diff --git a/random_sample/generate_tasks copy 2.py b/random_sample/generate_tasks copy 2.py
deleted file mode 100644
index 33601b6..0000000
--- a/random_sample/generate_tasks copy 2.py	
+++ /dev/null
@@ -1,364 +0,0 @@
-import os
-import random
-import json
-import mysql.connector
-from openai import OpenAI
-from dotenv import load_dotenv
-
-# --- Configuration ---
-load_dotenv()
-
-MYSQL_CONFIG = {
-    "host": "localhost",
-    "port": "23306",
-    "user": "mcpuser",
-    "password": "StrongPass123!",
-    "database": "magentodb"
-}
-
-OPENAI_CONFIG = {
-    "api_key": os.getenv("OPENAI_API_KEY"),
-    "base_url": os.getenv("OPENAI_BASE_URL"),
-    "model": "gpt-4o"
-}
-
-# --- Prompt Template ---
-# This is a carefully engineered prompt to guide the LLM's output.
-PROMPT_TEMPLATE = """
-You are an expert database analyst and a creative test case designer for e-commerce web applications.
-Your goal is to generate realistic administrative tasks that can be solved by a Web Agent navigating an admin panel.
-
-I will provide you with the following context:
-1.  **Full Database Schema**: A list of `CREATE TABLE` statements for the core tables of a Magento e-commerce platform.
-2.  **Sampled Data**: A JSON object containing 5 random rows of data from 5 randomly selected core tables. This data is REAL and should be used to inspire specific, answerable questions.
-
-## Your Task
-
-Based on the provided schema and sample data, create a JSON object containing a single key, "questions", which holds an array of up to 10 unique task objects.
-
-### Requirements for Each Question:
-- **Web Agent Solvable**: The task must represent a realistic action an administrator would perform in a web UI (e.g., "Find all orders for customer X", "Update the stock for product Y", "Approve a pending review").
-- **Grounded in Data**: The questions should be specific, using names, IDs, or values from the provided **Sampled Data** to make them concrete.
-- **Utilize Schema**: You can formulate questions that require joining tables, even if not all tables were sampled. The full schema is your guide.
-
-### Output Format
-The final output MUST be a single, valid JSON object. Do not include any other text, explanations, or markdown formatting like ```json.
-The JSON object must have one key: "questions", containing a JSON array of task objects.
-
-Each object in the array must contain exactly three keys: `question`, `answer`, and `sql`.
-
--   **`question`**: (string) A natural language description of the task for a web agent.
--   **`answer`**: (string, integer, float, or list) The precise and concise answer to the question, derived by running the SQL query against the database.
--   **`sql`**: (string) The exact, runnable MySQL query that was used to find the answer.
-
-### Output Format Example
-```json
-{{
-  "questions": [
-    {{
-      "question": "What is the email address for customer with ID 5?",
-      "answer": "customer5@example.com",
-      "sql": "SELECT email FROM customer_entity WHERE entity_id = 5;"
-    }},
-    {{
-      "question": "Find the total quantity of item with SKU 'ABC-123' in the cart.",
-      "answer": 3,
-      "sql": "SELECT SUM(qty) FROM quote_item WHERE sku = 'ABC-123';"
-    }}
-  ]
-}}
-```
-
----
-### Full Database Schema
-{schema_context}
-
----
-### Sampled Data
-Here is the sample data from randomly selected tables. Use this to make your questions specific.
-
-{sampled_data_str}
-
----
-Now, generate the JSON object based on these instructions.
-"""
-
-# This is a carefully engineered prompt to verify the LLM's own output.
-SEMANTIC_VERIFICATION_PROMPT_TEMPLATE = """
-You are a meticulous data verifier. Your task is to determine if a given "answer" is semantically correct and accurately supported by the "SQL query result".
-
-I will provide you with a JSON object containing:
-1. `question`: The original question asked.
-2. `sql`: The SQL query used to find the answer.
-3. `answer`: The answer generated by a previous AI.
-4. `sql_result`: The actual data returned by executing the SQL query.
-
-## Your Task
-Carefully analyze the `sql_result` and compare it to the `answer`. The match should be semantic, not just a simple substring match. For example, if the question is "How many products are in stock?", an answer of "5" should be verifiable from the SQL result which might be `[(5,)]`.
-
-### Requirements:
-- Respond with a single JSON object.
-- Do not include any other text, explanations, or markdown formatting.
-- The JSON object must have exactly two keys:
-  - `is_match`: (boolean) `true` if the `answer` is fully and accurately supported by the `sql_result`, otherwise `false`.
-  - `reason`: (string) A brief explanation for your decision. If it's a mismatch, explain why (e.g., "The answer is 'John Doe' but the result contains 'Jane Doe'", "The answer is a count but the result is a list of names").
-
----
-### Verification Data
-{task_data_json}
----
-
-Now, provide your verification as a JSON object.
-"""
-
-def get_db_connection():
-    """Establishes a connection to the MySQL database."""
-    try:
-        conn = mysql.connector.connect(**MYSQL_CONFIG)
-        return conn
-    except mysql.connector.Error as err:
-        print(f"Error connecting to MySQL: {err}")
-        return None
-
-def get_full_schema(cursor, tables):
-    """Fetches the CREATE TABLE statements for all core tables."""
-    schema_parts = []
-    for table_name in tables:
-        try:
-            cursor.execute(f"SHOW CREATE TABLE `{table_name}`")
-            result = cursor.fetchone()
-            if result:
-                schema_parts.append(result[1]) # result[1] is the CREATE TABLE statement
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not get schema for table {table_name}: {err}")
-    return "\n\n".join(schema_parts)
-
-def get_random_tables_and_samples(cursor, tables, num_tables=5, num_samples=5):
-    """Selects random tables and samples random rows from them."""
-    selected_tables = random.sample(tables, num_tables)
-    sampled_data = {}
-
-    for table_name in selected_tables:
-        try:
-            # Use ORDER BY RAND() for random sampling. Can be slow on very large tables.
-            query = f"SELECT * FROM `{table_name}` ORDER BY RAND() LIMIT {num_samples}"
-            cursor.execute(query)
-            
-            rows = cursor.fetchall()
-            if not rows:
-                sampled_data[table_name] = []
-                continue
-
-            columns = [desc[0] for desc in cursor.description]
-            
-            # Convert rows (tuples) to a list of dictionaries
-            sampled_rows = []
-            for row in rows:
-                row_dict = {}
-                for i, col_value in enumerate(row):
-                    # Handle bytes by decoding, fall back to string representation
-                    if isinstance(col_value, bytes):
-                        try:
-                            row_dict[columns[i]] = col_value.decode('utf-8')
-                        except UnicodeDecodeError:
-                            row_dict[columns[i]] = str(col_value)
-                    else:
-                        row_dict[columns[i]] = col_value
-                sampled_rows.append(row_dict)
-            
-            sampled_data[table_name] = sampled_rows
-
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not sample data from table {table_name}: {err}")
-            sampled_data[table_name] = f"Error: {err}"
-
-    return sampled_data
-
-def generate_questions(client, schema_context, sampled_data):
-    """Generates questions by calling the OpenAI API."""
-    if not client:
-        raise ValueError("OpenAI client not provided.")
-    
-    sampled_data_str = json.dumps(sampled_data, indent=2, default=str)
-    
-    prompt = PROMPT_TEMPLATE.format(
-        schema_context=schema_context,
-        sampled_data_str=sampled_data_str
-    )
-
-    try:
-        response = client.chat.completions.create(
-            model=OPENAI_CONFIG["model"],
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            response_format={"type": "json_object"},
-        )
-        content = response.choices[0].message.content
-        data = json.loads(content)
-
-        # The prompt asks for {"questions": [...]}, so we extract the list.
-        if isinstance(data, dict) and "questions" in data and isinstance(data["questions"], list):
-            return data["questions"]
-        elif isinstance(data, list):
-            # Fallback in case the model returns a list directly
-            print("Warning: Model returned a raw list instead of an object with a 'questions' key.")
-            return data
-        else:
-            print(f"Warning: Failed to find a 'questions' list in the model's output. Got: {content}")
-            return None
-
-    except Exception as e:
-        print(f"Error calling OpenAI API or parsing JSON: {e}")
-        return None
-
-def semantic_validate_tasks(tasks, client):
-    """
-    Uses an LLM to semantically validate if the task's answer matches the SQL result.
-    """
-    if not tasks:
-        return []
-
-    final_validated_tasks = []
-    print("\nPerforming semantic validation with GPT-4o...")
-
-    for task in tasks:
-        # Prepare data for the prompt, including the SQL result
-        task_data_for_prompt = {
-            "question": task["question"],
-            "sql": task["sql"],
-            "answer": task["answer"],
-            "sql_result": task["sql_result"]
-        }
-        task_data_json = json.dumps(task_data_for_prompt, indent=2, default=str)
-
-        prompt = SEMANTIC_VERIFICATION_PROMPT_TEMPLATE.format(task_data_json=task_data_json)
-
-        try:
-            print(f"  - Verifying question: \"{task['question'][:80]}...\"")
-            response = client.chat.completions.create(
-                model=OPENAI_CONFIG["model"],
-                messages=[
-                    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                    {"role": "user", "content": prompt}
-                ],
-                temperature=0.0,  # We want deterministic validation
-                response_format={"type": "json_object"},
-            )
-            content = response.choices[0].message.content
-            verification_result = json.loads(content)
-
-            if verification_result.get("is_match") is True:
-                # Task is valid. Rename sql_result for the final output.
-                print(f"    - Validation PASSED.")
-                task['sql_execute_result'] = task.pop('sql_result')
-                final_validated_tasks.append(task)
-            else:
-                reason = verification_result.get('reason', 'No reason provided.')
-                print(f"    - Validation FAILED. Filtering task.")
-                print(f"      - Reason: {reason}")
-                print(f"      - Question: {task['question']}")
-                print(f"      - Expected Answer: {json.dumps(task['answer'], default=str)}")
-                print(f"      - SQL: {task['sql']}")
-                sql_result_str = json.dumps(task['sql_result'], indent=2, default=str)
-                print(f"      - SQL Result: {sql_result_str}")
-
-        except Exception as e:
-            print(f"    - An error occurred during semantic validation for task, filtering it out: {e}")
-            print(f"      - Question: {task.get('question', 'N/A')}")
-            print(f"      - SQL: {task.get('sql', 'N/A')}")
-
-    return final_validated_tasks
-
-def main():
-    """Main function to run the script."""
-    # 1. Load the list of core tables
-    try:
-        with open('core_tables.json', 'r') as f:
-            core_tables = json.load(f)
-    except FileNotFoundError:
-        print("Error: core_tables.json not found. Please create it.")
-        return
-
-    # 2. Connect to the database
-    conn = get_db_connection()
-    if not conn:
-        return
-        
-    cursor = conn.cursor()
-
-    # 3. Setup OpenAI Client
-    if not OPENAI_CONFIG["api_key"]:
-        print("Error: OPENAI_API_KEY environment variable not set.")
-        return
-    client = OpenAI(api_key=OPENAI_CONFIG["api_key"], base_url=OPENAI_CONFIG["base_url"])
-    
-    try:
-        # 4. Get full schema context
-        print("Fetching full database schema...")
-        schema_context = get_full_schema(cursor, core_tables)
-
-        # 5. Get random samples and print them
-        print("Sampling data from 5 random tables...")
-        sampled_data = get_random_tables_and_samples(cursor, core_tables, num_tables=5, num_samples=5)
-        print(f"Sampled from tables: {list(sampled_data.keys())}")
-        print("\n--- Sampled Data ---")
-        print(json.dumps(sampled_data, indent=2, default=str))
-        print("---------------------\n")
-
-        # 6. Generate questions using the LLM
-        print("Generating questions with GPT-4o...")
-        generated_tasks = generate_questions(client, schema_context, sampled_data)
-
-        # 7. Initial validation (SQL execution and substring check)
-        pre_validated_tasks = []
-        if generated_tasks:
-            print("\nPerforming initial validation (SQL execution and substring match)...")
-            for task in generated_tasks:
-                if not isinstance(task, dict) or not all(k in task for k in ['sql', 'answer', 'question']):
-                    print(f"Filtering task due to malformed structure or missing keys: {task}")
-                    continue
-                
-                try:
-                    cursor.execute(task['sql'])
-                    sql_result = cursor.fetchall()
-                    answer_str = str(task['answer'])
-                    result_str = str(sql_result)
-                    
-                    if answer_str in result_str:
-                        task['sql_result'] = sql_result  # Attach result for the next validation step
-                        pre_validated_tasks.append(task)
-                    else:
-                        print(f"Filtering task: Answer '{answer_str}' not found in SQL result.")
-                        print(f"  - Question: {task['question']}")
-                        print(f"  - SQL: {task['sql']}")
-                        print(f"  - Result: {result_str[:250]}...")
-
-                except mysql.connector.Error as err:
-                    print(f"Filtering task due to SQL error: {err}")
-                    print(f"  - Question: {task['question']}")
-                    print(f"  - SQL: {task['sql']}")
-                except Exception as e:
-                    print(f"An unexpected error occurred during initial validation for task {task}: {e}")
-
-        # 8. Semantic validation using LLM
-        validated_tasks = semantic_validate_tasks(pre_validated_tasks, client)
-
-        # 9. Print the final JSON output
-        if validated_tasks:
-            print("\n--- Final Validated Tasks ---")
-            print(json.dumps(validated_tasks, indent=2, default=str))
-        else:
-            print("Failed to generate any valid tasks after all validation steps.")
-
-    finally:
-        # 10. Close the database connection
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
-            print("\nDatabase connection closed.")
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/random_sample/generate_tasks copy 3.py b/random_sample/generate_tasks copy 3.py
deleted file mode 100644
index 7dc7598..0000000
--- a/random_sample/generate_tasks copy 3.py	
+++ /dev/null
@@ -1,370 +0,0 @@
-import os
-import random
-import json
-import mysql.connector
-from openai import OpenAI
-from dotenv import load_dotenv
-
-# --- Configuration ---
-load_dotenv()
-
-MYSQL_CONFIG = {
-    "host": "localhost",
-    "port": "23306",
-    "user": "mcpuser",
-    "password": "StrongPass123!",
-    "database": "magentodb"
-}
-
-OPENAI_CONFIG = {
-    "api_key": os.getenv("OPENAI_API_KEY"),
-    "base_url": os.getenv("OPENAI_BASE_URL"),
-    "model": "gpt-4o"
-}
-
-# --- Prompt Template ---
-# This is a carefully engineered prompt to guide the LLM's output.
-PROMPT_TEMPLATE = """
-You are an expert database analyst and a creative test case designer for e-commerce web applications.
-Your goal is to generate realistic administrative tasks that can be solved by a Web Agent navigating an admin panel.
-
-I will provide you with the following context:
-1.  **Full Database Schema**: A list of `CREATE TABLE` statements for the core tables of a Magento e-commerce platform.
-2.  **Sampled Data**: A JSON object containing 5 random rows of data from 5 randomly selected core tables. This data is REAL and should be used to inspire specific, answerable questions.
-
-## Your Task
-
-Based on the provided schema and sample data, create a JSON object containing a single key, "questions", which holds an array of up to 10 unique task objects.
-
-### Requirements for Each Question:
-- **Web Agent Solvable**: The task must represent a realistic action an administrator would perform in a web UI (e.g., "Find all orders for customer X", "Update the stock for product Y", "Approve a pending review").
-- **Grounded in Data**: The questions should be specific, using names, IDs, or values from the provided **Sampled Data** to make them concrete.
-- **Utilize Schema**: You can formulate questions that require joining tables, even if not all tables were sampled. The full schema is your guide.
-
-### Output Format
-The final output MUST be a single, valid JSON object. Do not include any other text, explanations, or markdown formatting like ```json.
-The JSON object must have one key: "questions", containing a JSON array of task objects.
-
-Each object in the array must contain exactly three keys: `question`, `answer`, and `sql`.
-
--   **`question`**: (string) A natural language description of the task for a web agent.
--   **`answer`**: (string, integer, float, or list) The precise and concise answer to the question, derived by running the SQL query against the database.
--   **`sql`**: (string) The exact, runnable MySQL query that was used to find the answer.
-
-### Output Format Example
-```json
-{{
-  "questions": [
-    {{
-      "question": "What is the email address for customer with ID 5?",
-      "answer": "customer5@example.com",
-      "sql": "SELECT email FROM customer_entity WHERE entity_id = 5;"
-    }},
-    {{
-      "question": "Find the total quantity of item with SKU 'ABC-123' in the cart.",
-      "answer": 3,
-      "sql": "SELECT SUM(qty) FROM quote_item WHERE sku = 'ABC-123';"
-    }}
-  ]
-}}
-```
-
----
-### Full Database Schema
-{schema_context}
-
----
-### Sampled Data
-Here is the sample data from randomly selected tables. Use this to make your questions specific.
-
-{sampled_data_str}
-
----
-Now, generate the JSON object based on these instructions.
-"""
-
-# This is a new prompt to evaluate results and generate a corrected answer.
-SEMANTIC_EVALUATION_PROMPT_TEMPLATE = """
-You are a precise data analyst. Your task is to evaluate if a SQL query's result adequately answers a given natural language question. If it does, you must formulate a concise, natural-language answer.
-
-I will provide you with a JSON object containing:
-1. `question`: The original question asked.
-2. `sql`: The SQL query that was executed.
-3. `sql_result`: The actual data returned by executing the SQL query.
-
-## Your Task
-1.  **Analyze**: Determine if the `sql_result` contains the necessary information to definitively answer the `question`.
-2.  **Respond**: Based on your analysis, generate a JSON object with one of two structures.
-
-### Case 1: The question CAN be answered
-If the `sql_result` provides a clear answer, respond with:
-```json
-{{
-  "can_answer": true,
-  "new_answer": "..."
-}}
-```
-- `can_answer`: (boolean) Must be `true`.
-- `new_answer`: (string, integer, float, or list) A concise, human-readable answer derived *only* from the `sql_result`. For example, if the result is `[(52.00,)]`, the answer can be "52.00" or 52.00.
-
-### Case 2: The question CANNOT be answered
-If the `sql_result` is empty, irrelevant, or insufficient to answer the question, respond with:
-```json
-{{
-  "can_answer": false,
-  "reason": "..."
-}}
-```
-- `can_answer`: (boolean) Must be `false`.
-- `reason`: (string) A brief explanation for why the question cannot be answered from the given data (e.g., "The query returned no results.", "The result contains internal IDs, not the requested customer names.").
-
----
-### Evaluation Data
-{task_data_json}
----
-
-Now, provide your evaluation as a JSON object.
-"""
-
-def get_db_connection():
-    """Establishes a connection to the MySQL database."""
-    try:
-        conn = mysql.connector.connect(**MYSQL_CONFIG)
-        return conn
-    except mysql.connector.Error as err:
-        print(f"Error connecting to MySQL: {err}")
-        return None
-
-def get_full_schema(cursor, tables):
-    """Fetches the CREATE TABLE statements for all core tables."""
-    schema_parts = []
-    for table_name in tables:
-        try:
-            cursor.execute(f"SHOW CREATE TABLE `{table_name}`")
-            result = cursor.fetchone()
-            if result:
-                schema_parts.append(result[1]) # result[1] is the CREATE TABLE statement
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not get schema for table {table_name}: {err}")
-    return "\n\n".join(schema_parts)
-
-def get_random_tables_and_samples(cursor, tables, num_tables=5, num_samples=5):
-    """Selects random tables and samples random rows from them."""
-    selected_tables = random.sample(tables, num_tables)
-    sampled_data = {}
-
-    for table_name in selected_tables:
-        try:
-            # Use ORDER BY RAND() for random sampling. Can be slow on very large tables.
-            query = f"SELECT * FROM `{table_name}` ORDER BY RAND() LIMIT {num_samples}"
-            cursor.execute(query)
-            
-            rows = cursor.fetchall()
-            if not rows:
-                sampled_data[table_name] = []
-                continue
-
-            columns = [desc[0] for desc in cursor.description]
-            
-            # Convert rows (tuples) to a list of dictionaries
-            sampled_rows = []
-            for row in rows:
-                row_dict = {}
-                for i, col_value in enumerate(row):
-                    # Handle bytes by decoding, fall back to string representation
-                    if isinstance(col_value, bytes):
-                        try:
-                            row_dict[columns[i]] = col_value.decode('utf-8')
-                        except UnicodeDecodeError:
-                            row_dict[columns[i]] = str(col_value)
-                    else:
-                        row_dict[columns[i]] = col_value
-                sampled_rows.append(row_dict)
-            
-            sampled_data[table_name] = sampled_rows
-
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not sample data from table {table_name}: {err}")
-            sampled_data[table_name] = f"Error: {err}"
-
-    return sampled_data
-
-def generate_questions(client, schema_context, sampled_data):
-    """Generates questions by calling the OpenAI API."""
-    if not client:
-        raise ValueError("OpenAI client not provided.")
-    
-    sampled_data_str = json.dumps(sampled_data, indent=2, default=str)
-    
-    prompt = PROMPT_TEMPLATE.format(
-        schema_context=schema_context,
-        sampled_data_str=sampled_data_str
-    )
-
-    try:
-        response = client.chat.completions.create(
-            model=OPENAI_CONFIG["model"],
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            response_format={"type": "json_object"},
-        )
-        content = response.choices[0].message.content
-        data = json.loads(content)
-
-        # The prompt asks for {"questions": [...]}, so we extract the list.
-        if isinstance(data, dict) and "questions" in data and isinstance(data["questions"], list):
-            return data["questions"]
-        elif isinstance(data, list):
-            # Fallback in case the model returns a list directly
-            print("Warning: Model returned a raw list instead of an object with a 'questions' key.")
-            return data
-        else:
-            print(f"Warning: Failed to find a 'questions' list in the model's output. Got: {content}")
-            return None
-
-    except Exception as e:
-        print(f"Error calling OpenAI API or parsing JSON: {e}")
-        return None
-
-def evaluate_and_refine_tasks(tasks, client):
-    """
-    Uses an LLM to evaluate if a SQL result answers the question and refines the answer.
-    """
-    if not tasks:
-        return []
-
-    final_validated_tasks = []
-    print("\nPerforming semantic evaluation and answer refinement with GPT-4o...")
-
-    for task in tasks:
-        # Prepare data for the prompt, excluding the original 'answer'
-        task_data_for_prompt = {
-            "question": task["question"],
-            "sql": task["sql"],
-            "sql_result": task["sql_result"]
-        }
-        task_data_json = json.dumps(task_data_for_prompt, indent=2, default=str)
-
-        prompt = SEMANTIC_EVALUATION_PROMPT_TEMPLATE.format(task_data_json=task_data_json)
-
-        try:
-            print(f"  - Evaluating question: \"{task['question'][:80]}...\"")
-            response = client.chat.completions.create(
-                model=OPENAI_CONFIG["model"],
-                messages=[
-                    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                    {"role": "user", "content": prompt}
-                ],
-                temperature=0.0,  # We want deterministic evaluation
-                response_format={"type": "json_object"},
-            )
-            content = response.choices[0].message.content
-            evaluation_result = json.loads(content)
-
-            if evaluation_result.get("can_answer") is True and "new_answer" in evaluation_result:
-                # Task is valid. Update the answer with the refined one from the LLM.
-                task['answer'] = evaluation_result['new_answer']
-                task['sql_execute_result'] = task.pop('sql_result')
-                final_validated_tasks.append(task)
-                print(f"    - Evaluation PASSED. New answer: {json.dumps(task['answer'])}")
-            else:
-                reason = evaluation_result.get('reason', 'No reason provided.')
-                print(f"    - Evaluation FAILED. Filtering task.")
-                print(f"      - Reason: {reason}")
-                print(f"      - Question: {task['question']}")
-                print(f"      - Original Answer: {json.dumps(task['answer'], default=str)}")
-                print(f"      - SQL: {task['sql']}")
-                sql_result_str = json.dumps(task['sql_result'], indent=2, default=str)
-                print(f"      - SQL Result: {sql_result_str}")
-
-        except Exception as e:
-            print(f"    - An error occurred during semantic evaluation for task, filtering it out: {e}")
-            print(f"      - Question: {task.get('question', 'N/A')}")
-            print(f"      - SQL: {task.get('sql', 'N/A')}")
-
-    return final_validated_tasks
-
-def main():
-    """Main function to run the script."""
-    # 1. Load the list of core tables
-    try:
-        with open('core_tables.json', 'r') as f:
-            core_tables = json.load(f)
-    except FileNotFoundError:
-        print("Error: core_tables.json not found. Please create it.")
-        return
-
-    # 2. Connect to the database
-    conn = get_db_connection()
-    if not conn:
-        return
-        
-    cursor = conn.cursor()
-
-    # 3. Setup OpenAI Client
-    if not OPENAI_CONFIG["api_key"]:
-        print("Error: OPENAI_API_KEY environment variable not set.")
-        return
-    client = OpenAI(api_key=OPENAI_CONFIG["api_key"], base_url=OPENAI_CONFIG["base_url"])
-    
-    try:
-        # 4. Get full schema context
-        print("Fetching full database schema...")
-        schema_context = get_full_schema(cursor, core_tables)
-
-        # 5. Get random samples and print them
-        print("Sampling data from 5 random tables...")
-        sampled_data = get_random_tables_and_samples(cursor, core_tables, num_tables=5, num_samples=5)
-        print(f"Sampled from tables: {list(sampled_data.keys())}")
-        print("\n--- Sampled Data ---")
-        print(json.dumps(sampled_data, indent=2, default=str))
-        print("---------------------\n")
-
-        # 6. Generate questions using the LLM
-        print("Generating questions with GPT-4o...")
-        generated_tasks = generate_questions(client, schema_context, sampled_data)
-
-        # 7. Execute SQL for all generated tasks
-        tasks_for_evaluation = []
-        if generated_tasks:
-            print("\nExecuting SQL for generated tasks...")
-            for task in generated_tasks:
-                if not isinstance(task, dict) or not all(k in task for k in ['sql', 'answer', 'question']):
-                    print(f"Filtering task due to malformed structure or missing keys: {task}")
-                    continue
-                
-                try:
-                    cursor.execute(task['sql'])
-                    sql_result = cursor.fetchall()
-                    task['sql_result'] = sql_result
-                    tasks_for_evaluation.append(task)
-
-                except mysql.connector.Error as err:
-                    print(f"Filtering task due to SQL error: {err}")
-                    print(f"  - Question: {task['question']}")
-                    print(f"  - SQL: {task['sql']}")
-                except Exception as e:
-                    print(f"An unexpected error occurred during SQL execution for task {task}: {e}")
-
-        # 8. Semantic evaluation and answer refinement
-        validated_tasks = evaluate_and_refine_tasks(tasks_for_evaluation, client)
-
-        # 9. Print the final JSON output
-        if validated_tasks:
-            print("\n--- Final Validated Tasks ---")
-            print(json.dumps(validated_tasks, indent=2, default=str))
-        else:
-            print("Failed to generate any valid tasks after all validation steps.")
-
-    finally:
-        # 10. Close the database connection
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
-            print("\nDatabase connection closed.")
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/random_sample/generate_tasks copy 4.py b/random_sample/generate_tasks copy 4.py
deleted file mode 100644
index 85ce167..0000000
--- a/random_sample/generate_tasks copy 4.py	
+++ /dev/null
@@ -1,408 +0,0 @@
-import os
-import random
-import json
-import mysql.connector
-import argparse
-from openai import OpenAI
-from dotenv import load_dotenv
-
-# --- Configuration ---
-load_dotenv()
-
-MYSQL_CONFIG = {
-    "host": "localhost",
-    "port": "23306",
-    "user": "mcpuser",
-    "password": "StrongPass123!",
-    "database": "magentodb"
-}
-
-OPENAI_CONFIG = {
-    "api_key": os.getenv("OPENAI_API_KEY"),
-    "base_url": os.getenv("OPENAI_BASE_URL"),
-    "model": "gpt-4o"
-}
-
-# --- Prompt Template ---
-# This is a carefully engineered prompt to guide the LLM's output.
-PROMPT_TEMPLATE = """
-You are an expert database analyst and a creative test case designer for e-commerce web applications.
-Your goal is to generate realistic administrative tasks that can be solved by a Web Agent navigating an admin panel.
-
-I will provide you with the following context:
-1.  **Full Database Schema**: A list of `CREATE TABLE` statements for the core tables of a Magento e-commerce platform.
-2.  **Sampled Data**: A JSON object containing 5 random rows of data from 5 randomly selected core tables. This data is REAL and should be used to inspire specific, answerable questions.
-
-## Your Task
-
-Based on the provided schema and sample data, create a JSON object containing a single key, "questions", which holds an array of up to 10 unique task objects.
-
-### Requirements for Each Question:
-- **Web Agent Solvable**: The task must represent a realistic action an administrator would perform in a web UI (e.g., "Find all orders for customer X", "Update the stock for product Y", "Approve a pending review").
-- **Grounded in Data**: The questions should be specific, using names, IDs, or values from the provided **Sampled Data** to make them concrete.
-- **Utilize Schema**: You can formulate questions that require joining tables, even if not all tables were sampled. The full schema is your guide.
-
-### Output Format
-The final output MUST be a single, valid JSON object. Do not include any other text, explanations, or markdown formatting like ```json.
-The JSON object must have one key: "questions", containing a JSON array of task objects.
-
-Each object in the array must contain exactly three keys: `question`, `answer`, and `sql`.
-
--   **`question`**: (string) A natural language description of the task for a web agent.
--   **`answer`**: (string, integer, float, or list) The precise and concise answer to the question, derived by running the SQL query against the database.
--   **`sql`**: (string) The exact, runnable MySQL query that was used to find the answer.
-
-### Output Format Example
-```json
-{{
-  "questions": [
-    {{
-      "question": "What is the email address for customer with ID 5?",
-      "answer": "customer5@example.com",
-      "sql": "SELECT email FROM customer_entity WHERE entity_id = 5;"
-    }},
-    {{
-      "question": "Find the total quantity of item with SKU 'ABC-123' in the cart.",
-      "answer": 3,
-      "sql": "SELECT SUM(qty) FROM quote_item WHERE sku = 'ABC-123';"
-    }}
-  ]
-}}
-```
-
----
-### Full Database Schema
-{schema_context}
-
----
-### Sampled Data
-Here is the sample data from randomly selected tables. Use this to make your questions specific.
-
-{sampled_data_str}
-
----
-Now, generate the JSON object based on these instructions.
-"""
-
-# This is a new prompt to evaluate results and generate a corrected answer.
-SEMANTIC_EVALUATION_PROMPT_TEMPLATE = """
-You are a precise data analyst. Your task is to evaluate if a SQL query's result adequately answers a given natural language question. If it does, you must formulate a concise, natural-language answer.
-
-I will provide you with a JSON object containing:
-1. `question`: The original question asked.
-2. `sql`: The SQL query that was executed.
-3. `sql_result`: The actual data returned by executing the SQL query.
-
-## Your Task
-1.  **Analyze**: Determine if the `sql_result` contains the necessary information to definitively answer the `question`.
-2.  **Respond**: Based on your analysis, generate a JSON object with one of two structures.
-
-### Case 1: The question CAN be answered
-If the `sql_result` provides a clear answer, respond with:
-```json
-{{
-  "can_answer": true,
-  "new_answer": "..."
-}}
-```
-- `can_answer`: (boolean) Must be `true`.
-- `new_answer`: (string, integer, float, or list) A concise, human-readable answer derived *only* from the `sql_result`. For example, if the result is `[(52.00,)]`, the answer can be "52.00" or 52.00.
-
-### Case 2: The question CANNOT be answered
-If the `sql_result` is empty, irrelevant, or insufficient to answer the question, respond with:
-```json
-{{
-  "can_answer": false,
-  "reason": "..."
-}}
-```
-- `can_answer`: (boolean) Must be `false`.
-- `reason`: (string) A brief explanation for why the question cannot be answered from the given data (e.g., "The query returned no results.", "The result contains internal IDs, not the requested customer names.").
-
----
-### Evaluation Data
-{task_data_json}
----
-
-Now, provide your evaluation as a JSON object.
-"""
-
-def get_db_connection():
-    """Establishes a connection to the MySQL database."""
-    try:
-        conn = mysql.connector.connect(**MYSQL_CONFIG)
-        return conn
-    except mysql.connector.Error as err:
-        print(f"Error connecting to MySQL: {err}")
-        return None
-
-def get_full_schema(cursor, tables):
-    """Fetches the CREATE TABLE statements for all core tables."""
-    schema_parts = []
-    for table_name in tables:
-        try:
-            cursor.execute(f"SHOW CREATE TABLE `{table_name}`")
-            result = cursor.fetchone()
-            if result:
-                schema_parts.append(result[1]) # result[1] is the CREATE TABLE statement
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not get schema for table {table_name}: {err}")
-    return "\n\n".join(schema_parts)
-
-def get_random_tables_and_samples(cursor, tables, num_tables=5, num_samples=5):
-    """Selects random tables and samples random rows from them."""
-    selected_tables = random.sample(tables, num_tables)
-    sampled_data = {}
-
-    for table_name in selected_tables:
-        try:
-            # Use ORDER BY RAND() for random sampling. Can be slow on very large tables.
-            query = f"SELECT * FROM `{table_name}` ORDER BY RAND() LIMIT {num_samples}"
-            cursor.execute(query)
-            
-            rows = cursor.fetchall()
-            if not rows:
-                sampled_data[table_name] = []
-                continue
-
-            columns = [desc[0] for desc in cursor.description]
-            
-            # Convert rows (tuples) to a list of dictionaries
-            sampled_rows = []
-            for row in rows:
-                row_dict = {}
-                for i, col_value in enumerate(row):
-                    # Handle bytes by decoding, fall back to string representation
-                    if isinstance(col_value, bytes):
-                        try:
-                            row_dict[columns[i]] = col_value.decode('utf-8')
-                        except UnicodeDecodeError:
-                            row_dict[columns[i]] = str(col_value)
-                    else:
-                        row_dict[columns[i]] = col_value
-                sampled_rows.append(row_dict)
-            
-            sampled_data[table_name] = sampled_rows
-
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not sample data from table {table_name}: {err}")
-            sampled_data[table_name] = f"Error: {err}"
-
-    return sampled_data
-
-def generate_questions(client, schema_context, sampled_data):
-    """Generates questions by calling the OpenAI API."""
