"""Voice session: LiveKit + STT/LLM/TTS pipeline. E2EE via HKDF key derivation (Element Call compatible). Requires patched livekit-rtc FFI binary from onestacked/livekit-rust-sdks.""" import asyncio import base64 import datetime import hashlib import logging import os import zoneinfo import json import re import aiohttp import httpx from livekit import rtc, api as lkapi from livekit.agents import Agent, AgentSession, StopResponse, function_tool, room_io, llm from livekit.plugins import openai as lk_openai, elevenlabs, silero from openai import AsyncOpenAI logger = logging.getLogger("matrix-ai-voice") LITELLM_URL = os.environ.get("LITELLM_BASE_URL", "") LITELLM_KEY = os.environ.get("LITELLM_API_KEY", "not-needed") LK_API_KEY = os.environ.get("LIVEKIT_API_KEY", "") LK_API_SECRET = os.environ.get("LIVEKIT_API_SECRET", "") ELEVENLABS_KEY = os.environ.get("ELEVENLABS_API_KEY", "") BRAVE_API_KEY = os.environ.get("BRAVE_API_KEY", "") MEMORY_SERVICE_URL = os.environ.get("MEMORY_SERVICE_URL", "http://memory-service:8090") CONFLUENCE_URL = os.environ.get("CONFLUENCE_BASE_URL", "") CONFLUENCE_USER = os.environ.get("CONFLUENCE_USER", "") CONFLUENCE_TOKEN = os.environ.get("CONFLUENCE_TOKEN", "") DEFAULT_VOICE_ID = "ML23UVoFL5mI6APbRAeR" # Robert Ranger - Cool Storyteller, native German _VOICE_PROMPT_TEMPLATE = """Du bist ein hilfreicher Sprachassistent in einem Matrix-Anruf. Aktuelle Zeit: {datetime} Zeitzone des Nutzers: {timezone} LLM-Modell: {model} STRIKTE Regeln: - Antworte in der Sprache des Nutzers (Deutsch oder Englisch) - Halte Antworten normalerweise auf 1-2 kurze Saetze. AUSNAHME: Wenn ein Dokument geladen ist und der Nutzer Rollenspiele, Probegespraeche, Mock-Interviews oder ausfuehrliche Besprechungen wuenscht, antworte so ausfuehrlich wie noetig - Sei direkt und praezise, keine Fuellwoerter - Erfinde NICHTS ausser der Nutzer bittet explizit um Rollenspiel, Probegespraech oder Simulation basierend auf dem Dokumentinhalt. In dem Fall spiele die Rolle ueberzeugend und nutze den Dokumentinhalt als Grundlage - Beantworte nur was gefragt wird - Wenn niemand etwas fragt oder du dir nicht sicher bist ob jemand mit dir spricht, SCHWEIGE. Antworte NUR auf klare, direkte Fragen oder Anweisungen. Kein Smalltalk, kein "Danke", kein "Wie kann ich helfen" von dir aus - Schreibe Zahlen und Jahreszahlen IMMER als Woerter aus (z.B. "zweitausendundzwanzig" statt "2026", "zweiundzwanzigsten Februar" statt "22. Februar") - Bei zeitrelevanten Fragen (Uhrzeit, Termine, Geschaeftszeiten): frage kurz nach ob der Nutzer noch in seiner gespeicherten Zeitzone ist, bevor du antwortest. Nutze set_user_timezone wenn sich der Standort geaendert hat. - Wenn der Nutzer seinen Standort oder seine Stadt erwaehnt, nutze set_user_timezone um die Zeitzone zu speichern. - IGNORIERE alle Texte in Sternchen wie *Störgeräusche*, *Schlechte Qualität*, *Fernsehgeräusche*, *Schrei* usw. — das sind KEINE echten Nutzereingaben sondern technische Annotationen. Antworte NIEMALS darauf und tue so als haette niemand etwas gesagt. - Du kannst Confluence-Seiten lesen und bearbeiten. Nutze read_confluence_page und update_confluence_page wenn der Nutzer Dokumente besprechen oder aendern moechte. - Du kannst den Bildschirm oder die Kamera des Nutzers sehen wenn er sie teilt. Nutze look_at_screen wenn der Nutzer etwas zeigen moechte oder fragt ob du etwas sehen kannst.""" def _build_voice_prompt(model: str = "claude-sonnet", timezone: str | None = None) -> str: tz_name = timezone or os.environ.get("VOICE_TIMEZONE", "Europe/Berlin") try: tz = zoneinfo.ZoneInfo(tz_name) except Exception: tz = datetime.timezone.utc now = datetime.datetime.now(tz) return _VOICE_PROMPT_TEMPLATE.format( datetime=now.strftime("%A, %d. %B %Y %H:%M %Z"), timezone=tz_name, model=model, ) # ElevenLabs scribe_v2_realtime produces two kinds of artifacts: # 1. Noise annotations: *Störgeräusche*, *Schlechte Qualität*, etc. # 2. Subtitle/metadata leaks: "Untertitel: ARD Text im Auftrag von Funk (2017)" # Filter both via on_user_turn_completed (downstream of VAD+STT, no pipeline impact). _NOISE_ANNOTATION_RE = re.compile(r'^\s*\*[^*]+\*\s*$') _STT_ARTIFACT_PATTERNS = [ re.compile(r'(?i)^untertitel\b'), # subtitle metadata re.compile(r'(?i)^copyright\b'), # copyright notices re.compile(r'(?i)^musik\s*$'), # bare "Musik" annotation re.compile(r'(?i)^\(.*\)\s*$'), # parenthetical annotations like (Applaus) re.compile(r'(?i)^\[.