Remove excessive logging from AI moderator service

Eliminated several info and error log statements related to content size, chunking, and API call details to reduce log verbosity and potential exposure of sensitive content. This streamlines the logging output and focuses on essential warnings and errors.

Author: Bentlybro

app/services/ai/ai_moderator.py

@@ -300,9 +300,6 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
                 MAX_CHARS_PER_CHUNK = 50000  # ~50k tokens worst case, safe for any prompt
                 content_chars = len(content)
 
-                current_app.logger.info(
-                    f"Content: {content_tokens} tokens (tiktoken), {content_chars} chars")
-
                 # Force chunking if content is too large BY CHARACTER COUNT
                 if content_chars > MAX_CHARS_PER_CHUNK:
                     current_app.logger.warning(
@@ -313,9 +310,6 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
                     for i in range(0, content_chars, MAX_CHARS_PER_CHUNK):
                         chunks.append(content[i:i + MAX_CHARS_PER_CHUNK])
 
-                    current_app.logger.info(
-                        f"Split content into {len(chunks)} chunks by character count")
-
                     chunk_results = []
                     for i, chunk in enumerate(chunks):
                         result = self._analyze_with_custom_prompt(chunk, custom_prompt)
@@ -332,7 +326,6 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
 
             # STEP 2: For default moderation, run baseline check first
             # Note: OpenAI moderation API has its own limits, but typically handles larger content
-            current_app.logger.info(f"Content has {content_tokens} tokens")
             baseline_result = self._run_baseline_moderation(content)
             if baseline_result['decision'] == 'rejected':
                 return baseline_result
@@ -346,8 +339,6 @@ def moderate_content(self, content, content_type='text', custom_prompt=None):
             else:
                 # Split content and analyze each chunk
                 chunks = self.split_text_into_chunks(content, max_content_tokens)
-                current_app.logger.info(
-                    f"Split content into {len(chunks)} chunks for enhanced moderation")
 
                 chunk_results = []
                 for i, chunk in enumerate(chunks):
@@ -444,17 +435,6 @@ def _analyze_with_custom_prompt(self, content, custom_prompt):
 
 Does content violate this rule? JSON only:"""
 
-            # CRITICAL: Log what we're actually sending to identify cost issue
-            current_app.logger.error(
-                f"[COST INVESTIGATION] Sending to OpenAI - "
-                f"Content length: {len(content)} chars, "
-                f"Custom prompt length: {len(custom_prompt)} chars, "
-                f"System message length: {len(system_message)} chars, "
-                f"User message length: {len(user_message)} chars, "
-                f"Content type: {type(content).__name__}, "
-                f"Content first 200 chars: {content[:200] if len(content) > 0 else 'EMPTY'}"
-            )
-
             # Wrap API call with retry logic
             def make_api_call():
                 client = self.client_manager.get_client()