hotfix: redis dependency in scheduler

src/memos/mem_scheduler/task_schedule_modules/dispatcher.py

@@ -129,8 +129,6 @@ def status_tracker(self) -> TaskStatusTracker | None:
             try:
                 self._status_tracker = TaskStatusTracker(self.redis)
                 # Propagate to submodules when created lazily
-                if self.dispatcher:
-                    self.dispatcher.status_tracker = self._status_tracker
                 if self.memos_message_queue:
                     self.memos_message_queue.set_status_tracker(self._status_tracker)
             except Exception as e:

src/memos/mem_scheduler/task_schedule_modules/local_queue.py

@@ -4,9 +4,18 @@
 the local memos_message_queue functionality in BaseScheduler.
 """
 
+from typing import TYPE_CHECKING
+
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
 from memos.log import get_logger
 from memos.mem_scheduler.general_modules.misc import AutoDroppingQueue as Queue
 from memos.mem_scheduler.schemas.message_schemas import ScheduleMessageItem
+from memos.mem_scheduler.schemas.task_schemas import DEFAULT_STREAM_KEY_PREFIX
+from memos.mem_scheduler.task_schedule_modules.orchestrator import SchedulerOrchestrator
+from memos.mem_scheduler.utils.status_tracker import TaskStatusTracker
 from memos.mem_scheduler.webservice_modules.redis_service import RedisSchedulerModule
 
 
@@ -16,26 +25,38 @@
 class SchedulerLocalQueue(RedisSchedulerModule):
     def __init__(
         self,
-        maxsize: int,
+        maxsize: int = 0,
+        stream_key_prefix: str = DEFAULT_STREAM_KEY_PREFIX,
+        orchestrator: SchedulerOrchestrator | None = None,
+        status_tracker: TaskStatusTracker | None = None,
     ):
         """
         Initialize the SchedulerLocalQueue with a maximum queue size limit.
+        Arguments match SchedulerRedisQueue for compatibility.
 
         Args:
-            maxsize (int): Maximum number of messages allowed
-                                                 in each individual queue.
-                                                 If exceeded, subsequent puts will block
-                                                 or raise an exception based on `block` parameter.
+            maxsize (int): Maximum number of messages allowed in each individual queue.
+            stream_key_prefix (str): Prefix for stream keys (simulated).
+            orchestrator: SchedulerOrchestrator instance (ignored).
+            status_tracker: TaskStatusTracker instance (ignored).
         """
         super().__init__()
 
-        self.stream_key_prefix = "local_queue"
+        self.stream_key_prefix = stream_key_prefix or "local_queue"
 
         self.max_internal_message_queue_size = maxsize
+
         # Dictionary to hold per-stream queues: key = stream_key, value = Queue[ScheduleMessageItem]
         self.queue_streams: dict[str, Queue[ScheduleMessageItem]] = {}
+
+        self.orchestrator = orchestrator
+        self.status_tracker = status_tracker
+
+        self._is_listening = False
+        self._message_handler: Callable[[ScheduleMessageItem], None] | None = None
+
         logger.info(
-            f"SchedulerLocalQueue initialized with max_internal_message_queue_size={maxsize}"
+            f"SchedulerLocalQueue initialized with max_internal_message_queue_size={self.max_internal_message_queue_size}"
         )
 
     def get_stream_key(self, user_id: str, mem_cube_id: str, task_label: str) -> str:
@@ -62,7 +83,7 @@ def put(
             Exception: Any underlying error during queue.put() operation.
         """
         stream_key = self.get_stream_key(
-            user_id=message.user_id, mem_cube_id=message.mem_cube_id, task_label=message.task_label
+            user_id=message.user_id, mem_cube_id=message.mem_cube_id, task_label=message.label
         )
 
         message.stream_key = stream_key
@@ -86,7 +107,7 @@ def get(
         stream_key: str,
         block: bool = True,
         timeout: float | None = None,
-        batch_size: int | None = None,
+        batch_size: int | None = 1,
     ) -> list[ScheduleMessageItem]:
         if batch_size is not None and batch_size <= 0:
             logger.warning(
@@ -99,47 +120,85 @@ def get(
             logger.error(f"Stream {stream_key} does not exist when trying to get messages.")
             return []
 