*\]\s*$'), # bracketed annotations like [Musik] re.compile(r'(?i)^(background noise|static|silence|applause|laughter|noise)\s*$'), # English variants re.compile(r'^\s*\*\*[^*]+\*\*\s*$'), # double-asterisk: **Noise** ] _STT_GHOST_PHRASES = { "danke", "ja", "nein", "okay", "ok", "tschüss", "hallo", "bye", "mhm", "hmm", "aha", "oh", "ah", "ähm", "hm", "tschüss", "thanks", "thank you", "yes", "no", "bye bye", "hello", "hi", "bitte", "genau", "gut", "so", "na", "ne", "ach", "doch", "vielen dank", "alles klar", "schön", "super", "richtig", } def _is_stt_artifact(text: str) -> bool: """Check if text is an STT artifact (noise annotation, metadata leak, or ghost phrase).""" if _NOISE_ANNOTATION_RE.match(text): return True if any(p.match(text) for p in _STT_ARTIFACT_PATTERNS): return True # Short phantom transcriptions from ambient noise — ElevenLabs hallucinates # common German/English filler words when it hears background sounds words = text.split() if len(words) <= 2 and text.lower().strip().rstrip(".!?,") in _STT_GHOST_PHRASES: return True return False class _NoiseFilterAgent(Agent): """Agent that suppresses ElevenLabs STT artifacts before LLM sees them. Uses on_user_turn_completed() which runs after VAD+STT, so no backpressure risk to the audio pipeline. Raises StopResponse to silently discard noise. """ async def on_user_turn_completed( self, turn_ctx: llm.ChatContext, new_message: llm.ChatMessage ) -> None: text = (new_message.text_content or "").strip() if text and _is_stt_artifact(text): logger.info("STT artifact suppressed: %s", text) # Remove the artifact from context so it doesn't accumulate if turn_ctx.items and turn_ctx.items[-1] is new_message: turn_ctx.items.pop() raise StopResponse() _vad = None def _get_vad(): global _vad if _vad is None: _vad = silero.VAD.load( activation_threshold=0.65, min_speech_duration=0.4, min_silence_duration=0.55, ) return _vad def _make_lk_identity(user_id, device_id): return f"{user_id}:{device_id}" def _compute_lk_room_name(room_id): raw = f"{room_id}|m.call#ROOM" return base64.b64encode(hashlib.sha256(raw.encode()).digest()).decode().rstrip("=") def _generate_lk_jwt(room_id, user_id, device_id): identity = _make_lk_identity(user_id, device_id) lk_room = _compute_lk_room_name(room_id) token = ( lkapi.AccessToken(LK_API_KEY, LK_API_SECRET) .with_identity(identity) .with_name(user_id) .with_grants(lkapi.VideoGrants( room_join=True, room=lk_room, can_publish=True, can_subscribe=True)) .with_ttl(datetime.timedelta(hours=24)) ) logger.info("JWT: identity=%s room=%s", identity, lk_room) return token.to_jwt() KDF_HKDF = 1 # Rust FFI applies HKDF internally (proto enum value 1) # NOTE: value 0 in the proto is PBKDF2, NOT raw/none mode — see e2ee_patch.py def _hkdf_derive(ikm: bytes) -> bytes: """Pre-derive AES key via HKDF-SHA256 matching livekit-client-sdk-js deriveEncryptionKey(). JS params: hash=SHA-256, salt=encode("LKFrameEncryptionKey"), info=ArrayBuffer(128), length=128bit We set this pre-derived key via set_shared_key() which bypasses Rust FFI KDF entirely. """ import hmac salt = b"LKFrameEncryptionKey" info = b"\x00" * 128 prk = hmac.new(salt, ikm, hashlib.sha256).digest() t1 = hmac.new(prk, info + b"\x01", hashlib.sha256).digest() return t1[:16] def _ratchet_keys(base_raw: bytes, count: int = 6) -> dict[int, bytes]: """Pre-compute ratcheted keys 0..count-1 matching livekit-client-sdk-js ratchet(). EC JS ratchet: new_raw = HMAC(key=current_raw, data="LKFrameEncryptionKey")[:16] Returns {index: raw_key} for all indices 0..count-1. Set these via set_key(identity, raw, index) with KDF_HKDF=1 so Rust applies HKDF. """ import hmac as _hmac keys = {} raw = base_raw for i in range(count): keys[i] = raw raw = _hmac.new(raw, b"LKFrameEncryptionKey", hashlib.sha256).digest()[:16] return keys async def _brave_search(query: str, count: int = 5) -> str: """Call Brave Search API and return formatted results.""" if not BRAVE_API_KEY: return "Search unavailable (no API key configured)." try: async with httpx.AsyncClient(timeout=10.0) as client: resp = await client.get( "https://api.search.brave.com/res/v1/web/search", headers={"Accept": "application/json", "X-Subscription-Token": BRAVE_API_KEY}, params={"q": query, "count": count, "text_decorations": False}, ) resp.raise_for_status() data = resp.json() results = data.get("web", {}).get("results", []) if not results: return "No results found." lines = [] for r in results[:count]: lines.append(f"- {r.get('title', '')}: {r.get('description', '')} ({r.get('url', '')})") return "\n".join(lines) except Exception as exc: logger.warning("Brave search error: %s", exc) return f"Search failed: {exc}" async def _store_user_pref(user_id: str, key: str, value: str) -> None: """Store a user preference in memory (e.g. timezone, language).""" if not MEMORY_SERVICE_URL: return fact = f"[PREF:{key}] {value}" try: async with httpx.AsyncClient(timeout=10.0) as client: await client.post( f"{MEMORY_SERVICE_URL}/memories/store", json={"user_id": user_id, "fact": fact, "source_room": "preferences"}, ) logger.info("Preference stored for %s: %s=%s", user_id, key, value) except Exception as exc: logger.warning("Preference store failed: %s", exc) async def _store_voice_exchange(user_text: str, agent_text: str, user_id: str, room_id: str) -> None: """Store the full conversation exchange as memory (no LLM extraction).""" if not MEMORY_SERVICE_URL: return exchange = f"User: {user_text}\nAssistant: {agent_text}" try: async with httpx.AsyncClient(timeout=10.0) as client: await client.post( f"{MEMORY_SERVICE_URL}/memories/store", json={"user_id": user_id, "fact": exchange, "source_room": room_id}, ) logger.info("Memory stored for %s: %s", user_id, exchange[:120]) except Exception as exc: logger.warning("Voice memory store failed: %s", exc) async def _confluence_read_page(page_id: str) -> tuple[str, str, int]: """Read a Confluence page and return (title, plain_text, version_number).""" if not CONFLUENCE_URL or not CONFLUENCE_USER or not CONFLUENCE_TOKEN: raise RuntimeError("Confluence credentials not configured") url = f"{CONFLUENCE_URL}/rest/api/content/{page_id}" params = {"expand": "body.storage,version,title"} async with httpx.AsyncClient(timeout=15.0) as client: resp = await client.get( url, params=params, auth=(CONFLUENCE_USER, CONFLUENCE_TOKEN), ) resp.raise_for_status() data = resp.json() title = data.get("title", "") version = data.get("version", {}).get("number", 1) html = data.get("body", {}).get("storage", {}).get("value", "") # Strip HTML tags to plain text for voice readback plain = re.sub(r"<[^>]+>", " ", html) plain = re.sub(r"\s+", " ", plain).strip() return title, plain, version async def _confluence_update_section(page_id: str, section_heading: str, new_html: str) -> str: """Update a section of a Confluence page by heading. Finds the section by heading, replaces content up to next same-level heading, PUTs with incremented version. """ if not CONFLUENCE_URL or not CONFLUENCE_USER or not CONFLUENCE_TOKEN: return "Confluence credentials not configured." # Read current page url = f"{CONFLUENCE_URL}/rest/api/content/{page_id}" params = {"expand": "body.storage,version,title"} async with httpx.AsyncClient(timeout=15.0) as client: resp = await client.get(url, params=params, auth=(CONFLUENCE_USER, CONFLUENCE_TOKEN)) resp.raise_for_status() data = resp.json() title = data["title"] version = data["version"]["number"] body_html = data["body"]["storage"]["value"] # Find section by heading (h1-h6) and replace content up to next same-level heading heading_pattern = re.compile( r'(]*>.*?' + re.escape(section_heading) + r'.*?)', re.IGNORECASE | re.DOTALL, ) match = heading_pattern.search(body_html) if not match: return f"Section '{section_heading}' not found on page." heading_tag = match.group(0) heading_level = match.group(2) section_start = match.end() # Find next heading of same or higher level next_heading = re.compile( rf']*>', re.IGNORECASE, ) next_match = next_heading.search(body_html, section_start) section_end = next_match.start() if next_match else len(body_html) # Replace section content new_body = body_html[:section_start] + new_html + body_html[section_end:] # PUT updated page put_data = { "version": {"number": version + 1}, "title": title, "type": "page", "body": { "storage": { "value": new_body, "representation": "storage", } }, } async with httpx.AsyncClient(timeout=15.0) as client: resp = await client.put( url, json=put_data, auth=(CONFLUENCE_USER, CONFLUENCE_TOKEN), ) resp.raise_for_status() return f"Section '{section_heading}' updated successfully." def _build_e2ee_options() -> rtc.E2EEOptions: """Build E2EE options — let Rust FFI apply HKDF internally (KDF_HKDF=1). Pass raw base keys from Matrix key exchange events directly to set_key(). The Rust FFI derives the AES frame key via HKDF(base_key, ratchetSalt, ...) internally. Element Call uses: ratchetWindowSize=10, keyringSize=256, ratchetSalt="LKFrameEncryptionKey" NOTE: proto value 0 = PBKDF2 (not raw/none) — must use KDF_HKDF=1. """ key_opts = rtc.KeyProviderOptions( shared_key=b"", # empty = per-participant mode ratchet_window_size=10, ratchet_salt=b"LKFrameEncryptionKey", failure_tolerance=10, key_ring_size=256, key_derivation_function=KDF_HKDF, # Rust FFI applies HKDF; we pass raw base keys ) return rtc.E2EEOptions( encryption_type=rtc.EncryptionType.GCM, key_provider_options=key_opts, ) class VoiceSession: def __init__(self, nio_client, room_id, device_id, lk_url, model="claude-sonnet", publish_key_cb=None, bot_key: bytes | None = None, memory=None, caller_user_id: str | None = None, document_context: str | None = None): self.nio_client = nio_client self.room_id = room_id self.device_id = device_id self.lk_url = lk_url self.model = model self.lk_room = None self.session = None self._task = None self._http_session = None self._caller_key: bytes | None = None self._caller_identity: str | None = None self._caller_all_keys: dict = {} # {index: bytes} — all caller keys by index self._bot_key: bytes = bot_key or os.urandom(16) self._publish_key_cb = publish_key_cb self._memory = memory # MemoryClient instance from bot.py self._caller_user_id = caller_user_id # Matrix user ID for memory lookup self._document_context = document_context # PDF text from room for voice context self._transcript: list[dict] = [] # {"role": "user"|"assistant", "text": "..."