Fixes 02

modules/workflows/methods/methodOutlook.py

@@ -251,6 +251,10 @@ class MethodOutlook(MethodBase):
         if '@' in filter_text and '.' in filter_text and ' ' not in filter_text and not filter_text.startswith('from:'):
             return {"$filter": f"from/fromAddress/address eq '{filter_text}'"}
         
+        # Handle OData filter conditions (contains 'eq', 'ne', 'gt', 'lt', etc.)
+        if any(op in filter_text.lower() for op in [' eq ', ' ne ', ' gt ', ' lt ', ' ge ', ' le ', ' and ', ' or ']):
+            return {"$filter": filter_text}
+        
         # Handle text content - search in subject
         return {"$filter": f"contains(subject,'{filter_text}')"}
     

modules/workflows/methods/methodSharepoint.py

@@ -931,7 +931,8 @@ class MethodSharepoint(MethodBase):
                     return ActionResult.isFailure(error="pathQuery must start with '/' and include site name with syntax /site:<Site Display Name>/... e.g. /site:KM LayerFinance/Documents/Work")
                 
                 # Check if pathQuery contains search terms (words without proper path structure)
-                if not pathQuery.startswith('/site:') and not pathQuery.startswith('/Documents') and not pathQuery.startswith('/Shared Documents'):
+                valid_path_prefixes = ['/site:', '/Documents', '/documents', '/Shared Documents', '/shared documents']
+                if not any(pathQuery.startswith(prefix) for prefix in valid_path_prefixes):
                     return ActionResult.isFailure(error=f"Invalid pathQuery '{pathQuery}'. This appears to be search terms, not a valid SharePoint path. Use findDocumentPath action first to search for folders, then use the returned folder path as pathQuery.")
                 
                 # For pathQuery, we need to discover sites to find the specific one
@@ -1627,7 +1628,8 @@ class MethodSharepoint(MethodBase):
                     return ActionResult.isFailure(error="pathQuery must start with '/' and include site name with syntax /site:<Site Display Name>/... e.g. /site:KM LayerFinance/Documents/Work")
                 
                 # Check if pathQuery contains search terms (words without proper path structure)
-                if not pathQuery.startswith('/site:') and not pathQuery.startswith('/Documents') and not pathQuery.startswith('/Shared Documents'):
+                valid_path_prefixes = ['/site:', '/Documents', '/documents', '/Shared Documents', '/shared documents']
+                if not any(pathQuery.startswith(prefix) for prefix in valid_path_prefixes):
                     return ActionResult.isFailure(error=f"Invalid pathQuery '{pathQuery}'. This appears to be search terms, not a valid SharePoint path. Use findDocumentPath action first to search for folders, then use the returned folder path as pathQuery.")
                 
                 # For pathQuery, we need to discover sites to find the specific one

modules/workflows/processing/adaptive/contentValidator.py

@@ -46,6 +46,53 @@ class ContentValidator:
             "improvementSuggestions": [f"NEXT STEP: Fix validation error - {error}. Check system logs for more details and retry the operation."]
         }
     
+    def _isValidJsonResponse(self, response: str) -> bool:
+        """Checks if response contains valid JSON structure"""
+        try:
+            import re
+            # Look for JSON with expected structure
+            json_match = re.search(r'\{[^{}]*"overallSuccess"[^{}]*\}', response, re.DOTALL)
+            if json_match:
+                json.loads(json_match.group(0))
+                return True
+            return False
+        except:
+            return False
+    
+    def _extractFallbackValidationResult(self, response: str) -> Dict[str, Any]:
+        """Extracts validation result from malformed AI response"""
+        try:
+            import re
+            
+            # Extract key values using regex patterns
+            overall_success = re.search(r'"overallSuccess"\s*:\s*(true|false)', response, re.IGNORECASE)
+            quality_score = re.search(r'"qualityScore"\s*:\s*([0-9.]+)', response)
+            gap_analysis = re.search(r'"gapAnalysis"\s*:\s*"([^"]*)"', response)
+            
+            # Determine overall success from context if not found
+            if not overall_success:
+                # Look for positive/negative indicators in the text
+                if any(word in response.lower() for word in ['success', 'complete', 'fulfilled', 'satisfied']):
+                    overall_success = True
+                elif any(word in response.lower() for word in ['failed', 'incomplete', 'missing', 'error']):
+                    overall_success = False
+                else:
+                    overall_success = False
+            
+            return {
+                "overallSuccess": overall_success.group(1).lower() == 'true' if overall_success else False,
+                "qualityScore": float(quality_score.group(1)) if quality_score else 0.5,
+                "validationDetails": [{
+                    "documentName": "AI Validation (Fallback)",
+                    "gapAnalysis": gap_analysis.group(1) if gap_analysis else "Unable to parse detailed analysis",
+                    "successCriteriaMet": [False]  # Conservative fallback
+                }],
+                "improvementSuggestions": ["NEXT STEP: AI response was malformed - retry the operation for better results"]
+            }
+        except Exception as e:
+            logger.error(f"Fallback extraction failed: {str(e)}")
+            return None
+    
     async def _validateWithAI(self, documents: List[Any], intent: Dict[str, Any]) -> Dict[str, Any]:
         """AI-based comprehensive validation - single main function"""
         try:
@@ -81,7 +128,10 @@ Perform comprehensive validation:
 5. Identify specific gaps and issues
 6. Provide actionable next steps
 
