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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"]
]
)
# Launch interface with public sharing enabled
iface.launch(share=True)
if __name__ == "__main__":
create_interface()
# Test the API endpoint using Gradio Client
client = Client("nileshhanotia/PePe")
result = client.predict(
query="Hello!!",
api_name="/predict"
)
print(result)
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