feat： 取消补充分数的docker服务

docker-compose.yaml

@@ -17,36 +17,3 @@ services:
     environment:
       - APP_ENV=prod
     entrypoint: ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
-
-  add_score_scheduler:
-    build:
-      context: .
-      dockerfile: Dockerfile
-    image: video_decode
-    container_name: add_score_scheduler
-    restart: always
-    volumes:
-      - ./logs:/video_decode/logs
-    env_file:
-      - .env
-    environment:
-      - APP_ENV=prod
-      - ADD_SCORE_CUTOFF_DT=20260429
-      - ADD_SCORE_TIMEOUT=2400
-      - ADD_SCORE_WORKERS=3
-      - ADD_SCORE_START_ID=1130
-      - ADD_SCORE_INTERVAL_SECONDS=600
-      - ADD_SCORE_DRY_RUN=
-    entrypoint:
-      - sh
-      - -lc
-      - |
-        while true; do
-          python scheduler/add_score_job.py \
-            --cutoff-dt "$$ADD_SCORE_CUTOFF_DT" \
-            --timeout "$$ADD_SCORE_TIMEOUT" \
-            --workers "$$ADD_SCORE_WORKERS" \
-            --start-id "$$ADD_SCORE_START_ID" \
-            $${ADD_SCORE_DRY_RUN:+--dry-run};
-          sleep "$$ADD_SCORE_INTERVAL_SECONDS";
-        done

scheduler/add_score_job.py

@@ -23,7 +23,7 @@ SCORE_API_URL = "http://47.236.83.130:8200/process_note"
 DEFAULT_CUTOFF_DT = "20260429"
 DEFAULT_TIMEOUT = 2400
 DEFAULT_WORKERS = 3
-DEFAULT_START_ID = 6035
+DEFAULT_START_ID = 7150
 FETCH_BATCH_SIZE = 20
 EXISTING_SCORE_KEYS = {"分享意愿度", "消费意愿度", "点击意愿度"}