content_quality_tool/attr_extraction/views.py

from rest_framework.views import APIView
from rest_framework.response import Response
from rest_framework import status
from rest_framework.parsers import MultiPartParser, FormParser
from django.db import transaction
import pandas as pd
from .models import Product, ProductType, ProductAttribute, AttributePossibleValue
from .serializers import (
    SingleProductRequestSerializer,
    BatchProductRequestSerializer,
    ProductAttributeResultSerializer, 
    BatchProductResponseSerializer,
    ProductSerializer,
    ProductTypeSerializer,
    ProductAttributeSerializer,
    AttributePossibleValueSerializer
)
from .services import ProductAttributeService
from .ocr_service import OCRService


class ExtractProductAttributesView(APIView):
    """
    API endpoint to extract product attributes for a single product by item_id.
    Fetches product details from database with source tracking.
    Returns attributes in array format: [{"value": "...", "source": "..."}]
    """

    def post(self, request):
        serializer = SingleProductRequestSerializer(data=request.data)
        if not serializer.is_valid():
            return Response({"error": serializer.errors}, status=status.HTTP_400_BAD_REQUEST)

        validated_data = serializer.validated_data
        item_id = validated_data.get("item_id")

        # Fetch product from DB
        try:
            product = Product.objects.get(item_id=item_id)
        except Product.DoesNotExist:
            return Response(
                {"error": f"Product with item_id '{item_id}' not found."},
                status=status.HTTP_404_NOT_FOUND
            )

        # Extract product details
        title = product.product_name
        short_desc = product.product_short_description
        long_desc = product.product_long_description
        image_url = product.image_path

        # Process image for OCR if required
        ocr_results = None
        ocr_text = None

        if validated_data.get("process_image", True) and image_url:
            ocr_service = OCRService()
            ocr_results = ocr_service.process_image(image_url)

            if ocr_results and ocr_results.get("detected_text"):
                ocr_attrs = ProductAttributeService.extract_attributes_from_ocr(
                    ocr_results, validated_data.get("model")
                )
                ocr_results["extracted_attributes"] = ocr_attrs

                ocr_text = "\n".join([
                    f"{item['text']} (confidence: {item['confidence']:.2f})"
                    for item in ocr_results["detected_text"]
                ])

        # Combine all product text with source tracking
        product_text, source_map = ProductAttributeService.combine_product_text(
            title=title,
            short_desc=short_desc,
            long_desc=long_desc,
            ocr_text=ocr_text
        )

        # Extract attributes with enhanced features and source tracking
        result = ProductAttributeService.extract_attributes(
            product_text=product_text,
            mandatory_attrs=validated_data["mandatory_attrs"],
            source_map=source_map,
            model=validated_data.get("model"),
            extract_additional=validated_data.get("extract_additional", True),
            multiple=validated_data.get("multiple", []),
            threshold_abs=validated_data.get("threshold_abs", 0.65),
            margin=validated_data.get("margin", 0.15),
            use_dynamic_thresholds=validated_data.get("use_dynamic_thresholds", True),
            use_adaptive_margin=validated_data.get("use_adaptive_margin", True),
            use_semantic_clustering=validated_data.get("use_semantic_clustering", True)
        )

        # Attach OCR results if available
        if ocr_results:
            result["ocr_results"] = ocr_results

        response_serializer = ProductAttributeResultSerializer(data=result)
        if response_serializer.is_valid():
            return Response(response_serializer.data, status=status.HTTP_200_OK)

        return Response(result, status=status.HTTP_200_OK)


class BatchExtractProductAttributesView(APIView):
    """
    API endpoint to extract product attributes for multiple products in batch.
    Uses item-specific mandatory_attrs with source tracking.
    Returns attributes in array format: [{"value": "...", "source": "..."}]
    """

    def post(self, request):
        serializer = BatchProductRequestSerializer(data=request.data)
        if not serializer.is_valid():
            return Response({"error": serializer.errors}, status=status.HTTP_400_BAD_REQUEST)

        validated_data = serializer.validated_data
        
        # Get batch-level settings
        product_list = validated_data.get("products", [])
        model = validated_data.get("model")
        extract_additional = validated_data.get("extract_additional", True)
        process_image = validated_data.get("process_image", True)
        multiple = validated_data.get("multiple", [])
        threshold_abs = validated_data.get("threshold_abs", 0.65)
        margin = validated_data.get("margin", 0.15)
        use_dynamic_thresholds = validated_data.get("use_dynamic_thresholds", True)
        use_adaptive_margin = validated_data.get("use_adaptive_margin", True)
        use_semantic_clustering = validated_data.get("use_semantic_clustering", True)
        
