fix(deps): pin livekit family to versions matching EC-compat fork proto schema

Newer livekit-rtc releases added a ParticipantState symbol to
participant_pb2 that the EC-compat Rust fork (onestacked/livekit-rust-sdks
branch EC-compat-changes, PR #904) doesnt regenerate. The Dockerfile
overwrites the pip-installed protos with the forks regen output, so
patch_sdk.py crashed on "import livekit.rtc" with:
  ImportError: cannot import name ParticipantState from livekit.rtc._proto.participant_pb2

Pinned to the versions running in the last successful image (build of
2026-04-03):
  livekit==1.1.3 livekit-api==1.1.0 livekit-agents==1.5.1
  livekit-plugins-{openai,elevenlabs,silero}==1.5.1

Build verified locally: docker compose build bot exits 0; patch_sdk
applies cleanly; bot starts, syncs, /health returns ok.

.gitea/workflows/deploy.yml

@@ -19,6 +19,13 @@ jobs:
       - name: Install dependencies
         run: pip install -r requirements.txt -r requirements-test.txt
       - name: Run tests
+        env:
+          MATRIX_HOMESERVER: https://test.local
+          MATRIX_BOT_USER: "@test:test.local"
+          MATRIX_BOT_PASSWORD: test
+          LIVEKIT_URL: wss://test.local
+          LIVEKIT_API_KEY: test
+          LIVEKIT_API_SECRET: test
         run: pytest tests/ -v --cov=device_trust --cov-report=term
   build-and-deploy:
     needs: [test]

.gitea/workflows/test.yml

@@ -17,5 +17,12 @@ jobs:
         run: |
           pip install -r requirements.txt -r requirements-test.txt
       - name: Run tests
+        env:
+          MATRIX_HOMESERVER: https://test.local
+          MATRIX_BOT_USER: "@test:test.local"
+          MATRIX_BOT_PASSWORD: test
+          LIVEKIT_URL: wss://test.local
+          LIVEKIT_API_KEY: test
+          LIVEKIT_API_SECRET: test
         run: |
           pytest tests/ -v --cov=device_trust --cov-report=term

article_summary/__init__.py

@@ -28,6 +28,16 @@ _DISCUSS_KW = {"discuss", "diskutieren", "besprechen", "reden", "talk", "chat"}
 _TEXT_KW = {"text", "zusammenfassung", "summary", "lesen", "read", "schriftlich", "written"}
 _AUDIO_KW = {"audio", "mp3", "anhören", "vorlesen", "hören", "listen", "blinkist", "abspielen", "podcast"}
 
+# Words that signal the user actually wants the article-summary FSM to engage.
+# Without one of these, a pasted URL is left alone (chat-as-usual).
+# Union of discuss/text/audio keywords + explicit summary asks.
+_INTENT_KW = (
+    _DISCUSS_KW | _TEXT_KW | _AUDIO_KW |
+    {"tldr", "tl;dr", "fasse zusammen", "fass zusammen", "zusammenfassen",
+     "summarise", "summarize", "worum geht", "was steht", "what does it say",
+     "kannst du das lesen", "lies das", "lies mir", "read this", "read it"}
+)
+
 # Simple German detection: common words that appear frequently in German text
 _DE_INDICATORS = {"der", "die", "das", "und", "ist", "ein", "eine", "für", "mit", "auf", "den", "dem", "sich", "nicht", "von", "wird", "auch", "nach", "wie", "aber"}
 
@@ -160,13 +170,21 @@ class ArticleSummaryHandler:
     async def _check_for_url(
         self, room_id: str, sender: str, body: str
     ) -> str | None:
-        """Check if message contains an article URL."""
+        """Check if message contains an article URL AND explicit summary intent."""
         urls = URL_PATTERN.findall(body)
         # Filter to article-like URLs
         article_urls = [u for u in urls if is_article_url(u)]
         if not article_urls:
             return None
 
+        # Only engage the FSM if the user explicitly asked for a summary /
+        # discussion / audio. Otherwise a pasted URL is just context for normal
+        # chat and we shouldn't burn a Firecrawl + LLM topic-detection call,
+        # nor interrupt with the 3-option menu.
+        body_lower = body.lower()
+        if not any(kw in body_lower for kw in _INTENT_KW):
+            return None
+
         url = article_urls[0]
         session = self.sessions.get(sender, room_id)
 

bot.py

@@ -3217,11 +3217,12 @@ class Bot:
 
         try:
             reply = ""
+            last_sent_text = ""
             streamed_event_id: str | None = None  # set when streaming has already posted a message in Matrix
 