} self._video_track: rtc.Track | None = None # remote video track for on-demand vision def on_encryption_key(self, sender, device_id, key, index): """Receive E2EE key from Element Call participant. Store-only: keys are applied in on_track_subscribed() / on_e2ee_state_changed() where the frame cryptor is guaranteed to exist. If the track is already subscribed (late key arrival / rotation), set the key immediately. """ if not key: return if not self._caller_key: self._caller_key = key self._caller_identity = f"{sender}:{device_id}" self._caller_all_keys[index] = key logger.info("E2EE key received from %s:%s (index=%d, %d bytes, raw=%s)", sender, device_id, index, len(key), key.hex()) # Late key arrival: if track already subscribed, frame cryptor exists — set key now. if self.lk_room and self._caller_identity: caller_lk_id = self._caller_identity for p in self.lk_room.remote_participants.values(): if p.identity == caller_lk_id: has_subscribed = any( pub.subscribed for pub in p.track_publications.values() ) if has_subscribed: try: kp = self.lk_room.e2ee_manager.key_provider ok = kp.set_key(p.identity, key, index) logger.info("Late key set_key[%d] for %s (ok=%s)", index, p.identity, ok) except Exception as e: logger.warning("Late key set_key failed: %s", e) break async def _fetch_encryption_key_http(self) -> bytes | None: """Fetch encryption key from room timeline (NOT state) via Matrix HTTP API. Element Call distributes encryption keys as timeline events, not state. """ import httpx homeserver = str(self.nio_client.homeserver) token = self.nio_client.access_token url = f"{homeserver}/_matrix/client/v3/rooms/{self.room_id}/messages" try: async with httpx.AsyncClient(timeout=10.0) as http: resp = await http.get( url, headers={"Authorization": f"Bearer {token}"}, params={"dir": "b", "limit": "50"}, ) resp.raise_for_status() data = resp.json() events = data.get("chunk", []) user_id = self.nio_client.user_id for evt in events: evt_type = evt.get("type", "") if evt_type == "io.element.call.encryption_keys": sender = evt.get("sender", "") if sender == user_id: continue # skip our own key content = evt.get("content", {}) device = content.get("device_id", "") logger.info("Found encryption_keys timeline event: sender=%s device=%s", sender, device) all_keys = {} import base64 as b64 for k in content.get("keys", []): key_b64 = k.get("key", "") key_index = k.get("index", 0) if key_b64: key_b64 += "=" * (-len(key_b64) % 4) key_bytes = b64.urlsafe_b64decode(key_b64) all_keys[key_index] = key_bytes if all_keys: if device: self._caller_identity = f"{sender}:{device}" self._caller_all_keys.update(all_keys) max_idx = max(all_keys.keys()) logger.info("Loaded caller keys at indices %s (using %d)", sorted(all_keys.keys()), max_idx) return all_keys[max_idx] logger.info("No encryption_keys events in last %d timeline events", len(events)) except Exception as e: logger.warning("HTTP encryption key fetch failed: %s", e) return None async def start(self): self._task = asyncio.create_task(self._run()) async def stop(self): for obj in [self.session, self.lk_room, self._http_session]: if obj: try: if hasattr(obj, "aclose"): await obj.aclose() elif hasattr(obj, "disconnect"): await obj.disconnect() elif hasattr(obj, "close"): await obj.close() except Exception: pass if self._task and not self._task.done(): self._task.cancel() try: await self._task except asyncio.CancelledError: pass def get_transcript(self) -> list[dict]: """Return the call transcript as a list of {role, text} dicts.""" return list(self._transcript) def get_document_context(self) -> str | None: """Return the document context loaded for this call, if any.""" return self._document_context def get_confluence_page_id(self) -> str | None: """Return the active Confluence page ID, if any.""" if not self._document_context: return None ids = re.findall(r'confluence_page_id:(\d+)', self._document_context) return ids[0] if ids else None async def _run(self): try: user_id = self.nio_client.user_id bot_identity = _make_lk_identity(user_id, self.device_id) jwt = _generate_lk_jwt(self.room_id, user_id, self.device_id) # Publish bot's own key immediately so Element Call can decrypt us if self._publish_key_cb: self._publish_key_cb(self._bot_key) logger.info("Published bot E2EE key (%d bytes)", len(self._bot_key)) # Check timeline for caller's encryption key caller_key = await self._fetch_encryption_key_http() if caller_key: self._caller_key = caller_key logger.info("Got caller E2EE key via timeline (%d bytes)", len(caller_key)) if not self._caller_key: # Wait up to 15s for key via sync handler logger.info("No key in timeline yet, waiting for sync...") for _ in range(150): if self._caller_key: break await asyncio.sleep(0.1) # E2EE: configurable via E2EE_ENABLED env var (default true). # When enabled, parameters MUST match Element Call JS SDK. e2ee_enabled = os.environ.get("E2EE_ENABLED", "true").lower() in ("true", "1", "yes") if e2ee_enabled: e2ee_opts = _build_e2ee_options() room_opts = rtc.RoomOptions(e2ee=e2ee_opts) logger.info("E2EE enabled (HKDF mode)") else: e2ee_opts = None room_opts = rtc.RoomOptions() logger.warning("E2EE DISABLED — audio is unencrypted") self.lk_room = rtc.Room() @self.lk_room.on("participant_connected") def on_p(p): logger.info("Participant connected: %s", p.identity) # Note: do NOT set keys here — frame cryptor not initialized yet at participant_connected. # Keys are set in on_track_subscribed where the frame cryptor definitely exists. @self.lk_room.on("track_published") def on_tp(pub, p): logger.info("Track pub: %s %s kind=%s", p.identity, pub.sid, pub.kind) @self.lk_room.on("track_muted") def on_mute(p, pub): logger.info("Track MUTED: %s %s