Update app.py

app.py

@@ -10,26 +10,27 @@ import os
 OPENROUTER_API_KEY = "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"
 OPENROUTER_MODEL = "sophosympatheia/rogue-rose-103b-v0.2:free"
 
-# Hugging Face Space path
+# Path to the SQLite Database
 DB_PATH = "ecommerce.db"
 
-# Ensure dataset exists
+# Ensure database exists before proceeding
 if not os.path.exists(DB_PATH):
-    os.system("wget https://your-dataset-link.com/ecommerce.db -O ecommerce.db")  # Replace with actual dataset link
+    raise FileNotFoundError("Database file 'ecommerce.db' not found. Upload it first!")
 
 # Initialize OpenAI client
 openai_client = openai.OpenAI(api_key=OPENROUTER_API_KEY, base_url="https://openrouter.ai/api/v1")
 
-# Few-shot examples for text-to-SQL
+# Few-shot examples with SQLite-friendly queries
 few_shot_examples = [
     {"input": "Show all customers from São Paulo.", "output": "SELECT * FROM customers WHERE customer_state = 'SP';"},
-    {"input": "Find the total sales per product.", "output": "SELECT product_id, SUM(price) FROM order_items GROUP BY product_id;"},
-    {"input": "List all orders placed in 2017.", "output": "SELECT * FROM orders WHERE order_purchase_timestamp LIKE '2017%';"}
+    {"input": "Find the total sales per product.", "output": "SELECT product_id, SUM(price) AS total_sales FROM order_items GROUP BY product_id;"},
+    {"input": "List all orders placed in 2017.", "output": "SELECT * FROM orders WHERE order_purchase_timestamp LIKE '2017%';"},
+    {"input": "Find the busiest months for orders.", "output": "SELECT strftime('%m', order_purchase_timestamp) AS order_month, COUNT(*) AS orders_count FROM orders GROUP BY order_month ORDER BY orders_count DESC;"},
 ]
 
 # Function: Convert text to SQL
 def text_to_sql(query):
-    prompt = "Convert the following queries into SQL:\n\n"
+    prompt = "Convert the following queries into SQLite-compatible SQL:\n\n"
     for example in few_shot_examples:
         prompt += f"Input: {example['input']}\nOutput: {example['output']}\n\n"
     prompt += f"Input: {query}\nOutput:"