-    if not client:
-        raise ValueError("OpenAI client not provided.")
-    
-    sampled_data_str = json.dumps(sampled_data, indent=2, default=str)
-    
-    prompt = PROMPT_TEMPLATE.format(
-        schema_context=schema_context,
-        sampled_data_str=sampled_data_str
-    )
-
-    try:
-        response = client.chat.completions.create(
-            model=OPENAI_CONFIG["model"],
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            response_format={"type": "json_object"},
-        )
-        content = response.choices[0].message.content
-        data = json.loads(content)
-
-        # The prompt asks for {"questions": [...]}, so we extract the list.
-        if isinstance(data, dict) and "questions" in data and isinstance(data["questions"], list):
-            return data["questions"]
-        elif isinstance(data, list):
-            # Fallback in case the model returns a list directly
-            print("Warning: Model returned a raw list instead of an object with a 'questions' key.")
-            return data
-        else:
-            print(f"Warning: Failed to find a 'questions' list in the model's output. Got: {content}")
-            return None
-
-    except Exception as e:
-        print(f"Error calling OpenAI API or parsing JSON: {e}")
-        return None
-
-def load_existing_tasks(filepath):
-    """Loads tasks from a JSON file if it exists."""
-    if not os.path.exists(filepath):
-        return []
-    try:
-        with open(filepath, 'r') as f:
-            content = f.read()
-            if not content: # Handle empty file
-                return []
-            return json.loads(content)
-    except (json.JSONDecodeError, FileNotFoundError):
-        print(f"Warning: Could not read or parse {filepath}. Starting with an empty list.")
-        return []
-
-def evaluate_and_refine_tasks(tasks, client):
-    """
-    Uses an LLM to evaluate if a SQL result answers the question and refines the answer.
-    """
-    if not tasks:
-        return []
-
-    final_validated_tasks = []
-    print("\nPerforming semantic evaluation and answer refinement with GPT-4o...")
-
-    for task in tasks:
-        # Prepare data for the prompt, excluding the original 'answer'
-        task_data_for_prompt = {
-            "question": task["question"],
-            "sql": task["sql"],
-            "sql_result": task["sql_result"]
-        }
-        task_data_json = json.dumps(task_data_for_prompt, indent=2, default=str)
-
-        prompt = SEMANTIC_EVALUATION_PROMPT_TEMPLATE.format(task_data_json=task_data_json)
-
-        try:
-            print(f"  - Evaluating question: \"{task['question'][:80]}...\"")
-            response = client.chat.completions.create(
-                model=OPENAI_CONFIG["model"],
-                messages=[
-                    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                    {"role": "user", "content": prompt}
-                ],
-                temperature=0.0,  # We want deterministic evaluation
-                response_format={"type": "json_object"},
-            )
-            content = response.choices[0].message.content
-            evaluation_result = json.loads(content)
-
-            if evaluation_result.get("can_answer") is True and "new_answer" in evaluation_result:
-                # Task is valid. Update the answer with the refined one from the LLM.
-                task['answer'] = evaluation_result['new_answer']
-                task['sql_execute_result'] = task.pop('sql_result')
-                final_validated_tasks.append(task)
-                print(f"    - Evaluation PASSED. New answer: {json.dumps(task['answer'])}")
-            else:
-                reason = evaluation_result.get('reason', 'No reason provided.')
-                print(f"    - Evaluation FAILED. Filtering task.")
-                print(f"      - Reason: {reason}")
-                print(f"      - Question: {task['question']}")
-                print(f"      - Original Answer: {json.dumps(task['answer'], default=str)}")
-                print(f"      - SQL: {task['sql']}")
-                sql_result_str = json.dumps(task['sql_result'], indent=2, default=str)
-                print(f"      - SQL Result: {sql_result_str}")
-
-        except Exception as e:
-            print(f"    - An error occurred during semantic evaluation for task, filtering it out: {e}")
-            print(f"      - Question: {task.get('question', 'N/A')}")
-            print(f"      - SQL: {task.get('sql', 'N/A')}")
-
-    return final_validated_tasks
-
-def main():
-    """Main function to run the script."""
-    parser = argparse.ArgumentParser(description="Generate and validate e-commerce admin tasks.")
-    parser.add_argument(
-        "--target-count",
-        type=int,
-        required=True,
-        help="The total number of questions to generate."
-    )
-    parser.add_argument(
-        "--output-file",
-        type=str,
-        default="generated_tasks.json",
-        help="The file to save the generated tasks to (in JSON format)."
-    )
-    args = parser.parse_args()
-
-    # Load existing tasks from the output file
-    all_tasks = load_existing_tasks(args.output_file)
-    print(f"Found {len(all_tasks)} existing valid tasks in '{args.output_file}'.")
-
-    # Connect to DB and set up client
-    conn = get_db_connection()
-    if not conn:
-        return
-    cursor = conn.cursor()
-
-    if not OPENAI_CONFIG["api_key"]:
-        print("Error: OPENAI_API_KEY environment variable not set.")
-        return
-    client = OpenAI(api_key=OPENAI_CONFIG["api_key"], base_url=OPENAI_CONFIG["base_url"])
-
-    try:
-        # Load core tables and schema once
-        try:
-            with open('core_tables.json', 'r') as f:
-                core_tables = json.load(f)
-        except FileNotFoundError:
-            print("Error: core_tables.json not found. Please create it.")
-            return
-
-        print("Fetching full database schema...")
-        schema_context = get_full_schema(cursor, core_tables)
-        
-        # Start the generation loop
-        round_num = 1
-        while len(all_tasks) < args.target_count:
-            print(f"\n--- Starting Generation Round {round_num} ---")
-            print(f"Goal: {args.target_count} | Current: {len(all_tasks)} | Needed: {args.target_count - len(all_tasks)}")
-            
-            # Get random samples for this round
-            print("Sampling data from 5 random tables...")
-            sampled_data = get_random_tables_and_samples(cursor, core_tables, num_tables=5, num_samples=5)
-            
-            # Generate questions
-            print("Generating questions with GPT-4o...")
-            generated_tasks = generate_questions(client, schema_context, sampled_data)
-
-            # Execute SQL for generated tasks
-            tasks_for_evaluation = []
-            if generated_tasks:
-                print("\nExecuting SQL for generated tasks...")
-                for task in generated_tasks:
-                    if not isinstance(task, dict) or not all(k in task for k in ['sql', 'answer', 'question']):
-                        print(f"Filtering task due to malformed structure: {task}")
-                        continue
-                    try:
-                        cursor.execute(task['sql'])
-                        sql_result = cursor.fetchall()
-                        task['sql_result'] = sql_result
-                        tasks_for_evaluation.append(task)
-                    except mysql.connector.Error as err:
-                        print(f"Filtering task due to SQL error: {err} on SQL: {task['sql']}")
-
-            # Perform semantic evaluation and get validated tasks
-            validated_tasks = evaluate_and_refine_tasks(tasks_for_evaluation, client)
-
-            # Append new tasks and save to file
-            if validated_tasks:
-                all_tasks.extend(validated_tasks)
-                with open(args.output_file, 'w') as f:
-                    json.dump(all_tasks, f, indent=2, default=str)
-                
-                print("\n--- Round Summary ---")
-                print(f"Generated {len(validated_tasks)} new valid tasks in this round.")
-                print(f"Progress: {len(all_tasks)} / {args.target_count} tasks.")
-            else:
-                print("\n--- Round Summary ---")
-                print("No new valid tasks were generated in this round. Retrying...")
-
-            round_num += 1
-
-    finally:
-        # Close the database connection
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
-            print("\nDatabase connection closed.")
-    
-    print(f"\nTarget of {args.target_count} tasks reached. Final output saved to {args.output_file}.")
-
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/random_sample/generate_tasks copy 5.py b/random_sample/generate_tasks copy 5.py
deleted file mode 100644
index 2c0b0e2..0000000
--- a/random_sample/generate_tasks copy 5.py	
+++ /dev/null
@@ -1,437 +0,0 @@
-import os
-import random
-import json
-import mysql.connector
-import argparse
-from openai import OpenAI
-from dotenv import load_dotenv
-
-# --- Configuration ---
-load_dotenv()
-
-MYSQL_CONFIG = {
-    "host": "localhost",
-    "port": "23306",
-    "user": "mcpuser",
-    "password": "StrongPass123!",
-    "database": "magentodb"
-}
-
-OPENAI_CONFIG = {
-    "api_key": os.getenv("OPENAI_API_KEY"),
-    "base_url": os.getenv("OPENAI_BASE_URL"),
-    "model": "gpt-4o"
-}
-
-# --- Prompt Template ---
-# This is a carefully engineered prompt to guide the LLM's output.
-PROMPT_TEMPLATE = """
-You are an expert database analyst and a creative test case designer for e-commerce web applications.
-Your goal is to generate realistic administrative tasks that can be solved by a Web Agent navigating an admin panel.
-
-I will provide you with the following context:
-1.  **Full Database Schema**: A list of `CREATE TABLE` statements for the core tables of a Magento e-commerce platform.
-2.  **Sampled Data**: A JSON object containing 5 random rows of data from 5 randomly selected core tables. This data is REAL and should be used to inspire specific, answerable questions.
-
-## Your Task
-
-Based on the provided schema and sample data, create a JSON object containing a single key, "questions", which holds an array of up to 10 unique task objects.
-
-### Requirements for Each Question:
-- **Web Agent Solvable**: The task must represent a realistic action an administrator would perform in a web UI (e.g., "Find all orders for customer X", "Update the stock for product Y", "Approve a pending review").
-- **Grounded in Data**: The questions should be specific, using names, IDs, or values from the provided **Sampled Data** to make them concrete.
-- **Utilize Schema**: You can formulate questions that require joining tables, even if not all tables were sampled. The full schema is your guide.
-
-### Output Format
-The final output MUST be a single, valid JSON object. Do not include any other text, explanations, or markdown formatting like ```json.
-The JSON object must have one key: "questions", containing a JSON array of task objects.
-
-Each object in the array must contain exactly three keys: `question`, `answer`, and `sql`.
-
--   **`question`**: (string) A natural language description of the task for a web agent.
--   **`answer`**: (string, integer, float, or list) The precise and concise answer to the question, derived by running the SQL query against the database.
--   **`sql`**: (string) The exact, runnable MySQL query that was used to find the answer.
-
-### Output Format Example
-```json
-{{
-  "questions": [
-    {{
-      "question": "What is the email address for customer with ID 5?",
-      "answer": "customer5@example.com",
-      "sql": "SELECT email FROM customer_entity WHERE entity_id = 5;"
-    }},
-    {{
-      "question": "Find the total quantity of item with SKU 'ABC-123' in the cart.",
-      "answer": 3,
-      "sql": "SELECT SUM(qty) FROM quote_item WHERE sku = 'ABC-123';"
-    }}
-  ]
-}}
-```
-
----
-### Full Database Schema
-{schema_context}
-
----
-### Sampled Data
-Here is the sample data from randomly selected tables. Use this to make your questions specific.
-
-{sampled_data_str}
-
----
-Now, generate the JSON object based on these instructions.
-"""
-
-# This is a new prompt to evaluate results and generate a corrected answer.
-SEMANTIC_EVALUATION_PROMPT_TEMPLATE = """
-You are a precise data analyst. Your task is to evaluate if a SQL query's result adequately answers a given natural language question. You will then either refine the answer, or completely rephrase the question if the result set is large.
-
-I will provide you with a JSON object containing:
-1. `question`: The original question asked.
-2. `sql`: The SQL query that was executed.
-3. `sql_result`: The actual data returned by executing the SQL query.
-4. `row_count`: The number of rows in `sql_result`.
-
-## Your Task
-Analyze the inputs and respond with a JSON object. You have three cases. The `new_answer` field MUST always be an array of strings.
-
-### Case 1: Large Result Set (Question Transformation)
-If `row_count` is greater than 10 AND the original `question` does NOT already ask for a count (e.g., it is not phrased like "How many..."), you must transform the question.
-Respond with:
-```json
-{{
-  "can_answer": true,
-  "new_question": "How many items were found?",
-  "new_answer": ["42"]
-}}
-```
-- `can_answer`: (boolean) Must be `true`.
-- `new_question`: (string) A rephrased question that asks for the quantity of items. For example, if the original question was "List all products", the new question should be "How many products were found?".
-- `new_answer`: (array of strings) An array containing the `row_count` as a single string element.
-
-### Case 2: Standard Answer (No Transformation)
-If Case 1 does not apply, but the `sql_result` still provides a clear answer to the original `question`, respond with:
-```json
-{{
-  "can_answer": true,
-  "new_answer": ["value1", "value2", ...]
-}}
-```
-- `can_answer`: (boolean) Must be `true`.
-- `new_answer`: (array of strings) An array containing all the essential parts of the answer extracted from `sql_result`. Every value from the result set that contributes to the answer should be included as a string in the array. This ensures answer completeness.
-  - **Example 1**: If `question` is "What is the status of order 123?" and `sql_result` is `[["processing"]]`, `new_answer` should be `["processing"]`.
-  - **Example 2**: If `question` is "List emails for pending customers" and `sql_result` is `[["test@a.com"], ["test@b.com"]]`, `new_answer` should be `["test@a.com", "test@b.com"]`.
-  - **Example 3**: If `question` is "Get product name and price for SKU 'XYZ'" and `sql_result` is `[["My Product", 19.99]]`, `new_answer` should be `["My Product", "19.99"]`.
-
-### Case 3: The question CANNOT be answered
-If the `sql_result` is empty, irrelevant, or insufficient to answer the question, respond with:
-```json
-{{
-  "can_answer": false,
-  "reason": "..."
-}}
-```
-- `can_answer`: (boolean) Must be `false`.
-- `reason`: (string) A brief explanation for why the question cannot be answered.
-
----
-### Evaluation Data
-{task_data_json}
----
-
-Now, provide your evaluation as a JSON object.
-"""
-
-def get_db_connection():
-    """Establishes a connection to the MySQL database."""
-    try:
-        conn = mysql.connector.connect(**MYSQL_CONFIG)
-        return conn
-    except mysql.connector.Error as err:
-        print(f"Error connecting to MySQL: {err}")
-        return None
-
-def get_full_schema(cursor, tables):
-    """Fetches the CREATE TABLE statements for all core tables."""
-    schema_parts = []
-    for table_name in tables:
-        try:
-            cursor.execute(f"SHOW CREATE TABLE `{table_name}`")
-            result = cursor.fetchone()
-            if result:
-                schema_parts.append(result[1]) # result[1] is the CREATE TABLE statement
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not get schema for table {table_name}: {err}")
-    return "\n\n".join(schema_parts)
-
-def get_random_tables_and_samples(cursor, tables, num_tables=5, num_samples=5):
-    """Selects random tables and samples random rows from them."""
-    selected_tables = random.sample(tables, num_tables)
-    sampled_data = {}
-
-    for table_name in selected_tables:
-        try:
-            # Use ORDER BY RAND() for random sampling. Can be slow on very large tables.
-            query = f"SELECT * FROM `{table_name}` ORDER BY RAND() LIMIT {num_samples}"
-            cursor.execute(query)
-            
-            rows = cursor.fetchall()
-            if not rows:
-                sampled_data[table_name] = []
-                continue
-
-            columns = [desc[0] for desc in cursor.description]
-            
-            # Convert rows (tuples) to a list of dictionaries
-            sampled_rows = []
-            for row in rows:
-                row_dict = {}
-                for i, col_value in enumerate(row):
-                    # Handle bytes by decoding, fall back to string representation
-                    if isinstance(col_value, bytes):
-                        try:
-                            row_dict[columns[i]] = col_value.decode('utf-8')
-                        except UnicodeDecodeError:
-                            row_dict[columns[i]] = str(col_value)
-                    else:
-                        row_dict[columns[i]] = col_value
-                sampled_rows.append(row_dict)
-            
-            sampled_data[table_name] = sampled_rows
-
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not sample data from table {table_name}: {err}")
-            sampled_data[table_name] = f"Error: {err}"
-
-    return sampled_data
-
-def generate_questions(client, schema_context, sampled_data):
-    """Generates questions by calling the OpenAI API."""
-    if not client:
-        raise ValueError("OpenAI client not provided.")
-    
-    sampled_data_str = json.dumps(sampled_data, indent=2, default=str)
-    
-    prompt = PROMPT_TEMPLATE.format(
-        schema_context=schema_context,
-        sampled_data_str=sampled_data_str
-    )
-
-    try:
-        response = client.chat.completions.create(
-            model=OPENAI_CONFIG["model"],
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-            response_format={"type": "json_object"},
-        )
-        content = response.choices[0].message.content
-        data = json.loads(content)
-
-        # The prompt asks for {"questions": [...]}, so we extract the list.
-        if isinstance(data, dict) and "questions" in data and isinstance(data["questions"], list):
-            return data["questions"]
-        elif isinstance(data, list):
-            # Fallback in case the model returns a list directly
-            print("Warning: Model returned a raw list instead of an object with a 'questions' key.")
-            return data
-        else:
-            print(f"Warning: Failed to find a 'questions' list in the model's output. Got: {content}")
-            return None
-
-    except Exception as e:
-        print(f"Error calling OpenAI API or parsing JSON: {e}")
-        return None
-
-def load_existing_tasks(filepath):
-    """Loads tasks from a JSON file if it exists."""
-    if not os.path.exists(filepath):
-        return []
-    try:
-        with open(filepath, 'r') as f:
-            content = f.read()
-            if not content: # Handle empty file
-                return []
-            return json.loads(content)
-    except (json.JSONDecodeError, FileNotFoundError):
-        print(f"Warning: Could not read or parse {filepath}. Starting with an empty list.")
-        return []
-
-def evaluate_and_refine_tasks(tasks, client):
-    """
-    Uses an LLM to evaluate if a SQL result answers the question and refines the answer.
-    """
-    if not tasks:
-        return []
-
-    final_validated_tasks = []
-    print("\nPerforming semantic evaluation and answer refinement with GPT-4o...")
-
-    for task in tasks:
-        # Prepare data for the prompt, excluding the original 'answer'
-        task_data_for_prompt = {
-            "question": task["question"],
-            "sql": task["sql"],
-            "sql_result": task["sql_result"],
-            "row_count": task["row_count"]
-        }
-        task_data_json = json.dumps(task_data_for_prompt, indent=2, default=str)
-
-        prompt = SEMANTIC_EVALUATION_PROMPT_TEMPLATE.format(task_data_json=task_data_json)
-
-        try:
-            print(f"  - Evaluating question: \"{task['question'][:80]}...\"")
-            response = client.chat.completions.create(
-                model=OPENAI_CONFIG["model"],
-                messages=[
-                    {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                    {"role": "user", "content": prompt}
-                ],
-                temperature=0.0,  # We want deterministic evaluation
-                response_format={"type": "json_object"},
-            )
-            content = response.choices[0].message.content
-            evaluation_result = json.loads(content)
-
-            if evaluation_result.get("can_answer") is True and "new_answer" in evaluation_result:
-                # Task is valid. Update the answer with the refined one from the LLM.
-                task['answer'] = evaluation_result['new_answer']
-
-                # If the LLM provides a new question, update it.
-                if 'new_question' in evaluation_result:
-                    task['question'] = evaluation_result['new_question']
-                    print(f"    - Question was rephrased: \"{task['question']}\"")
-
-                task['sql_execute_result'] = task.pop('sql_result')
-                task.pop('row_count', None) # Clean up temp key
-                final_validated_tasks.append(task)
-                print(f"    - Evaluation PASSED. New answer: {json.dumps(task['answer'])}")
-            else:
-                reason = evaluation_result.get('reason', 'No reason provided.')
-                print(f"    - Evaluation FAILED. Filtering task.")
-                print(f"      - Reason: {reason}")
-                print(f"      - Question: {task['question']}")
-                print(f"      - SQL: {task['sql']}")
-                sql_result_str = json.dumps(task['sql_result'], indent=2, default=str)
-                print(f"      - SQL Result: {sql_result_str}")
-
-        except Exception as e:
-            print(f"    - An error occurred during semantic evaluation for task, filtering it out: {e}")
-            print(f"      - Question: {task.get('question', 'N/A')}")
-            print(f"      - SQL: {task.get('sql', 'N/A')}")
-
-    return final_validated_tasks
-
-def main():
-    """Main function to run the script."""
-    parser = argparse.ArgumentParser(description="Generate and validate e-commerce admin tasks.")
-    parser.add_argument(
-        "--target-count",
-        type=int,
-        required=True,
-        help="The total number of questions to generate."
-    )
-    parser.add_argument(
-        "--output-file",
-        type=str,
-        default="generated_tasks.json",
-        help="The file to save the generated tasks to (in JSON format)."
-    )
-    args = parser.parse_args()
-
-    # Load existing tasks from the output file
-    all_tasks = load_existing_tasks(args.output_file)
-    print(f"Found {len(all_tasks)} existing valid tasks in '{args.output_file}'.")
-
-    # Connect to DB and set up client
-    conn = get_db_connection()
-    if not conn:
-        return
-    cursor = conn.cursor()
-
-    if not OPENAI_CONFIG["api_key"]:
-        print("Error: OPENAI_API_KEY environment variable not set.")
-        return
-    client = OpenAI(api_key=OPENAI_CONFIG["api_key"], base_url=OPENAI_CONFIG["base_url"])
-
-    try:
-        # Load core tables and schema once
-        try:
-            with open('core_tables.json', 'r') as f:
-                core_tables = json.load(f)
-        except FileNotFoundError:
-            print("Error: core_tables.json not found. Please create it.")
-            return
-
-        print("Fetching full database schema...")
-        schema_context = get_full_schema(cursor, core_tables)
-        
-        # Start the generation loop
-        round_num = 1
-        while len(all_tasks) < args.target_count:
-            print(f"\n--- Starting Generation Round {round_num} ---")
-            print(f"Goal: {args.target_count} | Current: {len(all_tasks)} | Needed: {args.target_count - len(all_tasks)}")
-            
-            # Get random samples for this round
-            print("Sampling data from 5 random tables...")
-            sampled_data = get_random_tables_and_samples(cursor, core_tables, num_tables=5, num_samples=5)
-            
-            # Generate questions
-            print("Generating questions with GPT-4o...")
-            generated_tasks = generate_questions(client, schema_context, sampled_data)
-
-            # Execute SQL for generated tasks
-            tasks_for_evaluation = []
-            if generated_tasks:
-                print("\nExecuting SQL for generated tasks...")
-                for task in generated_tasks:
-                    if not isinstance(task, dict) or not all(k in task for k in ['sql', 'answer', 'question']):
-                        print(f"Filtering task due to malformed structure: {task}")
-                        continue
-                    try:
-                        cursor.execute(task['sql'])
-                        sql_result = cursor.fetchall()
-                        # Create a new dict for evaluation, excluding the original 'answer'.
-                        tasks_for_evaluation.append({
-                            'question': task['question'],
-                            'sql': task['sql'],
-                            'sql_result': sql_result,
-                            'row_count': len(sql_result)
-                        })
-                    except mysql.connector.Error as err:
-                        print(f"Filtering task due to SQL error: {err} on SQL: {task['sql']}")
-
-            # Perform semantic evaluation and get validated tasks
-            validated_tasks = evaluate_and_refine_tasks(tasks_for_evaluation, client)
-
-            # Append new tasks and save to file
-            if validated_tasks:
-                all_tasks.extend(validated_tasks)
-                with open(args.output_file, 'w') as f:
-                    json.dump(all_tasks, f, indent=2, default=str)
-                
-                print("\n--- Round Summary ---")
-                print(f"Generated {len(validated_tasks)} new valid tasks in this round.")
-                print(f"Progress: {len(all_tasks)} / {args.target_count} tasks.")
-            else:
-                print("\n--- Round Summary ---")
-                print("No new valid tasks were generated in this round. Retrying...")
-
-            round_num += 1
-
-    finally:
-        # Close the database connection
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
-            print("\nDatabase connection closed.")
-    
-    print(f"\nTarget of {args.target_count} tasks reached. Final output saved to {args.output_file}.")
-
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/random_sample/generate_tasks copy.py b/random_sample/generate_tasks copy.py
deleted file mode 100644
index 43324cc..0000000
--- a/random_sample/generate_tasks copy.py	
+++ /dev/null
@@ -1,246 +0,0 @@
-import os
-import random
-import json
-import mysql.connector
-from openai import OpenAI
-from dotenv import load_dotenv
-
-# --- Configuration ---
-load_dotenv()
-
-MYSQL_CONFIG = {
-    "host": "localhost",
-    "port": "23306",
-    "user": "mcpuser",
-    "password": "StrongPass123!",
-    "database": "magentodb"
-}
-
-OPENAI_CONFIG = {
-    "api_key": os.getenv("OPENAI_API_KEY"),
-    "base_url": os.getenv("OPENAI_BASE_URL"),
-    "model": "gpt-4o"
-}
-
-# --- Prompt Template ---
-# This is a carefully engineered prompt to guide the LLM's output.
-PROMPT_TEMPLATE = """
-You are an expert database analyst and a creative test case designer for e-commerce web applications.
-Your goal is to generate realistic administrative tasks that can be solved by a Web Agent navigating an admin panel.
-
-I will provide you with the following context:
-1.  **Full Database Schema**: A list of `CREATE TABLE` statements for the core tables of a Magento e-commerce platform.
-2.  **Sampled Data**: A JSON object containing 5 random rows of data from 5 randomly selected core tables. This data is REAL and should be used to inspire specific, answerable questions.
-
-## Your Task
-
-Based on the provided schema and sample data, create a JSON array of up to 10 unique questions.
-
-### Requirements for Each Question:
-- **Web Agent Solvable**: The task must represent a realistic action an administrator would perform in a web UI (e.g., "Find all orders for customer X", "Update the stock for product Y", "Approve a pending review").
-- **Grounded in Data**: The questions should be specific, using names, IDs, or values from the provided **Sampled Data** to make them concrete.
-- **Utilize Schema**: You can formulate questions that require joining tables, even if not all tables were sampled. The full schema is your guide.
-
-### Output Format
-The final output MUST be a single, valid JSON array of objects. Do not include any other text, explanations, or markdown formatting like ```json.
-
-Each object in the array must contain exactly three keys: `question`, `answer`, and `sql`.
-
--   **`question`**: (string) A natural language description of the task for a web agent.
--   **`answer`**: (string, integer, float, or list) The precise and concise answer to the question, derived by running the SQL query against the database.
--   **`sql`**: (string) The exact, runnable MySQL query that was used to find the answer.
-
----
-### Full Database Schema
-{schema_context}
-
----
-### Sampled Data
-Here is the sample data from randomly selected tables. Use this to make your questions specific.
-
-{sampled_data_str}
-
----
-Now, generate the JSON array based on these instructions.
-"""
-
-def get_db_connection():
-    """Establishes a connection to the MySQL database."""
-    try:
-        conn = mysql.connector.connect(**MYSQL_CONFIG)
-        return conn
-    except mysql.connector.Error as err:
-        print(f"Error connecting to MySQL: {err}")
-        return None
-
-def get_full_schema(cursor, tables):
-    """Fetches the CREATE TABLE statements for all core tables."""
-    schema_parts = []
-    for table_name in tables:
-        try:
-            cursor.execute(f"SHOW CREATE TABLE `{table_name}`")
-            result = cursor.fetchone()
-            if result:
-                schema_parts.append(result[1]) # result[1] is the CREATE TABLE statement
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not get schema for table {table_name}: {err}")
-    return "\n\n".join(schema_parts)
-
-def get_random_tables_and_samples(cursor, tables, num_tables=5, num_samples=5):
-    """Selects random tables and samples random rows from them."""
-    selected_tables = random.sample(tables, num_tables)
-    sampled_data = {}
-
-    for table_name in selected_tables:
-        try:
-            # Use ORDER BY RAND() for random sampling. Can be slow on very large tables.
-            query = f"SELECT * FROM `{table_name}` ORDER BY RAND() LIMIT {num_samples}"
-            cursor.execute(query)
-            
-            rows = cursor.fetchall()
-            if not rows:
-                sampled_data[table_name] = []
-                continue
-
-            columns = [desc[0] for desc in cursor.description]
-            
-            # Convert rows (tuples) to a list of dictionaries
-            sampled_rows = []
-            for row in rows:
-                row_dict = {}
-                for i, col_value in enumerate(row):
-                    # Handle bytes by decoding, fall back to string representation
-                    if isinstance(col_value, bytes):
-                        try:
-                            row_dict[columns[i]] = col_value.decode('utf-8')
-                        except UnicodeDecodeError:
-                            row_dict[columns[i]] = str(col_value)
-                    else:
-                        row_dict[columns[i]] = col_value
-                sampled_rows.append(row_dict)
-            
-            sampled_data[table_name] = sampled_rows
-
-        except mysql.connector.Error as err:
-            print(f"Warning: Could not sample data from table {table_name}: {err}")
-            sampled_data[table_name] = f"Error: {err}"
-
-    return sampled_data
-
-def generate_questions(schema_context, sampled_data):
-    """Generates questions by calling the OpenAI API."""
-    if not OPENAI_CONFIG["api_key"]:
-        raise ValueError("OPENAI_API_KEY environment variable not set.")
-
-    client = OpenAI(api_key=OPENAI_CONFIG["api_key"], base_url=OPENAI_CONFIG["base_url"])
-    
-    sampled_data_str = json.dumps(sampled_data, indent=2, default=str)
-    
-    prompt = PROMPT_TEMPLATE.format(
-        schema_context=schema_context,
-        sampled_data_str=sampled_data_str
-    )
-
-    try:
-        response = client.chat.completions.create(
-            model=OPENAI_CONFIG["model"],
-            messages=[
-                {"role": "system", "content": "You are a helpful assistant designed to output JSON."},
-                {"role": "user", "content": prompt}
-            ],
-            temperature=0.7,
-        )
-        content = response.choices[0].message.content
-        return json.loads(content)
-    except Exception as e:
-        print(f"Error calling OpenAI API: {e}")
-        return None
-
-def main():
-    """Main function to run the script."""
-    # 1. Load the list of core tables
-    try:
-        with open('core_tables.json', 'r') as f:
-            core_tables = json.load(f)
-    except FileNotFoundError:
-        print("Error: core_tables.json not found. Please create it.")
-        return
-
-    # 2. Connect to the database
-    conn = get_db_connection()
-    if not conn:
-        return
-        
-    cursor = conn.cursor()
-    
-    try:
-        # 3. Get full schema context
-        print("Fetching full database schema...")
-        schema_context = get_full_schema(cursor, core_tables)
-
-        # 4. Get random samples and print them
-        print("Sampling data from 5 random tables...")
-        sampled_data = get_random_tables_and_samples(cursor, core_tables, num_tables=5, num_samples=5)
-        print(f"Sampled from tables: {list(sampled_data.keys())}")
-        print("\n--- Sampled Data ---")
-        print(json.dumps(sampled_data, indent=2, default=str))
-        print("---------------------\n")
-
-        # 5. Generate questions using the LLM
-        print("Generating questions with GPT-4o...")
-        generated_tasks = generate_questions(schema_context, sampled_data)
-
-        # 6. Validate and filter the generated tasks
-        validated_tasks = []
-        if generated_tasks:
-            print("\nValidating generated tasks...")
-            for task in generated_tasks:
-                # Basic validation for task structure
-                if not isinstance(task, dict) or not all(k in task for k in ['sql', 'answer', 'question']):
-                    print(f"Filtering task due to malformed structure or missing keys: {task}")
-                    continue
-                
-                try:
-                    # Execute the SQL query from the task
-                    cursor.execute(task['sql'])
-                    sql_result = cursor.fetchall()
-
-                    # Convert both answer and result to string for flexible substring matching
-                    answer_str = str(task['answer'])
-                    result_str = str(sql_result)
-                    
-                    # If the answer exists in the result, the task is valid
-                    if answer_str in result_str:
-                        validated_tasks.append(task)
-                    else:
-                        # Log tasks that are filtered because the answer doesn't match
-                        print(f"Filtering task: Answer '{answer_str}' not found in SQL result.")
-                        print(f"  - Question: {task['question']}")
-                        print(f"  - SQL: {task['sql']}")
-                        # Showing a snippet of a large result is helpful for debugging
-                        print(f"  - Result: {result_str[:250]}...")
-
-                except mysql.connector.Error as err:
-                    # Log tasks that are filtered due to SQL errors
-                    print(f"Filtering task due to SQL error: {err}")
-                    print(f"  - Question: {task['question']}")
-                    print(f"  - SQL: {task['sql']}")
-                except Exception as e:
-                    print(f"An unexpected error occurred during validation for task {task}: {e}")
-
-        # 7. Print the final JSON output
-        if validated_tasks:
-            print("\n--- Generated and Validated Tasks ---")
-            print(json.dumps(validated_tasks, indent=2))
-        else:
-            print("Failed to generate any valid tasks.")
-
-    finally:
-        # 8. Close the database connection
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
-            print("\nDatabase connection closed.")
