feat(workflow): implement target channel personalities, raw review cards, on-demand AI rewrites and multi-target dispatch

services/queue_consumer.py

@@ -3,7 +3,6 @@ import asyncio
 import logging
 from typing import Optional
 from core.queue import RedisQueue
-from services.ai_processor import AIProcessor
 from core.metrics import QUEUE_POSTS_GAUGE, REDIS_QUEUE_SIZE_GAUGE
 
 logger = logging.getLogger(__name__)
@@ -11,9 +10,9 @@ logger = logging.getLogger(__name__)
 FETCH_INTERVAL_SECONDS = int(os.getenv("AI_PROCESSING_INTERVAL_SECONDS", "120"))
 
 class QueueConsumerService:
-    def __init__(self, queue: RedisQueue, ai_processor: AIProcessor, fetch_interval: int = FETCH_INTERVAL_SECONDS):
+    def __init__(self, queue: RedisQueue, on_post_popped = None, fetch_interval: int = FETCH_INTERVAL_SECONDS):
         self.queue = queue
-        self.ai_processor = ai_processor
+        self.on_post_popped = on_post_popped
         self.fetch_interval = fetch_interval
         self._running = False
         self._task: Optional[asyncio.Task] = None
@@ -33,9 +32,9 @@ class QueueConsumerService:
 
                 if qsize > 0:
                     post_id = await self.queue.pop()
-                    if post_id:
-                        logger.info(f"Paced Consumer: processing post ID {post_id} from Redis queue (remaining: {qsize - 1})")
-                        await self.ai_processor.process_post(post_id)
+                    if post_id and self.on_post_popped:
+                        logger.info(f"Dispatching raw post ID {post_id} to Admin Review channel (remaining in Redis: {qsize - 1})")
+                        await self.on_post_popped(post_id)
                         new_qsize = await self.queue.qsize()
                         QUEUE_POSTS_GAUGE.labels(status="redis_incoming").set(new_qsize)
                         REDIS_QUEUE_SIZE_GAUGE.set(new_qsize)