import gradio as gr import os import subprocess import spacy from sql_generator import SQLGenerator from intent_classifier import IntentClassifier from rag_system import RAGSystem class UnifiedSystem: def __init__(self): # Download the spaCy model if not present self.download_spacy_model() self.nlp = spacy.load("en_core_web_sm") # Load the spaCy model self.sql_generator = SQLGenerator() self.intent_classifier = IntentClassifier() self.rag_system = RAGSystem() self.base_url = "https://agkd0n-fa.myshopify.com/products/" def download_spacy_model(self): """Download the spaCy model if it's not already installed.""" try: # Check if the model is already downloaded import en_core_web_sm except ImportError: # If not, download the model subprocess.run(["python", "-m", "spacy", "download", "en_core_web_sm"]) def process_query(self, query): intent, confidence = self.intent_classifier.classify(query) if intent == "database_query": sql_query = self.sql_generator.generate_query(query) products = self.sql_generator.fetch_shopify_data("products") if products and 'products' in products: results = "\n".join([ f"Title: {p['title']}, Vendor: {p['vendor']}, URL: {self.base_url}{p['handle']}" for p in products['products'] ]) return f"Intent: Database Query (Confidence: {confidence:.2f})\n\n" \ f"SQL Query: {sql_query}\n\nResults:\n{results}" else: return "No results found or error fetching data from Shopify." elif intent == "product_description": rag_response = self.rag_system.process_query(query) # Assume the RAG system can return product handles for links product_handles = rag_response.get('product_handles', []) urls = [f"{self.base_url}{handle}" for handle in product_handles] response = rag_response.get('response', "No description available.") return f"Intent: Product Description (Confidence: {confidence:.2f})\n\n" \ f"Response: {response}\n\nProduct URLs:\n" + "\n".join(urls) return "Intent not recognized." def create_interface(): system = UnifiedSystem() iface = gr.Interface( fn=system.process_query, inputs=gr.Textbox( label="Enter your query", placeholder="e.g., 'Show me all T-shirts' or 'Describe the product features'" ), outputs=gr.Textbox(label="Response"), title="Unified Query Processing System", description="Enter a natural language query to search products or get descriptions.", examples=[ ["Show me shirts less than 5 USD"], ["Show me shirts with red color"], ["Show me T-shirts with M size"] ] ) return iface if __name__ == "__main__": iface = create_interface() iface.launch()