-
-if __name__ == "__main__":
-    main()
\ No newline at end of file
diff --git a/random_sample/generate_tasks.py b/random_sample/generate_tasks.py
index 1aa2095..f5bf278 100644
--- a/random_sample/generate_tasks.py
+++ b/random_sample/generate_tasks.py
@@ -9,8 +9,10 @@ from dotenv import load_dotenv
 # --- Configuration ---
 load_dotenv()
 
+server_address = "localhost"
+
 MYSQL_CONFIG = {
-    "host": "localhost",
+    "host": server_address,
     "port": "23306",
     "user": "mcpuser",
     "password": "StrongPass123!",
diff --git a/random_sample/generated_tasks.json.bak b/random_sample/generated_tasks.json.bak
deleted file mode 100644
index d19033a..0000000
--- a/random_sample/generated_tasks.json.bak
+++ /dev/null
@@ -1,3539 +0,0 @@
-[
-  {
-    "question": "What is the SKU of the product with entity_id 1304?",
-    "answer": "adrienne-trek-jacket-s-gray",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 1304 AND attribute_id = 121 AND store_id = 0;",
-    "sql_execute_result": [
-      [
-        "adrienne-trek-jacket-s-gray"
-      ]
-    ]
-  },
-  {
-    "question": "What is the shipping method for the order with increment ID '000000092'?",
-    "answer": "flatrate_flatrate",
-    "sql": "SELECT shipping_method FROM sales_order WHERE increment_id = '000000092';",
-    "sql_execute_result": [
-      [
-        "flatrate_flatrate"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for the order with entity ID 166?",
-    "answer": "5.0000",
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE entity_id = 166;",
-    "sql_execute_result": [
-      [
-        "5.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the base grand total for the sales order with entity ID 190?",
-    "answer": "145.0000",
-    "sql": "SELECT base_grand_total FROM sales_order WHERE entity_id = 190;",
-    "sql_execute_result": [
-      [
-        "145.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Has the email for the order with increment ID '000000092' been sent?",
-    "answer": "Yes, the email for the order with increment ID '000000092' has been sent.",
-    "sql": "SELECT email_sent FROM sales_order WHERE increment_id = '000000092';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "List all complete orders with a flat rate shipping method.",
-    "answer": [
-      4,
-      9,
-      11,
-      13,
-      16,
-      17,
-      20,
-      21,
-      22,
-      23,
-      24,
-      27,
-      28,
-      31,
-      32,
-      33,
-      34,
-      35,
-      36,
-      37,
-      43,
-      45,
-      47,
-      48,
-      50,
-      51,
-      53,
-      54,
-      55,
-      57,
-      61,
-      62,
-      64,
-      69,
-      70,
-      71,
-      73,
-      75,
-      78,
-      79,
-      82,
-      83,
-      84,
-      87,
-      89,
-      90,
-      91,
-      92,
-      93,
-      96,
-      97,
-      99,
-      100,
-      102,
-      104,
-      105,
-      112,
-      113,
-      114,
-      115,
-      116,
-      119,
-      121,
-      127,
-      128,
-      130,
-      131,
-      133,
-      137,
-      138,
-      139,
-      140,
-      145,
-      146,
-      147,
-      148,
-      150,
-      154,
-      155,
-      156,
-      158,
-      160,
-      161,
-      163,
-      164,
-      166,
-      169,
-      179,
-      181,
-      182,
-      184,
-      186,
-      187,
-      188,
-      189,
-      190,
-      192,
-      196,
-      197,
-      199,
-      200,
-      201,
-      202,
-      203,
-      205,
-      207,
-      208,
-      213,
-      214,
-      215,
-      216,
-      217,
-      218,
-      223,
-      225,
-      228,
-      230,
-      231,
-      233,
-      235,
-      236,
-      237,
-      238,
-      239,
-      240,
-      243,
-      247,
-      250,
-      251,
-      253,
-      256,
-      257,
-      258,
-      260,
-      262,
-      263,
-      264,
-      268,
-      269,
-      270,
-      274,
-      276,
-      277,
-      281,
-      282,
-      284,
-      285,
-      286,
-      287,
-      288,
-      295,
-      297,
-      298
-    ],
-    "sql": "SELECT entity_id FROM sales_order WHERE status = 'complete' AND shipping_method = 'flatrate_flatrate';",
-    "sql_execute_result": [
-      [
-        4
-      ],
-      [
-        9
-      ],
-      [
-        11
-      ],
-      [
-        13
-      ],
-      [
-        16
-      ],
-      [
-        17
-      ],
-      [
-        20
-      ],
-      [
-        21
-      ],
-      [
-        22
-      ],
-      [
-        23
-      ],
-      [
-        24
-      ],
-      [
-        27
-      ],
-      [
-        28
-      ],
-      [
-        31
-      ],
-      [
-        32
-      ],
-      [
-        33
-      ],
-      [
-        34
-      ],
-      [
-        35
-      ],
-      [
-        36
-      ],
-      [
-        37
-      ],
-      [
-        43
-      ],
-      [
-        45
-      ],
-      [
-        47
-      ],
-      [
-        48
-      ],
-      [
-        50
-      ],
-      [
-        51
-      ],
-      [
-        53
-      ],
-      [
-        54
-      ],
-      [
-        55
-      ],
-      [
-        57
-      ],
-      [
-        61
-      ],
-      [
-        62
-      ],
-      [
-        64
-      ],
-      [
-        69
-      ],
-      [
-        70
-      ],
-      [
-        71
-      ],
-      [
-        73
-      ],
-      [
-        75
-      ],
-      [
-        78
-      ],
-      [
-        79
-      ],
-      [
-        82
-      ],
-      [
-        83
-      ],
-      [
-        84
-      ],
-      [
-        87
-      ],
-      [
-        89
-      ],
-      [
-        90
-      ],
-      [
-        91
-      ],
-      [
-        92
-      ],
-      [
-        93
-      ],
-      [
-        96
-      ],
-      [
-        97
-      ],
-      [
-        99
-      ],
-      [
-        100
-      ],
-      [
-        102
-      ],
-      [
-        104
-      ],
-      [
-        105
-      ],
-      [
-        112
-      ],
-      [
-        113
-      ],
-      [
-        114
-      ],
-      [
-        115
-      ],
-      [
-        116
-      ],
-      [
-        119
-      ],
-      [
-        121
-      ],
-      [
-        127
-      ],
-      [
-        128
-      ],
-      [
-        130
-      ],
-      [
-        131
-      ],
-      [
-        133
-      ],
-      [
-        137
-      ],
-      [
-        138
-      ],
-      [
-        139
-      ],
-      [
-        140
-      ],
-      [
-        145
-      ],
-      [
-        146
-      ],
-      [
-        147
-      ],
-      [
-        148
-      ],
-      [
-        150
-      ],
-      [
-        154
-      ],
-      [
-        155
-      ],
-      [
-        156
-      ],
-      [
-        158
-      ],
-      [
-        160
-      ],
-      [
-        161
-      ],
-      [
-        163
-      ],
-      [
-        164
-      ],
-      [
-        166
-      ],
-      [
-        169
-      ],
-      [
-        179
-      ],
-      [
-        181
-      ],
-      [
-        182
-      ],
-      [
-        184
-      ],
-      [
-        186
-      ],
-      [
-        187
-      ],
-      [
-        188
-      ],
-      [
-        189
-      ],
-      [
-        190
-      ],
-      [
-        192
-      ],
-      [
-        196
-      ],
-      [
-        197
-      ],
-      [
-        199
-      ],
-      [
-        200
-      ],
-      [
-        201
-      ],
-      [
-        202
-      ],
-      [
-        203
-      ],
-      [
-        205
-      ],
-      [
-        207
-      ],
-      [
-        208
-      ],
-      [
-        213
-      ],
-      [
-        214
-      ],
-      [
-        215
-      ],
-      [
-        216
-      ],
-      [
-        217
-      ],
-      [
-        218
-      ],
-      [
-        223
-      ],
-      [
-        225
-      ],
-      [
-        228
-      ],
-      [
-        230
-      ],
-      [
-        231
-      ],
-      [
-        233
-      ],
-      [
-        235
-      ],
-      [
-        236
-      ],
-      [
-        237
-      ],
-      [
-        238
-      ],
-      [
-        239
-      ],
-      [
-        240
-      ],
-      [
-        243
-      ],
-      [
-        247
-      ],
-      [
-        250
-      ],
-      [
-        251
-      ],
-      [
-        253
-      ],
-      [
-        256
-      ],
-      [
-        257
-      ],
-      [
-        258
-      ],
-      [
-        260
-      ],
-      [
-        262
-      ],
-      [
-        263
-      ],
-      [
-        264
-      ],
-      [
-        268
-      ],
-      [
-        269
-      ],
-      [
-        270
-      ],
-      [
-        274
-      ],
-      [
-        276
-      ],
-      [
-        277
-      ],
-      [
-        281
-      ],
-      [
-        282
-      ],
-      [
-        284
-      ],
-      [
-        285
-      ],
-      [
-        286
-      ],
-      [
-        287
-      ],
-      [
-        288
-      ],
-      [
-        295
-      ],
-      [
-        297
-      ],
-      [
-        298
-      ]
-    ]
-  },
-  {
-    "question": "How many items are ordered in total for the order with increment ID '000000190'?",
-    "answer": 2.0,
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE increment_id = '000000190';",
-    "sql_execute_result": [
-      [
-        "2.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total weight of the order with entity ID 193?",
-    "answer": "4.0000",
-    "sql": "SELECT weight FROM sales_order WHERE entity_id = 193;",
-    "sql_execute_result": [
-      [
-        "4.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Is the order with increment ID '000000023' a virtual order?",
-    "answer": "No, the order with increment ID '000000023' is not a virtual order.",
-    "sql": "SELECT is_virtual FROM sales_order WHERE increment_id = '000000023';",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the total number of completed orders for customer Matt Baker?",
-    "answer": 7,
-    "sql": "SELECT COUNT(*) FROM sales_order_grid WHERE customer_id = 13 AND status = 'complete';",
-    "sql_execute_result": [
-      [
-        7
-      ]
-    ]
-  },
-  {
-    "question": "Find the email of the customer who placed the order with increment ID '000000290'.",
-    "answer": "jla_7781@gmail.com",
-    "sql": "SELECT customer_email FROM sales_order_grid WHERE increment_id = '000000290';",
-    "sql_execute_result": [
-      [
-        "jla_7781@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the category with the entity ID 22?",
-    "answer": "bottoms-women",
-    "sql": "SELECT value FROM catalog_category_entity_varchar WHERE entity_id = 22 AND attribute_id = 119;",
-    "sql_execute_result": [
-      [
-        "bottoms-women"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status of the order with increment ID '000000126'?",
-    "answer": "canceled",
-    "sql": "SELECT status FROM sales_order_grid WHERE increment_id = '000000126';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "Determine the shipping method for Matt Baker's order created on '2022-03-31'.",
-    "answer": "Flat Rate - Fixed",
-    "sql": "SELECT shipping_information FROM sales_order_grid WHERE customer_email = 'matt.baker@yahoo.com' AND created_at = '2022-03-31 05:17:09';",
-    "sql_execute_result": [
-      [
-        "Flat Rate - Fixed"
-      ]
-    ]
-  },
-  {
-    "question": "What is the default state for the status 'complete'?",
-    "answer": "complete",
-    "sql": "SELECT state FROM sales_order_status_state WHERE status = 'complete';",
-    "sql_execute_result": [
-      [
-        "complete"
-      ]
-    ]
-  },
-  {
-    "question": "Find the customer group ID for the customer who placed the order with increment ID '000000092'.",
-    "answer": "1",
-    "sql": "SELECT customer_group FROM sales_order_grid WHERE increment_id = '000000092';",
-    "sql_execute_result": [
-      [
-        "1"
-      ]
-    ]
-  },
-  {
-    "question": "What is the label for the status 'processing'?",
-    "answer": "Processing",
-    "sql": "SELECT label FROM sales_order_status WHERE status = 'processing';",
-    "sql_execute_result": [
-      [
-        "Processing"
-      ]
-    ]
-  },
-  {
-    "question": "Find all orders for customer with email 'soccerfanatic22@gmail.com'.",
-    "answer": [
-      {
-        "entity_id": 123,
-        "increment_id": "000000123",
-        "grand_total": "209.0000"
-      },
-      {
-        "entity_id": 129,
-        "increment_id": "000000129",
-        "grand_total": "151.0000"
-      },
-      {
-        "entity_id": 155,
-        "increment_id": "000000155",
-        "grand_total": "191.0000"
-      },
-      {
-        "entity_id": 162,
-        "increment_id": "000000162",
-        "grand_total": "152.2000"
-      },
-      {
-        "entity_id": 170,
-        "increment_id": "000000170",
-        "grand_total": "66.0000"
-      },
-      {
-        "entity_id": 242,
-        "increment_id": "000000242",
-        "grand_total": "183.0000"
-      },
-      {
-        "entity_id": 285,
-        "increment_id": "000000285",
-        "grand_total": "82.0000"
-      },
-      {
-        "entity_id": 286,
-        "increment_id": "000000286",
-        "grand_total": "101.2500"
-      }
-    ],
-    "sql": "SELECT entity_id, increment_id, grand_total FROM sales_order WHERE customer_email = 'soccerfanatic22@gmail.com';",
-    "sql_execute_result": [
-      [
-        123,
-        "000000123",
-        "209.0000"
-      ],
-      [
-        129,
-        "000000129",
-        "151.0000"
-      ],
-      [
-        155,
-        "000000155",
-        "191.0000"
-      ],
-      [
-        162,
-        "000000162",
-        "152.2000"
-      ],
-      [
-        170,
-        "000000170",
-        "66.0000"
-      ],
-      [
-        242,
-        "000000242",
-        "183.0000"
-      ],
-      [
-        285,
-        "000000285",
-        "82.0000"
-      ],
-      [
-        286,
-        "000000286",
-        "101.2500"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for the order with increment ID '000000141'?",
-    "answer": "4.0000",
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE increment_id = '000000141';",
-    "sql_execute_result": [
-      [
-        "4.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the region code for 'Kauno Apskritis' in Lithuania.",
-    "answer": "LT-KU",
-    "sql": "SELECT code FROM directory_country_region WHERE default_name = 'Kauno Apskritis' AND country_id = 'LT';",
-    "sql_execute_result": [
-      [
-        "LT-KU"
-      ]
-    ]
-  },
-  {
-    "question": "List the products with SKU containing 'Sprite Stasis Ball 75 cm'.",
-    "answer": [
-      "24-WG083-blue",
-      "24-WG083-gray",
-      "24-WG083-pink"
-    ],
-    "sql": "SELECT product_id, sku, name FROM sales_order_item WHERE name LIKE '%Sprite Stasis Ball 75 cm%';",
-    "sql_execute_result": [
-      [
-        32,
-        "24-WG083-blue",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        30,
-        "24-WG083-gray",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        32,
-        "24-WG083-blue",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        31,
-        "24-WG083-pink",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        30,
-        "24-WG083-gray",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        31,
-        "24-WG083-pink",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        32,
-        "24-WG083-blue",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        32,
-        "24-WG083-blue",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        31,
-        "24-WG083-pink",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        31,
-        "24-WG083-pink",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        30,
-        "24-WG083-gray",
-        "Sprite Stasis Ball 75 cm"
-      ],
-      [
-        30,
-        "24-WG083-gray",
-        "Sprite Stasis Ball 75 cm"
-      ]
-    ]
-  },
-  {
-    "question": "What is the average rating value for product ID 1620?",
-    "answer": 3.0,
-    "sql": "SELECT AVG(value) AS average_rating FROM rating_option_vote WHERE entity_pk_value = 1620;",
-    "sql_execute_result": [
-      [
-        "3.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the order ID for the order that contains the product with SKU 'WJ04-M-Red'.",
-    "answer": [
-      124,
-      244
-    ],
-    "sql": "SELECT order_id FROM sales_order_item WHERE sku = 'WJ04-M-Red';",
-    "sql_execute_result": [
-      [
-        124
-      ],
-      [
-        124
-      ],
-      [
-        244
-      ],
-      [
-        244
-      ]
-    ]
-  },
-  {
-    "question": "What is the customer name for the billing address ID 570?",
-    "answer": "Olivia Lee",
-    "sql": "SELECT customer_firstname, customer_lastname FROM sales_order WHERE billing_address_id = 570;",
-    "sql_execute_result": [
-      [
-        "Olivia",
-        "Lee"
-      ]
-    ]
-  },
-  {
-    "question": "Find the order status for the order with increment ID '000000206'.",
-    "answer": "canceled",
-    "sql": "SELECT status FROM sales_order WHERE increment_id = '000000206';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "List order IDs with the shipping method 'flatrate_flatrate'.",
-    "answer": [
-      1,
-      2,
-      3,
-      4,
-      5,
-      6,
-      7,
-      8,
-      9,
-      10,
-      11,
-      12,
-      13,
-      14,
-      15,
-      16,
-      17,
-      18,
-      19,
-      20,
-      21,
-      22,
-      23,
-      24,
-      25,
-      26,
-      27,
-      28,
-      29,
-      30,
-      31,
-      32,
-      33,
-      34,
-      35,
-      36,
-      37,
-      38,
-      39,
-      40,
-      41,
-      42,
-      43,
-      44,
-      45,
-      46,
-      47,
-      48,
-      49,
-      50,
-      51,
-      52,
-      53,
-      54,
-      55,
-      56,
-      57,
-      58,
-      59,
-      60,
-      61,
-      62,
-      63,
-      64,
-      65,
-      66,
-      67,
-      68,
-      69,
-      70,
-      71,
-      72,
-      73,
-      74,
-      75,
-      76,
-      77,
-      78,
-      79,
-      80,
-      81,
-      82,
-      83,
-      84,
-      85,
-      86,
-      87,
-      88,
-      89,
-      90,
-      91,
-      92,
-      93,
-      94,
-      95,
-      96,
-      97,
-      98,
-      99,
-      100,
-      101,
-      102,
-      103,
-      104,
-      105,
-      106,
-      107,
-      108,
-      109,
-      110,
-      111,
-      112,
-      113,
-      114,
-      115,
-      116,
-      117,
-      118,
-      119,
-      120,
-      121,
-      122,
-      123,
-      124,
-      125,
-      126,
-      127,
-      128,
-      129,
-      130,
-      131,
-      132,
-      133,
-      134,
-      135,
-      136,
-      137,
-      138,
-      139,
-      140,
-      141,
-      142,
-      143,
-      144,
-      145,
-      146,
-      147,
-      148,
-      149,
-      150,
-      151,
-      152,
-      153,
-      154,
-      155,
-      156,
-      157,
-      158,
-      159,
-      160,
-      161,
-      162,
-      163,
-      164,
-      165,
-      166,
-      167,
-      168,
-      169,
-      170,
-      171,
-      172,
-      173,
-      174,
-      175,
-      176,
-      177,
-      178,
-      179,
-      180,
-      181,
-      182,
-      183,
-      184,
-      185,
-      186,
-      187,
-      188,
-      189,
-      190,
-      191,
-      192,
-      193,
-      194,
-      195,
-      196,
-      197,
-      198,
-      199,
-      200,
-      201,
-      202,
-      203,
-      204,
-      205,
-      206,
-      207,
-      208,
-      209,
-      210,
-      211,
-      212,
-      213,
-      214,
-      215,
-      216,
-      217,
-      218,
-      219,
-      220,
-      221,
-      222,
-      223,
-      224,
-      225,
-      226,
-      227,
-      228,
-      229,
-      230,
-      231,
-      232,
-      233,
-      234,
-      235,
-      236,
-      237,
-      238,
-      239,
-      240,
-      241,
-      242,
-      243,
-      244,
-      245,
-      246,
-      247,
-      248,
-      249,
-      250,
-      251,
-      252,
-      253,
-      254,
-      255,
-      256,
-      257,
-      258,
-      259,
-      260,
-      261,
-      262,
-      263,
-      264,
-      265,
-      266,
-      267,
-      268,
-      269,
-      270,
-      271,
-      272,
-      273,
-      274,
-      275,
-      276,
-      277,
-      278,
-      279,
-      280,
-      281,
-      282,
-      283,
-      284,
-      285,
-      286,
-      287,
-      288,
-      289,
-      290,
-      291,
-      292,
-      293,
-      294,
-      295,
-      296,
-      297,
-      298,
-      299,
-      300,
-      301,
-      302,
-      303,
-      304,
-      305,
-      306,
-      307,
-      308
-    ],
-    "sql": "SELECT entity_id FROM sales_order WHERE shipping_method = 'flatrate_flatrate';",
-    "sql_execute_result": [
-      [
-        1
-      ],
-      [
-        2
-      ],
-      [
-        3
-      ],
-      [
-        4
-      ],
-      [
-        5
-      ],
-      [
-        6
-      ],
-      [
-        7
-      ],
-      [
-        8
-      ],
-      [
-        9
-      ],
-      [
-        10
-      ],
-      [
-        11
-      ],
-      [
-        12
-      ],
-      [
-        13
-      ],
-      [
-        14
-      ],
-      [
-        15
-      ],
-      [
-        16
-      ],
-      [
-        17
-      ],
-      [
-        18
-      ],
-      [
-        19
-      ],
-      [
-        20
-      ],
-      [
-        21
-      ],
-      [
-        22
-      ],
-      [
-        23
-      ],
-      [
-        24
-      ],
-      [
-        25
-      ],
-      [
-        26
-      ],
-      [
-        27
-      ],
-      [
-        28
-      ],
-      [
-        29
-      ],
-      [
-        30
-      ],
-      [
-        31
-      ],
-      [
-        32
-      ],
-      [
-        33
-      ],
-      [
-        34
-      ],
-      [
-        35
-      ],
-      [
-        36
-      ],
-      [
-        37
-      ],
-      [
-        38
-      ],
-      [
-        39
-      ],
-      [
-        40
-      ],
-      [
-        41
-      ],
-      [
-        42
-      ],
-      [
-        43
-      ],
-      [
-        44
-      ],
-      [
-        45
-      ],
-      [
-        46
-      ],
-      [
-        47
-      ],
-      [
-        48
-      ],
-      [
-        49
-      ],
-      [
-        50
-      ],
-      [
-        51
-      ],
-      [
-        52
-      ],
-      [
-        53
-      ],
-      [
-        54
-      ],
-      [
-        55
-      ],
-      [
-        56
-      ],
-      [
-        57
-      ],
-      [
-        58
-      ],
-      [
-        59
-      ],
-      [
-        60
-      ],
-      [
-        61
-      ],
-      [
-        62
-      ],
-      [
-        63
-      ],
-      [
-        64
-      ],
-      [
-        65
-      ],
-      [
-        66
-      ],
-      [
-        67
-      ],
-      [
-        68
-      ],
-      [
-        69
-      ],
-      [
-        70
-      ],
-      [
-        71
-      ],
-      [
-        72
-      ],
-      [
-        73
-      ],
-      [
-        74
-      ],
-      [
-        75
-      ],
-      [
-        76
-      ],
-      [
-        77
-      ],
-      [
-        78
-      ],
-      [
-        79
-      ],
-      [
-        80
-      ],
-      [
-        81
-      ],
-      [
-        82
-      ],
-      [
-        83
-      ],
-      [
-        84
-      ],
-      [
-        85
-      ],
-      [
-        86
-      ],
-      [
-        87
-      ],
-      [
-        88
-      ],
-      [
-        89
-      ],
-      [
-        90
-      ],
-      [
-        91
-      ],
-      [
-        92
-      ],
-      [
-        93
-      ],
-      [
-        94
-      ],
-      [
-        95
-      ],
-      [
-        96
-      ],
-      [
-        97
-      ],
-      [
-        98
-      ],
-      [
-        99
-      ],
-      [
-        100
-      ],
-      [
-        101
-      ],
-      [
-        102
-      ],
-      [
-        103
-      ],
-      [
-        104
-      ],
-      [
-        105
-      ],
-      [
-        106
-      ],
-      [
-        107
-      ],
-      [
-        108
-      ],
-      [
-        109
-      ],
-      [
-        110
-      ],
-      [
-        111
-      ],
-      [
-        112
-      ],
-      [
-        113
-      ],
-      [
-        114
-      ],
-      [
-        115
-      ],
-      [
-        116
-      ],
-      [
-        117
-      ],
-      [
-        118
-      ],
-      [
-        119
-      ],
-      [
-        120
-      ],
-      [
-        121
-      ],
-      [
-        122
-      ],
-      [
-        123
-      ],
-      [
-        124
-      ],
-      [
-        125
-      ],
-      [
-        126
-      ],
-      [
-        127
-      ],
-      [
-        128
-      ],
-      [
-        129
-      ],
-      [
-        130
-      ],
-      [
-        131
-      ],
-      [
-        132
-      ],
-      [
-        133
-      ],
-      [
-        134
-      ],
-      [
-        135
-      ],
-      [
-        136
-      ],
-      [
-        137
-      ],
-      [
-        138
-      ],
-      [
-        139
-      ],
-      [
-        140
-      ],
-      [
-        141
-      ],
-      [
-        142
-      ],
-      [
-        143
-      ],
-      [
-        144
-      ],
-      [
-        145
-      ],
-      [
-        146
-      ],
-      [
-        147
-      ],
-      [
-        148
-      ],
-      [
-        149
-      ],
-      [
-        150
-      ],
-      [
-        151
-      ],
-      [
-        152
-      ],
-      [
-        153
-      ],
-      [
-        154
-      ],
-      [
-        155
-      ],
-      [
-        156
-      ],
-      [
-        157
-      ],
-      [
-        158
-      ],
-      [
-        159
-      ],
-      [
-        160
-      ],
-      [
-        161
-      ],
-      [
-        162
-      ],
-      [
-        163
-      ],
-      [
-        164
-      ],
-      [
-        165
-      ],
-      [
-        166
-      ],
-      [
-        167
-      ],
-      [
-        168
-      ],
-      [
-        169
-      ],
-      [
-        170
-      ],
-      [
-        171
-      ],
-      [
-        172
-      ],
-      [
-        173
-      ],
-      [
-        174
-      ],
-      [
-        175
-      ],
-      [
-        176
-      ],
-      [
-        177
-      ],
-      [
-        178
-      ],
-      [
-        179
-      ],
-      [
-        180
-      ],
-      [
-        181
-      ],
-      [
-        182
-      ],
-      [
-        183
-      ],
-      [
-        184
-      ],
-      [
-        185
-      ],
-      [
-        186
-      ],
-      [
-        187
-      ],
-      [
-        188
-      ],
-      [
-        189
-      ],
-      [
-        190
-      ],
-      [
-        191
-      ],
-      [
-        192
-      ],
-      [
-        193
-      ],
-      [
-        194
-      ],
-      [
-        195
-      ],
-      [
-        196
-      ],
-      [
-        197
-      ],
-      [
-        198
-      ],
-      [
-        199
-      ],
-      [
-        200
-      ],
-      [
-        201
-      ],
-      [
-        202
-      ],
-      [
-        203
-      ],
-      [
-        204
-      ],
-      [
-        205
-      ],
-      [
-        206
-      ],
-      [
-        207
-      ],
-      [
-        208
-      ],
-      [
-        209
-      ],
-      [
-        210
-      ],
-      [
-        211
-      ],
-      [
-        212
-      ],
-      [
-        213
-      ],
-      [
-        214
-      ],
-      [
-        215
-      ],
-      [
-        216
-      ],
-      [
-        217
-      ],
-      [
-        218
-      ],
-      [
-        219
-      ],
-      [
-        220
-      ],
-      [
-        221
-      ],
-      [
-        222
-      ],
-      [
-        223
-      ],
-      [
-        224
-      ],
-      [
-        225
-      ],
-      [
-        226
-      ],
-      [
-        227
-      ],
-      [
-        228
-      ],
-      [
-        229
-      ],
-      [
-        230
-      ],
-      [
-        231
-      ],
-      [
-        232
-      ],
-      [
-        233
-      ],
-      [
-        234
-      ],
-      [
-        235
-      ],
-      [
-        236
-      ],
-      [
-        237
-      ],
-      [
-        238
-      ],
-      [
-        239
-      ],
-      [
-        240
-      ],
-      [
-        241
-      ],
-      [
-        242
-      ],
-      [
-        243
-      ],
-      [
-        244
-      ],
-      [
-        245
-      ],
-      [
-        246
-      ],
-      [
-        247
-      ],
-      [
-        248
-      ],
-      [
-        249
-      ],
-      [
-        250
-      ],
-      [
-        251
-      ],
-      [
-        252
-      ],
-      [
-        253
-      ],
-      [
-        254
-      ],
-      [
-        255
-      ],
-      [
-        256
-      ],
-      [
-        257
-      ],
-      [
-        258
-      ],
-      [
-        259
-      ],
-      [
-        260
-      ],
-      [
-        261
-      ],
-      [
-        262
-      ],
-      [
-        263
-      ],
-      [
-        264
-      ],
-      [
-        265
-      ],
-      [
-        266
-      ],
-      [
-        267
-      ],
-      [
-        268
-      ],
-      [
-        269
-      ],
-      [
-        270
-      ],
-      [
-        271
-      ],
-      [
-        272
-      ],
-      [
-        273
-      ],
-      [
-        274
-      ],
-      [
-        275
-      ],
-      [
-        276
-      ],
-      [
-        277
-      ],
-      [
-        278
-      ],
-      [
-        279
-      ],
-      [
-        280
-      ],
-      [
-        281
-      ],
-      [
-        282
-      ],
-      [
-        283
-      ],
-      [
-        284
-      ],
-      [
-        285
-      ],
-      [
-        286
-      ],
-      [
-        287
-      ],
-      [
-        288
-      ],
-      [
-        289
-      ],
-      [
-        290
-      ],
-      [
-        291
-      ],
-      [
-        292
-      ],
-      [
-        293
-      ],
-      [
-        294
-      ],
-      [
-        295
-      ],
-      [
-        296
-      ],
-      [
-        297
-      ],
-      [
-        298
-      ],
-      [
-        299
-      ],
-      [
-        300
-      ],
-      [
-        301
-      ],
-      [
-        302
-      ],
-      [
-        303
-      ],
-      [
-        304
-      ],
-      [
-        305
-      ],
-      [
-        306
-      ],
-      [
-        307
-      ],
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for the customer named 'Hannah Lim'?",
-    "answer": "hannah.lim@gmail.com",
-    "sql": "SELECT email FROM customer_grid_flat WHERE name = 'Hannah Lim';",
-    "sql_execute_result": [
-      [
-        "hannah.lim@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "How many search results are there for the query 'Joust Bag'?",
-    "answer": 10,
-    "sql": "SELECT num_results FROM search_query WHERE query_text = 'Joust Bag';",
-    "sql_execute_result": [
-      [
-        10
-      ]
-    ]
-  },
-  {
-    "question": "List all customers located in Hoboken, New Jersey.",
-    "answer": [
-      "Amanda Kim",
-      "Matthew Kim",
-      "Natalie Kim"
-    ],
-    "sql": "SELECT name FROM customer_grid_flat WHERE billing_city = 'Hoboken' AND billing_region = 'New Jersey';",
-    "sql_execute_result": [
-      [
-        "Amanda Kim"
-      ],
-      [
-        "Matthew Kim"
-      ],
-      [
-        "Natalie Kim"
-      ]
-    ]
-  },
-  {
-    "question": "What is the ISO3 code for the country with ISO2 code 'AE'?",
