord bot for monitoring chat sentiment and tracking drama using
Ollama LLM on athena.lan. Includes sentiment analysis, slash commands,
drama tracking, and SQL Server persistence via Docker Compose.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