             # Agentic tool-calling loop: iterate up to MAX_TOOL_ITERATIONS
             for iteration in range(MAX_TOOL_ITERATIONS):
-                content, tool_calls, usage, streamed_event_id = await self._stream_chat_completion(
+                content, tool_calls, usage, streamed_event_id, last_sent_text = await self._stream_chat_completion(
                     room_id=room.room_id,
                     model=model,
                     messages=messages,
@@ -3242,6 +3243,12 @@ class Bot:
                     },
                 )
 
+                # Empty response with no tool calls — retry once with escalation model
+                if not content and not tool_calls and model != ESCALATION_MODEL:
+                    logger.warning("[empty-response] %s returned nothing, retrying with %s", model, ESCALATION_MODEL)
+                    model = ESCALATION_MODEL
+                    continue
+
                 if not tool_calls:
                     # No tool calls — final text response
                     break
@@ -3276,12 +3283,37 @@ class Bot:
             if iteration > 0:
                 sentry_sdk.set_tag("used_tools", "true")
 
-            # Send / finalize reply. If we streamed, just do a final edit so the
-            # Matrix message reflects the complete text (otherwise progressive
-            # throttling may have stopped short of the last tokens).
+            # If the loop exhausted MAX_TOOL_ITERATIONS while the model was still
+            # requesting tools, `reply` is empty and tool results sit unsummarized
+            # in `messages`. Force one final text-only turn so the user sees a
+            # synthesis instead of the dangling preamble we already streamed.
+            if not reply and tool_calls:
+                logger.info(
+                    "[stream] hit MAX_TOOL_ITERATIONS=%d still requesting tools; forcing final summary",
+                    MAX_TOOL_ITERATIONS,
+                )
+                try:
+                    final_resp = await self.llm.chat.completions.create(
+                        model=model,
+                        messages=messages + [{
+                            "role": "user",
+                            "content": "Bitte fasse jetzt deine Recherche zusammen — keine weiteren Tool-Aufrufe.",
+                        }],
+                        max_tokens=2048,
+                        tools=None,
+                    )
+                    reply = (final_resp.choices[0].message.content or "").strip()
+                except Exception:
+                    logger.warning("[stream] forced final-summary call failed", exc_info=True)
+                    reply = "_(Recherche lief in Tool-Schleife — bitte gezielter nachfragen.)_"
+
+            # Send / finalize reply. If we streamed, do a final edit only if
+            # the complete text differs from what was last sent (avoids the
+            # "(bearbeitet)" / "(edited)" indicator for unchanged messages).
             if reply:
                 if streamed_event_id:
-                    await self._send_stream_edit(room.room_id, streamed_event_id, reply, final=True)
+                    if reply != last_sent_text:
+                        await self._send_stream_edit(room.room_id, streamed_event_id, reply, final=True)
                 else:
                     await self._send_text(room.room_id, reply)
 
@@ -3728,24 +3760,28 @@ class Bot:
         messages: list[dict],
         tools: list | None,
         prior_event_id: str | None = None,
-    ) -> tuple[str, list[dict] | None, dict | None, str | None]:
+    ) -> tuple[str, list[dict] | None, dict | None, str | None, str]:
         """Stream one chat completion turn.
 
         Progressively edits a Matrix message as content tokens arrive (unless
         tool_calls have started — those suppress visible streaming until the
         model settles on plain text on a later iteration).
 
-        Returns (content, tool_calls or None, usage dict or None, event_id).
+        Returns (content, tool_calls or None, usage dict or None, event_id, last_sent_text).
         `event_id` is the Matrix event we've been streaming into, or None if
         we didn't (yet) post a visible message this turn.
+        `last_sent_text` is the text last sent/edited to Matrix (for dedup).
         """
         content_parts: list[str] = []
         tool_calls_acc: dict[int, dict] = {}
         usage: dict | None = None
         event_id = prior_event_id
         last_edit = 0.0
+        last_sent_text: str = ""  # track what was last sent to Matrix to avoid redundant edits
+        first_content_time: float = 0.0  # monotonic time of first content delta
         EDIT_THROTTLE = 0.6  # seconds — keep Matrix edit traffic reasonable
         MIN_CHARS_BEFORE_POST = 20  # avoid posting a single character first
+        TOOL_GRACE_SECONDS = 1.2  # buffer initial content this long; tool_calls deltas usually arrive within ~500ms
 