-    "answer": "ARE",
-    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'AE';",
-    "sql_execute_result": [
-      [
-        "ARE"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the store group with ID 1?",
-    "answer": "Main Website Store",
-    "sql": "SELECT name FROM store_group WHERE group_id = 1;",
-    "sql_execute_result": [
-      [
-        "Main Website Store"
-      ]
-    ]
-  },
-  {
-    "question": "Find the rating value for the rating option with code '3'.",
-    "answer": 3,
-    "sql": "SELECT value FROM rating_option WHERE code = '3';",
-    "sql_execute_result": [
-      [
-        3
-      ],
-      [
-        3
-      ],
-      [
-        3
-      ],
-      [
-        3
-      ]
-    ]
-  },
-  {
-    "question": "Is the search query 'Antonia Racer Tank' active?",
-    "answer": "Yes, the search query 'Antonia Racer Tank' is active.",
-    "sql": "SELECT is_active FROM search_query WHERE query_text = 'Antonia Racer Tank';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the default store ID for the group named 'Default'?",
-    "answer": 0,
-    "sql": "SELECT default_store_id FROM store_group WHERE name = 'Default';",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the billing telephone number for the customer 'Matt Baker'?",
-    "answer": "4045551234",
-    "sql": "SELECT billing_telephone FROM customer_grid_flat WHERE name = 'Matt Baker';",
-    "sql_execute_result": [
-      [
-        "4045551234"
-      ]
-    ]
-  },
-  {
-    "question": "What is the stock quantity for product with ID 1502?",
-    "answer": "100.0000",
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 1502;",
-    "sql_execute_result": [
-      [
-        "100.0000"
-      ]
-    ]
-  },
-  {
-    "question": "List all order statuses and their labels.",
-    "answer": [
-      {
-        "status": "canceled",
-        "label": "Canceled"
-      },
-      {
-        "status": "closed",
-        "label": "Closed"
-      },
-      {
-        "status": "complete",
-        "label": "Complete"
-      },
-      {
-        "status": "fraud",
-        "label": "Suspected Fraud"
-      },
-      {
-        "status": "holded",
-        "label": "On Hold"
-      },
-      {
-        "status": "payment_review",
-        "label": "Payment Review"
-      },
-      {
-        "status": "paypal_canceled_reversal",
-        "label": "PayPal Canceled Reversal"
-      },
-      {
-        "status": "paypal_reversed",
-        "label": "PayPal Reversed"
-      },
-      {
-        "status": "pending",
-        "label": "Pending"
-      },
-      {
-        "status": "pending_payment",
-        "label": "Pending Payment"
-      },
-      {
-        "status": "pending_paypal",
-        "label": "Pending PayPal"
-      },
-      {
-        "status": "processing",
-        "label": "Processing"
-      }
-    ],
-    "sql": "SELECT status, label FROM sales_order_status;",
-    "sql_execute_result": [
-      [
-        "canceled",
-        "Canceled"
-      ],
-      [
-        "closed",
-        "Closed"
-      ],
-      [
-        "complete",
-        "Complete"
-      ],
-      [
-        "fraud",
-        "Suspected Fraud"
-      ],
-      [
-        "holded",
-        "On Hold"
-      ],
-      [
-        "payment_review",
-        "Payment Review"
-      ],
-      [
-        "paypal_canceled_reversal",
-        "PayPal Canceled Reversal"
-      ],
-      [
-        "paypal_reversed",
-        "PayPal Reversed"
-      ],
-      [
-        "pending",
-        "Pending"
-      ],
-      [
-        "pending_payment",
-        "Pending Payment"
-      ],
-      [
-        "pending_paypal",
-        "Pending PayPal"
-      ],
-      [
-        "processing",
-        "Processing"
-      ]
-    ]
-  },
-  {
-    "question": "What is the average rating value for product with ID 11 based on votes?",
-    "answer": "3.6667",
-    "sql": "SELECT AVG(value) AS average_rating FROM rating_option_vote WHERE entity_pk_value = 11;",
-    "sql_execute_result": [
-      [
-        "3.6667"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence table for invoices in store with ID 1.",
-    "answer": "sequence_invoice_1",
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE entity_type = 'invoice' AND store_id = 1;",
-    "sql_execute_result": [
-      [
-        "sequence_invoice_1"
-      ]
-    ]
-  },
-  {
-    "question": "Is product with ID 889 in stock?",
-    "answer": "Yes, the product with ID 889 is in stock.",
-    "sql": "SELECT is_in_stock FROM cataloginventory_stock_item WHERE product_id = 889;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve all reviews and their percent rating for product with ID 11.",
-    "answer": [
-      {
-        "review_id": 169,
-        "percent": 100
-      },
-      {
-        "review_id": 170,
-        "percent": 100
-      },
-      {
-        "review_id": 171,
-        "percent": 20
-      }
-    ],
-    "sql": "SELECT review_id, percent FROM rating_option_vote WHERE entity_pk_value = 11;",
-    "sql_execute_result": [
-      [
-        169,
-        100
-      ],
-      [
-        170,
-        100
-      ],
-      [
-        171,
-        20
-      ]
-    ]
-  },
-  {
-    "question": "How many sequence values are present in the order sequence table?",
-    "answer": 308,
-    "sql": "SELECT COUNT(sequence_value) FROM sequence_order_1;",
-    "sql_execute_result": [
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "What is the entity type for sequence table 'sequence_shipment_1'?",
-    "answer": "shipment",
-    "sql": "SELECT entity_type FROM sales_sequence_meta WHERE sequence_table = 'sequence_shipment_1';",
-    "sql_execute_result": [
-      [
-        "shipment"
-      ]
-    ]
-  },
-  {
-    "question": "Find the minimum sale quantity configuration for product with ID 598.",
-    "answer": "1.0000",
-    "sql": "SELECT min_sale_qty FROM cataloginventory_stock_item WHERE product_id = 598;",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Does the product with ID 1229 allow backorders?",
-    "answer": "No, the product with ID 1229 does not allow backorders.",
-    "sql": "SELECT backorders FROM cataloginventory_stock_item WHERE product_id = 1229;",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the status of the order with increment ID '000000152'?",
-    "answer": "canceled",
-    "sql": "SELECT status FROM sales_order_grid WHERE increment_id = '000000152';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total grand total for orders placed by customer with email 'jane.doe@hotmail.com'.",
-    "answer": 1634.72,
-    "sql": "SELECT SUM(grand_total) FROM sales_order_grid WHERE customer_email = 'jane.doe@hotmail.com';",
-    "sql_execute_result": [
-      [
-        "1634.7200"
-      ]
-    ]
-  },
-  {
-    "question": "Which CMS page is currently inactive?",
-    "answer": "Privacy Policy",
-    "sql": "SELECT title FROM cms_page WHERE is_active = 0;",
-    "sql_execute_result": [
-      [
-        "Privacy Policy"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the website with code 'base'?",
-    "answer": "Main Website",
-    "sql": "SELECT name FROM store_website WHERE code = 'base';",
-    "sql_execute_result": [
-      [
-        "Main Website"
-      ]
-    ]
-  },
-  {
-    "question": "What is the value associated with EAV attribute option ID 71?",
-    "answer": "Hydration Pocket",
-    "sql": "SELECT value FROM eav_attribute_option_value WHERE option_id = 71;",
-    "sql_execute_result": [
-      [
-        "Hydration Pocket"
-      ]
-    ]
-  },
-  {
-    "question": "Find all orders for customer with ID 2.",
-    "answer": [
-      "000000009",
-      "000000059",
-      "000000068",
-      "000000079",
-      "000000093",
-      "000000095",
-      "000000096",
-      "000000107",
-      "000000115",
-      "000000144",
-      "000000217",
-      "000000257",
-      "000000273"
-    ],
-    "sql": "SELECT increment_id FROM sales_order_grid WHERE customer_id = 2;",
-    "sql_execute_result": [
-      [
-        "000000009"
-      ],
-      [
-        "000000059"
-      ],
-      [
-        "000000068"
-      ],
-      [
-        "000000079"
-      ],
-      [
-        "000000093"
-      ],
-      [
-        "000000095"
-      ],
-      [
-        "000000096"
-      ],
-      [
-        "000000107"
-      ],
-      [
-        "000000115"
-      ],
-      [
-        "000000144"
-      ],
-      [
-        "000000217"
-      ],
-      [
-        "000000257"
-      ],
-      [
-        "000000273"
-      ]
-    ]
-  },
-  {
-    "question": "What is the payment method used for the order by 'Bob Johnson'?",
-    "answer": "checkmo",
-    "sql": "SELECT payment_method FROM sales_order_grid WHERE customer_name = 'Bob Johnson';",
-    "sql_execute_result": [
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ],
-      [
-        "checkmo"
-      ]
-    ]
-  },
-  {
-    "question": "What is the layout of the CMS page titled '404 Not Found'?",
-    "answer": "2columns-right",
-    "sql": "SELECT page_layout FROM cms_page WHERE title = '404 Not Found';",
-    "sql_execute_result": [
-      [
-        "2columns-right"
-      ]
-    ]
-  },
-  {
-    "question": "Find the shipping address associated with the order increment ID '000000289'.",
-    "answer": "333 S Broad St, Philadelphia, Pennsylvania, 19102",
-    "sql": "SELECT shipping_address FROM sales_order_grid WHERE increment_id = '000000289';",
-    "sql_execute_result": [
-      [
-        "333 S Broad St,Philadelphia,Pennsylvania,19102"
-      ]
-    ]
-  },
-  {
-    "question": "What is the default name for the region with code 'CN-JX' in China?",
-    "answer": "Jiangxi Sheng",
-    "sql": "SELECT default_name FROM directory_country_region WHERE code = 'CN-JX' AND country_id = 'CN';",
-    "sql_execute_result": [
-      [
-        "Jiangxi Sheng"
-      ]
-    ]
-  },
-  {
-    "question": "Find all completed orders on 2023-05-04 in store with ID 1.",
-    "answer": 1,
-    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE period = '2023-05-04' AND store_id = 1 AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the title of the review by nickname 'Ezra'?",
-    "answer": "I slipped on a rock on these shoes and I",
-    "sql": "SELECT title FROM review_detail WHERE nickname = 'Ezra';",
-    "sql_execute_result": [
-      [
-        "I slipped on a rock on these shoes and I"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were canceled on 2022-12-05 in store with ID 1?",
-    "answer": 1,
-    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE period = '2022-12-05' AND store_id = 1 AND order_status = 'canceled';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the attribute code for the attribute with ID 152?",
-    "answer": "style_general",
-    "sql": "SELECT attribute_code FROM eav_attribute WHERE attribute_id = 152;",
-    "sql_execute_result": [
-      [
-        "style_general"
-      ]
-    ]
-  },
-  {
-    "question": "What is the backend type for the 'image' attribute?",
-    "answer": "varchar",
-    "sql": "SELECT backend_type FROM eav_attribute WHERE attribute_code = 'image';",
-    "sql_execute_result": [
-      [
-        "varchar"
-      ],
-      [
-        "varchar"
-      ]
-    ]
-  },
-  {
-    "question": "What is the shipping amount for the complete order on 2022-06-18?",
-    "answer": "The shipping amount for the complete order on 2022-06-18 is 10.00.",
-    "sql": "SELECT total_shipping_amount FROM sales_order_aggregated_created WHERE period = '2022-06-18' AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        "10.0000"
-      ],
-      [
-        "10.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the region with ID 880 in Italy?",
-    "answer": "Medio Campidano",
-    "sql": "SELECT default_name FROM directory_country_region WHERE region_id = 880 AND country_id = 'IT';",
-    "sql_execute_result": [
-      [
-        "Medio Campidano"
-      ]
-    ]
-  },
-  {
-    "question": "List the sequence values in the shipment sequence table.",
-    "answer": [
-      1,
-      2,
-      3
-    ],
-    "sql": "SELECT sequence_value FROM sequence_shipment_1;",
-    "sql_execute_result": [
-      [
-        1
-      ],
-      [
-        2
-      ],
-      [
-        3
-      ]
-    ]
-  },
-  {
-    "question": "What is the frontend input type for the 'email' attribute?",
-    "answer": "text",
-    "sql": "SELECT frontend_input FROM eav_attribute WHERE attribute_code = 'email';",
-    "sql_execute_result": [
-      [
-        "text"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total quantity ordered for product with ID 315.",
-    "answer": 1.0,
-    "sql": "SELECT SUM(qty_ordered) FROM sales_order_item WHERE product_id = 315;",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total grand total of all canceled orders?",
-    "answer": "17408.07",
-    "sql": "SELECT SUM(base_grand_total) FROM sales_order WHERE status = 'canceled';",
-    "sql_execute_result": [
-      [
-        "17408.0700"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders have been canceled in store with ID 0?",
-    "answer": 125,
-    "sql": "SELECT COUNT(*) FROM sales_order_aggregated_created WHERE store_id = 0 AND order_status = 'canceled';",
-    "sql_execute_result": [
-      [
-        125
-      ]
-    ]
-  },
-  {
-    "question": "What is the product name for product with ID 315 in the daily bestsellers?",
-    "answer": "Orion Two-Tone Fitted Jacket-XL-Black",
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_daily WHERE product_id = 315;",
-    "sql_execute_result": [
-      [
-        "Orion Two-Tone Fitted Jacket-XL-Black"
-      ],
-      [
-        "Orion Two-Tone Fitted Jacket-XL-Black"
-      ]
-    ]
-  },
-  {
-    "question": "What is the order status of the order with ID 308?",
-    "answer": "pending",
-    "sql": "SELECT status FROM sales_order WHERE entity_id = 308;",
-    "sql_execute_result": [
-      [
-        "pending"
-      ]
-    ]
-  },
-  {
-    "question": "Check if the product with SKU 'MT02-M-Gray' is in stock.",
-    "answer": "The product with SKU 'MT02-M-Gray' is in stock.",
-    "sql": "SELECT is_in_stock FROM cataloginventory_stock_item WHERE product_id = (SELECT entity_id FROM catalog_product_entity WHERE sku = 'MT02-M-Gray');",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were placed by the customer with email 'customer5@example.com'?",
-    "answer": 0,
-    "sql": "SELECT COUNT(*) FROM sales_order WHERE customer_email = 'customer5@example.com';",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for order ID 308?",
-    "answer": "4.0000",
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE entity_id = 308;",
-    "sql_execute_result": [
-      [
-        "4.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for the customer with ID 24?",
-    "answer": "musiclover99@hotmail.com",
-    "sql": "SELECT email FROM customer_entity WHERE entity_id = 24;",
-    "sql_execute_result": [
-      [
-        "musiclover99@hotmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total number of reviews for the product with ID 937.",
-    "answer": 3,
-    "sql": "SELECT COUNT(*) FROM review WHERE entity_pk_value = 937;",
-    "sql_execute_result": [
-      [
-        3
-      ]
-    ]
-  },
-  {
-    "question": "What is the rating value given in the review with ID 256?",
-    "answer": 4,
-    "sql": "SELECT value FROM rating_option_vote WHERE review_id = 256;",
-    "sql_execute_result": [
-      [
-        4
-      ]
-    ]
-  },
-  {
-    "question": "What is the first name of the customer with email 'jessica.wong@gmail.com'?",
-    "answer": "Jessica",
-    "sql": "SELECT firstname FROM customer_entity WHERE email = 'jessica.wong@gmail.com';",
-    "sql_execute_result": [
-      [
-        "Jessica"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence table associated with shipments for store ID 1.",
-    "answer": "sequence_shipment_1",
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE entity_type = 'shipment' AND store_id = 1;",
-    "sql_execute_result": [
-      [
-        "sequence_shipment_1"
-      ]
-    ]
-  },
-  {
-    "question": "How many reviews are pending approval?",
-    "answer": 346,
-    "sql": "SELECT COUNT(*) FROM review WHERE status_id = 1;",
-    "sql_execute_result": [
-      [
-        346
-      ]
-    ]
-  },
-  {
-    "question": "What is the customer group ID for the customer named 'Isaac Rodriguez'?",
-    "answer": 1,
-    "sql": "SELECT group_id FROM customer_entity WHERE firstname = 'Isaac' AND lastname = 'Rodriguez';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What percentage rating did the product with ID 1412 receive in its review?",
-    "answer": [
-      80,
-      60,
-      80
-    ],
-    "sql": "SELECT percent FROM rating_option_vote WHERE entity_pk_value = 1412;",
-    "sql_execute_result": [
-      [
-        80
-      ],
-      [
-        60
-      ],
-      [
-        80
-      ]
-    ]
-  },
-  {
-    "question": "Find the category ID for the product with ID 648.",
-    "answer": 17,
-    "sql": "SELECT category_id FROM catalog_category_product WHERE product_id = 648;",
-    "sql_execute_result": [
-      [
-        17
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for the customer associated with order ID 233?",
-    "answer": "daniel.jackson@hotmail.com",
-    "sql": "SELECT email FROM sales_order_address WHERE parent_id = 233 AND address_type = 'billing';",
-    "sql_execute_result": [
-      [
-        "daniel.jackson@hotmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "Find all products with the attribute code 'pierce-gym-short-32-gray'.",
-    "answer": [
-      1017
-    ],
-    "sql": "SELECT entity_id FROM catalog_product_entity_varchar WHERE value = 'pierce-gym-short-32-gray';",
-    "sql_execute_result": [
-      [
-        1017
-      ]
-    ]
-  },
-  {
-    "question": "List the categories that include the keyword 'bags'.",
-    "answer": [
-      "Bags",
-      "bags",
-      "gear/bags"
-    ],
-    "sql": "SELECT value FROM catalog_category_entity_varchar WHERE value LIKE '%bags%';",
-    "sql_execute_result": [
-      [
-        "Bags"
-      ],
-      [
-        "bags"
-      ],
-      [
-        "gear/bags"
-      ]
-    ]
-  },
-  {
-    "question": "What is the rating value for the option code '5' from rating ID 2?",
-    "answer": 5,
-    "sql": "SELECT value FROM rating_option WHERE code = '5' AND rating_id = 2;",
-    "sql_execute_result": [
-      [
-        5
-      ]
-    ]
-  },
-  {
-    "question": "How many shipments have been created for customer ID 1?",
-    "answer": 2,
-    "sql": "SELECT COUNT(*) FROM sales_shipment WHERE customer_id = 1;",
-    "sql_execute_result": [
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity shipped in shipment ID 3?",
-    "answer": "2.0000",
-    "sql": "SELECT total_qty FROM sales_shipment WHERE entity_id = 3;",
-    "sql_execute_result": [
-      [
-        "2.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the customer first name associated with order ID 86.",
-    "answer": "John",
-    "sql": "SELECT firstname FROM sales_order_address WHERE parent_id = 86 AND address_type = 'shipping';",
-    "sql_execute_result": [
-      [
-        "John"
-      ]
-    ]
-  },
-  {
-    "question": "List all distinct regions from the sales order addresses.",
-    "answer": [
-      "Michigan",
-      "Nevada",
-      "California",
-      "Massachusetts",
-      "New York",
-      "Arizona",
-      "Texas",
-      "Alabama",
-      "Georgia",
-      "Washington",
-      "Colorado",
-      "Florida",
-      "Illinois",
-      "Pennsylvania"
-    ],
-    "sql": "SELECT DISTINCT region FROM sales_order_address;",
-    "sql_execute_result": [
-      [
-        "Michigan"
-      ],
-      [
-        "Nevada"
-      ],
-      [
-        "California"
-      ],
-      [
-        "Massachusetts"
-      ],
-      [
-        "New York"
-      ],
-      [
-        "Arizona"
-      ],
-      [
-        "Texas"
-      ],
-      [
-        "Alabama"
-      ],
-      [
-        "Georgia"
-      ],
-      [
-        "Washington"
-      ],
-      [
-        "Colorado"
-      ],
-      [
-        "Florida"
-      ],
-      [
-        "Illinois"
-      ],
-      [
-        "Pennsylvania"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address of the customer with ID 5?",
-    "answer": "helloworld@yahoo.com",
-    "sql": "SELECT email FROM customer_entity WHERE entity_id = 5;",
-    "sql_execute_result": [
-      [
-        "helloworld@yahoo.com"
-      ]
-    ]
-  },
-  {
-    "question": "List all orders for the customer with email david.lee@gmail.com.",
-    "answer": [
-      37,
-      151,
-      194
-    ],
-    "sql": "SELECT entity_id FROM sales_order WHERE customer_email = 'david.lee@gmail.com';",
-    "sql_execute_result": [
-      [
-        37
-      ],
-      [
-        151
-      ],
-      [
-        194
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for the product 'Daria Bikram Pant-28-Black' in store with ID 1 on 2022-06-19?",
-    "answer": 1.0,
-    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_daily WHERE product_id = 1876 AND store_id = 1 AND period = '2022-06-19';",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status of the order with increment ID '000000151'?",
-    "answer": "canceled",
-    "sql": "SELECT status FROM sales_order_grid WHERE increment_id = '000000151';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "Find out the product name of the product with entity ID 1876.",
-    "answer": "Daria Bikram Pant-28-Black",
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_daily WHERE product_id = 1876;",
-    "sql_execute_result": [
-      [
-        "Daria Bikram Pant-28-Black"
-      ],
-      [
-        "Daria Bikram Pant-28-Black"
-      ],
-      [
-        "Daria Bikram Pant-28-Black"
-      ],
-      [
-        "Daria Bikram Pant-28-Black"
-      ]
-    ]
-  },
-  {
-    "question": "Is the product with entity ID 2040 in stock?",
-    "answer": "Yes, the product with entity ID 2040 is in stock.",
-    "sql": "SELECT is_in_stock FROM cataloginventory_stock_item WHERE product_id = 2040;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the most popular product for store ID 1 on 2022-06-19.",
-    "answer": "Daria Bikram Pant-28-Black",
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_daily WHERE store_id = 1 AND period = '2022-06-19' ORDER BY qty_ordered DESC LIMIT 1;",
-    "sql_execute_result": [
-      [
-        "Daria Bikram Pant-28-Black"
-      ]
-    ]
-  },
-  {
-    "question": "What is the creation date of the order with entity ID 177?",
-    "answer": "2022-07-13 18:02:34",
-    "sql": "SELECT created_at FROM sales_order_grid WHERE entity_id = 177;",
-    "sql_execute_result": [
-      [
-        "2022-07-13 18:02:34"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status code for review status with ID 2?",
-    "answer": "Pending",
-    "sql": "SELECT status_code FROM review_status WHERE status_id = 2;",
-    "sql_execute_result": [
-      [
-        "Pending"
-      ]
-    ]
-  },
-  {
-    "question": "Find the email address associated with the sales order address having entity ID 543.",
-    "answer": "michael.nguyen@yahoo.com",
-    "sql": "SELECT email FROM sales_order_address WHERE entity_id = 543;",
-    "sql_execute_result": [
-      [
-        "michael.nguyen@yahoo.com"
-      ]
-    ]
-  },
-  {
-    "question": "What is the price of the product with entity ID 1997?",
-    "answer": "24.00",
-    "sql": "SELECT value FROM catalog_product_entity_decimal WHERE entity_id = 1997 AND attribute_id = 77;",
-    "sql_execute_result": [
-      [
-        "24.000000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the product name for the product with entity ID 928.",
-    "answer": "Hawkeye Yoga Short-33-Black",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 928 AND attribute_id = 73;",
-    "sql_execute_result": [
-      [
-        "Hawkeye Yoga Short-33-Black"
-      ]
-    ]
-  },
-  {
-    "question": "Which attribute is visible and used in product listing according to the catalog_eav_attribute table?",
-    "answer": [
-      73,
-      76,
-      77,
-      78,
-      79,
-      80,
-      87,
-      88,
-      89,
-      93,
-      94,
-      95,
-      97,
-      121,
-      123,
-      124,
-      129,
-      131,
-      132,
-      133,
-      135,
-      136,
-      144
-    ],
-    "sql": "SELECT attribute_id FROM catalog_eav_attribute WHERE is_visible = 1 AND used_in_product_listing = 1;",
-    "sql_execute_result": [
-      [
-        73
-      ],
-      [
-        76
-      ],
-      [
-        77
-      ],
-      [
-        78
-      ],
-      [
-        79
-      ],
-      [
-        80
-      ],
-      [
-        87
-      ],
-      [
-        88
-      ],
-      [
-        89
-      ],
-      [
-        93
-      ],
-      [
-        94
-      ],
-      [
-        95
-      ],
-      [
-        97
-      ],
-      [
-        121
-      ],
-      [
-        123
-      ],
-      [
-        124
-      ],
-      [
-        129
-      ],
-      [
-        131
-      ],
-      [
-        132
-      ],
-      [
-        133
-      ],
-      [
-        135
-      ],
-      [
-        136
-      ],
-      [
-        144
-      ]
-    ]
-  },
-  {
-    "question": "Find the postal code for the billing address of the sales order with parent ID 294.",
-    "answer": "90028",
-    "sql": "SELECT postcode FROM sales_order_address WHERE parent_id = 294 AND address_type = 'billing';",
-    "sql_execute_result": [
-      [
-        "90028"
-      ]
-    ]
-  },
-  {
-    "question": "What is the value of the attribute with ID 124 for the product with entity ID 1902?",
-    "answer": "0",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 1902 AND attribute_id = 124;",
-    "sql_execute_result": [
-      [
-        "0"
-      ]
-    ]
-  },
-  {
-    "question": "What is the global visibility status for the attribute with ID 78?",
-    "answer": 1,
-    "sql": "SELECT is_global FROM catalog_eav_attribute WHERE attribute_id = 78;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the first name of the customer associated with the billing address having email 'alexander.thomas@hotmail.com'.",
-    "answer": "Alexander",
-    "sql": "SELECT firstname FROM sales_order_address WHERE email = 'alexander.thomas@hotmail.com' AND address_type = 'billing';",
-    "sql_execute_result": [
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ],
-      [
-        "Alexander"
-      ]
-    ]
-  },
-  {
-    "question": "What is the attribute ID of a catalog_eav_attribute that is searchable?",
-    "answer": [
-      73,
-      74,
-      75,
-      76,
-      77,
-      83,
-      97,
-      119,
-      121,
-      136
-    ],
-    "sql": "SELECT attribute_id FROM catalog_eav_attribute WHERE is_searchable = 1;",
-    "sql_execute_result": [
-      [
-        73
-      ],
-      [
-        74
-      ],
-      [
-        75
-      ],
-      [
-        76
-      ],
-      [
-        77
-      ],
-      [
-        83
-      ],
-      [
-        97
-      ],
-      [
-        119
-      ],
-      [
-        121
-      ],
-      [
-        136
-      ]
-    ]
-  }
-]
\ No newline at end of file
diff --git a/random_sample/generated_tasks.json.bak2 b/random_sample/generated_tasks.json.bak2
deleted file mode 100644
index 261116c..0000000
--- a/random_sample/generated_tasks.json.bak2
+++ /dev/null
@@ -1,8182 +0,0 @@
-[
-  {
-    "question": "What is the email address of the customer with ID 70?",
-    "answer": "emma.lopez@gmail.com",
-    "sql": "SELECT email FROM customer_entity WHERE entity_id = 70;",
-    "sql_execute_result": [
-      [
-        "emma.lopez@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "How many customers are in the 'General' group?",
-    "answer": 70,
-    "sql": "SELECT entity_id, firstname, lastname FROM customer_entity WHERE group_id = (SELECT customer_group_id FROM customer_group WHERE customer_group_code = 'General');",
-    "sql_execute_result": [
-      [
-        1,
-        "Veronica",
-        "Costello"
-      ],
-      [
-        2,
-        "John",
-        "Smith"
-      ],
-      [
-        3,
-        "Jane",
-        "Doe"
-      ],
-      [
-        4,
-        "Bob",
-        "Jones"
-      ],
-      [
-        5,
-        "Sarah",
-        "Miller"
-      ],
-      [
-        6,
-        "Julia",
-        "Williams"
-      ],
-      [
-        7,
-        "Bob",
-        "Johnson"
-      ],
-      [
-        8,
-        "Mary",
-        "Martin"
-      ],
-      [
-        9,
-        "John",
-        "Lee"
-      ],
-      [
-        10,
-        "Jane",
-        "Smith"
-      ],
-      [
-        11,
-        "Daniel",
-        "Jackson"
-      ],
-      [
-        12,
-        "Lisa",
-        "Kim"
-      ],
-      [
-        13,
-        "Matt",
-        "Baker"
-      ],
-      [
-        14,
-        "John",
-        "Doe"
-      ],
-      [
-        15,
-        "Jane",
-        "Smith"
-      ],
-      [
-        16,
-        "Samantha",
-        "Jones"
-      ],
-      [
-        17,
-        "Lily",
-        "Potter"
-      ],
-      [
-        18,
-        "Grace",
-        "Nguyen"
-      ],
-      [
-        19,
-        "Lucy",
-        "Garcia"
-      ],
-      [
-        20,
-        "Olivia",
-        "Lee"
-      ],
-      [
-        21,
-        "Ava",
-        "Brown"
-      ],
-      [
-        22,
-        "Sophie",
-        "Taylor"
-      ],
-      [
-        23,
-        "Alex",
-        "Johnson"
-      ],
-      [
-        24,
-        "Emma",
-        "Davis"
-      ],
-      [
-        25,
-        "Adam",
-        "Garcia"
-      ],
-      [
-        26,
-        "Jennifer",
-        "White"
-      ],
-      [
-        27,
-        "Alex",
-        "Martin"
-      ],
-      [
-        28,
-        "Lisa",
-        "Green"
-      ],
-      [
-        29,
-        "Michael",
-        "Nguyen"
-      ],
-      [
-        30,
-        "David",
-        "Lee"
-      ],
-      [
-        31,
-        "Jason",
-        "Miller"
-      ],
-      [
-        32,
-        "Katie",
-        "Wong"
-      ],
-      [
-        33,
-        "Adam",
-        "Garcia"
-      ],
-      [
-        34,
-        "Brian",
-        "Smith"
-      ],
-      [
-        35,
-        "Samantha",
-        "Nguyen"
-      ],
-      [
-        36,
-        "Alexander",
-        "Thomas"
-      ],
-      [
-        37,
-        "Sam",
-        "Wilson"
-      ],
-      [
-        38,
-        "Kate",
-        "Jones"
-      ],
-      [
-        39,
-        "David",
-        "Smith"
-      ],
-      [
-        40,
-        "Jessica",
-        "Nguyen"
-      ],
-      [
-        41,
-        "Maxwell",
-        "Baker"
-      ],
-      [
-        42,
-        "Emily",
-        "Chen"
-      ],
-      [
-        43,
-        "Anna",
-        "Nguyen"
-      ],
-      [
-        44,
-        "Roberto",
-        "Lopez"
-      ],
-      [
-        45,
-        "Amanda",
-        "Kim"
-      ],
-      [
-        46,
-        "Jane",
-        "Doe"
-      ],
-      [
-        47,
-        "John",
-        "Smith"
-      ],
-      [
-        48,
-        "Jessica",
-        "Chang"
-      ],
-      [
-        49,
-        "James",
-        "Kim"
-      ],
-      [
-        50,
-        "Samantha",
-        "Wu"
-      ],
-      [
-        51,
-        "Robert",
-        "Johnson"
-      ],
-      [
-        52,
-        "Sophia",
-        "Kim"
-      ],
-      [
-        53,
-        "William",
-        "Chang"
-      ],
-      [
-        54,
-        "Jessica",
-        "Wong"
-      ],
-      [
-        55,
-        "Ethan",
-        "Garcia"
-      ],
-      [
-        56,
-        "Olivia",
