Create app.py

app.py

@@ -0,0 +1,76 @@
+import gradio as gr
+from sql_generator import SQLGenerator
+from intent_classifier import IntentClassifier
+from rag_system import RAGSystem
+from gradio_client import Client
+
+class UnifiedSystem:
+    def __init__(self):
+        self.sql_generator = SQLGenerator()
+        self.intent_classifier = IntentClassifier()
+        self.rag_system = RAGSystem()
+        self.base_url = "https://agkd0n-fa.myshopify.com/products/"
+
+    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']}\nVendor: {p['vendor']}\nDescription: {p.get('body_html', 'No description available.')}\nURL: {self.base_url}{p['handle']}\n"
+                    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)
+            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 Details:\n" + "\n".join(
+                       [f"Product URL: {url}" for url in 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 50 rupee"],
+            ["Show me shirts with red color"],
+            ["Show me T-shirts with M size"]
+        ]
+    )
+    
+    # This will enable an API endpoint for your Space
+    iface.launch(share=True, api_name="/predict")  # Ensure share=True for public access if needed
+
+if __name__ == "__main__":
+    iface = create_interface()
+    iface.launch()
+
+# Test the API endpoint using Gradio Client
+client = Client("nileshhanotia/PePe")
+result = client.predict(
+    query="Hello!!",
+    api_name="/predict"
+)
+print(result)