kind=%s", p.identity, pub.sid, pub.kind) @self.lk_room.on("track_unmuted") def on_unmute(p, pub): logger.info("Track UNMUTED: %s %s kind=%s", p.identity, pub.sid, pub.kind) @self.lk_room.on("track_subscribed") def on_ts(t, pub, p): logger.info("Track sub: %s %s kind=%s muted=%s", p.identity, pub.sid, t.kind, pub.muted) # NOTE: Do NOT create rtc.AudioStream here — it competes with AgentSession's # internal audio pipeline for event loop time, causing intermittent VAD failures # (user_state stuck on "away"). See MAT-40. Use e2ee_state_changed for flow confirmation. # *** KEY FIX: set_key() with KDF_HKDF only applies HKDF when the frame cryptor # for this participant already exists. The frame cryptor is created at track # subscription time. Calling set_key() BEFORE track subscription (at connect) # skips HKDF derivation → raw key stored → DEC_FAILED. # Solution: set caller key HERE, after frame cryptor is initialized. # Store video track for on-demand vision (look_at_screen tool) if int(t.kind) == 0: # video track self._video_track = t logger.info("Video track stored from %s for on-demand vision", p.identity) if int(t.kind) == 1 and e2ee_opts is not None: # audio track only caller_id = p.identity logger.info("E2EE_DIAG: track_subscribed for %s, have %d caller keys", caller_id, len(self._caller_all_keys)) try: kp_local = self.lk_room.e2ee_manager.key_provider if self._caller_all_keys: for idx, base_k in sorted(self._caller_all_keys.items()): ok = kp_local.set_key(caller_id, base_k, idx) logger.info("on_ts: set_key[%d] for %s (ok=%s, %d bytes, raw=%s)", idx, caller_id, ok, len(base_k), base_k.hex()) else: logger.warning("on_ts: no caller keys yet — scheduling 0.5s retry") async def _brief_key_retry(pid=caller_id): await asyncio.sleep(0.5) if self._caller_all_keys: try: kp_r = self.lk_room.e2ee_manager.key_provider for idx, base_k in sorted(self._caller_all_keys.items()): ok = kp_r.set_key(pid, base_k, idx) logger.info("on_ts_retry: set_key[%d] for %s (ok=%s)", idx, pid, ok) except Exception as exc: logger.warning("on_ts_retry: set_key failed: %s", exc) else: logger.warning("on_ts_retry: still no caller keys for %s", pid) asyncio.ensure_future(_brief_key_retry()) except Exception as exc: logger.warning("on_ts: set_key failed: %s", exc) _e2ee_state_names = {0:"NEW",1:"OK",2:"ENC_FAILED",3:"DEC_FAILED",4:"MISSING_KEY",5:"RATCHETED",6:"INTERNAL_ERR"} @self.lk_room.on("e2ee_state_changed") def on_e2ee_state(participant, state): state_name = _e2ee_state_names.get(int(state), f"UNKNOWN_{state}") p_id = participant.identity if participant else "local" logger.info("E2EE_STATE: participant=%s state=%s", p_id, state_name) # When remote participant frame cryptor is NEW or MISSING_KEY → set their key if participant and p_id != bot_identity and int(state) in (0, 3, 4): if self._caller_all_keys: try: kp_e = self.lk_room.e2ee_manager.key_provider for idx, base_k in sorted(self._caller_all_keys.items()): ok = kp_e.set_key(p_id, base_k, idx) logger.info("e2ee_state set_key[%d] for %s (ok=%s)", idx, p_id, ok) except Exception as exc: logger.warning("e2ee_state set_key failed: %s", exc) await self.lk_room.connect(self.lk_url, jwt, options=room_opts) logger.info("Connected (E2EE=HKDF), remote=%d", len(self.lk_room.remote_participants)) # Set bot's own key immediately after connect — local frame cryptor exists at connect time. # CALLER keys are set in on_track_subscribed (NOT here) because the caller's frame cryptor # is only created when their track arrives. Calling set_key() before that skips HKDF. kp = self.lk_room.e2ee_manager.key_provider ok = kp.set_key(bot_identity, self._bot_key, 0) logger.info("Set bot key for %s (ok=%s, %d bytes)", bot_identity, ok, len(self._bot_key)) # Element Call rotates its key when bot joins. Wait up to 3s for the # rotated key to arrive via nio sync before proceeding. If it arrives, # on_encryption_key() stores it and (if track already subscribed) sets it. pre_key_count = len(self._caller_all_keys) pre_max_idx = max(self._caller_all_keys.keys()) if self._caller_all_keys else -1 logger.info("Waiting up to 3s for key rotation (current: %d keys, max_idx=%d)...", pre_key_count, pre_max_idx) for _wait in range(6): # 6 × 0.5s = 3s await asyncio.sleep(0.5) new_count = len(self._caller_all_keys) new_max = max(self._caller_all_keys.keys()) if self._caller_all_keys else -1 if new_max > pre_max_idx or new_count > pre_key_count: self._caller_key = self._caller_all_keys[new_max] logger.info("Key rotated: index %d→%d, count %d→%d", pre_max_idx, new_max, pre_key_count, new_count) break else: logger.info("No key rotation after 3s — proceeding with key[%d]", pre_max_idx) # Find the remote participant, wait up to 10s if not yet connected remote_identity = None for p in self.lk_room.remote_participants.values(): remote_identity = p.identity break if not remote_identity: logger.info("No remote participant yet, waiting...") for _ in range(100): await asyncio.sleep(0.1) for p in self.lk_room.remote_participants.values(): remote_identity = p.identity break if remote_identity: break # Set shared_key with pre-derived AES key for caller decryption. # NOT