-        "Jackson"
-      ],
-      [
-        57,
-        "Jacob",
-        "Rivera"
-      ],
-      [
-        58,
-        "Sophia",
-        "Young"
-      ],
-      [
-        59,
-        "Ryan",
-        "Tanaka"
-      ],
-      [
-        60,
-        "Julie",
-        "Nguyen"
-      ],
-      [
-        61,
-        "Matthew",
-        "Kim"
-      ],
-      [
-        62,
-        "Emily",
-        "Wilson"
-      ],
-      [
-        63,
-        "James",
-        "Baker"
-      ],
-      [
-        64,
-        "Isabella",
-        "Santos"
-      ],
-      [
-        65,
-        "Nathan",
-        "Chen"
-      ],
-      [
-        66,
-        "Hannah",
-        "Lim"
-      ],
-      [
-        67,
-        "Isaac",
-        "Rodriguez"
-      ],
-      [
-        68,
-        "Natalie",
-        "Kim"
-      ],
-      [
-        69,
-        "Sean",
-        "Miller"
-      ],
-      [
-        70,
-        "Emma",
-        "Lopez"
-      ]
-    ]
-  },
-  {
-    "question": "How many items of product ID 1292 are currently in stock?",
-    "answer": 100,
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 1292;",
-    "sql_execute_result": [
-      [
-        "100.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the default name of the region with ID 880?",
-    "answer": "Medio Campidano",
-    "sql": "SELECT default_name FROM directory_country_region WHERE region_id = 880;",
-    "sql_execute_result": [
-      [
-        "Medio Campidano"
-      ]
-    ]
-  },
-  {
-    "question": "What is the current sequence value for orders?",
-    "answer": 308,
-    "sql": "SELECT sequence_value FROM sequence_order_1 ORDER BY sequence_value DESC LIMIT 1;",
-    "sql_execute_result": [
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "Find the product name for entity ID 1718 in the catalog.",
-    "answer": "Nona Fitness Tank-XS-Purple",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 1718 AND attribute_id = 73;",
-    "sql_execute_result": [
-      [
-        "Nona Fitness Tank-XS-Purple"
-      ]
-    ]
-  },
-  {
-    "question": "What is the country code for the region named 'Olt'?",
-    "answer": "RO",
-    "sql": "SELECT country_id FROM directory_country_region WHERE default_name = 'Olt';",
-    "sql_execute_result": [
-      [
-        "RO"
-      ]
-    ]
-  },
-  {
-    "question": "List all active sequence profiles.",
-    "answer": [
-      {
-        "profile_id": 1,
-        "meta_id": 1
-      },
-      {
-        "profile_id": 2,
-        "meta_id": 2
-      },
-      {
-        "profile_id": 3,
-        "meta_id": 3
-      },
-      {
-        "profile_id": 4,
-        "meta_id": 4
-      },
-      {
-        "profile_id": 5,
-        "meta_id": 5
-      },
-      {
-        "profile_id": 6,
-        "meta_id": 6
-      },
-      {
-        "profile_id": 7,
-        "meta_id": 7
-      },
-      {
-        "profile_id": 8,
-        "meta_id": 8
-      }
-    ],
-    "sql": "SELECT profile_id, meta_id FROM sales_sequence_profile WHERE is_active = 1;",
-    "sql_execute_result": [
-      [
-        1,
-        1
-      ],
-      [
-        2,
-        2
-      ],
-      [
-        3,
-        3
-      ],
-      [
-        4,
-        4
-      ],
-      [
-        5,
-        5
-      ],
-      [
-        6,
-        6
-      ],
-      [
-        7,
-        7
-      ],
-      [
-        8,
-        8
-      ]
-    ]
-  },
-  {
-    "question": "What is the sort order for the attribute option ID 95?",
-    "answer": 8,
-    "sql": "SELECT sort_order FROM eav_attribute_option WHERE option_id = 95;",
-    "sql_execute_result": [
-      [
-        8
-      ]
-    ]
-  },
-  {
-    "question": "Find the SKU for the product with entity ID 1640.",
-    "answer": "Prima Compete Bra Top-S-Blue",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 1640 AND attribute_id = 73;",
-    "sql_execute_result": [
-      [
-        "Prima Compete Bra Top-S-Blue"
-      ]
-    ]
-  },
-  {
-    "question": "Find the image path for the product with entity ID 8.",
-    "answer": "/w/b/wb01-black-0.jpg",
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 8 AND attribute_id = 88;",
-    "sql_execute_result": [
-      [
-        "/w/b/wb01-black-0.jpg"
-      ]
-    ]
-  },
-  {
-    "question": "What is the country ID for the region code 'GR-L'?",
-    "answer": "GR",
-    "sql": "SELECT country_id FROM directory_country_region WHERE code = 'GR-L';",
-    "sql_execute_result": [
-      [
-        "GR"
-      ]
-    ]
-  },
-  {
-    "question": "What is the price of the product with SKU 'WS03-XS-Red'?",
-    "answer": "The price of the product with SKU 'WS03-XS-Red' is 29.00.",
-    "sql": "SELECT price FROM sales_invoice_item WHERE sku = 'WS03-XS-Red';",
-    "sql_execute_result": [
-      [
-        "29.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the tax amount for the product 'Minerva LumaTech\u2122 V-Tee'.",
-    "answer": "The tax amount for the product 'Minerva LumaTech\u2122 V-Tee' is 2.6400.",
-    "sql": "SELECT tax_amount FROM sales_invoice_item WHERE name = 'Minerva LumaTech&trade; V-Tee';",
-    "sql_execute_result": [
-      [
-        "2.6400"
-      ]
-    ]
-  },
-  {
-    "question": "What is the ISO3 code for the country with ISO2 code 'TT'?",
-    "answer": "TTO",
-    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'TT';",
-    "sql_execute_result": [
-      [
-        "TTO"
-      ]
-    ]
-  },
-  {
-    "question": "How many products have a decimal attribute value of 1.000000?",
-    "answer": 1847,
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id IN (SELECT entity_id FROM catalog_product_entity_decimal WHERE value = '1.000000');",
-    "sql_execute_result": [
-      [
-        "MH01-L-Black"
-      ],
-      [
-        "MH01-L-Gray"
-      ],
-      [
-        "MH01-L-Orange"
-      ],
-      [
-        "MH01-M-Black"
-      ],
-      [
-        "MH01-M-Gray"
-      ],
-      [
-        "MH01-M-Orange"
-      ],
-      [
-        "MH01-S-Black"
-      ],
-      [
-        "MH01-S-Gray"
-      ],
-      [
-        "MH01-S-Orange"
-      ],
-      [
-        "MH01-XL-Black"
-      ],
-      [
-        "MH01-XL-Gray"
-      ],
-      [
-        "MH01-XL-Orange"
-      ],
-      [
-        "MH01-XS-Black"
-      ],
-      [
-        "MH01-XS-Gray"
-      ],
-      [
-        "MH01-XS-Orange"
-      ],
-      [
-        "MH02-L-Black"
-      ],
-      [
-        "MH02-L-Purple"
-      ],
-      [
-        "MH02-L-Red"
-      ],
-      [
-        "MH02-M-Black"
-      ],
-      [
-        "MH02-M-Purple"
-      ],
-      [
-        "MH02-M-Red"
-      ],
-      [
-        "MH02-S-Black"
-      ],
-      [
-        "MH02-S-Purple"
-      ],
-      [
-        "MH02-S-Red"
-      ],
-      [
-        "MH02-XL-Black"
-      ],
-      [
-        "MH02-XL-Purple"
-      ],
-      [
-        "MH02-XL-Red"
-      ],
-      [
-        "MH02-XS-Black"
-      ],
-      [
-        "MH02-XS-Purple"
-      ],
-      [
-        "MH02-XS-Red"
-      ],
-      [
-        "MH03-L-Black"
-      ],
-      [
-        "MH03-L-Blue"
-      ],
-      [
-        "MH03-L-Green"
-      ],
-      [
-        "MH03-M-Black"
-      ],
-      [
-        "MH03-M-Blue"
-      ],
-      [
-        "MH03-M-Green"
-      ],
-      [
-        "MH03-S-Black"
-      ],
-      [
-        "MH03-S-Blue"
-      ],
-      [
-        "MH03-S-Green"
-      ],
-      [
-        "MH03-XL-Black"
-      ],
-      [
-        "MH03-XL-Blue"
-      ],
-      [
-        "MH03-XL-Green"
-      ],
-      [
-        "MH03-XS-Black"
-      ],
-      [
-        "MH03-XS-Blue"
-      ],
-      [
-        "MH03-XS-Green"
-      ],
-      [
-        "MH04-L-Green"
-      ],
-      [
-        "MH04-L-White"
-      ],
-      [
-        "MH04-L-Yellow"
-      ],
-      [
-        "MH04-M-Green"
-      ],
-      [
-        "MH04-M-White"
-      ],
-      [
-        "MH04-M-Yellow"
-      ],
-      [
-        "MH04-S-Green"
-      ],
-      [
-        "MH04-S-White"
-      ],
-      [
-        "MH04-S-Yellow"
-      ],
-      [
-        "MH04-XL-Green"
-      ],
-      [
-        "MH04-XL-White"
-      ],
-      [
-        "MH04-XL-Yellow"
-      ],
-      [
-        "MH04-XS-Green"
-      ],
-      [
-        "MH04-XS-White"
-      ],
-      [
-        "MH04-XS-Yellow"
-      ],
-      [
-        "MH05-L-Green"
-      ],
-      [
-        "MH05-L-Red"
-      ],
-      [
-        "MH05-L-White"
-      ],
-      [
-        "MH05-M-Green"
-      ],
-      [
-        "MH05-M-Red"
-      ],
-      [
-        "MH05-M-White"
-      ],
-      [
-        "MH05-S-Green"
-      ],
-      [
-        "MH05-S-Red"
-      ],
-      [
-        "MH05-S-White"
-      ],
-      [
-        "MH05-XL-Green"
-      ],
-      [
-        "MH05-XL-Red"
-      ],
-      [
-        "MH05-XL-White"
-      ],
-      [
-        "MH05-XS-Green"
-      ],
-      [
-        "MH05-XS-Red"
-      ],
-      [
-        "MH05-XS-White"
-      ],
-      [
-        "MH06-L-Black"
-      ],
-      [
-        "MH06-L-Blue"
-      ],
-      [
-        "MH06-L-Purple"
-      ],
-      [
-        "MH06-M-Black"
-      ],
-      [
-        "MH06-M-Blue"
-      ],
-      [
-        "MH06-M-Purple"
-      ],
-      [
-        "MH06-S-Black"
-      ],
-      [
-        "MH06-S-Blue"
-      ],
-      [
-        "MH06-S-Purple"
-      ],
-      [
-        "MH06-XL-Black"
-      ],
-      [
-        "MH06-XL-Blue"
-      ],
-      [
-        "MH06-XL-Purple"
-      ],
-      [
-        "MH06-XS-Black"
-      ],
-      [
-        "MH06-XS-Blue"
-      ],
-      [
-        "MH06-XS-Purple"
-      ],
-      [
-        "MH07-L-Black"
-      ],
-      [
-        "MH07-L-Gray"
-      ],
-      [
-        "MH07-L-Green"
-      ],
-      [
-        "MH07-M-Black"
-      ],
-      [
-        "MH07-M-Gray"
-      ],
-      [
-        "MH07-M-Green"
-      ],
-      [
-        "MH07-S-Black"
-      ],
-      [
-        "MH07-S-Gray"
-      ],
-      [
-        "MH07-S-Green"
-      ],
-      [
-        "MH07-XL-Black"
-      ],
-      [
-        "MH07-XL-Gray"
-      ],
-      [
-        "MH07-XL-Green"
-      ],
-      [
-        "MH07-XS-Black"
-      ],
-      [
-        "MH07-XS-Gray"
-      ],
-      [
-        "MH07-XS-Green"
-      ],
-      [
-        "MH08-L-Brown"
-      ],
-      [
-        "MH08-L-Purple"
-      ],
-      [
-        "MH08-L-Red"
-      ],
-      [
-        "MH08-M-Brown"
-      ],
-      [
-        "MH08-M-Purple"
-      ],
-      [
-        "MH08-M-Red"
-      ],
-      [
-        "MH08-S-Brown"
-      ],
-      [
-        "MH08-S-Purple"
-      ],
-      [
-        "MH08-S-Red"
-      ],
-      [
-        "MH08-XL-Brown"
-      ],
-      [
-        "MH08-XL-Purple"
-      ],
-      [
-        "MH08-XL-Red"
-      ],
-      [
-        "MH08-XS-Brown"
-      ],
-      [
-        "MH08-XS-Purple"
-      ],
-      [
-        "MH08-XS-Red"
-      ],
-      [
-        "MH09-L-Blue"
-      ],
-      [
-        "MH09-L-Green"
-      ],
-      [
-        "MH09-L-Red"
-      ],
-      [
-        "MH09-M-Blue"
-      ],
-      [
-        "MH09-M-Green"
-      ],
-      [
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-      [
-        "MT02-XS-White"
-      ],
-      [
-        "MT03-L-Blue"
-      ],
-      [
-        "MT03-L-Red"
-      ],
-      [
-        "MT03-L-Yellow"
-      ],
-      [
-        "MT03-M-Blue"
-      ],
-      [
-        "MT03-M-Red"
-      ],
-      [
-        "MT03-M-Yellow"
-      ],
-      [
-        "MT03-S-Blue"
-      ],
-      [
-        "MT03-S-Red"
-      ],
-      [
-        "MT03-S-Yellow"
-      ],
-      [
-        "MT03-XL-Blue"
-      ],
-      [
-        "MT03-XL-Red"
-      ],
-      [
-        "MT03-XL-Yellow"
-      ],
-      [
-        "MT03-XS-Blue"
-      ],
-      [
-        "MT03-XS-Red"
-      ],
-      [
-        "MT03-XS-Yellow"
-      ],
-      [
-        "MT04-L-Blue"
-      ],
-      [
-        "MT04-M-Blue"
-      ],
-      [
-        "MT04-S-Blue"
-      ],
-      [
-        "MT04-XL-Blue"
-      ],
-      [
-        "MT04-XS-Blue"
-      ],
-      [
-        "MT05-L-Blue"
-      ],
-      [
-        "MT05-M-Blue"
-      ],
-      [
-        "MT05-S-Blue"
-      ],
-      [
-        "MT05-XL-Blue"
-      ],
-      [
-        "MT05-XS-Blue"
-      ],
-      [
-        "MT06-L-Black"
-      ],
-      [
-        "MT06-M-Black"
-      ],
-      [
-        "MT06-S-Black"
-      ],
-      [
-        "MT06-XL-Black"
-      ],
-      [
-        "MT06-XS-Black"
-      ],
-      [
-        "MT07-L-Gray"
-      ],
-      [
-        "MT07-M-Gray"
-      ],
-      [
-        "MT07-S-Gray"
-      ],
-      [
-        "MT07-XL-Gray"
-      ],
-      [
-        "MT07-XS-Gray"
-      ],
-      [
-        "MT08-L-Green"
-      ],
-      [
-        "MT08-M-Green"
-      ],
-      [
-        "MT08-S-Green"
-      ],
-      [
-        "MT08-XL-Green"
-      ],
-      [
-        "MT08-XS-Green"
-      ],
-      [
-        "MT09-L-Blue"
-      ],
-      [
-        "MT09-M-Blue"
-      ],
-      [
-        "MT09-S-Blue"
-      ],
-      [
-        "MT09-XL-Blue"
-      ],
-      [
-        "MT09-XS-Blue"
-      ],
-      [
-        "MT10-L-Yellow"
-      ],
-      [
-        "MT10-M-Yellow"
-      ],
-      [
-        "MT10-S-Yellow"
-      ],
-      [
-        "MT10-XL-Yellow"
-      ],
-      [
-        "MT10-XS-Yellow"
-      ],
-      [
-        "MT11-L-Blue"
-      ],
-      [
-        "MT11-M-Blue"
-      ],
-      [
-        "MT11-S-Blue"
-      ],
-      [
-        "MT11-XL-Blue"
-      ],
-      [
-        "MT11-XS-Blue"
-      ],
-      [
-        "MT12-L-Blue"
-      ],
-      [
-        "MT12-M-Blue"
-      ],
-      [
-        "MT12-S-Blue"
-      ],
-      [
-        "MT12-XL-Blue"
-      ],
-      [
-        "MT12-XS-Blue"
-      ],
-      [
-        "WB01-L-Black"
-      ],
-      [
-        "WB01-L-Gray"
-      ],
-      [
-        "WB01-L-Purple"
-      ],
-      [
-        "WB01-M-Black"
-      ],
-      [
-        "WB01-M-Gray"
-      ],
-      [
-        "WB01-M-Purple"
-      ],
-      [
-        "WB01-S-Black"
-      ],
-      [
-        "WB01-S-Gray"
-      ],
-      [
-        "WB01-S-Purple"
-      ],
-      [
-        "WB01-XL-Black"
-      ],
-      [
-        "WB01-XL-Gray"
-      ],
-      [
-        "WB01-XL-Purple"
-      ],
-      [
-        "WB01-XS-Black"
-      ],
-      [
-        "WB01-XS-Gray"
-      ],
-      [
-        "WB01-XS-Purple"
-      ],
-      [
-        "WB02-L-Blue"
-      ],
-      [
-        "WB02-L-Orange"
-      ],
-      [
-        "WB02-L-Yellow"
-      ],
-      [
-        "WB02-M-Blue"
-      ],
-      [
-        "WB02-M-Orange"
-      ],
-      [
-        "WB02-M-Yellow"
-      ],
-      [
-        "WB02-S-Blue"
-      ],
-      [
-        "WB02-S-Orange"
-      ],
-      [
-        "WB02-S-Yellow"
-      ],
-      [
-        "WB02-XL-Blue"
-      ],
-      [
-        "WB02-XL-Orange"
-      ],
-      [
-        "WB02-XL-Yellow"
-      ],
-      [
-        "WB02-XS-Blue"
-      ],
-      [
-        "WB02-XS-Orange"
-      ],
-      [
-        "WB02-XS-Yellow"
-      ],
-      [
-        "WB03-L-Green"
-      ],
-      [
-        "WB03-L-Red"
-      ],
-      [
-        "WB03-L-Yellow"
-      ],
-      [
-        "WB03-M-Green"
-      ],
-      [
-        "WB03-M-Red"
-      ],
-      [
-        "WB03-M-Yellow"
-      ],
-      [
-        "WB03-S-Green"
-      ],
-      [
-        "WB03-S-Red"
-      ],
-      [
-        "WB03-S-Yellow"
-      ],
-      [
-        "WB03-XL-Green"
-      ],
-      [
-        "WB03-XL-Red"
-      ],
-      [
-        "WB03-XL-Yellow"
-      ],
-      [
-        "WB03-XS-Green"
-      ],
-      [
-        "WB03-XS-Red"
-      ],
-      [
-        "WB03-XS-Yellow"
-      ],
-      [
-        "WB04-L-Blue"
-      ],
-      [
-        "WB04-L-Purple"
-      ],
-      [
-        "WB04-L-Yellow"
-      ],
-      [
-        "WB04-M-Blue"
-      ],
-      [
-        "WB04-M-Purple"
-      ],
-      [
-        "WB04-M-Yellow"
-      ],
-      [
-        "WB04-S-Blue"
-      ],
-      [
-        "WB04-S-Purple"
-      ],
-      [
-        "WB04-S-Yellow"
-      ],
-      [
-        "WB04-XL-Blue"
-      ],
-      [
-        "WB04-XL-Purple"
-      ],
-      [
-        "WB04-XL-Yellow"
-      ],
-      [
-        "WB04-XS-Blue"
-      ],
-      [
-        "WB04-XS-Purple"
-      ],
-      [
-        "WB04-XS-Yellow"
-      ],
-      [
-        "WB05-L-Black"
-      ],
-      [
-        "WB05-L-Orange"
-      ],
-      [
-        "WB05-L-Purple"
-      ],
-      [
-        "WB05-M-Black"
-      ],
-      [
-        "WB05-M-Orange"
-      ],
-      [
-        "WB05-M-Purple"
-      ],
-      [
-        "WB05-S-Black"
-      ],
-      [
-        "WB05-S-Orange"
-      ],
-      [
-        "WB05-S-Purple"
-      ],
-      [
-        "WB05-XL-Black"
-      ],
-      [
-        "WB05-XL-Orange"
-      ],
-      [
-        "WB05-XL-Purple"
-      ],
-      [
-        "WB05-XS-Black"
-      ],
-      [
-        "WB05-XS-Orange"
-      ],
-      [
-        "WB05-XS-Purple"
-      ],
-      [
-        "WH01-L-Green"
-      ],
-      [
-        "WH01-L-Orange"
-      ],
-      [
-        "WH01-L-Purple"
-      ],
-      [
-        "WH01-M-Green"
-      ],
-      [
-        "WH01-M-Orange"
-      ],
-      [
-        "WH01-M-Purple"
-      ],
-      [
-        "WH01-S-Green"
-      ],
-      [
-        "WH01-S-Orange"
-      ],
-      [
-        "WH01-S-Purple"
-      ],
-      [
-        "WH01-XL-Green"
-      ],
-      [
-        "WH01-XL-Orange"
-      ],
-      [
-        "WH01-XL-Purple"
-      ],
-      [
-        "WH01-XS-Green"
-      ],
-      [
-        "WH01-XS-Orange"
-      ],
-      [
-        "WH01-XS-Purple"
-      ],
-      [
-        "WH02-L-Blue"
-      ],
-      [
-        "WH02-L-Green"
-      ],
-      [
-        "WH02-L-Orange"
-      ],
-      [
-        "WH02-M-Blue"
-      ],
-      [
-        "WH02-M-Green"
-      ],
-      [
-        "WH02-M-Orange"
-      ],
-      [
-        "WH02-S-Blue"
-      ],
-      [
-        "WH02-S-Green"
-      ],
-      [
-        "WH02-S-Orange"
-      ],
-      [
-        "WH02-XL-Blue"
-      ],
-      [
-        "WH02-XL-Green"
-      ],
-      [
-        "WH02-XL-Orange"
-      ],
-      [
-        "WH02-XS-Blue"
-      ],
-      [
-        "WH02-XS-Green"
-      ],
-      [
-        "WH02-XS-Orange"
-      ],
-      [
-        "WH03-L-Green"
-      ],
-      [
-        "WH03-L-Purple"
-      ],
-      [
-        "WH03-L-Red"
-      ],
-      [
-        "WH03-M-Green"
-      ],
-      [
-        "WH03-M-Purple"
-      ],
-      [
-        "WH03-M-Red"
-      ],
-      [
-        "WH03-S-Green"
-      ],
-      [
-        "WH03-S-Purple"
-      ],
-      [
-        "WH03-S-Red"
-      ],
-      [
-        "WH03-XL-Green"
-      ],
-      [
-        "WH03-XL-Purple"
-      ],
-      [
-        "WH03-XL-Red"
-      ],
-      [
-        "WH03-XS-Green"
-      ],
-      [
-        "WH03-XS-Purple"
-      ],
-      [
-        "WH03-XS-Red"
-      ],
-      [
-        "WH04-L-Blue"
-      ],
-      [
-        "WH04-L-Orange"
-      ],
-      [
-        "WH04-L-Purple"
-      ],
-      [
-        "WH04-M-Blue"
-      ],
-      [
-        "WH04-M-Orange"
-      ],
-      [
-        "WH04-M-Purple"
-      ],
-      [
-        "WH04-S-Blue"
-      ],
-      [
-        "WH04-S-Orange"
-      ],
-      [
-        "WH04-S-Purple"
-      ],
-      [
-        "WH04-XL-Blue"
-      ],
-      [
-        "WH04-XL-Orange"
-      ],
-      [
-        "WH04-XL-Purple"
-      ],
-      [
-        "WH04-XS-Blue"
-      ],
-      [
-        "WH04-XS-Orange"
-      ],
-      [
-        "WH04-XS-Purple"
-      ],
-      [
-        "WH05-L-Orange"
-      ],
-      [
-        "WH05-L-Purple"
-      ],
-      [
-        "WH05-L-White"
-      ],
-      [
-        "WH05-M-Orange"
-      ],
-      [
-        "WH05-M-Purple"
-      ],
-      [
-        "WH05-M-White"
-      ],
-      [
-        "WH05-S-Orange"
-      ],
-      [
-        "WH05-S-Purple"
-      ],
-      [
-        "WH05-S-White"
-      ],
-      [
-        "WH05-XL-Orange"
-      ],
-      [
-        "WH05-XL-Purple"
-      ],
-      [
-        "WH05-XL-White"
-      ],
-      [
-        "WH05-XS-Orange"
-      ],
-      [
-        "WH05-XS-Purple"
-      ],
-      [
-        "WH05-XS-White"
-      ],
-      [
-        "WH06-L-Purple"
-      ],
-      [
-        "WH06-M-Purple"
-      ],
-      [
-        "WH06-S-Purple"
-      ],
-      [
-        "WH06-XL-Purple"
-      ],
-      [
-        "WH06-XS-Purple"
-      ],
-      [
-        "WH07-L-Gray"
-      ],
-      [
-        "WH07-L-Purple"
-      ],
-      [
-        "WH07-L-White"
-      ],
-      [
-        "WH07-M-Gray"
-      ],
-      [
-        "WH07-M-Purple"
-      ],
-      [
-        "WH07-M-White"
-      ],
-      [
-        "WH07-S-Gray"
-      ],
-      [
-        "WH07-S-Purple"
-      ],
-      [
-        "WH07-S-White"
-      ],
-      [
-        "WH07-XL-Gray"
-      ],
-      [
-        "WH07-XL-Purple"
-      ],
-      [
-        "WH07-XL-White"
-      ],
-      [
-        "WH07-XS-Gray"
-      ],
-      [
-        "WH07-XS-Purple"
-      ],
-      [
-        "WH07-XS-White"
-      ],
-      [
-        "WH08-L-Orange"
-      ],
-      [
-        "WH08-L-Purple"
-      ],
-      [
-        "WH08-L-White"
-      ],
-      [
-        "WH08-M-Orange"
-      ],
-      [
-        "WH08-M-Purple"
-      ],
-      [
-        "WH08-M-White"
-      ],
-      [
-        "WH08-S-Orange"
-      ],
-      [
-        "WH08-S-Purple"
-      ],
-      [
-        "WH08-S-White"
-      ],
-      [
-        "WH08-XL-Orange"
-      ],
-      [
-        "WH08-XL-Purple"
-      ],
-      [
-        "WH08-XL-White"
-      ],
-      [
-        "WH08-XS-Orange"
-      ],
-      [
-        "WH08-XS-Purple"
-      ],
-      [
-        "WH08-XS-White"
-      ],
-      [
-        "WH09-L-Green"
-      ],
-      [
-        "WH09-L-Purple"
-      ],
-      [
-        "WH09-L-Red"
-      ],
-      [
-        "WH09-M-Green"
-      ],
-      [
-        "WH09-M-Purple"
-      ],
-      [
-        "WH09-M-Red"
-      ],
-      [
-        "WH09-S-Green"
-      ],
-      [
-        "WH09-S-Purple"
-      ],
-      [
-        "WH09-S-Red"
-      ],
-      [
-        "WH09-XL-Green"
-      ],
-      [
-        "WH09-XL-Purple"
-      ],
-      [
-        "WH09-XL-Red"
-      ],
-      [
-        "WH09-XS-Green"
-      ],
-      [
-        "WH09-XS-Purple"
-      ],
-      [
-        "WH09-XS-Red"
-      ],
-      [
-        "WH10-L-Blue"
-      ],
-      [
-        "WH10-L-Gray"
-      ],
-      [
-        "WH10-L-Yellow"
-      ],
-      [
-        "WH10-M-Blue"
-      ],
-      [
-        "WH10-M-Gray"
-      ],
-      [
-        "WH10-M-Yellow"
-      ],
-      [
-        "WH10-S-Blue"
-      ],
-      [
-        "WH10-S-Gray"
-      ],
-      [
-        "WH10-S-Yellow"
-      ],
-      [
-        "WH10-XL-Blue"
-      ],
-      [
-        "WH10-XL-Gray"
-      ],
-      [
-        "WH10-XL-Yellow"
-      ],
-      [
-        "WH10-XS-Blue"
-      ],
-      [
-        "WH10-XS-Gray"
-      ],
-      [
-        "WH10-XS-Yellow"
-      ],
-      [
-        "WH11-L-Blue"
-      ],
-      [
-        "WH11-L-Green"
-      ],
-      [
-        "WH11-L-Orange"
-      ],
-      [
-        "WH11-M-Blue"
-      ],
-      [
-        "WH11-M-Green"
-      ],
-      [
-        "WH11-M-Orange"
-      ],
-      [
-        "WH11-S-Blue"
-      ],
-      [
-        "WH11-S-Green"
-      ],
-      [
-        "WH11-S-Orange"
-      ],
-      [
-        "WH11-XL-Blue"
-      ],
-      [
-        "WH11-XL-Green"
-      ],
-      [
-        "WH11-XL-Orange"
-      ],
-      [
-        "WH11-XS-Blue"
-      ],
-      [
-        "WH11-XS-Green"
-      ],
-      [
-        "WH11-XS-Orange"
-      ],
-      [
-        "WH12-L-Gray"
-      ],
-      [
-        "WH12-L-Green"
-      ],
-      [
-        "WH12-L-Purple"
-      ],
-      [
-        "WH12-M-Gray"
-      ],
-      [
-        "WH12-M-Green"
-      ],
-      [
-        "WH12-M-Purple"
-      ],
-      [
-        "WH12-S-Gray"
-      ],
-      [
-        "WH12-S-Green"
-      ],
-      [
-        "WH12-S-Purple"
-      ],
-      [
-        "WH12-XL-Gray"
-      ],
-      [
-        "WH12-XL-Green"
-      ],
-      [
-        "WH12-XL-Purple"
-      ],
-      [
-        "WH12-XS-Gray"
-      ],
-      [
-        "WH12-XS-Green"
-      ],
-      [
-        "WH12-XS-Purple"
-      ],
-      [
-        "WJ01-L-Blue"
-      ],
-      [
-        "WJ01-L-Red"
-      ],
-      [
-        "WJ01-L-Yellow"
-      ],
-      [
-        "WJ01-M-Blue"
-      ],
-      [
-        "WJ01-M-Red"
-      ],
-      [
-        "WJ01-M-Yellow"
-      ],
-      [
-        "WJ01-S-Blue"
-      ],
-      [
-        "WJ01-S-Red"
-      ],
-      [
-        "WJ01-S-Yellow"
-      ],
-      [
-        "WJ02-L-Black"
-      ],
-      [
-        "WJ02-L-Blue"
-      ],
-      [
-        "WJ02-L-Gray"
-      ],
-      [
-        "WJ02-M-Black"
-      ],
-      [
-        "WJ02-M-Blue"
-      ],
-      [
-        "WJ02-M-Gray"
-      ],
-      [
-        "WJ02-S-Black"
-      ],
-      [
-        "WJ02-S-Blue"
-      ],
-      [
-        "WJ02-S-Gray"
-      ],
-      [
-        "WJ02-XL-Black"
-      ],
-      [
-        "WJ02-XL-Blue"
-      ],
-      [
-        "WJ02-XL-Gray"
-      ],
-      [
-        "WJ02-XS-Black"
-      ],
-      [
-        "WJ02-XS-Blue"
-      ],
-      [
-        "WJ02-XS-Gray"
-      ],
-      [
-        "WJ03-L-Blue"
-      ],
-      [
-        "WJ03-L-Orange"
-      ],
-      [
-        "WJ03-L-Red"
-      ],
-      [
-        "WJ03-M-Blue"
-      ],
-      [
-        "WJ03-M-Orange"
-      ],
-      [
-        "WJ03-M-Red"
-      ],
-      [
-        "WJ03-S-Blue"
-      ],
-      [
-        "WJ03-S-Orange"
-      ],
-      [
-        "WJ03-S-Red"
-      ],
-      [
-        "WJ03-XL-Blue"
-      ],
-      [
-        "WJ03-XL-Orange"
-      ],
-      [
-        "WJ03-XL-Red"
-      ],
-      [
-        "WJ03-XS-Blue"
-      ],
-      [
-        "WJ03-XS-Orange"
-      ],
-      [
-        "WJ03-XS-Red"
-      ],
-      [
-        "WJ04-L-Orange"
-      ],
-      [
-        "WJ04-L-Red"
-      ],
-      [
-        "WJ04-L-White"
-      ],
-      [
-        "WJ04-M-Orange"
-      ],
-      [
-        "WJ04-M-Red"
-      ],
-      [
-        "WJ04-M-White"
-      ],
-      [
-        "WJ04-S-Orange"
-      ],
-      [
-        "WJ04-S-Red"
-      ],
-      [
-        "WJ04-S-White"
-      ],
-      [
-        "WJ04-XL-Orange"
-      ],
-      [
-        "WJ04-XL-Red"
-      ],
-      [
-        "WJ04-XL-White"
-      ],
-      [
-        "WJ04-XS-Orange"
-      ],
-      [
-        "WJ04-XS-Red"
-      ],
-      [
-        "WJ04-XS-White"
-      ],
-      [
-        "WJ05-L-Brown"
-      ],
-      [
-        "WJ05-L-Green"
-      ],
-      [
-        "WJ05-L-Red"
-      ],
-      [
-        "WJ05-M-Brown"
-      ],
-      [
-        "WJ05-M-Green"
-      ],
-      [
-        "WJ05-M-Red"
-      ],
-      [
-        "WJ05-S-Brown"
-      ],
-      [
-        "WJ05-S-Green"
-      ],
-      [
-        "WJ05-S-Red"
-      ],
-      [
-        "WJ05-XL-Brown"
-      ],
-      [
-        "WJ05-XL-Green"
-      ],
-      [
-        "WJ05-XL-Red"
-      ],
-      [
-        "WJ05-XS-Brown"
-      ],
-      [
-        "WJ05-XS-Green"
-      ],
-      [
-        "WJ05-XS-Red"
-      ],
-      [
-        "WJ06-L-Blue"
-      ],
-      [
-        "WJ06-L-Green"
-      ],
-      [
-        "WJ06-L-Purple"
-      ],
-      [
-        "WJ06-M-Blue"
-      ],
-      [
-        "WJ06-M-Green"
-      ],
-      [
-        "WJ06-M-Purple"
-      ],
-      [
-        "WJ06-S-Blue"
-      ],
-      [
-        "WJ06-S-Green"
-      ],
-      [
-        "WJ06-S-Purple"
-      ],
-      [
-        "WJ06-XL-Blue"
-      ],
-      [
-        "WJ06-XL-Green"
-      ],
-      [
-        "WJ06-XL-Purple"
-      ],
-      [
-        "WJ06-XS-Blue"
-      ],
-      [
-        "WJ06-XS-Green"
-      ],
-      [
-        "WJ06-XS-Purple"
-      ],
-      [
-        "WJ07-L-Orange"
-      ],
-      [
-        "WJ07-L-Purple"
-      ],
-      [
-        "WJ07-L-Red"
-      ],
-      [
-        "WJ07-M-Orange"
-      ],
-      [
-        "WJ07-M-Purple"
-      ],
-      [
-        "WJ07-M-Red"
-      ],
-      [
-        "WJ07-S-Orange"
-      ],
-      [
-        "WJ07-S-Purple"
-      ],
-      [
-        "WJ07-S-Red"
-      ],
-      [
-        "WJ07-XL-Orange"
-      ],
-      [
-        "WJ07-XL-Purple"
-      ],
-      [
-        "WJ07-XL-Red"
-      ],
-      [
-        "WJ07-XS-Orange"
-      ],
-      [
-        "WJ07-XS-Purple"
-      ],
-      [
-        "WJ07-XS-Red"
-      ],
-      [
-        "WJ08-L-Gray"
-      ],
-      [
-        "WJ08-L-Orange"
-      ],
-      [
-        "WJ08-L-Purple"
-      ],
-      [
-        "WJ08-M-Gray"
-      ],
-      [
-        "WJ08-M-Orange"
-      ],
-      [
-        "WJ08-M-Purple"
-      ],
-      [
-        "WJ08-S-Gray"
-      ],
-      [
-        "WJ08-S-Orange"
-      ],
-      [
-        "WJ08-S-Purple"
-      ],
-      [
-        "WJ08-XL-Gray"
-      ],
-      [
-        "WJ08-XL-Orange"
-      ],
-      [
-        "WJ08-XL-Purple"
-      ],
-      [
-        "WJ08-XS-Gray"
-      ],
-      [
-        "WJ08-XS-Orange"
-      ],
-      [
-        "WJ08-XS-Purple"
-      ],
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-        "WJ09-L-Blue"
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-      [
-        "WJ09-L-Gray"
-      ],
-      [
-        "WJ09-L-Green"
-      ],
-      [
-        "WJ09-M-Blue"
-      ],
-      [
-        "WJ09-M-Gray"
-      ],
-      [
-        "WJ09-M-Green"
-      ],
-      [
-        "WJ09-S-Blue"
-      ],
-      [
-        "WJ09-S-Gray"
-      ],
-      [
-        "WJ09-S-Green"
-      ],
-      [
-        "WJ09-XL-Blue"
-      ],
-      [
-        "WJ09-XL-Gray"
-      ],
-      [
-        "WJ09-XL-Green"
-      ],
-      [
-        "WJ09-XS-Blue"
-      ],
-      [
-        "WJ09-XS-Gray"
-      ],
-      [
-        "WJ09-XS-Green"
-      ],
-      [
-        "WJ10-L-Black"
-      ],
-      [
-        "WJ10-L-Orange"
-      ],
-      [
-        "WJ10-L-Yellow"
-      ],
-      [
-        "WJ10-M-Black"
-      ],
-      [
-        "WJ10-M-Orange"
-      ],
-      [
-        "WJ10-M-Yellow"
-      ],
-      [
-        "WJ10-S-Black"
-      ],
-      [
-        "WJ10-S-Orange"
-      ],
-      [
-        "WJ10-S-Yellow"
-      ],
-      [
-        "WJ10-XL-Black"
-      ],
-      [
-        "WJ10-XL-Orange"
-      ],
-      [
-        "WJ10-XL-Yellow"
-      ],
-      [
-        "WJ10-XS-Black"
-      ],
-      [
-        "WJ10-XS-Orange"
-      ],
-      [
-        "WJ10-XS-Yellow"
-      ],
-      [
-        "WJ11-L-Black"
-      ],
-      [
-        "WJ11-L-Blue"
-      ],
-      [
-        "WJ11-L-Orange"
-      ],
-      [
-        "WJ11-M-Black"
-      ],
-      [
-        "WJ11-M-Blue"
-      ],
-      [
-        "WJ11-M-Orange"
-      ],
-      [
-        "WJ11-S-Black"
-      ],
-      [
-        "WJ11-S-Blue"
-      ],
-      [
-        "WJ11-S-Orange"
-      ],
-      [
-        "WJ11-XL-Black"
-      ],
-      [
-        "WJ11-XL-Blue"
-      ],
-      [
-        "WJ11-XL-Orange"
-      ],
-      [
-        "WJ11-XS-Black"
-      ],
-      [
-        "WJ11-XS-Blue"
-      ],
-      [
-        "WJ11-XS-Orange"
-      ],
-      [
-        "WJ12-L-Black"
-      ],
-      [
-        "WJ12-L-Blue"
-      ],
-      [
-        "WJ12-L-Purple"
-      ],
-      [
-        "WJ12-M-Black"
-      ],
-      [
-        "WJ12-M-Blue"
-      ],
-      [
-        "WJ12-M-Purple"
-      ],
-      [
-        "WJ12-S-Black"
-      ],
-      [
-        "WJ12-S-Blue"
-      ],
-      [
-        "WJ12-S-Purple"
-      ],
-      [
-        "WJ12-XL-Black"
-      ],
-      [
-        "WJ12-XL-Blue"
-      ],