        # Extract all item_ids to query the database efficiently
        item_ids = [p['item_id'] for p in product_list] 
        
        # Fetch all products in one query
        products_queryset = Product.objects.filter(item_id__in=item_ids)
        
        # Create a dictionary for easy lookup: item_id -> Product object
        product_map = {product.item_id: product for product in products_queryset}
        found_ids = set(product_map.keys())
        
        results = []
        successful = 0
        failed = 0

        for product_entry in product_list:
            item_id = product_entry['item_id']
            # Get item-specific mandatory attributes
            mandatory_attrs = product_entry['mandatory_attrs'] 

            if item_id not in found_ids:
                failed += 1
                results.append({
                    "product_id": item_id,
                    "error": "Product not found in database"
                })
                continue

            product = product_map[item_id]
            
            try:
                title = product.product_name
                short_desc = product.product_short_description
                long_desc = product.product_long_description
                image_url = product.image_path

                ocr_results = None
                ocr_text = None

                # Image Processing Logic
                if process_image and image_url:
                    ocr_service = OCRService()
                    ocr_results = ocr_service.process_image(image_url)

                    if ocr_results and ocr_results.get("detected_text"):
                        ocr_attrs = ProductAttributeService.extract_attributes_from_ocr(
                            ocr_results, model
                        )
                        ocr_results["extracted_attributes"] = ocr_attrs
                        ocr_text = "\n".join([
                            f"{item['text']} (confidence: {item['confidence']:.2f})"
                            for item in ocr_results["detected_text"]
                        ])

                # Combine product text with source tracking
                product_text, source_map = ProductAttributeService.combine_product_text(
                    title=title,
                    short_desc=short_desc,
                    long_desc=long_desc,
                    ocr_text=ocr_text
                )

                # Attribute Extraction with source tracking (returns array format)
                extracted = ProductAttributeService.extract_attributes(
                    product_text=product_text,
                    mandatory_attrs=mandatory_attrs,
                    source_map=source_map,
                    model=model,
                    extract_additional=extract_additional,
                    multiple=multiple,
                    threshold_abs=threshold_abs,
                    margin=margin,
                    use_dynamic_thresholds=use_dynamic_thresholds,
                    use_adaptive_margin=use_adaptive_margin,
                    use_semantic_clustering=use_semantic_clustering
                )

                result = {
                    "product_id": product.item_id,
                    "mandatory": extracted.get("mandatory", {}),
                    "additional": extracted.get("additional", {}),
                }

                if ocr_results:
                    result["ocr_results"] = ocr_results

                results.append(result)
                successful += 1

            except Exception as e:
                failed += 1
                results.append({
                    "product_id": item_id,
                    "error": str(e)
                })

        batch_result = {
            "results": results,
            "total_products": len(product_list),
            "successful": successful,
            "failed": failed
        }

        response_serializer = BatchProductResponseSerializer(data=batch_result)
        if response_serializer.is_valid():
            return Response(response_serializer.data, status=status.HTTP_200_OK)

        return Response(batch_result, status=status.HTTP_200_OK)


class ProductListView(APIView):
    """
    GET API to list all products with details
    """
    def get(self, request):
        products = Product.objects.all()
        serializer = ProductSerializer(products, many=True)
        return Response(serializer.data, status=status.HTTP_200_OK)


class ProductUploadExcelView(APIView):
    """
    POST API to upload an Excel file and add data to Product model (skip duplicates)
    """
    parser_classes = (MultiPartParser, FormParser)

    def post(self, request, *args, **kwargs):
        file_obj = request.FILES.get('file')
        if not file_obj:
            return Response({'error': 'No file provided'}, status=status.HTTP_400_BAD_REQUEST)

        try:
            df = pd.read_excel(file_obj)
            df.columns = [c.strip().lower().replace(' ', '_') for c in df.columns]

            expected_cols = {
                'item_id',
                'product_name',
                'product_long_description',
                'product_short_description',
                'product_type',
                'image_path'
            }

            if not expected_cols.issubset(df.columns):
                return Response({
                    'error': 'Missing required columns',
                    'required_columns': list(expected_cols)
                }, status=status.HTTP_400_BAD_REQUEST)

            created_count = 0
            skipped_count = 0

            for _, row in df.iterrows():
                item_id = row.get('item_id', '')

                # Check if this item already exists
                if Product.objects.filter(item_id=item_id).exists():
                    skipped_count += 1
                    continue