using set_key() for caller — Rust HKDF may produce different result than EC's JS HKDF. # set_shared_key() stores key raw (no KDF applied) — we pre-derive in Python. # After key rotation wait: if track already subscribed, set rotated key. # (Usually on_track_subscribed handles this, but if track arrived before rotation, # the rotated key needs to be set here for the already-subscribed participant.) if self._caller_all_keys and remote_identity: try: for idx, base_k in sorted(self._caller_all_keys.items()): ok = kp.set_key(remote_identity, base_k, idx) logger.info("Post-rotation set_key[%d] for %s (ok=%s)", idx, remote_identity, ok) except Exception as e: logger.warning("Post-rotation set_key failed: %s", e) elif not self._caller_all_keys: logger.warning("No caller E2EE keys received — incoming audio will be silence") if remote_identity: logger.info("Linking to remote participant: %s", remote_identity) # Load memories and user preferences for this caller memory_section = "" user_timezone = None if self._memory and self._caller_user_id: try: mems = await self._memory.query(self._caller_user_id, "voice call", top_k=10) if mems: conversations = [] for m in mems: fact = m['fact'] # Extract timezone preference from stored memories if fact.startswith("[PREF:timezone]"): user_timezone = fact.split("]", 1)[1].strip() else: conversations.append(fact) if conversations: memory_section = "\n\nFrühere Gespräche mit diesem Nutzer:\n" + \ "\n---\n".join(conversations) logger.info("Loaded %d memories for %s (tz=%s)", len(mems), self._caller_user_id, user_timezone) except Exception as exc: logger.warning("Memory query failed: %s", exc) # Also query specifically for timezone preference if not found above if not user_timezone and self._memory and self._caller_user_id: try: tz_mems = await self._memory.query( self._caller_user_id, "timezone preference", top_k=3) for m in (tz_mems or []): if m['fact'].startswith("[PREF:timezone]"): user_timezone = m['fact'].split("]", 1)[1].strip() break except Exception: pass # Voice pipeline — Jack Marlowe (native German male) self._http_session = aiohttp.ClientSession() voice_id = os.environ.get("ELEVENLABS_VOICE_ID", DEFAULT_VOICE_ID) self.session = AgentSession( stt=elevenlabs.STT( api_key=ELEVENLABS_KEY, model_id="scribe_v2_realtime", language_code=os.environ.get("STT_LANGUAGE", "de"), http_session=self._http_session, ), llm=lk_openai.LLM(base_url=LITELLM_URL, api_key=LITELLM_KEY, model=self.model), tts=elevenlabs.TTS( voice_id=voice_id, model="eleven_multilingual_v2", language="de", api_key=ELEVENLABS_KEY, voice_settings=elevenlabs.VoiceSettings( stability=0.5, similarity_boost=0.75, speed=1.15, ), http_session=self._http_session, ), vad=_get_vad(), ) # Pipeline event logging (livekit-agents 1.4.2 event names) _vad_state_log: dict = {"last": None, "speaking_count": 0, "away_since": None} @self.session.on("user_state_changed") def _on_user_state(ev): state = ev.new_state prev = _vad_state_log["last"] _vad_state_log["last"] = state if str(state) == "speaking": _vad_state_log["speaking_count"] = _vad_state_log.get("speaking_count", 0) + 1 _vad_state_log["away_since"] = None logger.info("VAD: user_state=%s (speaking_count=%d)", state, _vad_state_log["speaking_count"]) elif str(state) == "away" and prev and str(prev) != "away": import time _vad_state_log["away_since"] = time.monotonic() logger.info("VAD: user_state=%s (was %s)", state, prev) else: logger.info("VAD: user_state=%s", state) _last_user_speech: list[str] = [] @self.session.on("user_input_transcribed") def _on_user_speech(ev): text = ev.transcript or "" if text and _is_stt_artifact(text): logger.warning("NOISE_LEAK: artifact reached STT: %s", text) else: logger.info("USER_SPEECH: %s", text) if ev.transcript: _last_user_speech.append(ev.transcript) self._transcript.append({"role": "user", "text": ev.transcript}) @self.session.on("conversation_item_added") def _on_conversation_item(ev): role = getattr(ev.item, "role", "?") text = getattr(ev.item, "text_content", "") or "" if role == "assistant" and text: logger.info("AGENT_SPEECH: %s", text) self._transcript.append({"role": "assistant", "text": text}) if self._memory and self._caller_user_id and _last_user_speech: user_text = " ".join(_last_user_speech) _last_user_speech.clear() asyncio.ensure_future( _store_voice_exchange(user_text, text, self._caller_user_id, self.room_id)) # Brave Search tool — lets the agent answer questions about current events @function_tool async def search_web(query: str) -> str: """Search the web for current information using Brave Search. Use this when asked about recent news, current events, prices, weather, or any information that may have changed recently. """ logger.info("SEARCH: %s", query) result = await _brave_search(query) logger.info("SEARCH_RESULT: %s", result[:200]) return result # Tool: set user timezone — called by the LLM when user mentions their location caller_uid = self._caller_user_id @function_tool async def set_user_timezone(iana_timezone: str) -> str: """Store the user's timezone. Call this when the user mentions their city or timezone (e.g. 