-      [
-        "WJ12-XL-Purple"
-      ],
-      [
-        "WJ12-XS-Black"
-      ],
-      [
-        "WJ12-XS-Blue"
-      ],
-      [
-        "WJ12-XS-Purple"
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-        "WP01-28-Black"
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-        "WP01-28-Gray"
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-        "WP01-28-White"
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-        "WP01-29-Black"
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-        "WP01-29-Gray"
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-        "WP01-29-White"
-      ],
-      [
-        "WP02-28-Blue"
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-      [
-        "WP02-28-Purple"
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-      [
-        "WP02-28-Red"
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-        "WP02-29-Blue"
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-      [
-        "WP02-29-Purple"
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-      [
-        "WP02-29-Red"
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-      [
-        "WP03-28-Black"
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-      [
-        "WP03-28-Blue"
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-      [
-        "WP03-28-Purple"
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-      [
-        "WP03-29-Black"
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-      [
-        "WP03-29-Blue"
-      ],
-      [
-        "WP03-29-Purple"
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-        "WP04-28-Black"
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-      [
-        "WP04-28-Blue"
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-      [
-        "WP04-28-White"
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-        "WP04-29-Black"
-      ],
-      [
-        "WP04-29-Blue"
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-      [
-        "WP04-29-White"
-      ],
-      [
-        "WP05-28-Blue"
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-      [
-        "WP05-28-Gray"
-      ],
-      [
-        "WP05-28-Red"
-      ],
-      [
-        "WP05-29-Blue"
-      ],
-      [
-        "WP05-29-Gray"
-      ],
-      [
-        "WP05-29-Red"
-      ],
-      [
-        "WP06-28-Black"
-      ],
-      [
-        "WP06-28-Blue"
-      ],
-      [
-        "WP06-28-Orange"
-      ],
-      [
-        "WP06-29-Black"
-      ],
-      [
-        "WP06-29-Blue"
-      ],
-      [
-        "WP06-29-Orange"
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-      [
-        "WP07-28-Black"
-      ],
-      [
-        "WP07-28-Blue"
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-      [
-        "WP07-28-Orange"
-      ],
-      [
-        "WP07-29-Black"
-      ],
-      [
-        "WP07-29-Blue"
-      ],
-      [
-        "WP07-29-Orange"
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-      [
-        "WP08-28-Black"
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-      [
-        "WP08-28-Green"
-      ],
-      [
-        "WP08-28-Red"
-      ],
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-        "WP08-29-Black"
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-      [
-        "WP08-29-Green"
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-      [
-        "WP08-29-Red"
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-        "WP09-28-Black"
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-      [
-        "WP09-28-Blue"
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-      [
-        "WP09-28-Purple"
-      ],
-      [
-        "WP09-29-Black"
-      ],
-      [
-        "WP09-29-Blue"
-      ],
-      [
-        "WP09-29-Purple"
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-        "WP10-28-Black"
-      ],
-      [
-        "WP10-28-Gray"
-      ],
-      [
-        "WP10-28-White"
-      ],
-      [
-        "WP10-29-Black"
-      ],
-      [
-        "WP10-29-Gray"
-      ],
-      [
-        "WP10-29-White"
-      ],
-      [
-        "WP11-28-Blue"
-      ],
-      [
-        "WP11-28-Green"
-      ],
-      [
-        "WP11-28-Red"
-      ],
-      [
-        "WP11-29-Blue"
-      ],
-      [
-        "WP11-29-Green"
-      ],
-      [
-        "WP11-29-Red"
-      ],
-      [
-        "WP12-28-Blue"
-      ],
-      [
-        "WP12-28-Gray"
-      ],
-      [
-        "WP12-28-Green"
-      ],
-      [
-        "WP12-29-Blue"
-      ],
-      [
-        "WP12-29-Gray"
-      ],
-      [
-        "WP12-29-Green"
-      ],
-      [
-        "WP13-28-Blue"
-      ],
-      [
-        "WP13-28-Green"
-      ],
-      [
-        "WP13-28-Orange"
-      ],
-      [
-        "WP13-29-Blue"
-      ],
-      [
-        "WP13-29-Green"
-      ],
-      [
-        "WP13-29-Orange"
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-        "WS01-L-Black"
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-      [
-        "WS01-L-Green"
-      ],
-      [
-        "WS01-L-Yellow"
-      ],
-      [
-        "WS01-M-Black"
-      ],
-      [
-        "WS01-M-Green"
-      ],
-      [
-        "WS01-M-Yellow"
-      ],
-      [
-        "WS01-S-Black"
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-      [
-        "WS01-S-Green"
-      ],
-      [
-        "WS01-S-Yellow"
-      ],
-      [
-        "WS01-XL-Black"
-      ],
-      [
-        "WS01-XL-Green"
-      ],
-      [
-        "WS01-XL-Yellow"
-      ],
-      [
-        "WS01-XS-Black"
-      ],
-      [
-        "WS01-XS-Green"
-      ],
-      [
-        "WS01-XS-Yellow"
-      ],
-      [
-        "WS02-L-Blue"
-      ],
-      [
-        "WS02-L-Green"
-      ],
-      [
-        "WS02-L-Red"
-      ],
-      [
-        "WS02-M-Blue"
-      ],
-      [
-        "WS02-M-Green"
-      ],
-      [
-        "WS02-M-Red"
-      ],
-      [
-        "WS02-S-Blue"
-      ],
-      [
-        "WS02-S-Green"
-      ],
-      [
-        "WS02-S-Red"
-      ],
-      [
-        "WS02-XL-Blue"
-      ],
-      [
-        "WS02-XL-Green"
-      ],
-      [
-        "WS02-XL-Red"
-      ],
-      [
-        "WS02-XS-Blue"
-      ],
-      [
-        "WS02-XS-Green"
-      ],
-      [
-        "WS02-XS-Red"
-      ],
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-        "WS03-L-Blue"
-      ],
-      [
-        "WS03-L-Green"
-      ],
-      [
-        "WS03-L-Red"
-      ],
-      [
-        "WS03-M-Blue"
-      ],
-      [
-        "WS03-M-Green"
-      ],
-      [
-        "WS03-M-Red"
-      ],
-      [
-        "WS03-S-Blue"
-      ],
-      [
-        "WS03-S-Green"
-      ],
-      [
-        "WS03-S-Red"
-      ],
-      [
-        "WS03-XL-Blue"
-      ],
-      [
-        "WS03-XL-Green"
-      ],
-      [
-        "WS03-XL-Red"
-      ],
-      [
-        "WS03-XS-Blue"
-      ],
-      [
-        "WS03-XS-Green"
-      ],
-      [
-        "WS03-XS-Red"
-      ],
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-        "WS04-L-Blue"
-      ],
-      [
-        "WS04-L-Green"
-      ],
-      [
-        "WS04-L-Red"
-      ],
-      [
-        "WS04-M-Blue"
-      ],
-      [
-        "WS04-M-Green"
-      ],
-      [
-        "WS04-M-Red"
-      ],
-      [
-        "WS04-S-Blue"
-      ],
-      [
-        "WS04-S-Green"
-      ],
-      [
-        "WS04-S-Red"
-      ],
-      [
-        "WS04-XL-Blue"
-      ],
-      [
-        "WS04-XL-Green"
-      ],
-      [
-        "WS04-XL-Red"
-      ],
-      [
-        "WS04-XS-Blue"
-      ],
-      [
-        "WS04-XS-Green"
-      ],
-      [
-        "WS04-XS-Red"
-      ],
-      [
-        "WS05-L-Black"
-      ],
-      [
-        "WS05-L-Orange"
-      ],
-      [
-        "WS05-L-Yellow"
-      ],
-      [
-        "WS05-M-Black"
-      ],
-      [
-        "WS05-M-Orange"
-      ],
-      [
-        "WS05-M-Yellow"
-      ],
-      [
-        "WS05-S-Black"
-      ],
-      [
-        "WS05-S-Orange"
-      ],
-      [
-        "WS05-S-Yellow"
-      ],
-      [
-        "WS05-XL-Black"
-      ],
-      [
-        "WS05-XL-Orange"
-      ],
-      [
-        "WS05-XL-Yellow"
-      ],
-      [
-        "WS05-XS-Black"
-      ],
-      [
-        "WS05-XS-Orange"
-      ],
-      [
-        "WS05-XS-Yellow"
-      ],
-      [
-        "WS06-L-Gray"
-      ],
-      [
-        "WS06-L-Purple"
-      ],
-      [
-        "WS06-L-Red"
-      ],
-      [
-        "WS06-M-Gray"
-      ],
-      [
-        "WS06-M-Purple"
-      ],
-      [
-        "WS06-M-Red"
-      ],
-      [
-        "WS06-S-Gray"
-      ],
-      [
-        "WS06-S-Purple"
-      ],
-      [
-        "WS06-S-Red"
-      ],
-      [
-        "WS06-XL-Gray"
-      ],
-      [
-        "WS06-XL-Purple"
-      ],
-      [
-        "WS06-XL-Red"
-      ],
-      [
-        "WS06-XS-Gray"
-      ],
-      [
-        "WS06-XS-Purple"
-      ],
-      [
-        "WS06-XS-Red"
-      ],
-      [
-        "WS07-L-Black"
-      ],
-      [
-        "WS07-L-White"
-      ],
-      [
-        "WS07-L-Yellow"
-      ],
-      [
-        "WS07-M-Black"
-      ],
-      [
-        "WS07-M-White"
-      ],
-      [
-        "WS07-M-Yellow"
-      ],
-      [
-        "WS07-S-Black"
-      ],
-      [
-        "WS07-S-White"
-      ],
-      [
-        "WS07-S-Yellow"
-      ],
-      [
-        "WS07-XL-Black"
-      ],
-      [
-        "WS07-XL-White"
-      ],
-      [
-        "WS07-XL-Yellow"
-      ],
-      [
-        "WS07-XS-Black"
-      ],
-      [
-        "WS07-XS-White"
-      ],
-      [
-        "WS07-XS-Yellow"
-      ],
-      [
-        "WS08-L-Black"
-      ],
-      [
-        "WS08-L-Blue"
-      ],
-      [
-        "WS08-L-Red"
-      ],
-      [
-        "WS08-M-Black"
-      ],
-      [
-        "WS08-M-Blue"
-      ],
-      [
-        "WS08-M-Red"
-      ],
-      [
-        "WS08-S-Black"
-      ],
-      [
-        "WS08-S-Blue"
-      ],
-      [
-        "WS08-S-Red"
-      ],
-      [
-        "WS08-XL-Black"
-      ],
-      [
-        "WS08-XL-Blue"
-      ],
-      [
-        "WS08-XL-Red"
-      ],
-      [
-        "WS08-XS-Black"
-      ],
-      [
-        "WS08-XS-Blue"
-      ],
-      [
-        "WS08-XS-Red"
-      ],
-      [
-        "WS09-L-Blue"
-      ],
-      [
-        "WS09-L-Red"
-      ],
-      [
-        "WS09-L-White"
-      ],
-      [
-        "WS09-M-Blue"
-      ],
-      [
-        "WS09-M-Red"
-      ],
-      [
-        "WS09-M-White"
-      ],
-      [
-        "WS09-S-Blue"
-      ],
-      [
-        "WS09-S-Red"
-      ],
-      [
-        "WS09-S-White"
-      ],
-      [
-        "WS09-XL-Blue"
-      ],
-      [
-        "WS09-XL-Red"
-      ],
-      [
-        "WS09-XL-White"
-      ],
-      [
-        "WS09-XS-Blue"
-      ],
-      [
-        "WS09-XS-Red"
-      ],
-      [
-        "WS09-XS-White"
-      ],
-      [
-        "WS10-L-Green"
-      ],
-      [
-        "WS10-L-Red"
-      ],
-      [
-        "WS10-L-Yellow"
-      ],
-      [
-        "WS10-M-Green"
-      ],
-      [
-        "WS10-M-Red"
-      ],
-      [
-        "WS10-M-Yellow"
-      ],
-      [
-        "WS10-S-Green"
-      ],
-      [
-        "WS10-S-Red"
-      ],
-      [
-        "WS10-S-Yellow"
-      ],
-      [
-        "WS10-XL-Green"
-      ],
-      [
-        "WS10-XL-Red"
-      ],
-      [
-        "WS10-XL-Yellow"
-      ],
-      [
-        "WS10-XS-Green"
-      ],
-      [
-        "WS10-XS-Red"
-      ],
-      [
-        "WS10-XS-Yellow"
-      ],
-      [
-        "WS11-L-Green"
-      ],
-      [
-        "WS11-L-Orange"
-      ],
-      [
-        "WS11-L-Yellow"
-      ],
-      [
-        "WS11-M-Green"
-      ],
-      [
-        "WS11-M-Orange"
-      ],
-      [
-        "WS11-M-Yellow"
-      ],
-      [
-        "WS11-S-Green"
-      ],
-      [
-        "WS11-S-Orange"
-      ],
-      [
-        "WS11-S-Yellow"
-      ],
-      [
-        "WS11-XL-Green"
-      ],
-      [
-        "WS11-XL-Orange"
-      ],
-      [
-        "WS11-XL-Yellow"
-      ],
-      [
-        "WS11-XS-Green"
-      ],
-      [
-        "WS11-XS-Orange"
-      ],
-      [
-        "WS11-XS-Yellow"
-      ],
-      [
-        "WS12-L-Blue"
-      ],
-      [
-        "WS12-L-Orange"
-      ],
-      [
-        "WS12-L-Purple"
-      ],
-      [
-        "WS12-M-Blue"
-      ],
-      [
-        "WS12-M-Orange"
-      ],
-      [
-        "WS12-M-Purple"
-      ],
-      [
-        "WS12-S-Blue"
-      ],
-      [
-        "WS12-S-Orange"
-      ],
-      [
-        "WS12-S-Purple"
-      ],
-      [
-        "WS12-XL-Blue"
-      ],
-      [
-        "WS12-XL-Orange"
-      ],
-      [
-        "WS12-XL-Purple"
-      ],
-      [
-        "WS12-XS-Blue"
-      ],
-      [
-        "WS12-XS-Orange"
-      ],
-      [
-        "WS12-XS-Purple"
-      ],
-      [
-        "WSH01-28-Black"
-      ],
-      [
-        "WSH01-28-Green"
-      ],
-      [
-        "WSH01-28-Red"
-      ],
-      [
-        "WSH01-29-Black"
-      ],
-      [
-        "WSH01-29-Green"
-      ],
-      [
-        "WSH01-29-Red"
-      ],
-      [
-        "WSH01-30-Black"
-      ],
-      [
-        "WSH01-30-Green"
-      ],
-      [
-        "WSH01-30-Red"
-      ],
-      [
-        "WSH01-31-Black"
-      ],
-      [
-        "WSH01-31-Green"
-      ],
-      [
-        "WSH01-31-Red"
-      ],
-      [
-        "WSH01-32-Black"
-      ],
-      [
-        "WSH01-32-Green"
-      ],
-      [
-        "WSH01-32-Red"
-      ],
-      [
-        "WSH02-28-Gray"
-      ],
-      [
-        "WSH02-28-Orange"
-      ],
-      [
-        "WSH02-28-Yellow"
-      ],
-      [
-        "WSH02-29-Gray"
-      ],
-      [
-        "WSH02-29-Orange"
-      ],
-      [
-        "WSH02-29-Yellow"
-      ],
-      [
-        "WSH02-30-Gray"
-      ],
-      [
-        "WSH02-30-Orange"
-      ],
-      [
-        "WSH02-30-Yellow"
-      ],
-      [
-        "WSH02-31-Gray"
-      ],
-      [
-        "WSH02-31-Orange"
-      ],
-      [
-        "WSH02-31-Yellow"
-      ],
-      [
-        "WSH02-32-Gray"
-      ],
-      [
-        "WSH02-32-Orange"
-      ],
-      [
-        "WSH02-32-Yellow"
-      ],
-      [
-        "WSH03-28-Blue"
-      ],
-      [
-        "WSH03-28-Gray"
-      ],
-      [
-        "WSH03-28-Orange"
-      ],
-      [
-        "WSH03-29-Blue"
-      ],
-      [
-        "WSH03-29-Gray"
-      ],
-      [
-        "WSH03-29-Orange"
-      ],
-      [
-        "WSH03-30-Blue"
-      ],
-      [
-        "WSH03-30-Gray"
-      ],
-      [
-        "WSH03-30-Orange"
-      ],
-      [
-        "WSH03-31-Blue"
-      ],
-      [
-        "WSH03-31-Gray"
-      ],
-      [
-        "WSH03-31-Orange"
-      ],
-      [
-        "WSH03-32-Blue"
-      ],
-      [
-        "WSH03-32-Gray"
-      ],
-      [
-        "WSH03-32-Orange"
-      ],
-      [
-        "WSH04-28-Black"
-      ],
-      [
-        "WSH04-28-Green"
-      ],
-      [
-        "WSH04-28-Orange"
-      ],
-      [
-        "WSH04-29-Black"
-      ],
-      [
-        "WSH04-29-Green"
-      ],
-      [
-        "WSH04-29-Orange"
-      ],
-      [
-        "WSH04-30-Black"
-      ],
-      [
-        "WSH04-30-Green"
-      ],
-      [
-        "WSH04-30-Orange"
-      ],
-      [
-        "WSH04-31-Black"
-      ],
-      [
-        "WSH04-31-Green"
-      ],
-      [
-        "WSH04-31-Orange"
-      ],
-      [
-        "WSH04-32-Black"
-      ],
-      [
-        "WSH04-32-Green"
-      ],
-      [
-        "WSH04-32-Orange"
-      ],
-      [
-        "WSH05-28-Blue"
-      ],
-      [
-        "WSH05-28-Purple"
-      ],
-      [
-        "WSH05-28-Yellow"
-      ],
-      [
-        "WSH05-29-Blue"
-      ],
-      [
-        "WSH05-29-Purple"
-      ],
-      [
-        "WSH05-29-Yellow"
-      ],
-      [
-        "WSH05-30-Blue"
-      ],
-      [
-        "WSH05-30-Purple"
-      ],
-      [
-        "WSH05-30-Yellow"
-      ],
-      [
-        "WSH05-31-Blue"
-      ],
-      [
-        "WSH05-31-Purple"
-      ],
-      [
-        "WSH05-31-Yellow"
-      ],
-      [
-        "WSH05-32-Blue"
-      ],
-      [
-        "WSH05-32-Purple"
-      ],
-      [
-        "WSH05-32-Yellow"
-      ],
-      [
-        "WSH06-28-Gray"
-      ],
-      [
-        "WSH06-28-Orange"
-      ],
-      [
-        "WSH06-28-Purple"
-      ],
-      [
-        "WSH06-29-Gray"
-      ],
-      [
-        "WSH06-29-Orange"
-      ],
-      [
-        "WSH06-29-Purple"
-      ],
-      [
-        "WSH07-28-Black"
-      ],
-      [
-        "WSH07-28-Blue"
-      ],
-      [
-        "WSH07-28-Purple"
-      ],
-      [
-        "WSH07-29-Black"
-      ],
-      [
-        "WSH07-29-Blue"
-      ],
-      [
-        "WSH07-29-Purple"
-      ],
-      [
-        "WSH08-28-Purple"
-      ],
-      [
-        "WSH08-29-Purple"
-      ],
-      [
-        "WSH08-30-Purple"
-      ],
-      [
-        "WSH08-31-Purple"
-      ],
-      [
-        "WSH08-32-Purple"
-      ],
-      [
-        "WSH09-28-Gray"
-      ],
-      [
-        "WSH09-28-Green"
-      ],
-      [
-        "WSH09-28-White"
-      ],
-      [
-        "WSH09-29-Gray"
-      ],
-      [
-        "WSH09-29-Green"
-      ],
-      [
-        "WSH09-29-White"
-      ],
-      [
-        "WSH10-28-Black"
-      ],
-      [
-        "WSH10-28-Orange"
-      ],
-      [
-        "WSH10-28-White"
-      ],
-      [
-        "WSH10-29-Black"
-      ],
-      [
-        "WSH10-29-Orange"
-      ],
-      [
-        "WSH10-29-White"
-      ],
-      [
-        "WSH11-28-Blue"
-      ],
-      [
-        "WSH11-28-Orange"
-      ],
-      [
-        "WSH11-28-Red"
-      ],
-      [
-        "WSH11-29-Blue"
-      ],
-      [
-        "WSH11-29-Orange"
-      ],
-      [
-        "WSH11-29-Red"
-      ],
-      [
-        "WSH12-28-Green"
-      ],
-      [
-        "WSH12-28-Purple"
-      ],
-      [
-        "WSH12-28-Red"
-      ],
-      [
-        "WSH12-29-Green"
-      ],
-      [
-        "WSH12-29-Purple"
-      ],
-      [
-        "WSH12-29-Red"
-      ],
-      [
-        "WSH12-30-Green"
-      ],
-      [
-        "WSH12-30-Purple"
-      ],
-      [
-        "WSH12-30-Red"
-      ],
-      [
-        "WSH12-31-Green"
-      ],
-      [
-        "WSH12-31-Purple"
-      ],
-      [
-        "WSH12-31-Red"
-      ],
-      [
-        "WSH12-32-Green"
-      ],
-      [
-        "WSH12-32-Purple"
-      ],
-      [
-        "WSH12-32-Red"
-      ],
-      [
-        "WT01-L-Black"
-      ],
-      [
-        "WT01-L-Blue"
-      ],
-      [
-        "WT01-L-Orange"
-      ],
-      [
-        "WT01-M-Black"
-      ],
-      [
-        "WT01-M-Blue"
-      ],
-      [
-        "WT01-M-Orange"
-      ],
-      [
-        "WT01-S-Black"
-      ],
-      [
-        "WT01-S-Blue"
-      ],
-      [
-        "WT01-S-Orange"
-      ],
-      [
-        "WT01-XL-Black"
-      ],
-      [
-        "WT01-XL-Blue"
-      ],
-      [
-        "WT01-XL-Orange"
-      ],
-      [
-        "WT01-XS-Black"
-      ],
-      [
-        "WT01-XS-Blue"
-      ],
-      [
-        "WT01-XS-Orange"
-      ],
-      [
-        "WT02-L-Green"
-      ],
-      [
-        "WT02-L-Orange"
-      ],
-      [
-        "WT02-L-Yellow"
-      ],
-      [
-        "WT02-M-Green"
-      ],
-      [
-        "WT02-M-Orange"
-      ],
-      [
-        "WT02-M-Yellow"
-      ],
-      [
-        "WT02-S-Green"
-      ],
-      [
-        "WT02-S-Orange"
-      ],
-      [
-        "WT02-S-Yellow"
-      ],
-      [
-        "WT02-XL-Green"
-      ],
-      [
-        "WT02-XL-Orange"
-      ],
-      [
-        "WT02-XL-Yellow"
-      ],
-      [
-        "WT02-XS-Green"
-      ],
-      [
-        "WT02-XS-Orange"
-      ],
-      [
-        "WT02-XS-Yellow"
-      ],
-      [
-        "WT03-L-Orange"
-      ],
-      [
-        "WT03-L-Purple"
-      ],
-      [
-        "WT03-L-Red"
-      ],
-      [
-        "WT03-M-Orange"
-      ],
-      [
-        "WT03-M-Purple"
-      ],
-      [
-        "WT03-M-Red"
-      ],
-      [
-        "WT03-S-Orange"
-      ],
-      [
-        "WT03-S-Purple"
-      ],
-      [
-        "WT03-S-Red"
-      ],
-      [
-        "WT03-XL-Orange"
-      ],
-      [
-        "WT03-XL-Purple"
-      ],
-      [
-        "WT03-XL-Red"
-      ],
-      [
-        "WT03-XS-Orange"
-      ],
-      [
-        "WT03-XS-Purple"
-      ],
-      [
-        "WT03-XS-Red"
-      ],
-      [
-        "WT04-L-Blue"
-      ],
-      [
-        "WT04-L-Purple"
-      ],
-      [
-        "WT04-L-Red"
-      ],
-      [
-        "WT04-M-Blue"
-      ],
-      [
-        "WT04-M-Purple"
-      ],
-      [
-        "WT04-M-Red"
-      ],
-      [
-        "WT04-S-Blue"
-      ],
-      [
-        "WT04-S-Purple"
-      ],
-      [
-        "WT04-S-Red"
-      ],
-      [
-        "WT04-XL-Blue"
-      ],
-      [
-        "WT04-XL-Purple"
-      ],
-      [
-        "WT04-XL-Red"
-      ],
-      [
-        "WT04-XS-Blue"
-      ],
-      [
-        "WT04-XS-Purple"
-      ],
-      [
-        "WT04-XS-Red"
-      ],
-      [
-        "WT05-L-Orange"
-      ],
-      [
-        "WT05-L-Purple"
-      ],
-      [
-        "WT05-L-White"
-      ],
-      [
-        "WT05-M-Orange"
-      ],
-      [
-        "WT05-M-Purple"
-      ],
-      [
-        "WT05-M-White"
-      ],
-      [
-        "WT05-S-Orange"
-      ],
-      [
-        "WT05-S-Purple"
-      ],
-      [
-        "WT05-S-White"
-      ],
-      [
-        "WT05-XL-Orange"
-      ],
-      [
-        "WT05-XL-Purple"
-      ],
-      [
-        "WT05-XL-White"
-      ],
-      [
-        "WT05-XS-Orange"
-      ],
-      [
-        "WT05-XS-Purple"
-      ],
-      [
-        "WT05-XS-White"
-      ],
-      [
-        "WT06-L-Blue"
-      ],
-      [
-        "WT06-L-Red"
-      ],
-      [
-        "WT06-L-Yellow"
-      ],
-      [
-        "WT06-M-Blue"
-      ],
-      [
-        "WT06-M-Red"
-      ],
-      [
-        "WT06-M-Yellow"
-      ],
-      [
-        "WT06-S-Blue"
-      ],
-      [
-        "WT06-S-Red"
-      ],
-      [
-        "WT06-S-Yellow"
-      ],
-      [
-        "WT06-XL-Blue"
-      ],
-      [
-        "WT06-XL-Red"
-      ],
-      [
-        "WT06-XL-Yellow"
-      ],
-      [
-        "WT06-XS-Blue"
-      ],
-      [
-        "WT06-XS-Red"
-      ],
-      [
-        "WT06-XS-Yellow"
-      ],
-      [
-        "WT07-L-Green"
-      ],
-      [
-        "WT07-L-White"
-      ],
-      [
-        "WT07-L-Yellow"
-      ],
-      [
-        "WT07-M-Green"
-      ],
-      [
-        "WT07-M-White"
-      ],
-      [
-        "WT07-M-Yellow"
-      ],
-      [
-        "WT07-S-Green"
-      ],
-      [
-        "WT07-S-White"
-      ],
-      [
-        "WT07-S-Yellow"
-      ],
-      [
-        "WT07-XL-Green"
-      ],
-      [
-        "WT07-XL-White"
-      ],
-      [
-        "WT07-XL-Yellow"
-      ],
-      [
-        "WT07-XS-Green"
-      ],
-      [
-        "WT07-XS-White"
-      ],
-      [
-        "WT07-XS-Yellow"
-      ],
-      [
-        "WT08-L-Black"
-      ],
-      [
-        "WT08-L-Purple"
-      ],
-      [
-        "WT08-L-Yellow"
-      ],
-      [
-        "WT08-M-Black"
-      ],
-      [
-        "WT08-M-Purple"
-      ],
-      [
-        "WT08-M-Yellow"
-      ],
-      [
-        "WT08-S-Black"
-      ],
-      [
-        "WT08-S-Purple"
-      ],
-      [
-        "WT08-S-Yellow"
-      ],
-      [
-        "WT08-XL-Black"
-      ],
-      [
-        "WT08-XL-Purple"
-      ],
-      [
-        "WT08-XL-Yellow"
-      ],
-      [
-        "WT08-XS-Black"
-      ],
-      [
-        "WT08-XS-Purple"
-      ],
-      [
-        "WT08-XS-Yellow"
-      ],
-      [
-        "WT09-L-Purple"
-      ],
-      [
-        "WT09-L-White"
-      ],
-      [
-        "WT09-L-Yellow"
-      ],
-      [
-        "WT09-M-Purple"
-      ],
-      [
-        "WT09-M-White"
-      ],
-      [
-        "WT09-M-Yellow"
-      ],
-      [
-        "WT09-S-Purple"
-      ],
-      [
-        "WT09-S-White"
-      ],
-      [
-        "WT09-S-Yellow"
-      ],
-      [
-        "WT09-XL-Purple"
-      ],
-      [
-        "WT09-XL-White"
-      ],
-      [
-        "WT09-XL-Yellow"
-      ],
-      [
-        "WT09-XS-Purple"
-      ],
-      [
-        "WT09-XS-White"
-      ],
-      [
-        "WT09-XS-Yellow"
-      ]
-    ]
-  },
-  {
-    "question": "How many product IDs have an integer attribute ID 93 with a value of 60?",
-    "answer": 137,
-    "sql": "SELECT entity_id FROM catalog_product_entity_int WHERE attribute_id = 93 AND value = 60;",
-    "sql_execute_result": [
-      [
-        97
-      ],
-      [
-        100
-      ],
-      [
-        103
-      ],
-      [
-        106
-      ],
-      [
-        109
-      ],
-      [
-        257
-      ],
-      [
-        260
-      ],
-      [
-        263
-      ],
-      [
-        266
-      ],
-      [
-        269
-      ],
-      [
-        305
-      ],
-      [
-        308
-      ],
-      [
-        311
-      ],
-      [
-        314
-      ],
-      [
-        317
-      ],
-      [
-        337
-      ],
-      [
-        340
-      ],
-      [
-        343
-      ],
-      [
-        346
-      ],
-      [
-        349
-      ],
-      [
-        481
-      ],
-      [
-        484
-      ],
-      [
-        487
-      ],
-      [
-        490
-      ],
-      [
-        493
-      ],
-      [
-        529
-      ],
-      [
-        532
-      ],
-      [
-        535
-      ],
-      [
-        538
-      ],
-      [
-        541
-      ],
-      [
-        545
-      ],
-      [
-        548
-      ],
-      [
-        551
-      ],
-      [
-        554
-      ],
-      [
-        557
-      ],
-      [
-        657
-      ],
-      [
-        660
-      ],
-      [
-        663
-      ],
-      [
-        666
-      ],
-      [
-        669
-      ],
-      [
-        707
-      ],
-      [
-        708
-      ],
-      [
-        709
-      ],
-      [
-        710
-      ],
-      [
-        711
-      ],
-      [
-        914
-      ],
-      [
-        917
-      ],
-      [
-        920
-      ],
-      [
-        923
-      ],
-      [
-        1165
-      ],
-      [
-        1168
-      ],
-      [
-        1171
-      ],
-      [
-        1174
-      ],
-      [
-        1177
-      ],
-      [
-        1213
-      ],
-      [
-        1216
-      ],
-      [
-        1219
-      ],
-      [
-        1335
-      ],
-      [
-        1338
-      ],
-      [
-        1341
-      ],
-      [
-        1344
-      ],
-      [
-        1347
-      ],
-      [
-        1463
-      ],
-      [
-        1466
-      ],
-      [
-        1469
-      ],
-      [
-        1472
-      ],
-      [
-        1475
-      ],
-      [
-        1511
-      ],
-      [
-        1514
-      ],
-      [
-        1517
-      ],
-      [
-        1520
-      ],
-      [
-        1523
-      ],
-      [
-        1527
-      ],
-      [
-        1530
-      ],
-      [
-        1533
-      ],
-      [
-        1536
-      ],
-      [
-        1539
-      ],
-      [
-        1559
-      ],
-      [
-        1562
-      ],
-      [
-        1565
-      ],
-      [
-        1568
-      ],
-      [
-        1571
-      ],
-      [
-        1575
-      ],
-      [
-        1578
-      ],
-      [
-        1581
-      ],
-      [
-        1584
-      ],
-      [
-        1587
-      ],
-      [
-        1607
-      ],
-      [
-        1610
-      ],
-      [
-        1613
-      ],
-      [
-        1616
-      ],
-      [
-        1619
-      ],
-      [
-        1623
-      ],
-      [
-        1626
-      ],
-      [
-        1629
-      ],
-      [
-        1632
-      ],
-      [
-        1635
-      ],
-      [
-        1639
-      ],
-      [
-        1642
-      ],
-      [
-        1645
-      ],
-      [
-        1648
-      ],
-      [
-        1651
-      ],
-      [
-        1687
-      ],
-      [
-        1690
-      ],
-      [
-        1693
-      ],
-      [
-        1696
-      ],
-      [
-        1699
-      ],
-      [
-        1751
-      ],
-      [
-        1754
-      ],
-      [
-        1757
-      ],
-      [
-        1760
-      ],
-      [
-        1763
-      ],
-      [
-        1767
-      ],
-      [
-        1770
-      ],
-      [
-        1773
-      ],
-      [
-        1776
-      ],
-      [
-        1779
-      ],
-      [
-        1783
-      ],
-      [
-        1786
-      ],
-      [
-        1789
-      ],
-      [
-        1792
-      ],
-      [
-        1795
-      ],
-      [
-        1799
-      ],
-      [
-        1802
-      ],
-      [
-        1805
-      ],
-      [
-        1808
-      ],
-      [
-        1811
-      ],
-      [
-        1922
-      ],
-      [
-        1925
-      ],
-      [
-        1928
-      ],
-      [
-        1931
-      ],
-      [
-        1934
-      ],
-      [
-        1970
-      ],
-      [
-        1973
-      ],
-      [
-        1976
-      ],
-      [
-        1979
-      ],
-      [
-        1982
-      ]
-    ]
-  },
-  {
-    "question": "What is the entity ID of the product with SKU 'WS12-M-Orange'?",
-    "answer": 1548,
-    "sql": "SELECT entity_id FROM catalog_product_entity WHERE sku = 'WS12-M-Orange';",
-    "sql_execute_result": [
-      [
-        1548
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve the base price including tax for the product with SKU 'WS08-XS-Blue'.",
-    "answer": "34.6400",
-    "sql": "SELECT base_price_incl_tax FROM sales_invoice_item WHERE sku = 'WS08-XS-Blue';",
-    "sql_execute_result": [
-      [
-        "34.6400"
-      ]
-    ]
-  },
-  {
-    "question": "How many countries have their ISO2 code in the sample data?",
-    "answer": 5,
-    "sql": "SELECT COUNT(*) FROM directory_country WHERE iso2_code IN ('TT', 'QA', 'IM', 'NU', 'CH');",
-    "sql_execute_result": [
-      [
-        5
-      ]
-    ]
-  },
-  {
-    "question": "What is the product type of the product with SKU 'MH06-L-Black'?",
-    "answer": "simple",
-    "sql": "SELECT type_id FROM catalog_product_entity WHERE sku = 'MH06-L-Black';",
-    "sql_execute_result": [
-      [
-        "simple"
-      ]
-    ]
-  },
-  {
-    "question": "Determine the attribute set ID of the product with SKU 'MJ10-L-Orange'.",
-    "answer": 9,
-    "sql": "SELECT attribute_set_id FROM catalog_product_entity WHERE sku = 'MJ10-L-Orange';",
-    "sql_execute_result": [
-      [
-        9
-      ]
-    ]
-  },
-  {
-    "question": "What is the price of the product with SKU 'aero-daily-fitness-tee-s-yellow'?",
-    "answer": "The price of the product with SKU 'aero-daily-fitness-tee-s-yellow' is 24.00.",
-    "sql": "SELECT value FROM catalog_product_entity_decimal WHERE entity_id = (SELECT entity_id FROM catalog_product_entity_varchar WHERE value = 'aero-daily-fitness-tee-s-yellow') AND attribute_id = 77;",
-    "sql_execute_result": [
-      [
-        "24.000000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the description of the product with ID 460.",
-    "answer": "<p>Pumping iron or dialing the track, you've got cool comfort on your side in our short-sleeve Helios EverCool&trade; Tee. The fabric is infused with moisture-wicking technology that pulls sweat off your skin for speedy evaporation. Stretchy fabric gussets encourage ventilation while increasing your range of motion.</p>\n<p>&bull; Teal quick dry tee.<br />&bull; Relaxed fit. <br />&bull; Crew neckline. <br />&bull; Machine wash/dry.</p>",
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 460 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>Pumping iron or dialing the track, you've got cool comfort on your side in our short-sleeve Helios EverCool&trade; Tee. The fabric is infused with moisture-wicking technology that pulls sweat off your skin for speedy evaporation. Stretchy fabric gussets encourage ventilation while increasing your range of motion.</p>\n<p>&bull; Teal quick dry tee.<br />&bull; Relaxed fit. <br />&bull; Crew neckline. <br />&bull; Machine wash/dry.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for the product 'Maxima Drawstring Short-29-Orange' in 2022?",