+        # Ensure we always request a batch so we get a list back
+        effective_batch_size = batch_size if batch_size is not None else 1
+
         # Note: Assumes custom Queue implementation supports batch_size parameter
         res = self.queue_streams[stream_key].get(
-            block=block, timeout=timeout, batch_size=batch_size
+            block=block, timeout=timeout, batch_size=effective_batch_size
         )
         logger.debug(
             f"Retrieved {len(res)} messages from queue '{stream_key}'. Current size: {self.queue_streams[stream_key].qsize()}"
         )
         return res
 
-    def get_nowait(self, batch_size: int | None = None) -> list[ScheduleMessageItem]:
+    def get_nowait(self, stream_key: str, batch_size: int | None = 1) -> list[ScheduleMessageItem]:
         """
-        Non-blocking version of get(). Equivalent to get(block=False, batch_size=batch_size).
+        Non-blocking version of get(). Equivalent to get(stream_key, block=False, batch_size=batch_size).
 
         Returns immediately with available messages or an empty list if queue is empty.
 
         Args:
+            stream_key (str): The stream/queue identifier.
             batch_size (int | None): Number of messages to retrieve in a batch.
                                    If None, retrieves one message.
 
         Returns:
             List[ScheduleMessageItem]: Retrieved messages or empty list if queue is empty.
         """
-        logger.debug(f"get_nowait() called with batch_size: {batch_size}")
-        return self.get(block=False, batch_size=batch_size)
+        logger.debug(f"get_nowait() called for {stream_key} with batch_size: {batch_size}")
+        return self.get(stream_key=stream_key, block=False, batch_size=batch_size)
+
+    def get_messages(self, batch_size: int) -> list[ScheduleMessageItem]:
+        """
+        Get messages from all streams in round-robin or sequential fashion.
+        Equivalent to SchedulerRedisQueue.get_messages.
+        """
+        messages = []
+        # Snapshot keys to avoid runtime modification issues
+        stream_keys = list(self.queue_streams.keys())
+
+        # Simple strategy: try to get up to batch_size messages across all streams
+        # We can just iterate and collect.
+
+        # Calculate how many to get per stream to be fair?
+        # Or just greedy? Redis implementation uses a complex logic.
+        # For local, let's keep it simple: just iterate and take what's available (non-blocking)
+
+        for stream_key in stream_keys:
+            if len(messages) >= batch_size:
+                break
+
+            needed = batch_size - len(messages)
+            # Use get_nowait to avoid blocking
+            fetched = self.get_nowait(stream_key=stream_key, batch_size=needed)
+            messages.extend(fetched)
+
+        return messages
 
     def qsize(self) -> dict:
         """
         Return the current size of all internal queues as a dictionary.
 
         Each key is the stream name, and each value is the number of messages in that queue.
+        Also includes 'total_size'.
 
         Returns:
             Dict[str, int]: Mapping from stream name to current queue size.
         """
         sizes = {stream: queue.qsize() for stream, queue in self.queue_streams.items()}
+        total_size = sum(sizes.values())
+        sizes["total_size"] = total_size
         logger.debug(f"Current queue sizes: {sizes}")
         return sizes
 
-    def clear(self) -> None:
-        for queue in self.queue_streams.values():
-            queue.clear()
+    def clear(self, stream_key: str | None = None) -> None:
+        if stream_key:
+            if stream_key in self.queue_streams:
+                self.queue_streams[stream_key].clear()
+        else:
+            for queue in self.queue_streams.values():
+                queue.clear()
 