-Respond with JSON only:
+CRITICAL: Respond with ONLY the JSON object below. Do not include any explanatory text, analysis, or other content before or after the JSON.
+
+IMPORTANT: Even if the content is binary files (like .docx, .pdf, etc.), you must still respond with JSON only. Do not explain that files are binary - just validate based on file names and types.
+
 {{
     "overallSuccess": true/false,
     "qualityScore": 0.0-1.0,
@@ -110,14 +160,63 @@ Respond with JSON only:
                 documents=None,
                 options=request_options
             )
-            if response:
-                import re
-                result = response.strip()
-                json_match = re.search(r'\{.*\}', result, re.DOTALL)
-                if json_match:
-                    result = json_match.group(0)
             
+            # If first attempt fails, try with more explicit prompt
+            if response and not self._isValidJsonResponse(response):
+                logger.warning("First AI validation attempt failed, retrying with explicit JSON-only prompt")
+                explicitPrompt = f"""
+{validationPrompt}
+
+IMPORTANT: You must respond with ONLY valid JSON. No explanations, no analysis, no text before or after. Just the JSON object.
+"""
+                response = await self.services.ai.callAi(
+                    prompt=explicitPrompt,
+                    documents=None,
+                    options=request_options
+                )
+            
+            if not response or not response.strip():
+                logger.warning("AI validation returned empty response")
+                return self._createFailedValidationResult("AI validation failed - empty response")
+            
+            # Clean and extract JSON from response
+            result = response.strip()
+            logger.debug(f"AI validation response length: {len(result)}")
+            
+            # Try to find JSON in the response with multiple strategies
+            import re
+            
+            # Strategy 1: Look for JSON in markdown code blocks
+            json_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', result, re.DOTALL)
+            if json_match:
+                result = json_match.group(1)
+                logger.debug(f"Extracted JSON from markdown code block: {result[:200]}...")
+            else:
+                # Strategy 2: Look for JSON object with proper structure
+                json_match = re.search(r'\{[^{}]*"overallSuccess"[^{}]*\}', result, re.DOTALL)
+                if not json_match:
+                    # Strategy 3: Look for any JSON object
+                    json_match = re.search(r'\{.*\}', result, re.DOTALL)
+                
+            if not json_match:
+                logger.debug(f"No JSON found in AI response, trying fallback extraction: {result[:200]}...")
+                logger.debug(f"Full AI response: {result}")
+                
+                # Try fallback extraction for text responses
+                fallback_result = self._extractFallbackValidationResult(result)
+                if fallback_result:
+                    logger.info("Using fallback text extraction for validation")
+                    return fallback_result
+                
+                logger.warning("All AI validation attempts failed - no JSON found and fallback extraction failed")
+                return self._createFailedValidationResult("AI validation failed - no JSON in response")
+            else:
+                result = json_match.group(0)
+                logger.debug(f"Extracted JSON directly: {result[:200]}...")
+            
+            try:
                 aiResult = json.loads(result)
+                logger.info("AI validation JSON parsed successfully")
                 
                 return {
                     "overallSuccess": aiResult.get("overallSuccess", False),
@@ -130,6 +229,18 @@ Respond with JSON only:
                     "improvementSuggestions": aiResult.get("improvementSuggestions", [])
                 }
                 