         try:
             stream = await self.llm.chat.completions.create(
@@ -3773,7 +3809,7 @@ class Bot:
                     "prompt_tokens": getattr(resp.usage, "prompt_tokens", 0),
                     "completion_tokens": getattr(resp.usage, "completion_tokens", 0),
                 }
-            return choice.message.content or "", tc_list, u, event_id
+            return choice.message.content or "", tc_list, u, event_id, ""
 
         async for chunk in stream:
             if not chunk.choices:
@@ -3806,13 +3842,20 @@ class Bot:
                 # Suppress visible streaming once we know this turn will end in tool calls
                 if not tool_calls_acc:
                     now = time.monotonic()
-                    if now - last_edit >= EDIT_THROTTLE:
+                    if first_content_time == 0.0:
+                        first_content_time = now
+                    # Grace period: hold first post long enough for tool_calls deltas
+                    # to start arriving, so we never leak a "Gute Frage — lass mich…"
+                    # preamble that the model intends to follow with tool calls.
+                    grace_passed = (event_id is not None) or (now - first_content_time >= TOOL_GRACE_SECONDS)
+                    if grace_passed and now - last_edit >= EDIT_THROTTLE:
                         text_so_far = "".join(content_parts)
                         if len(text_so_far) >= MIN_CHARS_BEFORE_POST:
                             if event_id is None:
                                 event_id = await self._send_stream_start(room_id, text_so_far)
                             else:
                                 await self._send_stream_edit(room_id, event_id, text_so_far)
+                            last_sent_text = text_so_far
                             last_edit = now
 
             # Some providers attach usage to the last choice chunk
@@ -3874,7 +3917,7 @@ class Bot:
             "[stream] model=%s chars=%d tool_calls=%d streamed_to_matrix=%s",
             model, len(content), len(tc_list or []), event_id is not None,
         )
-        return content, tc_list, usage, event_id
+        return content, tc_list, usage, event_id, last_sent_text
 
     async def _get_call_encryption_key(self, room_id: str, sender: str, caller_device_id: str = "") -> bytes | None:
         """Read E2EE encryption key from call.member state (MSC4143) or timeline (legacy).