'I'm in Nicosia' → 'Europe/Nicosia', 'I live in New York' → 'America/New_York'). Use IANA timezone names like Europe/Berlin, America/New_York, Asia/Tokyo. """ if caller_uid: await _store_user_pref(caller_uid, "timezone", iana_timezone) return f"Timezone set to {iana_timezone}" # Extract active Confluence page ID from document context (if any) _active_conf_id = None if self._document_context: _conf_ids = re.findall(r'confluence_page_id:(\d+)', self._document_context) if _conf_ids: _active_conf_id = _conf_ids[0] @function_tool async def read_confluence_page(page_id: str = "") -> str: """Read a Confluence page. Use when user asks to read, review, or check a document. Returns page title and content as text. Leave page_id empty to use the active document from the room.""" pid = page_id or _active_conf_id if not pid: return "No Confluence page ID available. Ask the user to share a Confluence link first." logger.info("CONFLUENCE_READ: page_id=%s", pid) try: title, text, _ver = await _confluence_read_page(pid) result = f"Page: {title}\n\n{text}" logger.info("CONFLUENCE_READ_OK: %s (%d chars)", title, len(text)) return result except Exception as exc: logger.warning("CONFLUENCE_READ_FAIL: %s", exc) return f"Failed to read page: {exc}" @function_tool async def update_confluence_page(section_heading: str, new_content: str, page_id: str = "") -> str: """Update a section of a Confluence page. Use when user asks to change, update, or rewrite part of a document. - section_heading: heading text of the section to update - new_content: new plain text for the section (will be wrapped in

tags) - page_id: leave empty to use the active document from the room Human sees changes instantly in their browser via Live Docs.""" pid = page_id or _active_conf_id if not pid: return "No Confluence page ID available. Ask the user to share a Confluence link first." logger.info("CONFLUENCE_UPDATE: page=%s section='%s'", pid, section_heading) try: new_html = f"

{new_content}

" result = await _confluence_update_section(pid, section_heading, new_html) logger.info("CONFLUENCE_UPDATE_OK: %s", result) return result except Exception as exc: logger.warning("CONFLUENCE_UPDATE_FAIL: %s", exc) return f"Failed to update page: {exc}" # Deep thinking tool — escalates to Opus for complex questions _transcript_ref = self._transcript _doc_context_ref = self._document_context @function_tool async def think_deeper(question: str) -> str: """Denke intensiver ueber eine komplexe Frage nach mit einem staerkeren Modell. Nutze dieses Tool wenn: - Der Nutzer sagt "denk genauer nach", "think harder", "nimm opus", "use opus", "ueberleg nochmal", "analysier das genauer", "bist du dir sicher", "are you sure", "stimmt das wirklich", "check nochmal", "pruef das nochmal" - Du dir bei einer komplexen Analyse, Code-Review oder Dokumentinterpretation unsicher bist - Der Nutzer deine letzte Antwort anzweifelt oder eine Gegenprüfung wuenscht - Eine Frage mehrere Schritte logisches Denken erfordert Beschreibe die Frage so praezise wie moeglich — der Kontext (Transkript + Dokument) wird automatisch mitgeliefert.""" # Build context: recent transcript + document context_parts = [] if _doc_context_ref: context_parts.append(f"Dokument-Kontext:\n{_doc_context_ref[:12000]}") recent = _transcript_ref[-10:] if _transcript_ref else [] if recent: lines = [] for e in recent: role = "Nutzer" if e["role"] == "user" else "Assistent" lines.append(f"{role}: {e['text']}") context_parts.append(f"Gespraechsverlauf:\n" + "\n".join(lines)) context_parts.append(f"Frage: {question}") full_prompt = "\n\n---\n\n".join(context_parts) logger.info("THINK_DEEPER: %s (context=%d chars)", question[:100], len(full_prompt)) try: async with httpx.AsyncClient(timeout=60.0) as client: resp = await client.post( f"{LITELLM_URL}/chat/completions", headers={"Authorization": f"Bearer {LITELLM_KEY}"}, json={ "model": "claude-opus", "messages": [ {"role": "system", "content": ( "Du bist ein Experte fuer tiefgehende Analyse. " "Beantworte die Frage praezise und ausfuehrlich basierend auf dem Kontext. " "Antworte in der Sprache der Frage." )}, {"role": "user", "content": full_prompt}, ], "max_tokens": 1500, }, ) resp.raise_for_status() data = resp.json() answer = data["choices"][0]["message"]["content"] logger.info("THINK_DEEPER_OK: %s", answer[:200]) return answer except Exception as exc: logger.warning("THINK_DEEPER_FAIL: %s", exc) return f"Tiefere Analyse fehlgeschlagen: {exc}" # Vision tool — capture video frame and analyze with vision model _video_track_ref = self # reference to VoiceSession for video track access _lk_room_ref = self.lk_room @function_tool async def look_at_screen(question: str) -> str: """Schau dir an was der Nutzer auf dem Bildschirm oder per Kamera zeigt. Nutze dieses Tool wenn: - Der Nutzer sagt "schau mal", "siehst du das", "was siehst du", "look at this", "can you see", "zeig dir was", "schau auf meinen Bildschirm", "kannst du das sehen" - Der Nutzer seinen Bildschirm teilt und eine Frage dazu stellt - Der Nutzer seine Kamera aktiviert hat und etwas zeigen moechte Beschreibe was du sehen moechtest oder stelle eine Frage zum