     @property
     def unfinished_tasks(self) -> int:
@@ -151,6 +210,38 @@ def unfinished_tasks(self) -> int:
         Returns:
             int: Sum of all message counts in all internal queues.
         """
-        total = sum(self.qsize().values())
+        # qsize() now includes "total_size", so we need to be careful not to double count if we use qsize() values
+        # But qsize() implementation above sums values from queue_streams, then adds total_size.
+        # So sum(self.queue_streams.values().qsize()) is safer.
+        total = sum(queue.qsize() for queue in self.queue_streams.values())
         logger.debug(f"Total unfinished tasks across all queues: {total}")
         return total
+
+    def get_stream_keys(self, stream_key_prefix: str | None = None) -> list[str]:
+        """
+        Return list of active stream keys.
+        """
+        prefix = stream_key_prefix or self.stream_key_prefix
+        return [k for k in self.queue_streams if k.startswith(prefix)]
+
+    def size(self) -> int:
+        """
+        Total size of all queues.
+        """
+        return sum(q.qsize() for q in self.queue_streams.values())
+
+    def empty(self) -> bool:
+        """
+        Check if all queues are empty.
+        """
+        return self.size() == 0
+
+    def full(self) -> bool:
+        """
+        Check if any queue is full (approximate).
+        """
+        if self.max_internal_message_queue_size <= 0:
+            return False
+        return any(
+            q.qsize() >= self.max_internal_message_queue_size for q in self.queue_streams.values()
+        )

src/memos/mem_scheduler/task_schedule_modules/redis_queue.py

@@ -5,7 +5,6 @@
 the local memos_message_queue functionality in BaseScheduler.
 """
 
-import contextlib
 import os
 import re
 import threading
@@ -201,6 +200,20 @@ def _refresh_stream_keys(
                 recent_seconds=DEFAULT_STREAM_RECENT_ACTIVE_SECONDS,
                 now_sec=now_sec,
             )
+
+            # Ensure consumer groups for newly discovered active streams
+            with self._stream_keys_lock:
+                # Identify keys we haven't seen yet
+                new_streams = [k for k in active_stream_keys if k not in self.seen_streams]
+
+            # Create groups outside the lock to avoid blocking
+            for key in new_streams:
+                self._ensure_consumer_group(key)
+
+            if new_streams:
+                with self._stream_keys_lock:
+                    self.seen_streams.update(new_streams)
+
             deleted_count = self._delete_streams(keys_to_delete)
             self._update_stream_cache_with_log(
                 stream_key_prefix=stream_key_prefix,
@@ -560,10 +573,7 @@ def _read_new_messages_batch(
             return {}
 
         # Pre-ensure consumer groups to avoid NOGROUP during batch reads
-        for stream_key in stream_keys:
-            with contextlib.suppress(Exception):
-                self._ensure_consumer_group(stream_key=stream_key)
-
+        # (Optimization: rely on put() and _refresh_stream_keys() to ensure groups)
         pipe = self._redis_conn.pipeline(transaction=False)
         for stream_key in stream_keys:
             pipe.xreadgroup(
@@ -676,13 +686,6 @@ def _batch_claim_pending_messages(
         Returns:
             A list of (stream_key, claimed_entries) pairs for all successful claims.
         """
-        if not self._redis_conn or not claims_spec:
-            return []
-
-        # Ensure consumer groups exist to avoid NOGROUP errors during batch claim
-        for stream_key, _need_count, _label in claims_spec:
-            with contextlib.suppress(Exception):
-                self._ensure_consumer_group(stream_key=stream_key)
 
         pipe = self._redis_conn.pipeline(transaction=False)
         for stream_key, need_count, label in claims_spec:
@@ -696,26 +699,42 @@ def _batch_claim_pending_messages(
                 justid=False,
             )
 