                Product.objects.create(
                    item_id=item_id,
                    product_name=row.get('product_name', ''),
                    product_long_description=row.get('product_long_description', ''),
                    product_short_description=row.get('product_short_description', ''),
                    product_type=row.get('product_type', ''),
                    image_path=row.get('image_path', ''),
                )
                created_count += 1

            return Response({
                'message': f'Successfully uploaded {created_count} products.',
                'skipped': f'Skipped {skipped_count} duplicates.'
            }, status=status.HTTP_201_CREATED)

        except Exception as e:
            return Response({'error': str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)


class ProductAttributesUploadView(APIView):
    """
    POST API to upload an Excel file and add mandatory/additional attributes
    for product types with possible values.
    """
    parser_classes = (MultiPartParser, FormParser)

    def post(self, request):
        file_obj = request.FILES.get('file')
        if not file_obj:
            return Response({"error": "No file provided."}, status=status.HTTP_400_BAD_REQUEST)

        try:
            df = pd.read_excel(file_obj)

            required_columns = {'product_type', 'attribute_name', 'is_mandatory', 'possible_values'}
            if not required_columns.issubset(df.columns):
                return Response({
                    "error": f"Missing required columns. Found: {list(df.columns)}"
                }, status=status.HTTP_400_BAD_REQUEST)

            for _, row in df.iterrows():
                product_type_name = str(row['product_type']).strip()
                attr_name = str(row['attribute_name']).strip()
                is_mandatory = str(row['is_mandatory']).strip().lower() in ['yes', 'true', '1']
                possible_values = str(row.get('possible_values', '')).strip()

                # Get or create product type
                product_type, _ = ProductType.objects.get_or_create(name=product_type_name)

                # Get or create attribute
                attribute, _ = ProductAttribute.objects.get_or_create(
                    product_type=product_type,
                    name=attr_name,
                    defaults={'is_mandatory': is_mandatory}
                )
                attribute.is_mandatory = is_mandatory
                attribute.save()

                # Handle possible values
                AttributePossibleValue.objects.filter(attribute=attribute).delete()
                if possible_values:
                    for val in [v.strip() for v in possible_values.split(',') if v.strip()]:
                        AttributePossibleValue.objects.create(attribute=attribute, value=val)

            return Response({"message": "Attributes uploaded successfully."}, status=status.HTTP_201_CREATED)

        except Exception as e:
            return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)


class ProductTypeAttributesView(APIView):
    """
    API to view, create, update, and delete product type attributes and their possible values.
    Also supports dynamic product type creation.
    """

    def get(self, request):
        """
        Retrieve all product types with their attributes and possible values.
        """
        product_types = ProductType.objects.all()
        serializer = ProductTypeSerializer(product_types, many=True)
        
        # Transform the serialized data into the requested format
        result = []
        for pt in serializer.data:
            for attr in pt['attributes']:
                result.append({
                    'product_type': pt['name'],
                    'attribute_name': attr['name'],
                    'is_mandatory': 'Yes' if attr['is_mandatory'] else 'No',
                    'possible_values': ', '.join([pv['value'] for pv in attr['possible_values']])
                })
                
        return Response(result, status=status.HTTP_200_OK)

    def post(self, request):
        """
        Create a new product type or attribute with possible values.
        Expected payload example:
        {
            "product_type": "Hardware Screws",
            "attribute_name": "Material",
            "is_mandatory": "Yes",
            "possible_values": "Steel, Zinc Plated, Stainless Steel"
        }
        """
        try:
            product_type_name = request.data.get('product_type')
            attribute_name = request.data.get('attribute_name', '')
            is_mandatory = request.data.get('is_mandatory', '').lower() in ['yes', 'true', '1']
            possible_values = request.data.get('possible_values', '')

            if not product_type_name:
                return Response({
                    "error": "product_type is required"
                }, status=status.HTTP_400_BAD_REQUEST)

            with transaction.atomic():
                # Get or create product type
                product_type, created = ProductType.objects.get_or_create(name=product_type_name)

                if created and not attribute_name:
                    return Response({
                        "message": f"Product type '{product_type_name}' created successfully",
                        "data": {"product_type": product_type_name}
                    }, status=status.HTTP_201_CREATED)

                if attribute_name:
                    # Create attribute
                    attribute, attr_created = ProductAttribute.objects.get_or_create(
                        product_type=product_type,
                        name=attribute_name,
                        defaults={'is_mandatory': is_mandatory}
                    )
                    
                    if not attr_created:
                        return Response({
                            "error": f"Attribute '{attribute_name}' already exists for product type '{product_type_name}'"
                        }, status=status.HTTP_400_BAD_REQUEST)

