Update index.md

Author: BohuTANG

docs/doc/15-sql-functions/61-ai-functions/index.md

@@ -2,11 +2,11 @@
 title: 'AI Functions'
 ---
 
-Databend can utilize the OpenAI `Code-Davinci-002` engine to translate natural language into SQL queries.
+Databend leverages the OpenAI **Code-Davinci-002** engine to convert natural language into SQL queries.
 
-By integrating OLAP and AI, Databend simplifies the process of writing SQL queries based on your table schema.
+By integrating OLAP and AI, Databend streamlines the process of crafting SQL queries based on your table schema.
 
-The `ai_to_sql` function allows us to effortlessly generate SQL queries using natural language.
+The `ai_to_sql` function enables the effortless generation of SQL queries using natural language.
 
 ## Syntax
 
@@ -23,21 +23,66 @@ Please note that the generated SQL query may need to be adapted to match Databen
 
 
 ```sql
-CREATE DATABASE openai;
+CREATE DATABASE IF NOT EXISTS openai;
 USE openai;
 
 CREATE TABLE users(
     id INT,
     name VARCHAR,
-    age INT
+    age INT,
+    country VARCHAR
 );
 
-SELECT * FROM ai_to_sql('List all users older than 30 years', '<openai-api-key>');
+CREATE TABLE orders(
+    order_id INT,
+    user_id INT,
+    product_name VARCHAR,
+    price DECIMAL(10,2),
+    order_date DATE
+);
+
+-- Insert sample data into the users table
+INSERT INTO users VALUES (1, 'Alice', 31, 'USA'),
+                         (2, 'Bob', 32, 'USA'),
+                         (3, 'Charlie', 45, 'USA'),
+                         (4, 'Diana', 29, 'USA'),
+                         (5, 'Eva', 35, 'Canada');
+
+-- Insert sample data into the orders table
+INSERT INTO orders VALUES (1, 1, 'iPhone', 1000.00, '2022-03-05'),
+                          (2, 1, 'OpenAI Plus', 20.00, '2022-03-06'),
+                          (3, 2, 'OpenAI Plus', 20.00, '2022-03-07'),
+                          (4, 2, 'MacBook Pro', 2000.00, '2022-03-10'),
+                          (5, 3, 'iPad', 500.00, '2022-03-12'),
+                          (6, 3, 'AirPods', 200.00, '2022-03-14');
+```
+
+AI-Powered SQL Query Generation:
+```sql
+-- Generate an SQL query using the ai_to_sql function
+SELECT * FROM ai_to_sql(
+    'List the total amount spent by users from the USA who are older than 30 years, grouped by their names, along with the number of orders they made in 2022', 
+    '<openai-api-key>');
 ```
 
 Output:
 ```sql
 *************************** 1. row ***************************
-     database: simple_example
-generated_sql:  SELECT * FROM users WHERE age > 30;
+     database: openai
+generated_sql: SELECT name, SUM(price) AS total_spent, COUNT(order_id) AS total_orders
+               FROM users
+                        JOIN orders ON users.id = orders.user_id
+               WHERE country = 'USA' AND age > 30 AND order_date BETWEEN '2022-01-01' AND '2022-12-31'
+               GROUP BY name;
+```
+
+Query Result:
+```sql
++---------+-------------+-------------+
+| name    | order_count | total_spent |
++---------+-------------+-------------+
+| Bob     |           2 |     2020.00 |
+| Alice   |           2 |     1020.00 |
+| Charlie |           2 |      700.00 |
++---------+-------------+-------------+
 ```