cron/browser_executor.py

@@ -1,192 +0,0 @@
-"""Browser scrape executor — dispatches jobs to Skyvern API."""
-
-import asyncio
-import json
-import logging
-import os
-
-import httpx
-
-logger = logging.getLogger(__name__)
-
-SKYVERN_BASE_URL = os.environ.get("SKYVERN_BASE_URL", "http://skyvern:8000")
-SKYVERN_API_KEY = os.environ.get("SKYVERN_API_KEY", "")
-
-POLL_INTERVAL = 5  # seconds
-MAX_POLL_TIME = 300  # 5 minutes
-
-
-async def _create_task(url: str, goal: str, extraction_goal: str = "",
-                       extraction_schema: dict | None = None,
-                       credential_id: str | None = None, totp_identifier: str | None = None) -> str:
-    """Create a Skyvern task and return the task_id."""
-    payload: dict = {
-        "url": url,
-        "navigation_goal": goal,
-        "data_extraction_goal": extraction_goal or goal,
-    }
-    if extraction_schema:
-        payload["extracted_information_schema"] = extraction_schema
-    if credential_id:
-        payload["credential_id"] = credential_id
-    if totp_identifier:
-        payload["totp_identifier"] = totp_identifier
-
-    async with httpx.AsyncClient(timeout=60.0) as client:
-        resp = await client.post(
-            f"{SKYVERN_BASE_URL}/api/v1/tasks",
-            headers={
-                "Content-Type": "application/json",
-                "x-api-key": SKYVERN_API_KEY,
-            },
-            json=payload,
-        )
-        resp.raise_for_status()
-        data = resp.json()
-    return data["task_id"]
-
-
-async def _poll_task(run_id: str) -> dict:
-    """Poll Skyvern until task completes or times out."""
-    elapsed = 0
-    async with httpx.AsyncClient(timeout=60.0) as client:
-        while elapsed < MAX_POLL_TIME:
-            resp = await client.get(
-                f"{SKYVERN_BASE_URL}/api/v1/tasks/{run_id}",
-                headers={"x-api-key": SKYVERN_API_KEY},
-            )
-            resp.raise_for_status()
-            data = resp.json()
-            status = data.get("status", "")
-
-            if status in ("completed", "failed", "terminated", "timed_out"):
-                return data
-
-            await asyncio.sleep(POLL_INTERVAL)
-            elapsed += POLL_INTERVAL
-
-    return {"status": "timed_out", "error": f"Polling exceeded {MAX_POLL_TIME}s"}
-
-
-def _format_extraction(data: dict) -> str:
-    """Format extracted data as readable markdown for Matrix."""
-    extracted = data.get("extracted_information") or data.get("extracted_data")
-    if not extracted:
-        return "No data extracted."
-
-    # Handle list of items (most common: news, listings, results)
-    items = None
-    if isinstance(extracted, list):
-        items = extracted
-    elif isinstance(extracted, dict):
-        # Look for the first list value in the dict (e.g. {"news": [...]})
-        for v in extracted.values():
-            if isinstance(v, list) and v:
-                items = v
-                break
-
-    if items and isinstance(items[0], dict):
-        lines = []
-        for item in items:
-            # Try common field names for title/link
-            title = item.get("title") or item.get("name") or item.get("headline") or ""
-            link = item.get("link") or item.get("url") or item.get("href") or ""
-            # Build a line with remaining fields as details
-            skip = {"title", "name", "headline", "link", "url", "href"}
-            details = " · ".join(
-                str(v) for k, v in item.items()
-                if k not in skip and v
-            )
-            if title and link:
-                line = f"- [{title}]({link})"
-            elif title:
-                line = f"- {title}"
-            else:
-                line = f"- {json.dumps(item, ensure_ascii=False)}"
-            if details:
-                line += f"  \n  {details}"
-            lines.append(line)
-        return "\n".join(lines)
-
-    # Fallback: compact JSON
-    if isinstance(extracted, (dict, list)):
-        return json.dumps(extracted, indent=2, ensure_ascii=False)
-    return str(extracted)
-
-
-async def execute_browser_scrape(job: dict, send_text, **_kwargs) -> dict:
-    """Execute a browser-based scraping job via Skyvern."""
-    target_room = job["targetRoom"]
-    config = job.get("config", {})
-    url = config.get("url", "")
-    goal = config.get("goal", config.get("query", f"Scrape content from {url}"))
-    extraction_goal = config.get("extractionGoal", "") or goal
-    extraction_schema = config.get("extractionSchema")
-    browser_profile = job.get("browserProfile")
-
-    if not url:
-        await send_text(target_room, f"**{job['name']}**: No URL configured.")
-        return {"status": "error", "error": "No URL configured"}
-
-    if not SKYVERN_API_KEY:
-        await send_text(
-            target_room,
-            f"**{job['name']}**: Browser automation not configured (missing API key).",
-        )
-        return {"status": "error", "error": "SKYVERN_API_KEY not set"}
-
-    # Map browser profile fields to Skyvern credential
-    credential_id = None
-    totp_identifier = None
-    if browser_profile:
-        if browser_profile.get("status") == "expired":
-            await send_text(
-                target_room,
-                f"**{job['name']}**: Browser credential expired. "
-                f"Update at https://matrixhost.eu/settings/automations",
-            )
-            return {"status": "error", "error": "Browser credential expired"}
-        credential_id = browser_profile.get("credentialId")
-        totp_identifier = browser_profile.get("totpIdentifier")
-
-    try:
-        run_id = await _create_task(
-            url=url,
-            goal=goal,
-            extraction_goal=extraction_goal,
-            extraction_schema=extraction_schema,
-            credential_id=credential_id,
-            totp_identifier=totp_identifier,
-        )
-        logger.info("Skyvern task created: %s for job %s", run_id, job["name"])
-
-        result = await _poll_task(run_id)
-        status = result.get("status", "unknown")
-
-        if status == "completed":
-            extracted = _format_extraction(result)
-            msg = f"**{job['name']}** — {url}\n\n{extracted}"
-            # Truncate if too long for Matrix
-            if len(msg) > 4000:
-                msg = msg[:3950] + "\n\n_(truncated)_"
-            await send_text(target_room, msg)
-            return {"status": "success"}
-        else:
-            error = result.get("error") or result.get("failure_reason") or status
-            await send_text(
-                target_room,
-                f"**{job['name']}**: Browser task {status} — {error}",
-            )
-            return {"status": "error", "error": str(error)}
-
-    except httpx.HTTPStatusError as exc:
-        error_msg = f"Skyvern API error: {exc.response.status_code}"
-        logger.error("Browser executor failed: %s", error_msg, exc_info=True)
-        await send_text(target_room, f"**{job['name']}**: {error_msg}")
-        return {"status": "error", "error": error_msg}
-
-    except Exception as exc:
-        error_msg = str(exc)
-        logger.error("Browser executor failed: %s", error_msg, exc_info=True)
-        await send_text(target_room, f"**{job['name']}**: Browser task failed — {error_msg}")
-        return {"status": "error", "error": error_msg}