                    # Handle possible values
                    if possible_values:
                        for val in [v.strip() for v in possible_values.split(',') if v.strip()]:
                            AttributePossibleValue.objects.create(attribute=attribute, value=val)

                    return Response({
                        "message": "Attribute created successfully",
                        "data": {
                            "product_type": product_type_name,
                            "attribute_name": attribute_name,
                            "is_mandatory": "Yes" if is_mandatory else "No",
                            "possible_values": possible_values
                        }
                    }, status=status.HTTP_201_CREATED)

                return Response({
                    "message": f"Product type '{product_type_name}' already exists",
                    "data": {"product_type": product_type_name}
                }, status=status.HTTP_200_OK)

        except Exception as e:
            return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)

    def put(self, request):
        """
        Update an existing product type attribute and its possible values.
        Expected payload example:
        {
            "product_type": "Hardware Screws",
            "attribute_name": "Material",
            "is_mandatory": "Yes",
            "possible_values": "Steel, Zinc Plated, Stainless Steel, Brass"
        }
        """
        try:
            product_type_name = request.data.get('product_type')
            attribute_name = request.data.get('attribute_name')
            is_mandatory = request.data.get('is_mandatory', '').lower() in ['yes', 'true', '1']
            possible_values = request.data.get('possible_values', '')

            if not all([product_type_name, attribute_name]):
                return Response({
                    "error": "product_type and attribute_name are required"
                }, status=status.HTTP_400_BAD_REQUEST)

            with transaction.atomic():
                try:
                    product_type = ProductType.objects.get(name=product_type_name)
                    attribute = ProductAttribute.objects.get(
                        product_type=product_type,
                        name=attribute_name
                    )
                except ProductType.DoesNotExist:
                    return Response({
                        "error": f"Product type '{product_type_name}' not found"
                    }, status=status.HTTP_404_NOT_FOUND)
                except ProductAttribute.DoesNotExist:
                    return Response({
                        "error": f"Attribute '{attribute_name}' not found for product type '{product_type_name}'"
                    }, status=status.HTTP_404_NOT_FOUND)

                # Update attribute
                attribute.is_mandatory = is_mandatory
                attribute.save()

                # Update possible values
                AttributePossibleValue.objects.filter(attribute=attribute).delete()
                if possible_values:
                    for val in [v.strip() for v in possible_values.split(',') if v.strip()]:
                        AttributePossibleValue.objects.create(attribute=attribute, value=val)

                return Response({
                    "message": "Attribute updated successfully",
                    "data": {
                        "product_type": product_type_name,
                        "attribute_name": attribute_name,
                        "is_mandatory": "Yes" if is_mandatory else "No",
                        "possible_values": possible_values
                    }
                }, status=status.HTTP_200_OK)

        except Exception as e:
            return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)

    def delete(self, request):
        """
        Delete a product type or a specific attribute.
        Expected payload example:
        {
            "product_type": "Hardware Screws",
            "attribute_name": "Material"
        }
        """
        try:
            product_type_name = request.data.get('product_type')
            attribute_name = request.data.get('attribute_name', '')

            if not product_type_name:
                return Response({
                    "error": "product_type is required"
                }, status=status.HTTP_400_BAD_REQUEST)

            with transaction.atomic():
                try:
                    product_type = ProductType.objects.get(name=product_type_name)
                except ProductType.DoesNotExist:
                    return Response({
                        "error": f"Product type '{product_type_name}' not found"
                    }, status=status.HTTP_404_NOT_FOUND)

                if attribute_name:
                    # Delete specific attribute
                    try:
                        attribute = ProductAttribute.objects.get(
                            product_type=product_type,
                            name=attribute_name
                        )
                        attribute.delete()
                        return Response({
                            "message": f"Attribute '{attribute_name}' deleted successfully from product type '{product_type_name}'"
                        }, status=status.HTTP_200_OK)
                    except ProductAttribute.DoesNotExist:
                        return Response({
                            "error": f"Attribute '{attribute_name}' not found for product type '{product_type_name}'"
                        }, status=status.HTTP_404_NOT_FOUND)
                else:
                    # Delete entire product type
                    product_type.delete()
                    return Response({
                        "message": f"Product type '{product_type_name}' and all its attributes deleted successfully"
                    }, status=status.HTTP_200_OK)

        except Exception as e:
            return Response({"error": str(e)}, status=status.HTTP_500_INTERNAL_SERVER_ERROR)


class ProductTypeListView(APIView):
    """
    GET API to list all product types (only names).
    """
    def get(self, request):
        product_types = ProductType.objects.values_list('name', flat=True)
        return Response({"product_types": list(product_types)}, status=status.HTTP_200_OK)