voice.py runs in bot container, not agent container.
- Wait 3s for encryption key before connecting
- Build E2EE options with HKDF when key received
- Bot container now uses patched Dockerfile (needs FFI)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Element Call uses HKDF-SHA256 + AES-128-GCM for frame encryption,
while the LiveKit Rust SDK defaults to PBKDF2 + AES-256-GCM.
- Multi-stage Dockerfile builds patched Rust FFI from EC-compat fork
- Generates Python protobuf bindings with new fields
- patch_sdk.py modifies installed livekit-rtc for new proto fields
- agent.py passes E2EE options with HKDF to ctx.connect()
- bot.py exchanges encryption keys via Matrix state events
- Separate Dockerfile.bot for bot service (no Rust build needed)
Ref: livekit/rust-sdks#904, livekit/python-sdks#570
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Add memory-service (FastAPI + pgvector) for semantic memory storage.
Bot now queries relevant memories per conversation instead of dumping all 50.
Includes migration script for existing JSON files.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Replace separate bot-crypto/bot-memories volumes with single bot-data:/data
volume so user_keys.json and language_prefs.json persist across restarts
- Remove redundant language_prefs.json infrastructure (constant, load/save,
dict) — language preference now read from memories (last match wins)
- Add robust JSON extraction in _extract_memories (regex fallback for
markdown fences, embedded arrays, non-array responses)
- Add info-level logging throughout memory extraction pipeline
- Add asyncio.wait_for timeout (15s) on memory extraction to prevent hangs
- Add !ai memory <fact> command for explicit, reliable memory storage
- Update _get_preferred_language to return last match (most recent wins)
- Update !ai forget to clear in-memory caches (pending translate/reply)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- Extract and store memorable facts (name, language, preferences) per user
- Inject memories into system prompt for personalized responses
- LLM-based extraction after each response, deduplication against existing
- JSON files on Docker volume (/data/memories), capped at 50 per user
- System prompt updated: respond in users language, use memories
- Commands: !ai memories (view), !ai forget (delete all)
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Extends bot.py with text message handling:
- RoomMessageText callback with @mention detection
- LLM responses via LiteLLM (OpenAI-compatible)
- WildFiles document search (DocumentRAG class)
- Per-room model selection via room state events
- Commands: !ai help/models/set-model/search
- Typing indicators during AI response generation
- 30s staleness check to avoid replaying history
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
AgentServer in livekit-agents 1.4.x does not support --agent-name CLI
flag. The agent_name must be set on @server.rtc_session() decorator.
Also reverts docker-compose.yml command back to plain python agent.py start.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Three fixes for voice agent not responding to speech:
1. Agent name: add --agent-name matrix-ai to CLI (was empty, dispatch couldnt match)
2. Move dispatch from on_invite to on_unknown call handler (dispatch when call starts, not on room join)
3. Use LiveKit room name from foci_preferred instead of raw Matrix room ID
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- matrix-nio[e2e] with libolm for Megolm encryption
- Persistent crypto store volume for key persistence
- Auto-accept key verification (SAS)
- Upload device keys on first login
CF-1147
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