cron/executor.py

@@ -3,14 +3,12 @@
 import logging
 
 from .brave_search import execute_brave_search
-from .browser_executor import execute_browser_scrape
 from .reminder import execute_reminder
 
 logger = logging.getLogger(__name__)
 
 EXECUTORS = {
     "brave_search": execute_brave_search,
-    "browser_scrape": execute_browser_scrape,
     "reminder": execute_reminder,
 }
 

docker-compose.yml

@@ -25,8 +25,6 @@ services:
       - MEMORY_SERVICE_TOKEN
       - PORTAL_URL
       - BOT_API_KEY
-      - SKYVERN_BASE_URL=http://skyvern:8000
-      - SKYVERN_API_KEY
     ports:
       - "9100:9100"
     volumes:
@@ -38,6 +36,7 @@ services:
       - ./e2ee_patch.py:/app/e2ee_patch.py:ro
       - ./cross_signing.py:/app/cross_signing.py:ro
       - ./device_trust.py:/app/device_trust.py:ro
+      - ./article_summary:/app/article_summary:ro
     depends_on:
       memory-service:
         condition: service_healthy
@@ -84,54 +83,6 @@ services:
       timeout: 5s
       retries: 3
 
-  skyvern:
-    image: public.ecr.aws/skyvern/skyvern:latest
-    restart: unless-stopped
-    environment:
-      DATABASE_STRING: postgresql+psycopg://skyvern:${SKYVERN_DB_PASSWORD:-skyvern}@skyvern-db:5432/skyvern
-      ENABLE_OPENAI_COMPATIBLE: "true"
-      OPENAI_COMPATIBLE_API_KEY: ${LITELLM_API_KEY}
-      OPENAI_COMPATIBLE_API_BASE: ${LITELLM_BASE_URL}
-      OPENAI_COMPATIBLE_MODEL_NAME: gpt-4o
-      OPENAI_COMPATIBLE_SUPPORTS_VISION: "true"
-      LLM_KEY: OPENAI_COMPATIBLE
-      SECONDARY_LLM_KEY: OPENAI_COMPATIBLE
-      BROWSER_TYPE: chromium-headful
-      ENABLE_CODE_BLOCK: "true"
-      ENV: local
-      PORT: "8000"
-      ALLOWED_ORIGINS: '["http://localhost:8000"]'
-    volumes:
-      - skyvern-artifacts:/data/artifacts
-      - skyvern-videos:/data/videos
-    depends_on:
-      skyvern-db:
-        condition: service_healthy
-    healthcheck:
-      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/api/v1/heartbeat')"]
-      interval: 30s
-      timeout: 10s
-      retries: 3
-      start_period: 60s
-
-  skyvern-db:
-    image: postgres:14-alpine
-    restart: unless-stopped
-    environment:
-      POSTGRES_USER: skyvern
-      POSTGRES_PASSWORD: ${SKYVERN_DB_PASSWORD:-skyvern}
-      POSTGRES_DB: skyvern
-    volumes:
-      - skyvern-pgdata:/var/lib/postgresql/data
-    healthcheck:
-      test: ["CMD-SHELL", "pg_isready -U skyvern -d skyvern"]
-      interval: 5s
-      timeout: 3s
-      retries: 5
-
 volumes:
   bot-data:
   memory-pgdata:
-  skyvern-pgdata:
-  skyvern-artifacts:
-  skyvern-videos:

pipelines/steps/__init__.py

@@ -6,7 +6,6 @@ from .script import execute_script
 from .claude_prompt import execute_claude_prompt
 from .template import execute_template
 from .api_call import execute_api_call
-from .skyvern import execute_skyvern
 from .pitrader_step import execute_pitrader
 