-        results = []
         try:
-            results = pipe.execute()
-        except Exception:
-            # Fallback: attempt sequential xautoclaim for robustness
-            for stream_key, need_count, label in claims_spec:
-                try:
-                    self._ensure_consumer_group(stream_key=stream_key)
-                    res = self._redis_conn.xautoclaim(
-                        name=stream_key,
-                        groupname=self.consumer_group,
-                        consumername=self.consumer_name,
-                        min_idle_time=self.orchestrator.get_task_idle_min(task_label=label),
-                        start_id="0-0",
-                        count=need_count,
-                        justid=False,
-                    )
-                    results.append(res)
-                except Exception:
-                    continue
+            # Execute with raise_on_error=False so we get exceptions in the results list
+            # instead of aborting the whole batch.
+            results = pipe.execute(raise_on_error=False)
+        except Exception as e:
+            logger.error(f"Pipeline execution critical failure: {e}")
+            results = [e] * len(claims_spec)
+
+            # Handle individual failures (e.g. NOGROUP) by retrying just that stream
+        final_results = []
+        for i, res in enumerate(results):
+            if isinstance(res, Exception):
+                err_msg = str(res).lower()
+                if "nogroup" in err_msg or "no such key" in err_msg:
+                    stream_key, need_count, label = claims_spec[i]
+                    try:
+                        self._ensure_consumer_group(stream_key=stream_key)
+                        retry_res = self._redis_conn.xautoclaim(
+                            name=stream_key,
+                            groupname=self.consumer_group,
+                            consumername=self.consumer_name,
+                            min_idle_time=self.orchestrator.get_task_idle_min(task_label=label),
+                            start_id="0-0",
+                            count=need_count,
+                            justid=False,
+                        )
+                        final_results.append(retry_res)
+                    except Exception as retry_err:
+                        logger.warning(f"Retry xautoclaim failed for {stream_key}: {retry_err}")
+                        final_results.append(None)
+                else:
+                    final_results.append(None)
+            else:
+                final_results.append(res)
+
+        results = final_results
 
         claimed_pairs: list[tuple[str, list[tuple[str, dict]]]] = []
         for (stream_key, _need_count, _label), claimed_result in zip(
@@ -1159,17 +1178,23 @@ def _delete_streams(self, keys_to_delete: list[str]) -> int:
                 del_pipe.delete(key)
             del_pipe.execute()
             deleted_count = len(keys_to_delete)
-            # Clean up empty-tracking state for deleted keys
+            # Clean up empty-tracking state and seen_streams for deleted keys
             with self._empty_stream_seen_lock:
                 for key in keys_to_delete:
                     self._empty_stream_seen_times.pop(key, None)
+
+            with self._stream_keys_lock:
+                for key in keys_to_delete:
+                    self.seen_streams.discard(key)
         except Exception:
             for key in keys_to_delete:
                 try:
                     self._redis_conn.delete(key)
                     deleted_count += 1
                     with self._empty_stream_seen_lock:
                         self._empty_stream_seen_times.pop(key, None)
+                    with self._stream_keys_lock:
+                        self.seen_streams.discard(key)
                 except Exception:
                     pass
         return deleted_count
@@ -1190,8 +1215,6 @@ def _update_stream_cache_with_log(
             self._stream_keys_last_refresh = time.time()
             cache_count = len(self._stream_keys_cache)
         logger.info(
-            f"[REDIS_QUEUE] Stream keys refresh: prefix='{stream_key_prefix}', "
-            f"total={len(candidate_keys)}, active={len(active_stream_keys)}, cached={cache_count}, "
-            f"active_threshold_sec={int(active_threshold_sec)}, deleted={deleted_count}, "
-            f"inactive_threshold_sec={int(DEFAULT_STREAM_INACTIVITY_DELETE_SECONDS)}"
+            f"Refreshed stream keys cache: {cache_count} active keys, "
+            f"{deleted_count} deleted, {len(candidate_keys)} candidates examined."
         )