' Product Classification Tool
' Classifies products into categories using AI and store taxonomy

PARAM product_name AS STRING DESCRIPTION "Product name to classify (e.g., 'nike air max shoes')"
PARAM include_suggestions AS BOOLEAN OPTIONAL DESCRIPTION "Include alternative category suggestions"

DESCRIPTION "Classify a product into the store's category taxonomy using AI"

' Load store categories for context
categories = FIND "Categories.csv"

' Build taxonomy tree for AI context
taxonomy = ""
FOR EACH cat IN categories
    taxonomy = taxonomy + cat.CategoryID + ": " + cat.CategoryName + " - " + cat.Description + "\n"
NEXT

' Search existing products for similar items
similar_products = SEARCH "Products.csv", product_name, 5

similar_context = ""
IF similar_products THEN
    FOR EACH p IN similar_products
        similar_context = similar_context + "- " + p.ProductName + " (Category: " + p.CategoryID + ")\n"
    NEXT
END IF

' Use AI to classify the product
BEGIN SYSTEM PROMPT
You are a product classification expert. Your task is to classify products into the correct category based on the store's taxonomy.

Available Categories:
${taxonomy}

Similar existing products in catalog:
${similar_context}

Rules:
1. Return the most specific category that fits
2. Consider product attributes like brand, type, material
3. If uncertain, suggest the most likely category with confidence level
4. Provide reasoning for the classification
END SYSTEM PROMPT

classification_prompt = "Classify this product: '" + product_name + "'\n\nReturn JSON format: {\"category_id\": number, \"category_name\": string, \"confidence\": number (0-100), \"reasoning\": string, \"attributes\": {\"brand\": string, \"type\": string, \"material\": string}}"

result = ASK classification_prompt

' Parse AI response
classification = PARSE JSON result

' Validate category exists
valid_category = FIND "Categories.csv", "CategoryID = " + classification.category_id

IF NOT valid_category THEN
    ' Fallback to closest match
    TALK "⚠️ AI suggested invalid category, finding closest match..."
    valid_category = FIND "Categories.csv", "CategoryName LIKE '%" + classification.category_name + "%'"
    IF valid_category THEN
        classification.category_id = valid_category.CategoryID
    END IF
END IF

' Build response
response = {}
response.product_name = product_name
response.category_id = classification.category_id
response.category_name = classification.category_name
response.confidence = classification.confidence
response.reasoning = classification.reasoning
response.attributes = classification.attributes

' Add suggestions if requested
IF include_suggestions THEN
    suggestions_prompt = "Suggest 2 alternative categories for '" + product_name + "' from: " + taxonomy
    alt_result = ASK suggestions_prompt
    response.alternative_categories = PARSE JSON alt_result
END IF

' Log classification for analytics
LOG "product_classification", {
    "product": product_name,
    "category": classification.category_id,
    "confidence": classification.confidence,
    "timestamp": NOW()
}

TALK "📦 **Product Classification Result**"
TALK ""
TALK "**Product:** " + product_name
TALK "**Category:** " + classification.category_name + " (ID: " + classification.category_id + ")"
TALK "**Confidence:** " + classification.confidence + "%"
TALK "**Reasoning:** " + classification.reasoning
TALK ""

IF classification.attributes THEN
    TALK "**Detected Attributes:**"
    IF classification.attributes.brand THEN
        TALK "  • Brand: " + classification.attributes.brand
    END IF
    IF classification.attributes.type THEN
        TALK "  • Type: " + classification.attributes.type
    END IF
    IF classification.attributes.material THEN
        TALK "  • Material: " + classification.attributes.material
    END IF
END IF

IF include_suggestions AND response.alternative_categories THEN
    TALK ""
    TALK "**Alternative Categories:**"
    FOR EACH alt IN response.alternative_categories
        TALK "  • " + alt.category_name + " (" + alt.confidence + "% confidence)"
    NEXT
END IF

RETURN response