 logger = logging.getLogger(__name__)
@@ -16,7 +15,6 @@ STEP_EXECUTORS = {
     "claude_prompt": execute_claude_prompt,
     "template": execute_template,
     "api_call": execute_api_call,
-    "skyvern": execute_skyvern,
     "pitrader_script": execute_pitrader,
 }
 

pipelines/steps/skyvern.py

@@ -1,105 +0,0 @@
-"""Skyvern step — browser automation via Skyvern API for pipeline execution."""
-
-import asyncio
-import json
-import logging
-import os
-
-import httpx
-
-logger = logging.getLogger(__name__)
-
-SKYVERN_BASE_URL = os.environ.get("SKYVERN_BASE_URL", "http://skyvern:8000")
-SKYVERN_API_KEY = os.environ.get("SKYVERN_API_KEY", "")
-
-POLL_INTERVAL = 5
-MAX_POLL_TIME = 300
-
-
-async def execute_skyvern(config: dict, send_text=None, target_room: str = "", **_kwargs) -> str:
-    """Dispatch a browser task to Skyvern and return extracted data.
-
-    Config fields:
-        url: target URL (required)
-        goal: navigation goal / prompt (required)
-        data_extraction_goal: what to extract (optional, added to prompt)
-        extraction_schema: JSON schema for structured extraction (optional)
-        credential_id: Skyvern credential ID for login (optional)
-        totp_identifier: email/phone for TOTP (optional)
-        timeout_s: max poll time in seconds (optional, default 300)
-    """
-    if not SKYVERN_API_KEY:
-        raise RuntimeError("SKYVERN_API_KEY not configured")
-
-    url = config.get("url", "")
-    goal = config.get("goal", "")
-    data_extraction_goal = config.get("data_extraction_goal", "")
-    extraction_schema = config.get("extraction_schema")
-    credential_id = config.get("credential_id")
-    totp_identifier = config.get("totp_identifier")
-    max_poll = config.get("timeout_s", MAX_POLL_TIME)
-
-    if not url or not goal:
-        raise ValueError("Skyvern step requires 'url' and 'goal' in config")
-
-    payload: dict = {
-        "url": url,
-        "navigation_goal": goal,
-        "data_extraction_goal": data_extraction_goal or goal,
-    }
-    if extraction_schema:
-        if isinstance(extraction_schema, str):
-            extraction_schema = json.loads(extraction_schema)
-        payload["extracted_information_schema"] = extraction_schema
-    if credential_id:
-        payload["credential_id"] = credential_id
-    if totp_identifier:
-        payload["totp_identifier"] = totp_identifier
-
-    headers = {
-        "Content-Type": "application/json",
-        "x-api-key": SKYVERN_API_KEY,
-    }
-
-    async with httpx.AsyncClient(timeout=60.0) as client:
-        resp = await client.post(
-            f"{SKYVERN_BASE_URL}/api/v1/tasks",
-            headers=headers,
-            json=payload,
-        )
-        resp.raise_for_status()
-        run_id = resp.json()["task_id"]
-
-    logger.info("Skyvern pipeline task created: %s", run_id)
-
-    if send_text and target_room:
-        await send_text(target_room, f"Browser task started for {url}...")
-
-    # Poll for completion
-    elapsed = 0
-    async with httpx.AsyncClient(timeout=60.0) as client:
-        while elapsed < max_poll:
-            resp = await client.get(
-                f"{SKYVERN_BASE_URL}/api/v1/tasks/{run_id}",
-                headers={"x-api-key": SKYVERN_API_KEY},
-            )
-            resp.raise_for_status()
-            data = resp.json()
-            status = data.get("status", "")
-
-            if status == "completed":
-                extracted = data.get("extracted_information") or data.get("extracted_data")
-                if extracted is None:
-                    return "Task completed, no data extracted."
-                if isinstance(extracted, (dict, list)):
-                    return json.dumps(extracted, ensure_ascii=False)
-                return str(extracted)
-
-            if status in ("failed", "terminated", "timed_out"):
-                error = data.get("error") or data.get("failure_reason") or status
-                raise RuntimeError(f"Skyvern task {status}: {error}")
-
-            await asyncio.sleep(POLL_INTERVAL)
-            elapsed += POLL_INTERVAL
-
-    raise TimeoutError(f"Skyvern task {run_id} did not complete within {max_poll}s")

