Update process.py
Keep current logic for analysis, generation, images and add simple mode for chatbot
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6ded28e21a
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1 changed files with 47 additions and 45 deletions
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@ -60,21 +60,28 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult:
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logger.error(f"Invalid documentList type: {type(documentListParam)}")
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documentList = DocumentReferenceList(references=[])
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resultType = parameters.get("resultType", "txt")
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# Optional: if omitted, formats determined from prompt. Default "txt" is validation fallback only.
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resultType = parameters.get("resultType")
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simpleMode = parameters.get("simpleMode", False)
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if not aiPrompt:
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logger.error(f"aiPrompt is missing or empty. Parameters: {parameters}")
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return ActionResult.isFailure(
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error="AI prompt is required"
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)
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# Determine output extension and default MIME type without duplicating service logic
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normalized_result_type = (str(resultType).strip().lstrip('.').lower() or "txt")
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output_extension = f".{normalized_result_type}"
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output_mime_type = "application/octet-stream" # Prefer service-provided mimeType when available
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logger.info(f"Using result type: {resultType} -> {output_extension}, simpleMode: {simpleMode}")
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# Handle optional resultType: if None, formats determined from prompt by AI
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if resultType:
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normalized_result_type = (str(resultType).strip().lstrip('.').lower() or "txt")
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output_extension = f".{normalized_result_type}"
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output_format = output_extension.replace('.', '') or 'txt'
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logger.info(f"Using result type: {resultType} -> {output_extension}, simpleMode: {simpleMode}")
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else:
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# No format specified - AI will determine formats from prompt
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normalized_result_type = None
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output_extension = None
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output_format = None
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logger.debug("resultType not provided - formats will be determined from prompt by AI")
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output_mime_type = "application/octet-stream" # Prefer service-provided mimeType when available
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@ -96,8 +103,8 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult:
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# Update progress - preparing AI call
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self.services.chat.progressLogUpdate(operationId, 0.4, "Preparing AI call")
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# Build options
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output_format = output_extension.replace('.', '') or 'txt'
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# Build output format for simple mode
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output_format_for_call = output_extension.replace('.', '') if output_extension else (output_format or 'txt')
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# Simple mode: fast path without document generation pipeline
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if simpleMode:
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@ -132,7 +139,7 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult:
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prompt=aiPrompt,
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context=context_text if context_text else None,
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options=AiCallOptions(
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resultFormat=output_format,
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resultFormat=output_format_for_call,
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operationType=OperationTypeEnum.DATA_ANALYSE,
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processingMode=ProcessingModeEnum.BASIC
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)
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@ -158,50 +165,45 @@ async def process(self, parameters: Dict[str, Any]) -> ActionResult:
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)
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else:
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# Full mode: use unified callAiContent method
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# For document generation (xlsx, docx, pdf, etc.), use DATA_GENERATE with document intent
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from modules.datamodels.datamodelAi import OperationTypeEnum
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# Detect image generation from resultType (if provided)
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imageFormats = ["png", "jpg", "jpeg", "gif", "webp"]
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isImageGeneration = normalized_result_type in imageFormats if normalized_result_type else False
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# Always use DATA_GENERATE with document intent for ai.process
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# This ensures proper document generation pipeline is used
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# Build options with correct operationType
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from modules.datamodels.datamodelAi import OperationTypeEnum
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# resultFormat in options can be None - formats will be determined by AI if not provided
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options = AiCallOptions(
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resultFormat=output_format,
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operationType=OperationTypeEnum.DATA_GENERATE
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resultFormat=output_format, # Can be None - formats determined by AI
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operationType=OperationTypeEnum.IMAGE_GENERATE if isImageGeneration else OperationTypeEnum.DATA_GENERATE
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)
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generation_intent = "document"
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# Get generationIntent from parameters (required for DATA_GENERATE)
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# Default to "document" if not provided (most common use case)
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# For code generation, use ai.generateCode action or explicitly pass generationIntent="code"
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generationIntent = parameters.get("generationIntent", "document")
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# Update progress - calling AI
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self.services.chat.progressLogUpdate(operationId, 0.6, "Calling AI")
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# Use unified callAiContent method
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# If contentParts provided (pre-extracted), use them directly
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# Otherwise, pass documentList and let callAiContent handle Phases 5A-5E internally
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# Use unified callAiContent method with BOTH documentList and contentParts
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# Extraction is handled by AI service - no extraction here
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# outputFormat: Optional - if None, formats determined from prompt by AI
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# Note: ContentExtracted documents (from context.extractContent) are now handled
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# automatically in _extractAndPrepareContent() (Phase 5B)
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if contentParts:
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# Pre-extracted ContentParts - use them directly
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aiResponse = await self.services.ai.callAiContent(
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prompt=aiPrompt,
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options=options,
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contentParts=contentParts, # Pre-extracted ContentParts
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outputFormat=output_format,
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parentOperationId=operationId,
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generationIntent=generation_intent
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)
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else:
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# Pass documentList - callAiContent handles Phases 5A-5E internally
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# This includes automatic detection of ContentExtracted documents
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logger.info(f"ai.process: Calling callAiContent with {len(documentList.references)} document references")
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if documentList.references:
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for idx, ref in enumerate(documentList.references):
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logger.info(f" Passing reference {idx + 1}: documentId={ref.documentId}")
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aiResponse = await self.services.ai.callAiContent(
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prompt=aiPrompt,
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options=options,
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documentList=documentList, # callAiContent macht Phasen 5A-5E
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outputFormat=output_format,
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parentOperationId=operationId,
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generationIntent=generation_intent
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)
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logger.info(f"ai.process: Calling callAiContent with {len(documentList.references)} document references")
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if documentList.references:
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for idx, ref in enumerate(documentList.references):
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logger.info(f" Passing reference {idx + 1}: documentId={ref.documentId}")
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aiResponse = await self.services.ai.callAiContent(
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prompt=aiPrompt,
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options=options,
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documentList=documentList, # Pass documentList - AI service handles extraction
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contentParts=contentParts, # Pass contentParts if provided (or None)
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outputFormat=output_format, # Can be None - AI determines from prompt
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parentOperationId=operationId,
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generationIntent=generationIntent # REQUIRED for DATA_GENERATE
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)
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# Update progress - processing result
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self.services.chat.progressLogUpdate(operationId, 0.8, "Processing result")
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