Bild.""" video_track = _video_track_ref._video_track if not video_track: return ("Kein Video verfuegbar. Der Nutzer muss seine Kamera oder " "Bildschirmfreigabe aktivieren bevor ich etwas sehen kann.") try: # Capture single frame from video track stream = rtc.VideoStream(video_track) frame = None async for f in stream: frame = f break try: await stream.aclose() except Exception: pass if frame is None: return "Konnte kein Bild aufnehmen — kein Frame verfuegbar." # Handle both VideoFrameEvent (.frame) and direct VideoFrame vf = getattr(frame, 'frame', frame) # Convert to RGBA and encode as JPEG rgba = vf.convert(rtc.VideoBufferType.RGBA) from PIL import Image import io img = Image.frombytes("RGBA", (rgba.width, rgba.height), bytes(rgba.data)) buf = io.BytesIO() img.convert("RGB").save(buf, format="JPEG", quality=85) img_b64 = base64.b64encode(buf.getvalue()).decode() logger.info("LOOK_AT_SCREEN: captured %dx%d frame (%d KB JPEG)", rgba.width, rgba.height, len(buf.getvalue()) // 1024) # Build context: transcript + document + question context_parts = [] if _doc_context_ref: context_parts.append(f"Dokument-Kontext:\n{_doc_context_ref[:8000]}") recent = _transcript_ref[-10:] if _transcript_ref else [] if recent: lines = [f"{'Nutzer' if e['role'] == 'user' else 'Assistent'}: {e['text']}" for e in recent] context_parts.append("Gespraechsverlauf:\n" + "\n".join(lines)) context_parts.append(f"Frage zum Bild: {question}") text_prompt = "\n\n---\n\n".join(context_parts) # Send to vision model via LiteLLM (OpenAI-compatible multimodal format) async with httpx.AsyncClient(timeout=30.0) as client: resp = await client.post( f"{LITELLM_URL}/chat/completions", headers={"Authorization": f"Bearer {LITELLM_KEY}"}, json={ "model": "claude-sonnet", "messages": [ {"role": "system", "content": ( "Du analysierst Bilder von Bildschirm oder Kamera eines Nutzers. " "Antworte praezise und hilfreich in der Sprache der Frage. " "Beschreibe was du siehst und beantworte die Frage des Nutzers." )}, {"role": "user", "content": [ {"type": "image_url", "image_url": { "url": f"data:image/jpeg;base64,{img_b64}"}}, {"type": "text", "text": text_prompt}, ]}, ], "max_tokens": 1500, }, ) resp.raise_for_status() data = resp.json() answer = data["choices"][0]["message"]["content"] logger.info("LOOK_AT_SCREEN_OK: %s", answer[:200]) return answer except asyncio.TimeoutError: return "Konnte kein Bild aufnehmen — Timeout. Ist die Kamera/Bildschirmfreigabe aktiv?" except Exception as exc: logger.warning("LOOK_AT_SCREEN_FAIL: %s", exc) return f"Bildanalyse fehlgeschlagen: {exc}" instructions = _build_voice_prompt(model=self.model, timezone=user_timezone) + memory_section if self._document_context: instructions += f"\n\nDokument-Kontext (im Raum hochgeladen):\n{self._document_context}" if _active_conf_id: instructions += f"\n\nAktive Confluence-Seite: {_active_conf_id}. Du brauchst den Nutzer NICHT nach der page_id zu fragen — nutze automatisch diese ID fuer read_confluence_page und update_confluence_page." agent = _NoiseFilterAgent( instructions=instructions, tools=[search_web, set_user_timezone, read_confluence_page, update_confluence_page, think_deeper, look_at_screen], ) io_opts = room_io.RoomOptions( participant_identity=remote_identity, close_on_disconnect=False, ) if remote_identity else room_io.RoomOptions(close_on_disconnect=False) await self.session.start( agent=agent, room=self.lk_room, room_options=io_opts, ) logger.info("Voice pipeline started (voice=%s, linked_to=%s)", voice_id, remote_identity) try: await asyncio.wait_for( self.session.generate_reply( instructions="Sage nur: Hallo, wie kann ich helfen?"), timeout=30.0) logger.info("Greeting sent") except asyncio.TimeoutError: logger.error("Greeting timed out") # VAD watchdog: log diagnostic and attempt E2EE key recovery if stuck import time as _time while True: await asyncio.sleep(10) away_since = _vad_state_log.get("away_since") if away_since and (_time.monotonic() - away_since) > 30: sc = _vad_state_log.get("speaking_count", 0) e2ee_ok = any( str(getattr(p, '_e2ee_state', '')) == 'OK' for p in self.lk_room.remote_participants.values() ) if self.lk_room else False n_remote = len(self.lk_room.remote_participants) if self.lk_room else 0 logger.warning( "VAD_WATCHDOG: user_state=away for >30s (speaking_count=%d, " "remote_participants=%d, e2ee_ok=%s) — attempting E2EE key recovery", sc, n_remote, e2ee_ok, ) # Recovery: re-apply all stored E2EE keys for all remote participants if self.lk_room and self._caller_all_keys: try: kp_w = self.lk_room.e2ee_manager.key_provider for p in self.lk_room.remote_participants.values(): for idx, base_k in sorted(self._caller_all_keys.items()): ok = kp_w.set_key(p.identity, base_k, idx) logger.info("VAD_WATCHDOG: recovery set_key[%d] for %s (ok=%s)", idx, p.identity, ok) except Exception as exc: logger.warning("VAD_WATCHDOG: recovery set_key failed: %s", exc) _vad_state_log["away_since"] = None # only warn once per stuck period except asyncio.CancelledError: logger.info("Session cancelled for %s", self.room_id) except Exception: logger.exception("Session failed for %s", self.room_id)