feat: Redis caching + async queue for LLM scaling (v1.6.0)

- Add async Redis client singleton (redis_client.py) for caching and arq pool
- Add arq job functions (jobs.py) for background LLM processing
- Cache ask/explain LLM responses with TTL (1h ask, 24h explain)
- Add async mode to /api/ask: enqueue job, return job_id, poll /api/jobs/{id}
- Add GET /api/jobs/{job_id} endpoint for job status polling
- Add arq worker service to docker-compose (dev + prod)
- Switch from Redis to Valkey (BSD fork) in Docker Compose
- Add REDIS_URL config setting
- Add tests for cache hit, async mode, and job status

docker-compose.yml

@@ -1,4 +1,13 @@
 services:
+  redis:
+    image: valkey/valkey:8-alpine
+    container_name: aoc-redis
+    restart: always
+    ports:
+      - "6379:6379"
+    volumes:
+      - redis_data:/data
+
   mongo:
     image: mongo:7
     container_name: aoc-mongo
@@ -21,10 +30,27 @@ services:
       - .env
     environment:
       MONGO_URI: mongodb://${MONGO_ROOT_USERNAME}:${MONGO_ROOT_PASSWORD}@mongo:${MONGO_PORT}/
+      REDIS_URL: redis://redis:6379/0
     depends_on:
       - mongo
+      - redis
     ports:
       - "8000:8000"
 
+  worker:
+    build: ./backend
+    container_name: aoc-worker
+    restart: always
+    env_file:
+      - .env
+    environment:
+      MONGO_URI: mongodb://${MONGO_ROOT_USERNAME}:${MONGO_ROOT_PASSWORD}@mongo:${MONGO_PORT}/
+      REDIS_URL: redis://redis:6379/0
+    command: ["arq", "jobs.WorkerSettings"]
+    depends_on:
+      - redis
+      - mongo
+
 volumes:
   mongo_data:
+  redis_data: