streamlined neutralization flow

modules/aicore/aicoreBase.py

@@ -18,7 +18,9 @@ from typing import List, Dict, Any, Optional, AsyncGenerator, Union
 from modules.datamodels.datamodelAi import AiModel, AiModelCall, AiModelResponse
 
 
-_RETRY_AFTER_PATTERN = _re.compile(r"try again in (\d+(?:\.\d+)?)\s*s", _re.IGNORECASE)
+_RETRY_AFTER_PATTERN = _re.compile(
+    r"(?:try again in|retry after)\s+(\d+(?:\.\d+)?)\s*s", _re.IGNORECASE
+)
 
 
 def _parseRetryAfterSeconds(message: str) -> float:

modules/aicore/aicorePluginPrivateLlm.py

@@ -22,7 +22,7 @@ import time
 from typing import List, Optional, Dict, Any
 from fastapi import HTTPException
 from modules.shared.configuration import APP_CONFIG
-from .aicoreBase import BaseConnectorAi
+from .aicoreBase import BaseConnectorAi, RateLimitExceededException
 from modules.datamodels.datamodelAi import (
     AiModel, 
     PriorityEnum, 
@@ -370,6 +370,9 @@ class AiPrivateLlm(BaseConnectorAi):
             
             if response.status_code != 200:
                 errorMessage = f"Private-LLM API error: {response.status_code} - {response.text}"
+                if response.status_code == 429:
+                    logger.warning(errorMessage)
+                    raise RateLimitExceededException(errorMessage)
                 logger.error(errorMessage)
                 raise HTTPException(status_code=500, detail=errorMessage)
             
@@ -461,6 +464,9 @@ class AiPrivateLlm(BaseConnectorAi):
             
             if response.status_code != 200:
                 errorMessage = f"Private-LLM API error: {response.status_code} - {response.text}"
+                if response.status_code == 429:
+                    logger.warning(errorMessage)
+                    raise RateLimitExceededException(errorMessage)
                 logger.error(errorMessage)
                 raise HTTPException(status_code=500, detail=errorMessage)
             

modules/features/neutralization/datamodelFeatureNeutralizer.py

@@ -58,6 +58,17 @@ class DataNeutralizerAttributes(BaseModel):
     originalText: str = Field(description="Original text that was neutralized", json_schema_extra={"frontend_type": "text", "frontend_readonly": True, "frontend_required": True})
     fileId: Optional[str] = Field(default=None, description="ID of the file this attribute belongs to", json_schema_extra={"frontend_type": "text", "frontend_readonly": True, "frontend_required": False})
     patternType: str = Field(description="Type of pattern that matched (email, phone, name, etc.)", json_schema_extra={"frontend_type": "text", "frontend_readonly": True, "frontend_required": True})
+
+
+class DataNeutralizationSnapshot(BaseModel):
+    """Stores the full neutralized text (with embedded placeholders) per source."""
+    id: str = Field(default_factory=lambda: str(uuid.uuid4()))
+    mandateId: str = Field(description="Mandate scope")
+    featureInstanceId: str = Field(default="", description="Feature instance scope")
+    userId: str = Field(description="User who triggered neutralization")
+    sourceLabel: str = Field(description="Human label, e.g. 'Prompt', 'Kontext', 'Nachricht 3'")
+    neutralizedText: str = Field(description="Full text with [type.uuid] placeholders embedded")
+    placeholderCount: int = Field(default=0, description="Number of placeholders in the text")
 registerModelLabels(
     "DataNeutralizerAttributes",
     {"en": "Neutralized Data Attribute", "fr": "Attribut de données neutralisées"},
@@ -71,5 +82,18 @@ registerModelLabels(
         "patternType": {"en": "Pattern Type", "fr": "Type de modèle"},
     },
 )
+registerModelLabels(
+    "DataNeutralizationSnapshot",
+    {"en": "Neutralization Snapshot", "de": "Neutralisierungs-Snapshot"},
+    {
+        "id": {"en": "ID"},
+        "mandateId": {"en": "Mandate ID"},
+        "featureInstanceId": {"en": "Feature Instance ID"},
+        "userId": {"en": "User ID"},
+        "sourceLabel": {"en": "Source", "de": "Quelle"},
+        "neutralizedText": {"en": "Neutralized Text", "de": "Neutralisierter Text"},
+        "placeholderCount": {"en": "Placeholders", "de": "Platzhalter"},
+    },
+)
 
 

modules/features/neutralization/interfaceFeatureNeutralizer.py

@@ -11,6 +11,7 @@ from typing import Dict, List, Any, Optional
 from modules.features.neutralization.datamodelFeatureNeutralizer import (
     DataNeutraliserConfig,
     DataNeutralizerAttributes,
+    DataNeutralizationSnapshot,
 )
 from modules.connectors.connectorDbPostgre import DatabaseConnector
 from modules.interfaces.interfaceRbac import getRecordsetWithRBAC
@@ -227,6 +228,74 @@ class InterfaceFeatureNeutralizer:
             logger.error(f"Error deleting attribute by ID: {str(e)}")
             return False
 
+    # ------------------------------------------------------------------
+    # Snapshot CRUD
+    # ------------------------------------------------------------------
+
+    def getSnapshots(self) -> List[DataNeutralizationSnapshot]:
+        """Return all neutralization snapshots for the current mandate + feature instance."""
+        try:
+            _filter: Dict[str, Any] = {"mandateId": self.mandateId}
+            if self.featureInstanceId:
+                _filter["featureInstanceId"] = self.featureInstanceId
+            rows = getRecordsetWithRBAC(
+                self.db,
+                DataNeutralizationSnapshot,
+                self.currentUser,
+                recordFilter=_filter,
+                mandateId=self.mandateId,
+            )
+            return [
+                DataNeutralizationSnapshot(**{k: v for k, v in r.items() if not k.startswith("_")})
+                for r in rows
+            ]
+        except Exception as e:
+            logger.error(f"Error getting snapshots: {e}")
+            return []
+
+    def clearSnapshots(self) -> int:
+        """Delete all snapshots for the current feature-instance scope. Returns count deleted."""
+        try:
+            _filter: Dict[str, Any] = {"mandateId": self.mandateId}
+            if self.featureInstanceId:
+                _filter["featureInstanceId"] = self.featureInstanceId
+            existing = self.db.getRecordset(DataNeutralizationSnapshot, recordFilter=_filter)
+            for row in existing:
+                self.db.recordDelete(DataNeutralizationSnapshot, row["id"])
+            return len(existing)
+        except Exception as e:
+            logger.error(f"Error clearing snapshots: {e}")
+            return 0
+
+    def createSnapshot(
+        self,
+        sourceLabel: str,
+        neutralizedText: str,
+        placeholderCount: int = 0,
+    ) -> Optional[DataNeutralizationSnapshot]:
+        """Persist one neutralization snapshot."""
+        try:
+            if not self.userId:
+                logger.warning("Cannot create snapshot: missing userId")
+                return None
+            snap = DataNeutralizationSnapshot(
+                mandateId=self.mandateId or "",
+                featureInstanceId=self.featureInstanceId or "",
+                userId=self.userId,
+                sourceLabel=sourceLabel,
+                neutralizedText=neutralizedText,
+                placeholderCount=placeholderCount,
+            )
+            created = self.db.recordCreate(DataNeutralizationSnapshot, snap.model_dump())
+            return DataNeutralizationSnapshot(**{k: v for k, v in created.items() if not k.startswith("_")})
+        except Exception as e:
+            logger.error(f"Error creating snapshot: {e}")
+            return None
+
+    # ------------------------------------------------------------------
+    # Attribute CRUD
+    # ------------------------------------------------------------------
+
     def createAttribute(
         self,
         attributeId: str,

modules/features/neutralization/neutralizePlayground.py

@@ -6,7 +6,7 @@ from typing import Any, Dict, List, Optional
 from urllib.parse import urlparse, unquote
 
 from modules.datamodels.datamodelUam import User
-from .datamodelFeatureNeutralizer import DataNeutralizerAttributes, DataNeutraliserConfig
+from .datamodelFeatureNeutralizer import DataNeutralizerAttributes, DataNeutraliserConfig, DataNeutralizationSnapshot
 from .interfaceFeatureNeutralizer import getInterface as _getNeutralizerInterface
 from modules.serviceHub import getInterface as getServices
 
@@ -86,7 +86,7 @@ class NeutralizationPlayground:
                     'neutralized_file_id': None,
                     'processed_info': {'type': 'error', 'error': 'File could not be decoded as text. Supported: UTF-8, Latin-1. For PDF/Word/Excel, use supported binary formats.'}
                 }
-        result = self.services.neutralization.processText(text_content)
+        result = await self.services.neutralization.processTextAsync(text_content)
         result['neutralized_file_name'] = f'neutralized_{filename}'
         # Save neutralized text as file to user files
         if self.services.interfaceDbComponent and result.get('neutralized_text') is not None:
@@ -198,12 +198,28 @@ class NeutralizationPlayground:
         """Resolve UIDs in neutralized text back to original text"""
         return self.services.neutralization.resolveText(text)
 
+    def getSnapshots(self) -> List[DataNeutralizationSnapshot]:
+        """Return stored neutralization text snapshots."""
+        try:
+            return self.services.neutralization.getSnapshots()
+        except Exception as e:
+            logger.error(f"Error getting snapshots: {e}")
+            return []
+
     def getAttributes(self, fileId: str = None) -> List[DataNeutralizerAttributes]:
         """Get neutralization attributes, optionally filtered by file ID"""
         try:
             allAttributes = self.services.neutralization.getAttributes()
             if fileId:
-                return [attr for attr in allAttributes if attr.fileId == fileId]
+                want = str(fileId).strip()
+
+                def _matches(a: DataNeutralizerAttributes) -> bool:
+                    af = a.fileId
+                    if af is None or (isinstance(af, str) and not str(af).strip()):
+                        return False
+                    return str(af).strip() == want
+
+                return [attr for attr in allAttributes if _matches(attr)]
             return allAttributes
         except Exception as e:
             logger.error(f"Error getting attributes: {str(e)}")
@@ -396,7 +412,7 @@ class SharepointProcessor:
                             textContent = fileContent.decode('utf-8')
                         except UnicodeDecodeError:
                             textContent = fileContent.decode('latin-1')
-                        result = self.services.neutralization.processText(textContent)
+                        result = await self.services.neutralization.processTextAsync(textContent)
                         content_to_upload = (result.get('neutralized_text') or '').encode('utf-8')
 
                     neutralizedFilename = f"neutralized_{fileInfo['name']}"

modules/features/neutralization/routeFeatureNeutralizer.py

@@ -8,12 +8,33 @@ import logging
 from modules.auth import limiter, getRequestContext, RequestContext
 
 # Import interfaces
-from .datamodelFeatureNeutralizer import DataNeutraliserConfig, DataNeutralizerAttributes
+from .datamodelFeatureNeutralizer import DataNeutraliserConfig, DataNeutralizerAttributes, DataNeutralizationSnapshot
 from .neutralizePlayground import NeutralizationPlayground
 
 # Configure logger
 logger = logging.getLogger(__name__)
 
+
+def _assertFeatureInstancePathMatchesContext(featureInstanceIdFromPath: str, context: RequestContext) -> None:
+    """Reject path/instance mismatch when request context already carries an instance id."""
+    ctxId = str(context.featureInstanceId).strip() if getattr(context, "featureInstanceId", None) else ""
+    pathId = (featureInstanceIdFromPath or "").strip()
+    if ctxId and pathId and pathId != ctxId:
+        raise HTTPException(
+            status_code=status.HTTP_403_FORBIDDEN,
+            detail="Feature instance id in URL does not match request context (X-Instance-Id)",
+        )
+
+
+def _fetchNeutralizationAttributes(context: RequestContext, fileId: Optional[str]) -> List[DataNeutralizerAttributes]:
+    service = NeutralizationPlayground(
+        context.user,
+        str(context.mandateId) if context.mandateId else "",
+        featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None,
+    )
+    return service.getAttributes(fileId)
+
+
 # Create router for neutralization endpoints
 router = APIRouter(
     prefix="/api/neutralization",
@@ -208,15 +229,9 @@ def get_neutralization_attributes(
 ) -> List[DataNeutralizerAttributes]:
     """Get neutralization attributes, optionally filtered by file ID"""
     try:
-        service = NeutralizationPlayground(
-            context.user,
-            str(context.mandateId) if context.mandateId else "",
-            featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None
-        )
-        attributes = service.getAttributes(fileId)
-        
-        return attributes
-        
+        return _fetchNeutralizationAttributes(context, fileId)
+    except HTTPException:
+        raise
     except Exception as e:
         logger.error(f"Error getting neutralization attributes: {str(e)}")
         raise HTTPException(
@@ -224,6 +239,72 @@ def get_neutralization_attributes(
             detail=f"Error getting neutralization attributes: {str(e)}"
         )
 
+
+@router.get("/{feature_instance_id}/attributes", response_model=List[DataNeutralizerAttributes])
+@limiter.limit("30/minute")
+def get_neutralization_attributes_scoped(
+    request: Request,
+    feature_instance_id: str = Path(..., description="Workspace / feature instance id (must match X-Instance-Id when set)"),
+    fileId: Optional[str] = Query(None, description="Filter by file ID"),
+    context: RequestContext = Depends(getRequestContext),
+) -> List[DataNeutralizerAttributes]:
+    """Same as GET /attributes; path includes instance id for workspace UI compatibility."""
+    _assertFeatureInstancePathMatchesContext(feature_instance_id, context)
+    try:
+        return _fetchNeutralizationAttributes(context, fileId)
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting neutralization attributes: {str(e)}")
+        raise HTTPException(
+            status_code=status.HTTP_500_INTERNAL_SERVER_ERROR,
+            detail=f"Error getting neutralization attributes: {str(e)}"
+        )
+
+@router.get("/snapshots", response_model=List[DataNeutralizationSnapshot])
+@limiter.limit("30/minute")
+def get_neutralization_snapshots(
+    request: Request,
+    context: RequestContext = Depends(getRequestContext),
+) -> List[DataNeutralizationSnapshot]:
+    """Return neutralized-text snapshots (full text with placeholders) for the current feature instance."""
+    try:
+        service = NeutralizationPlayground(
+            context.user,
+            str(context.mandateId) if context.mandateId else "",
+            featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None,
+        )
+        return service.getSnapshots()
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting neutralization snapshots: {e}")
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
+
+
+@router.get("/{feature_instance_id}/snapshots", response_model=List[DataNeutralizationSnapshot])
+@limiter.limit("30/minute")
+def get_neutralization_snapshots_scoped(
+    request: Request,
+    feature_instance_id: str = Path(..., description="Workspace instance id (must match X-Instance-Id when set)"),
+    context: RequestContext = Depends(getRequestContext),
+) -> List[DataNeutralizationSnapshot]:
+    """Same as GET /snapshots; path includes instance id for workspace UI (explicit scope)."""
+    _assertFeatureInstancePathMatchesContext(feature_instance_id, context)
+    try:
+        service = NeutralizationPlayground(
+            context.user,
+            str(context.mandateId) if context.mandateId else "",
+            featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None,
+        )
+        return service.getSnapshots()
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error getting neutralization snapshots (scoped): {e}")
+        raise HTTPException(status_code=status.HTTP_500_INTERNAL_SERVER_ERROR, detail=str(e))
+
+
 @router.post("/process-sharepoint", response_model=Dict[str, Any])
 @limiter.limit("5/minute")
 async def process_sharepoint_files(
@@ -317,6 +398,21 @@ def get_neutralization_stats(
             detail=f"Error getting neutralization stats: {str(e)}"
         )
 
+def _deleteSingleNeutralizationAttribute(context: RequestContext, attributeId: str) -> Dict[str, str]:
+    service = NeutralizationPlayground(
+        context.user,
+        str(context.mandateId) if context.mandateId else "",
+        featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None,
+    )
+    success = service.deleteAttribute(attributeId)
+    if success:
+        return {"message": f"Attribute {attributeId} deleted"}
+    raise HTTPException(
+        status_code=status.HTTP_404_NOT_FOUND,
+        detail=f"Attribute {attributeId} not found",
+    )
+
+
 @router.delete("/attributes/single/{attributeId}", response_model=Dict[str, str])
 @limiter.limit("30/minute")
 def deleteAttribute(
@@ -326,20 +422,7 @@ def deleteAttribute(
 ) -> Dict[str, str]:
     """Delete a single neutralization attribute by ID."""
     try:
-        service = NeutralizationPlayground(
-            context.user,
-            str(context.mandateId) if context.mandateId else "",
-            featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None
-        )
-        success = service.deleteAttribute(attributeId)
-
-        if success:
-            return {"message": f"Attribute {attributeId} deleted"}
-        else:
-            raise HTTPException(
-                status_code=status.HTTP_404_NOT_FOUND,
-                detail=f"Attribute {attributeId} not found"
-            )
+        return _deleteSingleNeutralizationAttribute(context, attributeId)
     except HTTPException:
         raise
     except Exception as e:
@@ -347,6 +430,40 @@ def deleteAttribute(
         raise HTTPException(status_code=500, detail=str(e))
 
 
+@router.delete("/{feature_instance_id}/attributes/single/{attributeId}", response_model=Dict[str, str])
+@limiter.limit("30/minute")
+def deleteAttributeScoped(
+    request: Request,
+    feature_instance_id: str = Path(..., description="Workspace / feature instance id"),
+    attributeId: str = Path(..., description="Attribute ID to delete"),
+    context: RequestContext = Depends(getRequestContext),
+) -> Dict[str, str]:
+    """Same as DELETE /attributes/single/{attributeId}; path includes instance id for workspace UI."""
+    _assertFeatureInstancePathMatchesContext(feature_instance_id, context)
+    try:
+        return _deleteSingleNeutralizationAttribute(context, attributeId)
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error deleting attribute: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
+
+
+def _retriggerNeutralizationBody(context: RequestContext, fileId: str) -> Dict[str, str]:
+    if not fileId:
+        raise HTTPException(
+            status_code=status.HTTP_400_BAD_REQUEST,
+            detail="fileId is required",
+        )
+    service = NeutralizationPlayground(
+        context.user,
+        str(context.mandateId) if context.mandateId else "",
+        featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None,
+    )
+    service.cleanupFileAttributes(fileId)
+    return {"message": f"Neutralization re-triggered for file {fileId}", "fileId": fileId}
+
+
 @router.post("/retrigger", response_model=Dict[str, str])
 @limiter.limit("10/minute")
 def retriggerNeutralization(
@@ -356,20 +473,26 @@ def retriggerNeutralization(
 ) -> Dict[str, str]:
     """Re-trigger neutralization for a specific file."""
     try:
-        fileId = retriggerData.get("fileId", "")
-        if not fileId:
-            raise HTTPException(
-                status_code=status.HTTP_400_BAD_REQUEST,
-                detail="fileId is required"
-            )
+        return _retriggerNeutralizationBody(context, retriggerData.get("fileId", ""))
+    except HTTPException:
+        raise
+    except Exception as e:
+        logger.error(f"Error re-triggering neutralization: {str(e)}")
+        raise HTTPException(status_code=500, detail=str(e))
 
-        service = NeutralizationPlayground(
-            context.user,
-            str(context.mandateId) if context.mandateId else "",
-            featureInstanceId=str(context.featureInstanceId) if context.featureInstanceId else None
-        )
-        service.cleanupFileAttributes(fileId)
-        return {"message": f"Neutralization re-triggered for file {fileId}", "fileId": fileId}
+
+@router.post("/{feature_instance_id}/retrigger", response_model=Dict[str, str])
+@limiter.limit("10/minute")
+def retriggerNeutralizationScoped(
+    request: Request,
+    feature_instance_id: str = Path(..., description="Workspace / feature instance id"),
+    retriggerData: Dict[str, str] = Body(...),
+    context: RequestContext = Depends(getRequestContext),
+) -> Dict[str, str]:
+    """Same as POST /retrigger; path includes instance id for workspace UI compatibility."""
+    _assertFeatureInstancePathMatchesContext(feature_instance_id, context)
+    try:
+        return _retriggerNeutralizationBody(context, retriggerData.get("fileId", ""))
     except HTTPException:
         raise
     except Exception as e:

modules/features/neutralization/serviceNeutralization/mainServiceNeutralization.py

@@ -60,6 +60,12 @@ class NeutralizationService:
                 mandateId=serviceCenter.mandateId or dbApp.mandateId,
                 featureInstanceId=getattr(serviceCenter, 'featureInstanceId', None) or getattr(dbApp, 'featureInstanceId', None)
             )
+        elif serviceCenter and getattr(serviceCenter, "user", None):
+            self.interfaceNeutralizer = getNeutralizerInterface(
+                currentUser=serviceCenter.user,
+                mandateId=getattr(serviceCenter, 'mandateId', None) or getattr(serviceCenter, 'mandate_id', None),
+                featureInstanceId=getattr(serviceCenter, 'featureInstanceId', None) or getattr(serviceCenter, 'feature_instance_id', None),
+            )
         
         namesList = NamesToParse if isinstance(NamesToParse, list) else []
         self.NamesToParse = namesList
@@ -82,11 +88,213 @@ class NeutralizationService:
     
     # Public API: process text or file
 
-    def processText(self, text: str) -> Dict[str, Any]:
-        """Neutralize a raw text string and return a standard result dict."""
-        result = self._neutralizeText(text, 'text')
-        self._persistAttributes(result.get('mapping', {}), None)
-        return result
+    _NEUT_INSTRUCTION = (
+        "Analyze the following text and identify ALL sensitive content that must be neutralized:\n"
+        "1. Personal data (PII): names of persons, email addresses, phone numbers, "
+        "physical addresses, ID numbers, dates of birth, financial data (IBAN, account numbers), "
+        "social security numbers\n"
+        "2. Protected business logic: proprietary algorithms, trade secrets, confidential "
+        "processes, internal procedures, code snippets that reveal implementation details\n"
+        "3. Named entities: company names, product names, project names, brand names\n\n"
+        "Return ONLY a JSON array (no markdown, no explanation):\n"
+        '[{"text":"exact substring","type":"name|email|phone|address|id|financial|logic|company|product|location|other"}]\n\n'
+        "Rules:\n"
+        "- Every entry's 'text' must be an exact, verbatim substring of the input.\n"
+        "- Do NOT include generic words, common language constructs or non-sensitive terms.\n"
+        "- If nothing is sensitive, return [].\n\n"
+    )
+    _BYTES_PER_TOKEN = 3
+    _SELECTOR_MAX_RATIO = 0.8
+    _CHUNK_SAFETY_MARGIN = 0.9
+
+    def _resolveNeutModel(self):
+        """Query the model registry for the best NEUTRALIZATION_TEXT model.
+        Returns the model object (with contextLength etc.) or None."""
+        try:
+            from modules.aicore.aicoreModelRegistry import modelRegistry
+            from modules.aicore.aicoreModelSelector import modelSelector as _modSel
+            from modules.datamodels.datamodelAi import AiCallOptions, OperationTypeEnum
+
+            _models = modelRegistry.getAvailableModels()
+            _opts = AiCallOptions(operationType=OperationTypeEnum.NEUTRALIZATION_TEXT)
+            _failover = _modSel.getFailoverModelList("x", "", _opts, _models)
+            return _failover[0] if _failover else None
+        except Exception as _e:
+            logger.warning(f"_resolveNeutModel failed: {_e}")
+            return None
+
+    def _calcMaxChunkChars(self, model) -> int:
+        """Derive the maximum text-chunk size (in characters) from the selected
+        model's contextLength, mirroring the rules in aicoreModelSelector:
+          promptTokens = promptBytes / 3  must be  <= contextLength * 0.8
+        Subtract the instruction overhead and apply a safety margin."""
+        if not model or getattr(model, 'contextLength', 0) <= 0:
+            return 5000
+        _instructionBytes = len(self._NEUT_INSTRUCTION.encode('utf-8')) + 30
+        _maxPromptBytes = int(model.contextLength * self._SELECTOR_MAX_RATIO * self._BYTES_PER_TOKEN)
+        _maxChunkChars = int((_maxPromptBytes - _instructionBytes) * self._CHUNK_SAFETY_MARGIN)
+        return max(_maxChunkChars, 500)
+
+    @staticmethod
+    def _splitTextIntoChunks(text: str, maxChars: int) -> List[str]:
+        """Split *text* into chunks of at most *maxChars*, preferring paragraph
+        then sentence boundaries so that the LLM sees coherent blocks."""
+        if len(text) <= maxChars:
+            return [text]
+
+        chunks: List[str] = []
+        remaining = text
+        while remaining:
+            if len(remaining) <= maxChars:
+                chunks.append(remaining)
+                break
+            _cut = maxChars
+            _para = remaining.rfind("\n\n", 0, _cut)
+            if _para > maxChars // 3:
+                _cut = _para + 2
+            else:
+                _nl = remaining.rfind("\n", 0, _cut)
+                if _nl > maxChars // 3:
+                    _cut = _nl + 1
+                else:
+                    _dot = remaining.rfind(". ", 0, _cut)
+                    if _dot > maxChars // 3:
+                        _cut = _dot + 2
+                    else:
+                        _sp = remaining.rfind(" ", 0, _cut)
+                        if _sp > maxChars // 3:
+                            _cut = _sp + 1
+            chunks.append(remaining[:_cut])
+            remaining = remaining[_cut:]
+        return chunks
+
+    async def _analyseChunk(self, aiService, chunkText: str) -> List[dict]:
+        """Send one chunk to the NEUTRALIZATION_TEXT model, return raw findings list."""
+        from modules.datamodels.datamodelAi import AiCallRequest, AiCallOptions, OperationTypeEnum
+
+        _prompt = self._NEUT_INSTRUCTION + "Text to analyze:\n---\n" + chunkText + "\n---"
+        _request = AiCallRequest(
+            prompt=_prompt,
+            options=AiCallOptions(operationType=OperationTypeEnum.NEUTRALIZATION_TEXT),
+        )
+        _response = await aiService.callAi(_request)
+        if not _response or not getattr(_response, 'content', None):
+            raise RuntimeError(
+                "Neutralization AI call returned no response "
+                "(no model available for NEUTRALIZATION_TEXT?)"
+            )
+        if getattr(_response, 'errorCount', 0) > 0 or getattr(_response, 'modelName', '') == 'error':
+            raise RuntimeError(
+                f"Neutralization AI call failed: {_response.content}"
+            )
+        _content = _response.content.strip()
+        if _content.startswith("```"):
+            _content = _content.split("\n", 1)[-1].rsplit("```", 1)[0].strip()
+        try:
+            return json.loads(_content)
+        except json.JSONDecodeError:
+            _bracket = _content.find("[")
+            if _bracket >= 0:
+                try:
+                    return json.loads(_content[_bracket:])
+                except json.JSONDecodeError:
+                    pass
+        return []
+
+    async def processTextAsync(self, text: str, fileId: Optional[str] = None) -> Dict[str, Any]:
+        """AI-powered text neutralization with automatic chunking.
+
+        If *text* exceeds the safe token budget for the neutralization model
+        it is split into smaller chunks, each analysed separately.  Findings
+        are merged and de-duplicated before placeholder replacement.
+
+        Regex patterns run as a supplementary pass to catch anything the
+        model missed.
+        """
+        import uuid as _uuid
+
+        aiService = None
+        if self._getService:
+            try:
+                aiService = self._getService("ai")
+            except Exception:
+                pass
+
+        aiMapping: Dict[str, str] = {}
+
+        if not aiService or not hasattr(aiService, 'callAi'):
+            raise RuntimeError("Neutralization requires an AI service but none is available")
+
+        if text.strip():
+            _neutModel = self._resolveNeutModel()
+            _maxChunkChars = self._calcMaxChunkChars(_neutModel)
+            logger.info(
+                f"processTextAsync: model={getattr(_neutModel, 'name', '?')}, "
+                f"contextLength={getattr(_neutModel, 'contextLength', '?')} tokens, "
+                f"maxChunkChars={_maxChunkChars}"
+            )
+
+            _chunks = self._splitTextIntoChunks(text, _maxChunkChars)
+            if len(_chunks) > 1:
+                logger.info(
+                    f"processTextAsync: text ({len(text)} chars) "
+                    f"split into {len(_chunks)} chunk(s) of max {_maxChunkChars} chars"
+                )
+
+            for _chunkIdx, _chunkText in enumerate(_chunks):
+                _findings = await self._analyseChunk(aiService, _chunkText)
+                if not isinstance(_findings, list):
+                    continue
+                for _f in _findings:
+                    if not isinstance(_f, dict):
+                        continue
+                    _origText = _f.get("text", "")
+                    _patType = _f.get("type", "other").lower()
+                    if not _origText or _origText not in text:
+                        continue
+                    if _origText in aiMapping:
+                        continue
+                    _uid = str(_uuid.uuid4())
+                    _placeholder = f"[{_patType}.{_uid}]"
+                    aiMapping[_origText] = _placeholder
+
+            logger.info(f"AI neutralization found {len(aiMapping)} item(s)"
+                        + (f" across {len(_chunks)} chunk(s)" if len(_chunks) > 1 else ""))
+
+        neutralizedText = text
+        for _orig, _ph in sorted(aiMapping.items(), key=lambda x: -len(x[0])):
+            neutralizedText = neutralizedText.replace(_orig, _ph)
+
+        regexMapping: Dict[str, str] = {}
+        finalText = neutralizedText
+
+        allMapping = {**aiMapping, **regexMapping}
+        if allMapping:
+            _loop = asyncio.get_event_loop()
+            await _loop.run_in_executor(
+                None, self._persistAttributes, allMapping, fileId
+            )
+            logger.debug(f"processTextAsync: {len(allMapping)} attribute(s) persisted")
+
+        return {
+            'neutralized_text': finalText,
+            'mapping': allMapping,
+            'attributes': [
+                NeutralizationAttribute(original=k, placeholder=v)
+                for k, v in allMapping.items()
+            ],
+            'processed_info': {'type': 'text', 'ai_findings': len(aiMapping), 'regex_findings': len(regexMapping)},
+        }
+
+    def processText(self, text: str, fileId: Optional[str] = None) -> Dict[str, Any]:
+        """Sync wrapper around processTextAsync.  Propagates errors."""
+        try:
+            return asyncio.run(self.processTextAsync(text, fileId))
+        except RuntimeError as _re:
+            if "cannot be called from a running event loop" in str(_re):
+                loop = asyncio.get_event_loop()
+                return loop.run_until_complete(self.processTextAsync(text, fileId))
+            raise
 
     def processFile(self, fileId: str) -> Dict[str, Any]:
         """Neutralize a file referenced by its fileId using component interface.
@@ -153,8 +361,7 @@ class NeutralizationService:
                 raise ValueError("Unable to decode file content as text.")
             textContent = decoded
 
-        result = self._neutralizeText(textContent, textType)
-        self._persistAttributes(result.get('mapping', {}), fileId)
+        result = self.processText(textContent, fileId)
         if fileName:
             result['neutralized_file_name'] = f"neutralized_{fileName}"
         result['file_id'] = fileId
@@ -319,6 +526,22 @@ class NeutralizationService:
             return False
         return self.interfaceNeutralizer.deleteNeutralizationAttributes(fileId)
 
+    def getSnapshots(self):
+        if not self.interfaceNeutralizer:
+            return []
+        return self.interfaceNeutralizer.getSnapshots()
+
+    def clearSnapshots(self) -> int:
+        if not self.interfaceNeutralizer:
+            return 0
+        return self.interfaceNeutralizer.clearSnapshots()
+
+    def saveSnapshot(self, sourceLabel: str, neutralizedText: str, placeholderCount: int = 0):
+        if not self.interfaceNeutralizer:
+            logger.warning("saveSnapshot: interfaceNeutralizer is None — snapshot not stored")
+            return None
+        return self.interfaceNeutralizer.createSnapshot(sourceLabel, neutralizedText, placeholderCount)
+
     def _persistAttributes(self, mapping: Dict[str, str], fileId: Optional[str]) -> None:
         """Persist mapping to DB for resolve to work. mapping: originalText -> placeholder e.g. '[email.uuid]'"""
         if not self.interfaceNeutralizer or not mapping:
@@ -393,7 +616,7 @@ class NeutralizationService:
                 except Exception as _imgErr:
                     logger.warning(f"Image check failed in binary file '{fileName}': {_imgErr}, removing (fail-safe)")
                 continue
-            nr = self._neutralizeText(str(data), 'text' if type_group != 'table' else 'csv')
+            nr = await self.processTextAsync(str(data), fileId)
             proc = nr.get('processed_info', {}) or {}
             if isinstance(proc, dict) and proc.get('type') == 'error':
                 neutralization_error = proc.get('error', 'Neutralization failed')
@@ -402,7 +625,6 @@ class NeutralizationService:
             all_mapping.update(mapping)
             new_part = {**p, 'data': neu_text}
             neutralized_parts.append(new_part)
-        self._persistAttributes(all_mapping, fileId)
 
         # 3. PDF: Use in-place only; no fallback to render
         if mimeType == "application/pdf":
@@ -546,10 +768,31 @@ class NeutralizationService:
 
     # Helper functions
 
+    def _neutralizeTextLight(self, text: str) -> Dict[str, Any]:
+        """Regex-only supplementary pass using already-initialised processors.
+
+        Unlike ``_neutralizeText`` this does **no** DB I/O
+        (``_reloadNamesFromConfig`` is skipped) so it is safe to call from
+        an async context without blocking the event-loop or risking a
+        DB-connection-pool deadlock during parallel document processing.
+        """
+        try:
+            data, mapping, replaced_fields, processed_info = self.textProcessor.processTextContent(text)
+            neutralized_text = str(data)
+            attributes = [NeutralizationAttribute(original=k, placeholder=v) for k, v in mapping.items()]
+            return NeutralizationResult(
+                neutralized_text=neutralized_text,
+                mapping=mapping,
+                attributes=attributes,
+                processed_info=processed_info,
+            ).model_dump()
+        except Exception as e:
+            logger.warning(f"_neutralizeTextLight error: {e}")
+            return {'neutralized_text': text, 'mapping': {}, 'attributes': [], 'processed_info': {'type': 'error', 'error': str(e)}}
+
     def _neutralizeText(self, text: str, textType: str = None) -> Dict[str, Any]:
         """Process text and return unified dict for API consumption."""
         try:
-            # Reload names from config before processing to ensure we have the latest names
             self._reloadNamesFromConfig()
             
             # Auto-detect content type if not provided

modules/features/workspace/routeFeatureWorkspace.py

@@ -689,6 +689,9 @@ async def _runWorkspaceAgent(
 
         if allowedProviders:
             aiService.services.allowedProviders = allowedProviders
+            logger.info(f"Workspace agent: allowedProviders={allowedProviders}")
+        else:
+            logger.debug("Workspace agent: no allowedProviders in request")
         if requireNeutralization is not None:
             ctx.requireNeutralization = requireNeutralization
 

modules/serviceCenter/services/serviceAgent/mainServiceAgent.py

@@ -690,8 +690,8 @@ def _registerCoreTools(registry: ToolRegistry, services):
                         if _fileNeedNeutralize:
                             try:
                                 _nSvc = services.getService("neutralization") if hasattr(services, "getService") else None
-                                if _nSvc and hasattr(_nSvc, 'processText'):
-                                    _nResult = _nSvc.processText(text)
+                                if _nSvc and hasattr(_nSvc, 'processTextAsync'):
+                                    _nResult = await _nSvc.processTextAsync(text, fileId)
                                     if _nResult and _nResult.get("neutralized_text"):
                                         text = _nResult["neutralized_text"]
                                         logger.debug(f"readFile: neutralized text for file {fileId}")
@@ -3054,7 +3054,7 @@ def _registerCoreTools(registry: ToolRegistry, services):
             if not neutralizationService.interfaceDbComponent:
                 neutralizationService.interfaceDbComponent = services.chat.interfaceDbComponent
             if text:
-                result = neutralizationService.processText(text)
+                result = await neutralizationService.processTextAsync(text, fileId or None)
             else:
                 result = neutralizationService.processFile(fileId)
             if result:

modules/serviceCenter/services/serviceAi/mainServiceAi.py

@@ -181,13 +181,11 @@ class AiService:
         _wasNeutralized = False
         _excludedDocs: List[str] = []
         if self._shouldNeutralize(request):
-            request, _wasNeutralized, _excludedDocs = self._neutralizeRequest(request)
+            request, _wasNeutralized, _excludedDocs = await self._neutralizeRequest(request)
             if _excludedDocs:
                 logger.warning(f"Neutralization partial failures (continuing): {_excludedDocs}")
         
-        # Set billing callback on aiObjects BEFORE the AI call
-        # This callback is invoked by _callWithModel() after EVERY individual model call
-        # For parallel content parts (e.g., 200 MB doc), each model call creates its own transaction
+        logger.debug("callAi: neutralization phase done, starting main AI call")
         self.aiObjects.billingCallback = self._createBillingCallback()
         
         try:
@@ -229,10 +227,11 @@ class AiService:
         _wasNeutralized = False
         _excludedDocs: List[str] = []
         if self._shouldNeutralize(request):
-            request, _wasNeutralized, _excludedDocs = self._neutralizeRequest(request)
+            request, _wasNeutralized, _excludedDocs = await self._neutralizeRequest(request)
             if _excludedDocs:
                 logger.warning(f"Neutralization partial failures in stream (continuing): {_excludedDocs}")
 
+        logger.debug("callAiStream: neutralization phase done, starting main AI stream")
         self.aiObjects.billingCallback = self._createBillingCallback()
         try:
             async for chunk in self.aiObjects.callWithTextContextStream(request):
@@ -557,6 +556,25 @@ detectedIntent-Werte:
     # NEUTRALIZATION: Centralized prompt neutralization / response rehydration
     # =========================================================================
 
+    async def _hasNeutralizationModel(self) -> bool:
+        """Fast check: is at least one model available for NEUTRALIZATION_TEXT
+        given the current effective provider list?  No AI call is made."""
+        try:
+            from modules.aicore.aicoreModelRegistry import modelRegistry
+            from modules.aicore.aicoreModelSelector import modelSelector as _modSel
+            from modules.datamodels.datamodelAi import AiCallOptions, OperationTypeEnum
+
+            _models = modelRegistry.getAvailableModels()
+            _providers = self._calculateEffectiveProviders()
+            if _providers:
+                _models = [m for m in _models if m.connectorType in _providers]
+            _opts = AiCallOptions(operationType=OperationTypeEnum.NEUTRALIZATION_TEXT)
+            _failover = _modSel.getFailoverModelList("x", "", _opts, _models)
+            return bool(_failover)
+        except Exception as _e:
+            logger.warning(f"_hasNeutralizationModel check failed: {_e}")
+            return True
+
     def _shouldNeutralize(self, request: AiCallRequest) -> bool:
         """Check if this AI request should have neutralization applied.
 
@@ -566,11 +584,17 @@ detectedIntent-Werte:
         3. Per-request (request.requireNeutralization)
 
         No source can override another's True with False.
+        Neutralization calls themselves (NEUTRALIZATION_TEXT / NEUTRALIZATION_IMAGE)
+        are never re-neutralized (recursion guard).
         """
         try:
             if not request.prompt and not request.messages and not request.context:
                 return False
 
+            _opType = request.options.operationType if request.options else None
+            if _opType in (OperationTypeEnum.NEUTRALIZATION_TEXT, OperationTypeEnum.NEUTRALIZATION_IMAGE):
+                return False
+
             _sources = []
 
             # Source 1: Feature-Instance config
@@ -600,11 +624,15 @@ detectedIntent-Werte:
             logger.error(f"_shouldNeutralize check failed: {e} — defaulting to False")
             return False
 
-    def _neutralizeRequest(self, request: AiCallRequest) -> Tuple[AiCallRequest, bool, List[str]]:
-        """Neutralize the prompt text and messages in an AiCallRequest.
+    async def _neutralizeRequest(self, request: AiCallRequest) -> Tuple[AiCallRequest, bool, List[str]]:
+        """Neutralize the prompt text and messages in an AiCallRequest (async).
 
         Returns (modifiedRequest, wasNeutralized, excludedDocs).
 
+        Uses ``processTextAsync`` which calls AI with NEUTRALIZATION_TEXT
+        to identify PII, protected logic and names — then applies regex as
+        supplementary pass.
+
         FAILSAFE behaviour when ``requireNeutralization is True`` (explicit):
         - Service unavailable → raises (caller must not send raw data to AI).
         - Prompt neutralization fails → raises.
@@ -619,7 +647,7 @@ detectedIntent-Werte:
         excludedDocs: List[str] = []
 
         neutralSvc = self._get_service("neutralization")
-        if not neutralSvc or not hasattr(neutralSvc, 'processText'):
+        if not neutralSvc or not hasattr(neutralSvc, 'processTextAsync'):
             if _hardMode:
                 raise RuntimeError("Neutralization explicitly required but service unavailable — AI call BLOCKED")
             logger.warning("Neutralization required by config but service unavailable — continuing without neutralization")
@@ -627,13 +655,25 @@ detectedIntent-Werte:
             return request, False, excludedDocs
 
         _wasNeutralized = False
+        _snapshots: list = []
+
+        if _hardMode:
+            _hasNeutModel = await self._hasNeutralizationModel()
+            if not _hasNeutModel:
+                raise RuntimeError(
+                    "Neutralisierung ist aktiviert, aber es ist kein AI-Modell für "
+                    "NEUTRALIZATION_TEXT verfügbar. Bitte ein Modell für Neutralisierung "
+                    "freigeben oder die Neutralisierung deaktivieren."
+                )
 
         if request.prompt:
+            logger.debug(f"_neutralizeRequest: neutralizing prompt ({len(request.prompt)} chars)")
             try:
-                result = neutralSvc.processText(request.prompt)
+                result = await neutralSvc.processTextAsync(request.prompt)
                 if result and result.get("neutralized_text"):
                     request.prompt = result["neutralized_text"]
                     _wasNeutralized = True
+                    _snapshots.append(("Prompt", result["neutralized_text"], len(result.get("mapping", {}))))
                     logger.debug("Neutralized prompt in AiCallRequest")
                 else:
                     if _hardMode:
@@ -649,11 +689,13 @@ detectedIntent-Werte:
                 excludedDocs.append(f"Prompt neutralization error: {e}")
 
         if request.context:
+            logger.debug(f"_neutralizeRequest: neutralizing context ({len(request.context)} chars)")
             try:
-                result = neutralSvc.processText(request.context)
+                result = await neutralSvc.processTextAsync(request.context)
                 if result and result.get("neutralized_text"):
                     request.context = result["neutralized_text"]
                     _wasNeutralized = True
+                    _snapshots.append(("Kontext", result["neutralized_text"], len(result.get("mapping", {}))))
                     logger.debug("Neutralized context in AiCallRequest")
                 else:
                     if _hardMode:
@@ -668,6 +710,9 @@ detectedIntent-Werte:
                 logger.warning(f"Neutralization of context failed: {e} — sending original context")
                 excludedDocs.append(f"Context neutralization error: {e}")
 
+        _msgCount = len(request.messages) if request.messages and isinstance(request.messages, list) else 0
+        if _msgCount:
+            logger.debug(f"_neutralizeRequest: neutralizing {_msgCount} message(s)")
         if request.messages and isinstance(request.messages, list):
             cleanMessages = []
             for idx, msg in enumerate(request.messages):
@@ -680,24 +725,30 @@ detectedIntent-Werte:
                         cleanMessages.append(msg)
                         continue
                     try:
-                        result = neutralSvc.processText(content)
+                        result = await neutralSvc.processTextAsync(content)
                         if result and result.get("neutralized_text"):
                             msg["content"] = result["neutralized_text"]
                             _wasNeutralized = True
+                            _role = msg.get("role", "?")
+                            _snapshots.append((f"Nachricht {idx+1} ({_role})", result["neutralized_text"], len(result.get("mapping", {}))))
                             cleanMessages.append(msg)
                         else:
                             if _hardMode:
-                                logger.warning(f"Message[{idx}] neutralization empty — REMOVING message (hard mode)")
-                                excludedDocs.append(f"Message[{idx}] neutralization failed; message REMOVED")
-                            else:
+                                raise RuntimeError(
+                                    f"Neutralisierung von Nachricht {idx+1}/{_msgCount} schlug fehl "
+                                    f"(leere Antwort). Konversation kann nicht sicher gesendet werden."
+                                )
                             logger.warning(f"Neutralization of message[{idx}] returned no neutralized_text — keeping original")
                             excludedDocs.append(f"Message[{idx}] neutralization failed; original kept")
                             cleanMessages.append(msg)
+                    except RuntimeError:
+                        raise
                     except Exception as e:
                         if _hardMode:
-                            logger.warning(f"Message[{idx}] neutralization error — REMOVING message (hard mode): {e}")
-                            excludedDocs.append(f"Message[{idx}] neutralization error; message REMOVED: {e}")
-                        else:
+                            raise RuntimeError(
+                                f"Neutralisierung von Nachricht {idx+1}/{_msgCount} schlug fehl: {e}. "
+                                f"Konversation kann nicht sicher gesendet werden."
+                            ) from e
                         logger.warning(f"Neutralization of message[{idx}] failed: {e} — keeping original")
                         excludedDocs.append(f"Message[{idx}] neutralization error: {e}")
                         cleanMessages.append(msg)
@@ -710,22 +761,28 @@ detectedIntent-Werte:
                         _partType = _part.get("type", "")
                         if _partType == "text" and _part.get("text"):
                             try:
-                                _result = neutralSvc.processText(_part["text"])
+                                _result = await neutralSvc.processTextAsync(_part["text"])
                                 if _result and _result.get("neutralized_text"):
                                     _part["text"] = _result["neutralized_text"]
                                     _wasNeutralized = True
+                                    _role = msg.get("role", "?")
+                                    _snapshots.append((f"Nachricht {idx+1}.{_partIdx+1} ({_role})", _result["neutralized_text"], len(_result.get("mapping", {}))))
                                     _cleanParts.append(_part)
                                 else:
                                     if _hardMode:
-                                        logger.warning(f"Message[{idx}].content[{_partIdx}] text neutralization empty — REMOVING part")
-                                        excludedDocs.append(f"Message[{idx}].content[{_partIdx}] text removed")
-                                    else:
+                                        raise RuntimeError(
+                                            f"Neutralisierung von Nachricht {idx+1}, Teil {_partIdx+1} "
+                                            f"schlug fehl (leere Antwort)."
+                                        )
                                     _cleanParts.append(_part)
+                            except RuntimeError:
+                                raise
                             except Exception as e:
                                 if _hardMode:
-                                    logger.warning(f"Message[{idx}].content[{_partIdx}] text neutralization error — REMOVING: {e}")
-                                    excludedDocs.append(f"Message[{idx}].content[{_partIdx}] text error: {e}")
-                                else:
+                                    raise RuntimeError(
+                                        f"Neutralisierung von Nachricht {idx+1}, Teil {_partIdx+1} "
+                                        f"schlug fehl: {e}"
+                                    ) from e
                                 _cleanParts.append(_part)
                         elif _partType == "image_url":
                             if _hardMode:
@@ -738,12 +795,12 @@ detectedIntent-Werte:
                     if _cleanParts:
                         msg["content"] = _cleanParts
                         cleanMessages.append(msg)
-                    elif _hardMode:
-                        logger.warning(f"Message[{idx}] all parts removed — REMOVING message")
-                        excludedDocs.append(f"Message[{idx}] fully removed after neutralization")
+                    else:
+                        cleanMessages.append(msg)
                 else:
                     cleanMessages.append(msg)
             request.messages = cleanMessages
+            logger.debug(f"_neutralizeRequest: messages done, {len(cleanMessages)} kept of {_msgCount}")
 
         if hasattr(request, 'contentParts') and request.contentParts:
             _cleanParts = []
@@ -752,10 +809,11 @@ detectedIntent-Werte:
                 _data = getattr(_cp, 'data', '') or ''
                 if _tg in ('text', 'table') and _data:
                     try:
-                        _result = neutralSvc.processText(str(_data))
+                        _result = await neutralSvc.processTextAsync(str(_data))
                         if _result and _result.get("neutralized_text"):
                             _cp.data = _result["neutralized_text"]
                             _wasNeutralized = True
+                            _snapshots.append((f"Inhalt {_cpIdx+1} ({_tg})", _result["neutralized_text"], len(_result.get("mapping", {}))))
                             _cleanParts.append(_cp)
                         else:
                             if _hardMode:
@@ -778,7 +836,18 @@ detectedIntent-Werte:
                 else:
                     _cleanParts.append(_cp)
             request.contentParts = _cleanParts
+            logger.debug(f"_neutralizeRequest: contentParts done, {len(_cleanParts)} kept")
 
+        if _snapshots and _wasNeutralized:
+            try:
+                neutralSvc.clearSnapshots()
+                for _label, _text, _phCount in _snapshots:
+                    neutralSvc.saveSnapshot(_label, _text, _phCount)
+                logger.debug(f"_neutralizeRequest: saved {len(_snapshots)} snapshot(s)")
+            except Exception as _snapErr:
+                logger.warning(f"_neutralizeRequest: could not save snapshots: {_snapErr}")
+
+        logger.info(f"_neutralizeRequest complete: neutralized={_wasNeutralized}, excluded={len(excludedDocs)}")
         return request, _wasNeutralized, excludedDocs
 
     def _rehydrateResponse(self, responseText: str) -> str:

modules/serviceCenter/services/serviceGeneration/renderers/registry.py

@@ -11,6 +11,7 @@ import logging
 import importlib
 from typing import Dict, Type, List, Optional, Tuple
 from .documentRendererBaseTemplate import BaseRenderer
+from .codeRendererBaseTemplate import BaseCodeRenderer
 
 logger = logging.getLogger(__name__)
 
@@ -54,7 +55,7 @@ class RendererRegistry:
                         attr = getattr(module, attrName)
                         if (isinstance(attr, type) and
                             issubclass(attr, BaseRenderer) and
-                            attr != BaseRenderer and
+                            attr not in (BaseRenderer, BaseCodeRenderer) and
                             hasattr(attr, 'getSupportedFormats')):
                             self._registerRendererClass(attr)
                 
@@ -72,6 +73,8 @@ class RendererRegistry:
         """Register a renderer class keyed by (format, outputStyle)."""
         try:
             supportedFormats = rendererClass.getSupportedFormats()
+            if not supportedFormats:
+                return
             priority = rendererClass.getPriority() if hasattr(rendererClass, 'getPriority') else 0
             
             for formatName in supportedFormats:

modules/serviceCenter/services/serviceKnowledge/mainServiceKnowledge.py

@@ -158,7 +158,7 @@ class KnowledgeService:
                     if not _textContent:
                         continue
                     try:
-                        _neutralResult = _neutralSvc.processText(_textContent)
+                        _neutralResult = await _neutralSvc.processTextAsync(_textContent, fileId)
                         if _neutralResult and _neutralResult.get("neutralized_text"):
                             _obj["data"] = _neutralResult["neutralized_text"]
                             _neutralizedObjects.append(_obj)

modules/workflows/methods/methodContext/actions/neutralizeData.py

@@ -169,7 +169,7 @@ async def neutralizeData(self, parameters: Dict[str, Any]) -> ActionResult:
                                 f"Neutralizing part {len(neutralizedParts) + 1} of document {i+1}"
                             )
                             
-                            neutralizationResult = self.services.neutralization.processText(part.data)
+                            neutralizationResult = await self.services.neutralization.processTextAsync(part.data)
                             
                             if neutralizationResult and 'neutralized_text' in neutralizationResult:
                                 neutralizedData = neutralizationResult['neutralized_text']