Increase ThreadPoolExecutor max_workers to 200

Raised the maximum number of workers from 150 to 200 in ai_moderator.py and rule_processor.py to improve parallel processing performance for chunk and rule analysis.

Author: Bentlybro

app/services/ai/ai_moderator.py

@@ -326,7 +326,7 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
 
                     # Process all chunks IN PARALLEL for maximum speed
                     chunk_results = []
-                    with ThreadPoolExecutor(max_workers=min(len(chunks), 150)) as executor:
+                    with ThreadPoolExecutor(max_workers=min(len(chunks), 200)) as executor:
                         # Submit all chunks at once with context wrapper
                         future_to_chunk = {
                             executor.submit(self._context_wrapper, self._analyze_with_custom_prompt, chunk, custom_prompt): i
@@ -375,7 +375,7 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
 
                 # Process all chunks IN PARALLEL for maximum speed
                 chunk_results = []
-                with ThreadPoolExecutor(max_workers=min(len(chunks), 150)) as executor:
+                with ThreadPoolExecutor(max_workers=min(len(chunks), 200)) as executor:
                     # Submit all chunks at once with context wrapper
                     future_to_chunk = {
                         executor.submit(self._context_wrapper, self._run_enhanced_default_moderation, chunk): i

app/services/moderation/rule_processor.py

@@ -103,7 +103,7 @@ def process_single_ai_rule(rule):
                 return (rule.id, None)
 
         # Execute in parallel
-        with ThreadPoolExecutor(max_workers=min(len(ai_rules), 150)) as executor:
+        with ThreadPoolExecutor(max_workers=min(len(ai_rules), 200)) as executor:
             futures = {executor.submit(
                 process_single_ai_rule, rule): rule for rule in ai_rules}