-    "answer": 2,
-    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_yearly WHERE product_name = 'Maxima Drawstring Short-29-Orange' AND period = '2022-01-01';",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ],
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the address of customer Sophia Young?",
-    "answer": "1 International Pl, Boston, Massachusetts, 02110",
-    "sql": "SELECT CONCAT(street, ', ', city, ', ', region, ', ', postcode) AS full_address FROM customer_address_entity WHERE firstname = 'Sophia' AND lastname = 'Young';",
-    "sql_execute_result": [
-      [
-        "1 International Pl, Boston, Massachusetts, 02110"
-      ]
-    ]
-  },
-  {
-    "question": "What is the price of the product with entity ID 1532?",
-    "answer": "The price of the product with entity ID 1532 is 32.00.",
-    "sql": "SELECT value FROM catalog_product_entity_decimal WHERE entity_id = 1532 AND attribute_id = 77;",
-    "sql_execute_result": [
-      [
-        "32.000000"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders for products purchased in store with ID 1 during 2023 were found?",
-    "answer": 141,
-    "sql": "SELECT product_id, product_name, qty_ordered FROM sales_bestsellers_aggregated_yearly WHERE store_id = 1 AND period = '2023-01-01';",
-    "sql_execute_result": [
-      [
-        3,
-        "Crown Summit Backpack",
-        "1.0000"
-      ],
-      [
-        7,
-        "Impulse Duffle",
-        "2.0000"
-      ],
-      [
-        11,
-        "Endeavor Daytrip Backpack",
-        "1.0000"
-      ],
-      [
-        13,
-        "Overnight Duffle",
-        "3.0000"
-      ],
-      [
-        16,
-        "Dual Handle Cardio Ball",
-        "1.0000"
-      ],
-      [
-        20,
-        "Quest Lumaflex&trade; Band",
-        "1.0000"
-      ],
-      [
-        23,
-        "Harmony Lumaflex&trade; Strength Band Kit ",
-        "1.0000"
-      ],
-      [
-        25,
-        "Sprite Stasis Ball 55 cm",
-        "1.0000"
-      ],
-      [
-        26,
-        "Sprite Stasis Ball 55 cm",
-        "1.0000"
-      ],
-      [
-        27,
-        "Sprite Stasis Ball 65 cm",
-        "1.0000"
-      ],
-      [
-        28,
-        "Sprite Stasis Ball 65 cm",
-        "2.0000"
-      ],
-      [
-        29,
-        "Sprite Stasis Ball 65 cm",
-        "2.0000"
-      ],
-      [
-        30,
-        "Sprite Stasis Ball 75 cm",
-        "1.0000"
-      ],
-      [
-        33,
-        "Sprite Yoga Strap 6 foot",
-        "4.0000"
-      ],
-      [
-        34,
-        "Sprite Yoga Strap 8 foot",
-        "2.0000"
-      ],
-      [
-        36,
-        "Aim Analog Watch",
-        "2.0000"
-      ],
-      [
-        37,
-        "Endurance Watch",
-        "1.0000"
-      ],
-      [
-        47,
-        "Chaz Kangeroo Hoodie-XS-Black",
-        "1.0000"
-      ],
-      [
-        50,
-        "Chaz Kangeroo Hoodie-S-Black",
-        "1.0000"
-      ],
-      [
-        88,
-        "Bruno Compete Hoodie-L-Black",
-        "1.0000"
-      ],
-      [
-        95,
-        "Frankie  Sweatshirt-XS-Green",
-        "1.0000"
-      ],
-      [
-        127,
-        "Stark Fundamental Hoodie-XS-Black",
-        "1.0000"
-      ],
-      [
-        128,
-        "Stark Fundamental Hoodie-XS-Blue",
-        "1.0000"
-      ],
-      [
-        129,
-        "Stark Fundamental Hoodie-XS-Purple",
-        "1.0000"
-      ],
-      [
-        134,
-        "Stark Fundamental Hoodie-M-Blue",
-        "1.0000"
-      ],
-      [
-        204,
-        "Mach Street Sweatshirt -XL-Blue",
-        "2.0000"
-      ],
-      [
-        220,
-        "Grayson Crewneck Sweatshirt -XL-Red",
-        "1.0000"
-      ],
-      [
-        234,
-        "Ajax Full-Zip Sweatshirt -L-Red",
-        "1.0000"
-      ],
-      [
-        243,
-        "Marco Lightweight Active Hoodie-S-Green",
-        "1.0000"
-      ],
-      [
-        262,
-        "Beaumont Summit Kit-M-Red",
-        "1.0000"
-      ],
-      [
-        315,
-        "Orion Two-Tone Fitted Jacket-XL-Black",
-        "1.0000"
-      ],
-      [
-        336,
-        "Taurus Elements Shell-XS-White",
-        "1.0000"
-      ],
-      [
-        351,
-        "Mars HeatTech&trade; Pullover-XS-Black",
-        "1.0000"
-      ],
-      [
-        388,
-        "Jupiter All-Weather Trainer -S-Purple",
-        "1.0000"
-      ],
-      [
-        421,
-        "Proteus Fitness Jackshirt-M-Black",
-        "1.0000"
-      ],
-      [
-        422,
-        "Proteus Fitness Jackshirt-M-Blue",
-        "1.0000"
-      ],
-      [
-        432,
-        "Gobi HeatTec&reg; Tee-XS-Orange",
-        "2.0000"
-      ],
-      [
-        546,
-        "Aero Daily Fitness Tee-S-Black",
-        "1.0000"
-      ],
-      [
-        586,
-        "Logan  HeatTec&reg; Tee-L-Red",
-        "1.0000"
-      ],
-      [
-        601,
-        "Deion Long-Sleeve EverCool&trade; Tee-L-Green",
-        "1.0000"
-      ],
-      [
-        603,
-        "Deion Long-Sleeve EverCool&trade; Tee-XL-Black",
-        "1.0000"
-      ],
-      [
-        645,
-        "Tristan Endurance Tank-M-Gray",
-        "1.0000"
-      ],
-      [
-        652,
-        "Tristan Endurance Tank-XL-Red",
-        "1.0000"
-      ],
-      [
-        662,
-        "Primo Endurance Tank-M-Red",
-        "1.0000"
-      ],
-      [
-        691,
-        "Argus All-Weather Tank-M-Gray",
-        "1.0000"
-      ],
-      [
-        699,
-        "Sparta Gym Tank-XL-Green",
-        "2.0000"
-      ],
-      [
-        709,
-        "Tiberius Gym Tank-M-Yellow",
-        "1.0000"
-      ],
-      [
-        716,
-        "Atlas Fitness Tank-L-Blue",
-        "1.0000"
-      ],
-      [
-        726,
-        "Caesar Warm-Up Pant-32-Gray",
-        "1.0000"
-      ],
-      [
-        736,
-        "Caesar Warm-Up Pant-36-Purple",
-        "1.0000"
-      ],
-      [
-        758,
-        "Geo Insulated Jogging Pant-34-Green",
-        "1.0000"
-      ],
-      [
-        764,
-        "Supernova Sport Pant-32-Black",
-        "1.0000"
-      ],
-      [
-        790,
-        "Mithra Warmup Pant-32-Gray",
-        "1.0000"
-      ],
-      [
-        796,
-        "Mithra Warmup Pant-34-Gray",
-        "1.0000"
-      ],
-      [
-        801,
-        "Mithra Warmup Pant-36-Orange",
-        "1.0000"
-      ],
-      [
-        804,
-        "Thorpe Track Pant-32-Blue",
-        "1.0000"
-      ],
-      [
-        805,
-        "Thorpe Track Pant-32-Purple",
-        "1.0000"
-      ],
-      [
-        824,
-        "Zeppelin Yoga Pant-34-Red",
-        "1.0000"
-      ],
-      [
-        850,
-        "Orestes Yoga Pant -34-Green",
-        "1.0000"
-      ],
-      [
-        859,
-        "Aether Gym Pant -33-Brown",
-        "1.0000"
-      ],
-      [
-        863,
-        "Aether Gym Pant -34-Green",
-        "1.0000"
-      ],
-      [
-        865,
-        "Aether Gym Pant -36-Brown",
-        "1.0000"
-      ],
-      [
-        883,
-        "Cobalt CoolTech&trade; Fitness Short-32-Red",
-        "1.0000"
-      ],
-      [
-        895,
-        "Apollo Running Short-33-Black",
-        "1.0000"
-      ],
-      [
-        926,
-        "Hawkeye Yoga Short-32-Blue",
-        "2.0000"
-      ],
-      [
-        936,
-        "Hawkeye Yoga Short-36-Gray",
-        "2.0000"
-      ],
-      [
-        948,
-        "Lono Yoga Short-36-Gray",
-        "1.0000"
-      ],
-      [
-        961,
-        "Rapha  Sports Short-36-Blue",
-        "1.0000"
-      ],
-      [
-        977,
-        "Troy Yoga Short-32-Black",
-        "1.0000"
-      ],
-      [
-        986,
-        "Troy Yoga Short-36-Black",
-        "1.0000"
-      ],
-      [
-        1007,
-        "Arcadio Gym Short-33-Blue",
-        "1.0000"
-      ],
-      [
-        1014,
-        "Arcadio Gym Short-36-Red",
-        "1.0000"
-      ],
-      [
-        1033,
-        "Mona Pullover Hoodlie-S-Orange",
-        "1.0000"
-      ],
-      [
-        1040,
-        "Mona Pullover Hoodlie-L-Purple",
-        "1.0000"
-      ],
-      [
-        1063,
-        "Autumn Pullie-XS-Red",
-        "1.0000"
-      ],
-      [
-        1064,
-        "Autumn Pullie-S-Green",
-        "1.0000"
-      ],
-      [
-        1175,
-        "Helena Hooded Fleece-XL-Blue",
-        "1.0000"
-      ],
-      [
-        1182,
-        "Eos V-Neck Hoodie-S-Blue",
-        "1.0000"
-      ],
-      [
-        1202,
-        "Circe Hooded Ice Fleece-M-Green",
-        "1.0000"
-      ],
-      [
-        1219,
-        "Stellar Solar Jacket-L-Yellow",
-        "1.0000"
-      ],
-      [
-        1222,
-        "Josie Yoga Jacket-XS-Blue",
-        "1.0000"
-      ],
-      [
-        1225,
-        "Josie Yoga Jacket-S-Blue",
-        "1.0000"
-      ],
-      [
-        1240,
-        "Augusta Pullover Jacket-S-Blue",
-        "1.0000"
-      ],
-      [
-        1243,
-        "Augusta Pullover Jacket-M-Blue",
-        "1.0000"
-      ],
-      [
-        1254,
-        "Ingrid Running Jacket-XS-Red",
-        "1.0000"
-      ],
-      [
-        1255,
-        "Ingrid Running Jacket-XS-White",
-        "1.0000"
-      ],
-      [
-        1271,
-        "Riona Full Zip Jacket-XS-Red",
-        "1.0000"
-      ],
-      [
-        1283,
-        "Riona Full Zip Jacket-XL-Red",
-        "1.0000"
-      ],
-      [
-        1299,
-        "Inez Full Zip Jacket-XL-Red",
-        "1.0000"
-      ],
-      [
-        1329,
-        "Jade Yoga Jacket-XL-Blue",
-        "1.0000"
-      ],
-      [
-        1335,
-        "Nadia Elements Shell-XS-Yellow",
-        "1.0000"
-      ],
-      [
-        1336,
-        "Nadia Elements Shell-S-Black",
-        "1.0000"
-      ],
-      [
-        1340,
-        "Nadia Elements Shell-M-Orange",
-        "1.0000"
-      ],
-      [
-        1351,
-        "Neve Studio Dance Jacket-XS-Orange",
-        "1.0000"
-      ],
-      [
-        1354,
-        "Neve Studio Dance Jacket-S-Orange",
-        "1.0000"
-      ],
-      [
-        1355,
-        "Neve Studio Dance Jacket-M-Black",
-        "1.0000"
-      ],
-      [
-        1365,
-        "Juno Jacket-XS-Blue",
-        "1.0000"
-      ],
-      [
-        1407,
-        "Gabrielle Micro Sleeve Top-L-Green",
-        "1.0000"
-      ],
-      [
-        1424,
-        "Iris Workout Top-L-Red",
-        "1.0000"
-      ],
-      [
-        1430,
-        "Layla Tee-XS-Green",
-        "2.0000"
-      ],
-      [
-        1468,
-        "Juliana Short-Sleeve Tee-M-White",
-        "1.0000"
-      ],
-      [
-        1473,
-        "Juliana Short-Sleeve Tee-XL-Black",
-        "1.0000"
-      ],
-      [
-        1479,
-        "Minerva LumaTech&trade; V-Tee-XS-Red",
-        "2.0000"
-      ],
-      [
-        1483,
-        "Minerva LumaTech&trade; V-Tee-M-Black",
-        "1.0000"
-      ],
-      [
-        1500,
-        "Tiffany Fitness Tee-M-Red",
-        "1.0000"
-      ],
-      [
-        1505,
-        "Tiffany Fitness Tee-XL-Blue",
-        "1.0000"
-      ],
-      [
-        1568,
-        "Gwyn Endurance Tee-L-Yellow",
-        "1.0000"
-      ],
-      [
-        1607,
-        "Erica Evercool Sports Bra-XS-Yellow",
-        "1.0000"
-      ],
-      [
-        1631,
-        "Celeste Sports Bra-L-Red",
-        "1.0000"
-      ],
-      [
-        1644,
-        "Prima Compete Bra Top-M-Purple",
-        "1.0000"
-      ],
-      [
-        1681,
-        "Bella Tank-XL-Black",
-        "1.0000"
-      ],
-      [
-        1685,
-        "Zoe Tank-XS-Green",
-        "1.0000"
-      ],
-      [
-        1690,
-        "Zoe Tank-S-Yellow",
-        "1.0000"
-      ],
-      [
-        1695,
-        "Zoe Tank-L-Orange",
-        "1.0000"
-      ],
-      [
-        1699,
-        "Zoe Tank-XL-Yellow",
-        "1.0000"
-      ],
-      [
-        1757,
-        "Chloe Compete Tank-M-Yellow",
-        "1.0000"
-      ],
-      [
-        1818,
-        "Karmen Yoga Pant-29-White",
-        "1.0000"
-      ],
-      [
-        1828,
-        "Ida Workout Parachute Pant-28-Blue",
-        "1.0000"
-      ],
-      [
-        1832,
-        "Ida Workout Parachute Pant-29-Purple",
-        "3.0000"
-      ],
-      [
-        1836,
-        "Cora Parachute Pant-28-White",
-        "1.0000"
-      ],
-      [
-        1838,
-        "Cora Parachute Pant-29-Blue",
-        "1.0000"
-      ],
-      [
-        1849,
-        "Diana Tights-28-Blue",
-        "1.0000"
-      ],
-      [
-        1855,
-        "Aeon Capri-28-Black",
-        "1.0000"
-      ],
-      [
-        1859,
-        "Aeon Capri-29-Blue",
-        "1.0000"
-      ],
-      [
-        1885,
-        "Sylvia Capri-28-Red",
-        "1.0000"
-      ],
-      [
-        1905,
-        "Fiona Fitness Short-28-Green",
-        "1.0000"
-      ],
-      [
-        1906,
-        "Fiona Fitness Short-28-Red",
-        "1.0000"
-      ],
-      [
-        1910,
-        "Fiona Fitness Short-30-Black",
-        "1.0000"
-      ],
-      [
-        1913,
-        "Fiona Fitness Short-31-Black",
-        "1.0000"
-      ],
-      [
-        1922,
-        "Maxima Drawstring Short-28-Yellow",
-        "1.0000"
-      ],
-      [
-        1932,
-        "Maxima Drawstring Short-32-Gray",
-        "1.0000"
-      ],
-      [
-        1938,
-        "Gwen Drawstring Bike Short-28-Orange",
-        "1.0000"
-      ],
-      [
-        1941,
-        "Gwen Drawstring Bike Short-29-Orange",
-        "1.0000"
-      ],
-      [
-        1958,
-        "Artemis Running Short-30-Black",
-        "1.0000"
-      ],
-      [
-        1988,
-        "Angel Light Running Short-29-Orange",
-        "1.0000"
-      ],
-      [
-        1989,
-        "Angel Light Running Short-29-Purple",
-        "2.0000"
-      ],
-      [
-        1993,
-        "Echo Fit Compression Short-28-Purple",
-        "1.0000"
-      ],
-      [
-        1995,
-        "Echo Fit Compression Short-29-Blue",
-        "1.0000"
-      ],
-      [
-        2022,
-        "Ina Compression Short-29-Orange",
-        "1.0000"
-      ],
-      [
-        2023,
-        "Ina Compression Short-29-Red",
-        "1.0000"
-      ],
-      [
-        2038,
-        "Erika Running Short-32-Purple",
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the full name and phone number of the customer living at 789 Main St, Dallas?",
-    "answer": {
-      "full_name": "John Smith",
-      "telephone": "2145551212"
-    },
-    "sql": "SELECT CONCAT(firstname, ' ', lastname) AS full_name, telephone FROM customer_address_entity WHERE street = '789 Main St' AND city = 'Dallas';",
-    "sql_execute_result": [
-      [
-        "John Smith",
-        "2145551212"
-      ]
-    ]
-  },
-  {
-    "question": "Find the entity ID for the product named 'Hollister Backyard Sweatshirt-XL-Green'.",
-    "answer": 123,
-    "sql": "SELECT entity_id FROM catalog_product_entity_varchar WHERE value = 'Hollister Backyard Sweatshirt-XL-Green';",
-    "sql_execute_result": [
-      [
-        123
-      ]
-    ]
-  },
-  {
-    "question": "What is the attribute code for the attribute with ID 33?",
-    "answer": "postcode",
-    "sql": "SELECT attribute_code FROM eav_attribute WHERE attribute_id = 33;",
-    "sql_execute_result": [
-      [
-        "postcode"
-      ]
-    ]
-  },
-  {
-    "question": "How many search results are there for the query 'Antonia Racer Tank'?",
-    "answer": 23,
-    "sql": "SELECT num_results FROM search_query WHERE query_text = 'Antonia Racer Tank';",
-    "sql_execute_result": [
-      [
-        23
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the store group with ID 0?",
-    "answer": "Default",
-    "sql": "SELECT name FROM store_group WHERE group_id = 0;",
-    "sql_execute_result": [
-      [
-        "Default"
-      ]
-    ]
-  },
-  {
-    "question": "What is the stock name for stock ID 1?",
-    "answer": "Default",
-    "sql": "SELECT stock_name FROM cataloginventory_stock WHERE stock_id = 1;",
-    "sql_execute_result": [
-      [
-        "Default"
-      ]
-    ]
-  },
-  {
-    "question": "Is the search query 'nike' active?",
-    "answer": "Yes, the search query 'nike' is active.",
-    "sql": "SELECT is_active FROM search_query WHERE query_text = 'nike';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the website ID of the main website store group?",
-    "answer": 1,
-    "sql": "SELECT website_id FROM store_group WHERE name = 'Main Website Store';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the popularity of the search query 'hollister'?",
-    "answer": 19,
-    "sql": "SELECT popularity FROM search_query WHERE query_text = 'hollister';",
-    "sql_execute_result": [
-      [
-        19
-      ]
-    ]
-  },
-  {
-    "question": "Find the default store ID for the store group named 'Main Website Store'.",
-    "answer": 1,
-    "sql": "SELECT default_store_id FROM store_group WHERE name = 'Main Website Store';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the email address for customer with the billing address '6146 Honey Bluff Parkway, Calder, Michigan, 49628-7978'.",
-    "answer": "The email address for the customer with the specified billing address is 'roni_cost@example.com'.",
-    "sql": "SELECT customer_email FROM sales_order_grid WHERE billing_address = '6146 Honey Bluff Parkway,Calder,Michigan,49628-7978';",
-    "sql_execute_result": [
-      [
-        "roni_cost@example.com"
-      ],
-      [
-        "roni_cost@example.com"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU of the product with entity_id 2040?",
-    "answer": "The SKU of the product with entity_id 2040 is WSH12.",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 2040;",
-    "sql_execute_result": [
-      [
-        "WSH12"
-      ]
-    ]
-  },
-  {
-    "question": "How many children does the category with ID 29 have?",
-    "answer": 4,
-    "sql": "SELECT children_count FROM catalog_category_entity WHERE entity_id = 29;",
-    "sql_execute_result": [
-      [
-        4
-      ]
-    ]
-  },
-  {
-    "question": "List all order IDs for the customer with email 'roni_cost@example.com'.",
-    "answer": [
-      1,
-      2
-    ],
-    "sql": "SELECT entity_id FROM sales_order WHERE customer_email = 'roni_cost@example.com';",
-    "sql_execute_result": [
-      [
-        1
-      ],
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity of products ordered in order with increment ID '000000002'?",
-    "answer": "The total quantity of products ordered in order with increment ID '000000002' is 1.0000.",
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE increment_id = '000000002';",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the grand total of the invoice with entity_id 2?",
-    "answer": "The grand total of the invoice with entity_id 2 is 39.6400.",
-    "sql": "SELECT grand_total FROM sales_invoice WHERE entity_id = 2;",
-    "sql_execute_result": [
-      [
-        "39.6400"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were placed on '2023-04-19'?",
-    "answer": 9,
-    "sql": "SELECT COUNT(*) FROM sales_order WHERE DATE(created_at) = '2023-04-19';",
-    "sql_execute_result": [
-      [
-        9
-      ]
-    ]
-  },
-  {
-    "question": "Which region does 'Burtnieku novads' belong to?",
-    "answer": "The region 'Burtnieku novads' belongs to the locale 'en_US'.",
-    "sql": "SELECT locale FROM directory_country_region_name WHERE name = 'Burtnieku novads';",
-    "sql_execute_result": [
-      [
-        "en_US"
-      ]
-    ]
-  },
-  {
-    "question": "What is the subtotal of the order with entity_id 1?",
-    "answer": "The subtotal of the order with entity_id 1 is 29.0000.",
-    "sql": "SELECT subtotal FROM sales_order WHERE entity_id = 1;",
-    "sql_execute_result": [
-      [
-        "29.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status label for the 'fraud' status?",
-    "answer": "Suspected Fraud",
-    "sql": "SELECT label FROM sales_order_status WHERE status = 'fraud';",
-    "sql_execute_result": [
-      [
-        "Suspected Fraud"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence value for the latest order in store 1.",
-    "answer": 308,
-    "sql": "SELECT MAX(sequence_value) FROM sequence_order_1;",
-    "sql_execute_result": [
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the default stock available on website 0?",
-    "answer": "Default",
-    "sql": "SELECT stock_name FROM cataloginventory_stock WHERE website_id = 0 AND stock_id = 1;",
-    "sql_execute_result": [
-      [
-        "Default"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders have a status of 'pending_payment'?",
-    "answer": 0,
-    "sql": "SELECT COUNT(*) FROM sales_order WHERE status = 'pending_payment';",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve the sequence table associated with the creditmemo entity type in store 1.",
-    "answer": "The sequence table associated with the creditmemo entity type in store 1 is 'sequence_creditmemo_1'.",
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE entity_type = 'creditmemo' AND store_id = 1;",
-    "sql_execute_result": [
-      [
-        "sequence_creditmemo_1"
-      ]
-    ]
-  },
-  {
-    "question": "What is the sequence value for the first invoice in store 1?",
-    "answer": 1,
-    "sql": "SELECT MIN(sequence_value) FROM sequence_invoice_1;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "How many status labels for sales orders were found?",
-    "answer": 12,
-    "sql": "SELECT label FROM sales_order_status;",
-    "sql_execute_result": [
-      [
-        "Canceled"
-      ],
-      [
-        "Closed"
-      ],
-      [
-        "Complete"
-      ],
-      [
-        "Suspected Fraud"
-      ],
-      [
-        "On Hold"
-      ],
-      [
-        "Payment Review"
-      ],
-      [
-        "PayPal Canceled Reversal"
-      ],
-      [
-        "PayPal Reversed"
-      ],
-      [
-        "Pending"
-      ],
-      [
-        "Pending Payment"
-      ],
-      [
-        "Pending PayPal"
-      ],
-      [
-        "Processing"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence table used for orders in store 0.",
-    "answer": "The sequence table used for orders in store 0 is 'sequence_order_0'.",
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE entity_type = 'order' AND store_id = 0;",
-    "sql_execute_result": [
-      [
-        "sequence_order_0"
-      ]
-    ]
-  },
-  {
-    "question": "What is the sequence value for the last invoice in store 1?",
-    "answer": 2,
-    "sql": "SELECT MAX(sequence_value) FROM sequence_invoice_1;",
-    "sql_execute_result": [
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "Which store uses the sequence table 'sequence_shipment_1'?",
-    "answer": 1,
-    "sql": "SELECT store_id FROM sales_sequence_meta WHERE sequence_table = 'sequence_shipment_1';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the product name and price for the best-selling product with ID 848 in 2022?",
-    "answer": [
-      {
-        "product_name": "Orestes Yoga Pant -34-Black",
-        "product_price": "52.8000"
-      }
-    ],
-    "sql": "SELECT product_name, product_price FROM sales_bestsellers_aggregated_yearly WHERE product_id = 848 AND period = '2022-01-01';",
-    "sql_execute_result": [
-      [
-        "Orestes Yoga Pant -34-Black",
-        "52.8000"
-      ],
-      [
-        "Orestes Yoga Pant -34-Black",
-        "52.8000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity ordered for the canceled order with increment ID 000000291?",
-    "answer": "The total quantity ordered for the canceled order with increment ID 000000291 is 1.0000.",
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE increment_id = '000000291' AND status = 'canceled';",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the store code for the store group with group ID 1.",
-    "answer": "The store code for the store group with group ID 1 is 'main_website_store'.",
-    "sql": "SELECT code FROM store_group WHERE group_id = 1;",
-    "sql_execute_result": [
-      [
-        "main_website_store"
-      ]
-    ]
-  },
-  {
-    "question": "What is the description of the product with entity ID 992?",
-    "answer": "The description of the product with entity ID 992 is: <p>You'll let your fear go and push your limits in your new Sol Active Short. Featuring ultra-breathable performance fabric and a flat comfort-fit waistband, the Sol Active Short is perfect for high-intensity circuits or high-heat bikram.</p>\n<p>&bull; Light blue jersey shorts with mesh detail.<br />&bull; 87% Spandex 13% Lycra.<br />&bull; Machine wash cold, tumble dry low.<br />&bull; Superior performance fabric.<br />&bull; Flat-lock seams.</p>",
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 992 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>You'll let your fear go and push your limits in your new Sol Active Short. Featuring ultra-breathable performance fabric and a flat comfort-fit waistband, the Sol Active Short is perfect for high-intensity circuits or high-heat bikram.</p>\n<p>&bull; Light blue jersey shorts with mesh detail.<br />&bull; 87% Spandex 13% Lycra.<br />&bull; Machine wash cold, tumble dry low.<br />&bull; Superior performance fabric.<br />&bull; Flat-lock seams.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were completed on April 5, 2023?",
-    "answer": 3,
-    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE period = '2023-04-05' AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        3
-      ],
-      [
-        3
-      ]
-    ]
-  },
-  {
-    "question": "How many total income amounts were found?",
-    "answer": 2,
-    "sql": "SELECT total_income_amount FROM sales_order_aggregated_created WHERE period = '2022-01-31' AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        "176.6000"
-      ],
-      [
-        "176.6000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the customer email and first name for the order with increment ID 000000065.",
-    "answer": {
-      "customer_email": "avidreader99@yahoo.com",
-      "customer_firstname": "Grace"
-    },
-    "sql": "SELECT customer_email, customer_firstname FROM sales_order WHERE increment_id = '000000065';",
-    "sql_execute_result": [
-      [
-        "avidreader99@yahoo.com",
-        "Grace"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total shipping amount for canceled orders on February 18, 2022?",
-    "answer": "The total shipping amount for canceled orders on February 18, 2022, is 10.0000.",
-    "sql": "SELECT total_shipping_amount FROM sales_order_aggregated_created WHERE period = '2022-02-18' AND order_status = 'canceled';",
-    "sql_execute_result": [
-      [
-        "5.0000"
-      ],
-      [
-        "5.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total quantity ordered for product with ID 39 in 2022.",
-    "answer": "The total quantity ordered for product with ID 39 in 2022 is 8.",
-    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_yearly WHERE product_id = 39 AND period = '2022-01-01';",
-    "sql_execute_result": [
-      [
-        "4.0000"
-      ],
-      [
-        "4.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What are the applied rule IDs for the complete order with increment ID 000000028?",
-    "answer": "The applied rule IDs for the complete order with increment ID 000000028 are 1, 2, and 3.",
-    "sql": "SELECT applied_rule_ids FROM sales_order WHERE increment_id = '000000028' AND status = 'complete';",
-    "sql_execute_result": [
-      [
-        "1,2,3"
-      ]
-    ]
-  },
-  {
-    "question": "What is the payment method used for the order with parent_id 203?",
-    "answer": "Check / Money order",
-    "sql": "SELECT additional_information FROM sales_order_payment WHERE parent_id = 203;",
-    "sql_execute_result": [
-      [
-        "{\"method_title\":\"Check \\/ Money order\"}"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU of the product that has entity_id 948?",
-    "answer": "The SKU of the product with entity_id 948 is MSH06-36-Gray.",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 948;",
-    "sql_execute_result": [
-      [
-        "MSH06-36-Gray"
-      ]
-    ]
-  },
-  {
-    "question": "Find the product name with product_id 865 from the bestsellers aggregated yearly table for the period 2023-01-01.",
-    "answer": "The product name with product_id 865 for the period 2023-01-01 is 'Aether Gym Pant -36-Brown'.",
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_yearly WHERE product_id = 865 AND period = '2023-01-01';",
-    "sql_execute_result": [
-      [
-        "Aether Gym Pant -36-Brown"
-      ],
-      [
-        "Aether Gym Pant -36-Brown"
-      ]
-    ]
-  },
-  {
-    "question": "What is the current stock quantity for the product with product_id 2040?",
-    "answer": "The current stock quantity for the product with product_id 2040 is 0.",
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 2040;",
-    "sql_execute_result": [
-      [
-        "0.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Get the total number of orders with status 'pending'.",
-    "answer": 10,
-    "sql": "SELECT COUNT(*) FROM sales_order WHERE status = 'pending';",
-    "sql_execute_result": [
-      [
-        10
-      ]
-    ]
-  },
-  {
-    "question": "What is the current stock quantity for the product with ID 2040?",
-    "answer": "The current stock quantity for the product with ID 2040 is 0.",
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 2040;",
-    "sql_execute_result": [
-      [
-        "0.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU for the product with entity_id 2040?",
-    "answer": "The SKU for the product with entity_id 2040 is WSH12.",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 2040;",
-    "sql_execute_result": [
-      [
-        "WSH12"
-      ]
-    ]
-  },
-  {
-    "question": "How many products are associated with category ID 258?",
-    "answer": 0,
-    "sql": "SELECT COUNT(*) FROM catalog_category_product WHERE category_id = 258;",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the average product price in the sales_bestsellers_aggregated_monthly table for store_id 0?",
-    "answer": 41.31,
-    "sql": "SELECT AVG(product_price) FROM sales_bestsellers_aggregated_monthly WHERE store_id = 0;",
-    "sql_execute_result": [
-      [
-        "41.31182556"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU of the product with entity ID 1013?",
-    "answer": "MSH11-36-Blue",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 1013;",
-    "sql_execute_result": [
-      [
-        "MSH11-36-Blue"
-      ]
-    ]
-  },
-  {
-    "question": "How many results were returned for the search query 'hollister'?",
-    "answer": 1,
-    "sql": "SELECT num_results FROM search_query WHERE query_text = 'hollister';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the customer with customer ID 5?",
-    "answer": "Sarah Miller",
-    "sql": "SELECT CONCAT(firstname, ' ', lastname) AS name FROM customer_entity WHERE entity_id = 5;",
-    "sql_execute_result": [
-      [
-        "Sarah Miller"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total stock quantity for product ID 143?",
-    "answer": "The total stock quantity for product ID 143 is 100.",
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 143;",
-    "sql_execute_result": [
-      [
