118 lines
4 KiB
QBasic
118 lines
4 KiB
QBasic
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' Product Classification Tool
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' Classifies products into categories using AI and store taxonomy
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PARAM product_name AS STRING DESCRIPTION "Product name to classify (e.g., 'nike air max shoes')"
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PARAM include_suggestions AS BOOLEAN OPTIONAL DESCRIPTION "Include alternative category suggestions"
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DESCRIPTION "Classify a product into the store's category taxonomy using AI"
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' Load store categories for context
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categories = FIND "Categories.csv"
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' Build taxonomy tree for AI context
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taxonomy = ""
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FOR EACH cat IN categories
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taxonomy = taxonomy + cat.CategoryID + ": " + cat.CategoryName + " - " + cat.Description + "\n"
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NEXT
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' Search existing products for similar items
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similar_products = SEARCH "Products.csv", product_name, 5
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similar_context = ""
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IF similar_products THEN
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FOR EACH p IN similar_products
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similar_context = similar_context + "- " + p.ProductName + " (Category: " + p.CategoryID + ")\n"
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NEXT
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END IF
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' Use AI to classify the product
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BEGIN SYSTEM PROMPT
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You are a product classification expert. Your task is to classify products into the correct category based on the store's taxonomy.
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Available Categories:
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${taxonomy}
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Similar existing products in catalog:
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${similar_context}
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Rules:
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1. Return the most specific category that fits
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2. Consider product attributes like brand, type, material
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3. If uncertain, suggest the most likely category with confidence level
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4. Provide reasoning for the classification
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END SYSTEM PROMPT
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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}}"
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result = ASK classification_prompt
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' Parse AI response
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classification = PARSE JSON result
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' Validate category exists
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valid_category = FIND "Categories.csv", "CategoryID = " + classification.category_id
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IF NOT valid_category THEN
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' Fallback to closest match
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TALK "⚠️ AI suggested invalid category, finding closest match..."
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valid_category = FIND "Categories.csv", "CategoryName LIKE '%" + classification.category_name + "%'"
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IF valid_category THEN
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classification.category_id = valid_category.CategoryID
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END IF
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END IF
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' Build response
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response = {}
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response.product_name = product_name
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response.category_id = classification.category_id
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response.category_name = classification.category_name
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response.confidence = classification.confidence
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response.reasoning = classification.reasoning
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response.attributes = classification.attributes
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' Add suggestions if requested
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IF include_suggestions THEN
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suggestions_prompt = "Suggest 2 alternative categories for '" + product_name + "' from: " + taxonomy
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alt_result = ASK suggestions_prompt
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response.alternative_categories = PARSE JSON alt_result
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END IF
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' Log classification for analytics
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LOG "product_classification", {
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"product": product_name,
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"category": classification.category_id,
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"confidence": classification.confidence,
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"timestamp": NOW()
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}
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TALK "📦 **Product Classification Result**"
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TALK ""
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TALK "**Product:** " + product_name
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TALK "**Category:** " + classification.category_name + " (ID: " + classification.category_id + ")"
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TALK "**Confidence:** " + classification.confidence + "%"
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TALK "**Reasoning:** " + classification.reasoning
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TALK ""
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IF classification.attributes THEN
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TALK "**Detected Attributes:**"
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IF classification.attributes.brand THEN
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TALK " • Brand: " + classification.attributes.brand
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END IF
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IF classification.attributes.type THEN
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TALK " • Type: " + classification.attributes.type
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END IF
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IF classification.attributes.material THEN
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TALK " • Material: " + classification.attributes.material
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END IF
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END IF
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IF include_suggestions AND response.alternative_categories THEN
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TALK ""
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TALK "**Alternative Categories:**"
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FOR EACH alt IN response.alternative_categories
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TALK " • " + alt.category_name + " (" + alt.confidence + "% confidence)"
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NEXT
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END IF
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RETURN response
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