Let parallism of RAPTOR controlable. (#5379)

### What problem does this PR solve?

#4874
### Type of change

- [x] Refactoring

rag/raptor.py

@@ -14,6 +14,7 @@
 #  limitations under the License.
 #
 import logging
+import os
 import re
 from concurrent.futures import ThreadPoolExecutor, ALL_COMPLETED, wait
 from threading import Lock
@@ -122,7 +123,7 @@ class RecursiveAbstractiveProcessing4TreeOrganizedRetrieval:
                 lbls = [np.where(prob > self._threshold)[0] for prob in probs]
                 lbls = [lbl[0] if isinstance(lbl, np.ndarray) else lbl for lbl in lbls]
             lock = Lock()
-            with ThreadPoolExecutor(max_workers=12) as executor:
+            with ThreadPoolExecutor(max_workers=int(os.environ.get('GRAPH_EXTRACTOR_MAX_WORKERS', 10))) as executor:
                 threads = []
                 for c in range(n_clusters):
                     ck_idx = [i + start for i in range(len(lbls)) if lbls[i] == c]