+            except json.JSONDecodeError as json_error:
+                logger.warning(f"All AI validation attempts failed - invalid JSON: {str(json_error)}")
+                logger.debug(f"JSON content: {result}")
+                
+                # Try to extract key information from malformed response
+                fallbackResult = self._extractFallbackValidationResult(result)
+                if fallbackResult:
+                    logger.info("Using fallback validation result from malformed JSON")
+                    return fallbackResult
+                
+                return self._createFailedValidationResult(f"AI validation failed - invalid JSON: {str(json_error)}")
+            
             return self._createFailedValidationResult("AI validation failed - no response")
             
         except Exception as e:

modules/workflows/processing/adaptive/intentAnalyzer.py

@@ -48,7 +48,8 @@ Analyze the user's intent and determine:
 3. What quality requirements they have (accuracy, completeness, format)
 4. What specific success criteria define completion
 
-Respond with JSON only:
+CRITICAL: Respond with ONLY the JSON object below. Do not include any explanatory text, analysis, or other content before or after the JSON.
+
 {{
     "primaryGoal": "The main objective the user wants to achieve",
     "dataType": "numbers|text|documents|analysis|code|unknown",
@@ -73,16 +74,62 @@ Respond with JSON only:
                 documents=None,
                 options=request_options
             )
-            if response:
-                import re
-                result = response.strip()
-                json_match = re.search(r'\{.*\}', result, re.DOTALL)
-                if json_match:
-                    result = json_match.group(0)
             
+            # If first attempt fails, try with more explicit prompt
+            if response and not self._isValidJsonResponse(response):
+                logger.debug("First AI intent analysis attempt failed, retrying with explicit JSON-only prompt")
+                explicitPrompt = f"""
+{analysisPrompt}
+
+IMPORTANT: You must respond with ONLY valid JSON. No explanations, no analysis, no text before or after. Just the JSON object.
+"""
+                response = await self.services.ai.callAi(
+                    prompt=explicitPrompt,
+                    documents=None,
+                    options=request_options
+                )
+            
+            if not response or not response.strip():
+                logger.warning("AI intent analysis returned empty response")
+                return None
+            
+            # Clean and extract JSON from response
+            result = response.strip()
+            logger.debug(f"AI intent analysis response length: {len(result)}")
+            
+            # Try to find JSON in the response with multiple strategies
+            import re
+            
+            # Strategy 1: Look for JSON in markdown code blocks
+            json_match = re.search(r'```(?:json)?\s*(\{.*?\})\s*```', result, re.DOTALL)
+            if json_match:
+                result = json_match.group(1)
+                logger.debug(f"Extracted JSON from markdown code block: {result[:200]}...")
+            else:
+                # Strategy 2: Look for JSON object with proper structure
+                json_match = re.search(r'\{[^{}]*"primaryGoal"[^{}]*\}', result, re.DOTALL)
+                if not json_match:
+                    # Strategy 3: Look for any JSON object
+                    json_match = re.search(r'\{.*\}', result, re.DOTALL)
+                
+                if not json_match:
+                    logger.warning(f"All AI intent analysis attempts failed - no JSON found in response: {result[:200]}...")
+                    logger.debug(f"Full AI response: {result}")
+                    return None
+                
+                result = json_match.group(0)
+                logger.debug(f"Extracted JSON directly: {result[:200]}...")
+            
+            try:
                 aiResult = json.loads(result)
+                logger.info("AI intent analysis JSON parsed successfully")
                 return aiResult
                 
+            except json.JSONDecodeError as json_error:
+                logger.warning(f"All AI intent analysis attempts failed - invalid JSON: {str(json_error)}")
+                logger.debug(f"JSON content: {result}")
+                return None
+            
             return None
             
         except Exception as e:
@@ -118,3 +165,16 @@ Respond with JSON only:
             "successCriteria": ["Delivers what the user requested"],
             "confidenceScore": 0.1
         }
+    
+    def _isValidJsonResponse(self, response: str) -> bool:
+        """Checks if response contains valid JSON structure"""
+        try:
+            import re
+            # Look for JSON with expected structure
+            json_match = re.search(r'\{[^{}]*"primaryGoal"[^{}]*\}', response, re.DOTALL)
+            if json_match:
+                json.loads(json_match.group(0))
+                return True
+            return False
+        except:
+            return False