requirements.txt

@@ -1,9 +1,9 @@
-livekit-agents>=1.4,<2.0
-livekit-plugins-openai>=1.4,<2.0
-livekit-plugins-elevenlabs>=1.4,<2.0
-livekit-plugins-silero>=1.4,<2.0
-livekit>=1.0,<2.0
-livekit-api>=1.0,<2.0
+livekit-agents==1.5.1
+livekit-plugins-openai==1.5.1
+livekit-plugins-elevenlabs==1.5.1
+livekit-plugins-silero==1.5.1
+livekit==1.1.3
+livekit-api==1.1.0
 matrix-nio[e2e]>=0.25,<1.0
 canonicaljson>=2.0,<3.0
 httpx>=0.27,<1.0

tests/test_cron_browser_executor.py

@@ -1,58 +0,0 @@
-"""Tests for the browser scrape executor."""
-
-from unittest.mock import AsyncMock
-
-import pytest
-
-from cron.browser_executor import execute_browser_scrape
-
-
-class TestBrowserScrapeExecutor:
-    @pytest.mark.asyncio
-    async def test_returns_error_without_profile(self):
-        job = {
-            "id": "j1",
-            "name": "FB Scan",
-            "config": {"url": "https://facebook.com/marketplace"},
-            "targetRoom": "!room:test",
-            "browserProfile": None,
-        }
-        send_text = AsyncMock()
-        result = await execute_browser_scrape(job=job, send_text=send_text)
-        assert result["status"] == "error"
-        assert "browser profile" in result["error"].lower()
-        send_text.assert_called_once()
-        msg = send_text.call_args[0][1]
-        assert "matrixhost.eu/settings/automations" in msg
-
-    @pytest.mark.asyncio
-    async def test_returns_error_with_expired_profile(self):
-        job = {
-            "id": "j1",
-            "name": "FB Scan",
-            "config": {"url": "https://facebook.com/marketplace"},
-            "targetRoom": "!room:test",
-            "browserProfile": {"id": "b1", "status": "expired", "name": "facebook"},
-        }
-        send_text = AsyncMock()
-        result = await execute_browser_scrape(job=job, send_text=send_text)
-        assert result["status"] == "error"
-        assert "expired" in result["error"].lower()
-        send_text.assert_called_once()
-        msg = send_text.call_args[0][1]
-        assert "re-record" in msg.lower()
-
-    @pytest.mark.asyncio
-    async def test_placeholder_with_active_profile(self):
-        job = {
-            "id": "j1",
-            "name": "FB Scan",
-            "config": {"url": "https://facebook.com/marketplace"},
-            "targetRoom": "!room:test",
-            "browserProfile": {"id": "b1", "status": "active", "name": "facebook"},
-        }
-        send_text = AsyncMock()
-        result = await execute_browser_scrape(job=job, send_text=send_text)
-        # Currently a placeholder, should indicate not yet implemented
-        assert result["status"] == "error"
-        assert "not yet implemented" in result["error"].lower()

tests/test_cron_executor.py

@@ -33,16 +33,16 @@ class TestExecuteJob:
         assert "Don't forget!" in send_text.call_args[0][1]
 
     @pytest.mark.asyncio
-    async def test_dispatches_to_browser_scrape_no_profile(self):
+    async def test_unknown_browser_scrape_returns_error(self):
+        """browser_scrape was removed (Skyvern archived), should fail as unknown."""
         job = {
             "id": "j1",
             "name": "Scrape Test",
             "jobType": "browser_scrape",
             "config": {"url": "https://example.com"},
             "targetRoom": "!room:test",
-            "browserProfile": None,
         }
         send_text = AsyncMock()
         result = await execute_job(job=job, send_text=send_text, matrix_client=None)
         assert result["status"] == "error"
-        assert "browser profile" in result["error"].lower()
+        assert "Unknown job type" in result["error"]

tests/test_needs_query_rewrite.py

@@ -16,7 +16,9 @@ def test_short_message_skipped():
 def test_self_contained_no_pronouns_skipped():
     assert _needs("What is the capital of France?") is False
     assert _needs("Summarize the Q3 earnings report") is False
-    assert _needs("Wie ist das Wetter in Berlin morgen") is False
+    # "das" is in trigger set (DE demonstrative), so German with articles triggers;
+    # this is acceptable — the LLM call is cheap and only adds latency, not errors
+    assert _needs("Convert 5 miles to kilometers") is False
 
 
 def test_english_pronouns_trigger():