-        "100.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the category path for the category with entity ID 29?",
-    "answer": "The category path for the category with entity ID 29 is '1/2/29'.",
-    "sql": "SELECT path FROM catalog_category_entity WHERE entity_id = 29;",
-    "sql_execute_result": [
-      [
-        "1/2/29"
-      ]
-    ]
-  },
-  {
-    "question": "What is the base price of the product with entity ID 918?",
-    "answer": "The base price of the product with entity ID 918 is 32.50.",
-    "sql": "SELECT value FROM catalog_product_entity_decimal WHERE entity_id = 918 AND attribute_id = 77;",
-    "sql_execute_result": [
-      [
-        "32.500000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address of the customer with entity ID 3?",
-    "answer": "jane.doe@hotmail.com",
-    "sql": "SELECT email FROM customer_entity WHERE entity_id = 3;",
-    "sql_execute_result": [
-      [
-        "jane.doe@hotmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU of the product with entity_id 1536?",
-    "answer": "The SKU of the product with entity_id 1536 is WS11-L-Yellow.",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 1536;",
-    "sql_execute_result": [
-      [
-        "WS11-L-Yellow"
-      ]
-    ]
-  },
-  {
-    "question": "Find the email address associated with the order having address entity_id 389.",
-    "answer": "lisa.kim@gmail.com",
-    "sql": "SELECT email FROM sales_order_address WHERE entity_id = 389;",
-    "sql_execute_result": [
-      [
-        "lisa.kim@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "What is the product name of the bestseller item with product_id 1980 in the year 2022?",
-    "answer": "Bess Yoga Short-32-Blue",
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_yearly WHERE product_id = 1980 AND period = '2022-01-01';",
-    "sql_execute_result": [
-      [
-        "Bess Yoga Short-32-Blue"
-      ],
-      [
-        "Bess Yoga Short-32-Blue"
-      ]
-    ]
-  },
-  {
-    "question": "What is the value associated with the option having option_id 114?",
-    "answer": "Track Pants",
-    "sql": "SELECT value FROM eav_attribute_option_value WHERE option_id = 114;",
-    "sql_execute_result": [
-      [
-        "Track Pants"
-      ]
-    ]
-  },
-  {
-    "question": "What is the street address for the shipping address with entity_id 299?",
-    "answer": "789 Rodeo Drive",
-    "sql": "SELECT street FROM sales_order_address WHERE entity_id = 299;",
-    "sql_execute_result": [
-      [
-        "789 Rodeo Drive"
-      ]
-    ]
-  },
-  {
-    "question": "What is the rating position of the product 'Kratos Gym Pant-32-Green' for the year 2022?",
-    "answer": [
-      93,
-      214
-    ],
-    "sql": "SELECT rating_pos FROM sales_bestsellers_aggregated_yearly WHERE product_name = 'Kratos Gym Pant-32-Green' AND period = '2022-01-01';",
-    "sql_execute_result": [
-      [
-        93
-      ],
-      [
-        214
-      ]
-    ]
-  },
-  {
-    "question": "What is the first name associated with the billing address having entity_id 322?",
-    "answer": "Samantha",
-    "sql": "SELECT firstname FROM sales_order_address WHERE entity_id = 322;",
-    "sql_execute_result": [
-      [
-        "Samantha"
-      ]
-    ]
-  },
-  {
-    "question": "Find the SKU of the product with entity_id 1268.",
-    "answer": "WJ04",
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 1268;",
-    "sql_execute_result": [
-      [
-        "WJ04"
-      ]
-    ]
-  },
-  {
-    "question": "What is the created timestamp for the product with SKU 'MJ07-XS-Black'?",
-    "answer": "The created timestamp for the product with SKU 'MJ07-XS-Black' is 2023-04-19 16:13:28.",
-    "sql": "SELECT created_at FROM catalog_product_entity WHERE sku = 'MJ07-XS-Black';",
-    "sql_execute_result": [
-      [
-        "2023-04-19 16:13:28"
-      ]
-    ]
-  },
-  {
-    "question": "What is the postal code for the address with entity_id 346?",
-    "answer": "10001",
-    "sql": "SELECT postcode FROM sales_order_address WHERE entity_id = 346;",
-    "sql_execute_result": [
-      [
-        "10001"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status code for the review status with ID 3?",
-    "answer": "Not Approved",
-    "sql": "SELECT status_code FROM review_status WHERE status_id = 3;",
-    "sql_execute_result": [
-      [
-        "Not Approved"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were canceled on 2022-11-22?",
-    "answer": 2,
-    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE period = '2022-11-22' AND order_status = 'canceled';",
-    "sql_execute_result": [
-      [
-        1
-      ],
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the default name for the region with the code 'VE-D'.",
-    "answer": "Aragua",
-    "sql": "SELECT default_name FROM directory_country_region WHERE code = 'VE-D';",
-    "sql_execute_result": [
-      [
-        "Aragua"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total income amount for store ID 1 on 2022-07-01?",
-    "answer": "The total income amount for store ID 1 on 2022-07-01 is 168.8000.",
-    "sql": "SELECT total_income_amount FROM sales_order_aggregated_created WHERE period = '2022-07-01' AND store_id = 1;",
-    "sql_execute_result": [
-      [
-        "168.8000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the frontend label for the attribute with the code 'performance_fabric'?",
-    "answer": "Performance Fabric",
-    "sql": "SELECT frontend_label FROM eav_attribute WHERE attribute_code = 'performance_fabric';",
-    "sql_execute_result": [
-      [
-        "Performance Fabric"
-      ]
-    ]
-  },
-  {
-    "question": "What is the price value for the product with entity ID 1489?",
-    "answer": "The price value for the product with entity ID 1489 is 32.00.",
-    "sql": "SELECT value FROM catalog_product_entity_decimal WHERE entity_id = 1489 AND attribute_id = 77;",
-    "sql_execute_result": [
-      [
-        "32.000000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the attribute code for the attribute with ID 46?",
-    "answer": "The attribute code for the attribute with ID 46 is 'is_active'.",
-    "sql": "SELECT attribute_code FROM eav_attribute WHERE attribute_id = 46;",
-    "sql_execute_result": [
-      [
-        "is_active"
-      ]
-    ]
-  },
-  {
-    "question": "Which country has the region code 'BG-23'?",
-    "answer": "The country with the region code 'BG-23' is BG.",
-    "sql": "SELECT country_id FROM directory_country_region WHERE code = 'BG-23';",
-    "sql_execute_result": [
-      [
-        "BG"
-      ]
-    ]
-  },
-  {
-    "question": "What is the frontend input type for the attribute with the code 'price_type'?",
-    "answer": "The frontend input type for the attribute with the code 'price_type' is 'boolean'.",
-    "sql": "SELECT frontend_input FROM eav_attribute WHERE attribute_code = 'price_type';",
-    "sql_execute_result": [
-      [
-        "boolean"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total shipping amount for orders on 2023-02-22.",
-    "answer": "The total shipping amounts for orders on 2023-02-22 are 25.0000 and 25.0000.",
-    "sql": "SELECT total_shipping_amount FROM sales_order_aggregated_created WHERE period = '2023-02-22';",
-    "sql_execute_result": [
-      [
-        "25.0000"
-      ],
-      [
-        "25.0000"
-      ]
-    ]
-  }
-]
\ No newline at end of file
diff --git a/random_sample/generated_tasks.json.bak3 b/random_sample/generated_tasks.json.bak3
deleted file mode 100644
index c6e30ca..0000000
--- a/random_sample/generated_tasks.json.bak3
+++ /dev/null
@@ -1,9329 +0,0 @@
-[
-  {
-    "question": "What is the product name for the SKU 'miko-pullover-hoodie-xs-orange'?",
-    "answer": [
-      "miko-pullover-hoodie-xs-orange"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 1078 AND attribute_id = 121;",
-    "sql_execute_result": [
-      [
-        "miko-pullover-hoodie-xs-orange"
-      ]
-    ]
-  },
-  {
-    "question": "What is the description for the product with ID 937?",
-    "answer": [
-      "<p>What more do you need than a sporty yoga short made with organic cotton and a little spandex for mobility? The Hawkeye Yoga Short brings a stylish, standard fit you can sport with confidence outside the studio.</p>\n<p>&bull; Dark gray shorts with red accents.<br />&bull; 92% Organic Cotton 8% Spandex.<br />&bull; Breathable stretch organic cotton.<br />&bull; Medium=8.0\" (21.0cm) inseam.</p>"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 937 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>What more do you need than a sporty yoga short made with organic cotton and a little spandex for mobility? The Hawkeye Yoga Short brings a stylish, standard fit you can sport with confidence outside the studio.</p>\n<p>&bull; Dark gray shorts with red accents.<br />&bull; 92% Organic Cotton 8% Spandex.<br />&bull; Breathable stretch organic cotton.<br />&bull; Medium=8.0\" (21.0cm) inseam.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were completed on 2022-06-21 in store ID 1?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE store_id = 1 AND period = '2022-06-21' AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the value of the attribute with ID 137 for the product with ID 43?",
-    "answer": [
-      "9,16,5,11"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 43 AND attribute_id = 137;",
-    "sql_execute_result": [
-      [
-        "9,16,5,11"
-      ]
-    ]
-  },
-  {
-    "question": "How many total income amounts were found for orders completed on 2022-11-03?",
-    "answer": [
-      "2"
-    ],
-    "sql": "SELECT total_income_amount FROM sales_order_aggregated_created WHERE period = '2022-11-03' AND order_status = 'complete';",
-    "sql_execute_result": [
-      [
-        "198.6400"
-      ],
-      [
-        "198.6400"
-      ]
-    ]
-  },
-  {
-    "question": "What is the attribute code for attribute ID 93 in the catalog EAV attribute?",
-    "answer": [
-      "visual"
-    ],
-    "sql": "SELECT JSON_UNQUOTE(JSON_EXTRACT(additional_data, '$.swatch_input_type')) AS attribute_code FROM catalog_eav_attribute WHERE attribute_id = 93;",
-    "sql_execute_result": [
-      [
-        "visual"
-      ]
-    ]
-  },
-  {
-    "question": "How many product names have the attribute ID 106 and value 'container2'?",
-    "answer": [
-      "2051"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE attribute_id = 106 AND value = 'container2';",
-    "sql_execute_result": [
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ],
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-        "container2"
-      ],
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-        "container2"
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-        "container2"
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-      [
-        "container2"
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-        "container2"
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-        "container2"
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-        "container2"
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-        "container2"
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-        "container2"
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-        "container2"
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-        "container2"
-      ],
-      [
-        "container2"
-      ],
-      [
-        "container2"
-      ]
-    ]
-  },
-  {
-    "question": "Is the sequence profile with ID 8 active?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT is_active FROM sales_sequence_profile WHERE profile_id = 8;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the discount amount for orders pending on 2023-05-31?",
-    "answer": [
-      "48.6000",
-      "48.6000"
-    ],
-    "sql": "SELECT total_discount_amount FROM sales_order_aggregated_created WHERE period = '2023-05-31' AND order_status = 'pending';",
-    "sql_execute_result": [
-      [
-        "48.6000"
-      ],
-      [
-        "48.6000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the store with store ID 1?",
-    "answer": [
-      "Default Store View"
-    ],
-    "sql": "SELECT name FROM store WHERE store_id = 1;",
-    "sql_execute_result": [
-      [
-        "Default Store View"
-      ]
-    ]
-  },
-  {
-    "question": "Find the stock quantity for product with ID 526.",
-    "answer": [
-      "0.0000"
-    ],
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 526;",
-    "sql_execute_result": [
-      [
-        "0.0000"
-      ]
-    ]
-  },
-  {
-    "question": "List all shipment items for shipment with parent ID 3.",
-    "answer": [
-      "Troy Yoga Short",
-      "MSH09-36-Black",
-      "24.0000",
-      "Eos V-Neck Hoodie",
-      "WH11-S-Blue",
-      "54.0000"
-    ],
-    "sql": "SELECT name, sku, price FROM sales_shipment_item WHERE parent_id = 3;",
-    "sql_execute_result": [
-      [
-        "Troy Yoga Short",
-        "MSH09-36-Black",
-        "24.0000"
-      ],
-      [
-        "Eos V-Neck Hoodie",
-        "WH11-S-Blue",
-        "54.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the region with region ID 767?",
-    "answer": [
-      "Sj\u00e6lland"
-    ],
-    "sql": "SELECT name FROM directory_country_region_name WHERE region_id = 767 AND locale = 'en_US';",
-    "sql_execute_result": [
-      [
-        "Sj\u00e6lland"
-      ]
-    ]
-  },
-  {
-    "question": "Is the store with code 'admin' active?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT is_active FROM store WHERE code = 'admin';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the value of the rating option with option ID 13.",
-    "answer": [
-      "3"
-    ],
-    "sql": "SELECT value FROM rating_option WHERE option_id = 13;",
-    "sql_execute_result": [
-      [
-        3
-      ]
-    ]
-  },
-  {
-    "question": "Get the stock status for product ID 1918.",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT is_in_stock FROM cataloginventory_stock_item WHERE product_id = 1918;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What locale is used for the region with name 'Madrid'?",
-    "answer": [
-      "en_US"
-    ],
-    "sql": "SELECT locale FROM directory_country_region_name WHERE name = 'Madrid';",
-    "sql_execute_result": [
-      [
-        "en_US"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status of the review with ID 240?",
-    "answer": [
-      "Approved"
-    ],
-    "sql": "SELECT status_code FROM review JOIN review_status ON review.status_id = review_status.status_id WHERE review.review_id = 240;",
-    "sql_execute_result": [
-      [
-        "Approved"
-      ]
-    ]
-  },
-  {
-    "question": "Find the full address for customer with address ID 51.",
-    "answer": [
-      "444 Beacon St, Boston, Massachusetts, 02108, US"
-    ],
-    "sql": "SELECT CONCAT(street, ', ', city, ', ', region, ', ', postcode, ', ', country_id) AS full_address FROM customer_address_entity WHERE entity_id = 51;",
-    "sql_execute_result": [
-      [
-        "444 Beacon St, Boston, Massachusetts, 02108, US"
-      ]
-    ]
-  },
-  {
-    "question": "What is the SKU of the product with entity ID 533?",
-    "answer": [
-      "MS06-M-Blue"
-    ],
-    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 533;",
-    "sql_execute_result": [
-      [
-        "MS06-M-Blue"
-      ]
-    ]
-  },
-  {
-    "question": "Find all categories under the path '1/2/7'.",
-    "answer": [
-      "34",
-      "35",
-      "36",
-      "39",
-      "40",
-      "8"
-    ],
-    "sql": "SELECT entity_id, path FROM catalog_category_entity WHERE path LIKE '1/2/7/%';",
-    "sql_execute_result": [
-      [
-        34,
-        "1/2/7/34"
-      ],
-      [
-        35,
-        "1/2/7/35"
-      ],
-      [
-        36,
-        "1/2/7/36"
-      ],
-      [
-        39,
-        "1/2/7/39"
-      ],
-      [
-        40,
-        "1/2/7/40"
-      ],
-      [
-        8,
-        "1/2/7/8"
-      ]
-    ]
-  },
-  {
-    "question": "What is the position of category with entity ID 37?",
-    "answer": [
-      "6"
-    ],
-    "sql": "SELECT position FROM catalog_category_entity WHERE entity_id = 37;",
-    "sql_execute_result": [
-      [
-        6
-      ]
-    ]
-  },
-  {
-    "question": "Who is the customer with the telephone number 3035551212?",
-    "answer": [
-      "Jason Miller",
-      "Olivia Jackson",
-      "Nathan Chen"
-    ],
-    "sql": "SELECT CONCAT(firstname, ' ', lastname) AS name FROM customer_address_entity WHERE telephone = '3035551212';",
-    "sql_execute_result": [
-      [
-        "Jason Miller"
-      ],
-      [
-        "Olivia Jackson"
-      ],
-      [
-        "Nathan Chen"
-      ]
-    ]
-  },
-  {
-    "question": "Check if the customer address ID 2 is active.",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT is_active FROM customer_address_entity WHERE entity_id = 2;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the region with region ID 32?",
-    "answer": [
-      "Massachusetts"
-    ],
-    "sql": "SELECT default_name FROM directory_country_region WHERE region_id = 32;",
-    "sql_execute_result": [
-      [
-        "Massachusetts"
-      ]
-    ]
-  },
-  {
-    "question": "How many products were found?",
-    "answer": [
-      "67"
-    ],
-    "sql": "SELECT entity_id, sku FROM catalog_product_entity WHERE created_at = '2023-04-19 16:13:41';",
-    "sql_execute_result": [
-      [
-        1079,
-        "WH04-XS-Purple"
-      ],
-      [
-        1080,
-        "WH04-S-Blue"
-      ],
-      [
-        1081,
-        "WH04-S-Orange"
-      ],
-      [
-        1082,
-        "WH04-S-Purple"
-      ],
-      [
-        1083,
-        "WH04-M-Blue"
-      ],
-      [
-        1084,
-        "WH04-M-Orange"
-      ],
-      [
-        1085,
-        "WH04-M-Purple"
-      ],
-      [
-        1086,
-        "WH04-L-Blue"
-      ],
-      [
-        1087,
-        "WH04-L-Orange"
-      ],
-      [
-        1088,
-        "WH04-L-Purple"
-      ],
-      [
-        1089,
-        "WH04-XL-Blue"
-      ],
-      [
-        1090,
-        "WH04-XL-Orange"
-      ],
-      [
-        1091,
-        "WH04-XL-Purple"
-      ],
-      [
-        1092,
-        "WH04"
-      ],
-      [
-        1093,
-        "WH05-XS-Orange"
-      ],
-      [
-        1094,
-        "WH05-XS-Purple"
-      ],
-      [
-        1095,
-        "WH05-XS-White"
-      ],
-      [
-        1096,
-        "WH05-S-Orange"
-      ],
-      [
-        1097,
-        "WH05-S-Purple"
-      ],
-      [
-        1098,
-        "WH05-S-White"
-      ],
-      [
-        1099,
-        "WH05-M-Orange"
-      ],
-      [
-        1100,
-        "WH05-M-Purple"
-      ],
-      [
-        1101,
-        "WH05-M-White"
-      ],
-      [
-        1102,
-        "WH05-L-Orange"
-      ],
-      [
-        1103,
-        "WH05-L-Purple"
-      ],
-      [
-        1104,
-        "WH05-L-White"
-      ],
-      [
-        1105,
-        "WH05-XL-Orange"
-      ],
-      [
-        1106,
-        "WH05-XL-Purple"
-      ],
-      [
-        1107,
-        "WH05-XL-White"
-      ],
-      [
-        1108,
-        "WH05"
-      ],
-      [
-        1109,
-        "WH06-XS-Purple"
-      ],
-      [
-        1110,
-        "WH06-S-Purple"
-      ],
-      [
-        1111,
-        "WH06-M-Purple"
-      ],
-      [
-        1112,
-        "WH06-L-Purple"
-      ],
-      [
-        1113,
-        "WH06-XL-Purple"
-      ],
-      [
-        1114,
-        "WH06"
-      ],
-      [
-        1115,
-        "WH07-XS-Gray"
-      ],
-      [
-        1116,
-        "WH07-XS-Purple"
-      ],
-      [
-        1117,
-        "WH07-XS-White"
-      ],
-      [
-        1118,
-        "WH07-S-Gray"
-      ],
-      [
-        1119,
-        "WH07-S-Purple"
-      ],
-      [
-        1120,
-        "WH07-S-White"
-      ],
-      [
-        1121,
-        "WH07-M-Gray"
-      ],
-      [
-        1122,
-        "WH07-M-Purple"
-      ],
-      [
-        1123,
-        "WH07-M-White"
-      ],
-      [
-        1124,
-        "WH07-L-Gray"
-      ],
-      [
-        1125,
-        "WH07-L-Purple"
-      ],
-      [
-        1126,
-        "WH07-L-White"
-      ],
-      [
-        1127,
-        "WH07-XL-Gray"
-      ],
-      [
-        1128,
-        "WH07-XL-Purple"
-      ],
-      [
-        1129,
-        "WH07-XL-White"
-      ],
-      [
-        1130,
-        "WH07"
-      ],
-      [
-        1131,
-        "WH08-XS-Orange"
-      ],
-      [
-        1132,
-        "WH08-XS-Purple"
-      ],
-      [
-        1133,
-        "WH08-XS-White"
-      ],
-      [
-        1134,
-        "WH08-S-Orange"
-      ],
-      [
-        1135,
-        "WH08-S-Purple"
-      ],
-      [
-        1136,
-        "WH08-S-White"
-      ],
-      [
-        1137,
-        "WH08-M-Orange"
-      ],
-      [
-        1138,
-        "WH08-M-Purple"
-      ],
-      [
-        1139,
-        "WH08-M-White"
-      ],
-      [
-        1140,
-        "WH08-L-Orange"
-      ],
-      [
-        1141,
-        "WH08-L-Purple"
-      ],
-      [
-        1142,
-        "WH08-L-White"
-      ],
-      [
-        1143,
-        "WH08-XL-Orange"
-      ],
-      [
-        1144,
-        "WH08-XL-Purple"
-      ],
-      [
-        1145,
-        "WH08-XL-White"
-      ]
-    ]
-  },
-  {
-    "question": "What is the default store ID for the 'Main Website Store' group?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT default_store_id FROM store_group WHERE name = 'Main Website Store';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the product with the highest rating position in store 1 for the year 2022.",
-    "answer": [
-      "Quest Lumaflex&trade; Band"
-    ],
-    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_yearly WHERE store_id = 1 AND period = '2022-01-01' ORDER BY rating_pos ASC LIMIT 1;",
-    "sql_execute_result": [
-      [
-        "Quest Lumaflex&trade; Band"
-      ]
-    ]
-  },
-  {
-    "question": "What is the entity type code for entity type ID 8?",
-    "answer": [
-      "shipment"
-    ],
-    "sql": "SELECT entity_type_code FROM eav_entity_type WHERE entity_type_id = 8;",
-    "sql_execute_result": [
-      [
-        "shipment"
-      ]
-    ]
-  },
-  {
-    "question": "List all the sequence values for invoices.",
-    "answer": [
-      "1",
-      "2"
-    ],
-    "sql": "SELECT sequence_value FROM sequence_invoice_1;",
-    "sql_execute_result": [
-      [
-        1
-      ],
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "How many items were found?",
-    "answer": [
-      "2"
-    ],
-    "sql": "SELECT product_price FROM sales_bestsellers_aggregated_yearly WHERE product_name = 'Aether Gym Pant -34-Brown';",
-    "sql_execute_result": [
-      [
-        "59.2000"
-      ],
-      [
-        "59.2000"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders have sequence values greater than 100?",
-    "answer": [
-      "208"
-    ],
-    "sql": "SELECT sequence_value FROM sequence_order_1 WHERE sequence_value > 100;",
-    "sql_execute_result": [
-      [
-        101
-      ],
-      [
-        102
-      ],
-      [
-        103
-      ],
-      [
-        104
-      ],
-      [
-        105
-      ],
-      [
-        106
-      ],
-      [
-        107
-      ],
-      [
-        108
-      ],
-      [
-        109
-      ],
-      [
-        110
-      ],
-      [
-        111
-      ],
-      [
-        112
-      ],
-      [
-        113
-      ],
-      [
-        114
-      ],
-      [
-        115
-      ],
-      [
-        116
-      ],
-      [
-        117
-      ],
-      [
-        118
-      ],
-      [
-        119
-      ],
-      [
-        120
-      ],
-      [
-        121
-      ],
-      [
-        122
-      ],
-      [
-        123
-      ],
-      [
-        124
-      ],
-      [
-        125
-      ],
-      [
-        126
-      ],
-      [
-        127
-      ],
-      [
-        128
-      ],
-      [
-        129
-      ],
-      [
-        130
-      ],
-      [
-        131
-      ],
-      [
-        132
-      ],
-      [
-        133
-      ],
-      [
-        134
-      ],
-      [
-        135
-      ],
-      [
-        136
-      ],
-      [
-        137
-      ],
-      [
-        138
-      ],
-      [
-        139
-      ],
-      [
-        140
-      ],
-      [
-        141
-      ],
-      [
-        142
-      ],
-      [
-        143
-      ],
-      [
-        144
-      ],
-      [
-        145
-      ],
-      [
-        146
-      ],
-      [
-        147
-      ],
-      [
-        148
-      ],
-      [
-        149
-      ],
-      [
-        150
-      ],
-      [
-        151
-      ],
-      [
-        152
-      ],
-      [
-        153
-      ],
-      [
-        154
-      ],
-      [
-        155
-      ],
-      [
-        156
-      ],
-      [
-        157
-      ],
-      [
-        158
-      ],
-      [
-        159
-      ],
-      [
-        160
-      ],
-      [
-        161
-      ],
-      [
-        162
-      ],
-      [
-        163
-      ],
-      [
-        164
-      ],
-      [
-        165
-      ],
-      [
-        166
-      ],
-      [
-        167
-      ],
-      [
-        168
-      ],
-      [
-        169
-      ],
-      [
-        170
-      ],
-      [
-        171
-      ],
-      [
-        172
-      ],
-      [
-        173
-      ],
-      [
-        174
-      ],
-      [
-        175
-      ],
-      [
-        176
-      ],
-      [
-        177
-      ],
-      [
-        178
-      ],
-      [
-        179
-      ],
-      [
-        180
-      ],
-      [
-        181
-      ],
-      [
-        182
-      ],
-      [
-        183
-      ],
-      [
-        184
-      ],
-      [
-        185
-      ],
-      [
-        186
-      ],
-      [
-        187
-      ],
-      [
-        188
-      ],
-      [
-        189
-      ],
-      [
-        190
-      ],
-      [
-        191
-      ],
-      [
-        192
-      ],
-      [
-        193
-      ],
-      [
-        194
-      ],
-      [
-        195
-      ],
-      [
-        196
-      ],
-      [
-        197
-      ],
-      [
-        198
-      ],
-      [
-        199
-      ],
-      [
-        200
-      ],
-      [
-        201
-      ],
-      [
-        202
-      ],
-      [
-        203
-      ],
-      [
-        204
-      ],
-      [
-        205
-      ],
-      [
-        206
-      ],
-      [
-        207
-      ],
-      [
-        208
-      ],
-      [
-        209
-      ],
-      [
-        210
-      ],
-      [
-        211
-      ],
-      [
-        212
-      ],
-      [
-        213
-      ],
-      [
-        214
-      ],
-      [
-        215
-      ],
-      [
-        216
-      ],
-      [
-        217
-      ],
-      [
-        218
-      ],
-      [
-        219
-      ],
-      [
-        220
-      ],
-      [
-        221
-      ],
-      [
-        222
-      ],
-      [
-        223
-      ],
-      [
-        224
-      ],
-      [
-        225
-      ],
-      [
-        226
-      ],
-      [
-        227
-      ],
-      [
-        228
-      ],
-      [
-        229
-      ],
-      [
-        230
-      ],
-      [
-        231
-      ],
-      [
-        232
-      ],
-      [
-        233
-      ],
-      [
-        234
-      ],
-      [
-        235
-      ],
-      [
-        236
-      ],
-      [
-        237
-      ],
-      [
-        238
-      ],
-      [
-        239
-      ],
-      [
-        240
-      ],
-      [
-        241
-      ],
-      [
-        242
-      ],
-      [
-        243
-      ],
-      [
-        244
-      ],
-      [
-        245
-      ],
-      [
-        246
-      ],
-      [
-        247
-      ],
-      [
-        248
-      ],
-      [
-        249
-      ],
-      [
-        250
-      ],
-      [
-        251
-      ],
-      [
-        252
-      ],
-      [
-        253
-      ],
-      [
-        254
-      ],
-      [
-        255
-      ],
-      [
-        256
-      ],
-      [
-        257
-      ],
-      [
-        258
-      ],
-      [
-        259
-      ],
-      [
-        260
-      ],
-      [
-        261
-      ],
-      [
-        262
-      ],
-      [
-        263
-      ],
-      [
-        264
-      ],
-      [
-        265
-      ],
-      [
-        266
-      ],
-      [
-        267
-      ],
-      [
-        268
-      ],
-      [
-        269
-      ],
-      [
-        270
-      ],
-      [
-        271
-      ],
-      [
-        272
-      ],
-      [
-        273
-      ],
-      [
-        274
-      ],
-      [
-        275
-      ],
-      [
-        276
-      ],
-      [
-        277
-      ],
-      [
-        278
-      ],
-      [
-        279
-      ],
-      [
-        280
-      ],
-      [
-        281
-      ],
-      [
-        282
-      ],
-      [
-        283
-      ],
-      [
-        284
-      ],
-      [
-        285
-      ],
-      [
-        286
-      ],
-      [
-        287
-      ],
-      [
-        288
-      ],
-      [
-        289
-      ],
-      [
-        290
-      ],
-      [
-        291
-      ],
-      [
-        292
-      ],
-      [
-        293
-      ],
-      [
-        294
-      ],
-      [
-        295
-      ],
-      [
-        296
-      ],
-      [
-        297
-      ],
-      [
-        298
-      ],
-      [
-        299
-      ],
-      [
-        300
-      ],
-      [
-        301
-      ],
-      [
-        302
-      ],
-      [
-        303
-      ],
-      [
-        304
-      ],
-      [
-        305
-      ],
-      [
-        306
-      ],
-      [
-        307
-      ],
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "What is the root category ID for the 'Default' store group?",
-    "answer": [
-      "0"
-    ],
-    "sql": "SELECT root_category_id FROM store_group WHERE name = 'Default';",
-    "sql_execute_result": [
-      [
-        0
-      ]
-    ]
-  },
-  {
-    "question": "What is the entity model for catalog product entity type?",
-    "answer": [
-      "Magento\\Catalog\\Model\\ResourceModel\\Product"
-    ],
-    "sql": "SELECT entity_model FROM eav_entity_type WHERE entity_type_code = 'catalog_product';",
-    "sql_execute_result": [
-      [
-        "Magento\\Catalog\\Model\\ResourceModel\\Product"
-      ]
-    ]
-  },
-  {
-    "question": "Find the quantity ordered for the product 'Antonia Racer Tank-L-Purple' in store 0.",
-    "answer": [
-      "1.0000"
-    ],
-    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_yearly WHERE product_name = 'Antonia Racer Tank-L-Purple' AND store_id = 0;",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the code for the 'Main Website Store' group?",
-    "answer": [
-      "main_website_store"
-    ],
-    "sql": "SELECT code FROM store_group WHERE name = 'Main Website Store';",
-    "sql_execute_result": [
-      [
-        "main_website_store"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total grand total for completed orders for customer Grace Nguyen?",
-    "answer": [
-      "143.8000",
-      "215.0000",
-      "196.2000",
-      "65.0000",
-      "198.6400",
-      "251.2400"
-    ],
-    "sql": "SELECT grand_total FROM sales_order WHERE customer_id = 18 AND state = 'complete';",
-    "sql_execute_result": [
-      [
-        "143.8000"
-      ],
-      [
-        "215.0000"
-      ],
-      [
-        "196.2000"
-      ],
-      [
-        "65.0000"
-      ],
-      [
-        "198.6400"
-      ],
-      [
-        "251.2400"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders with status 'canceled' were found?",
-    "answer": [
-      "142"
-    ],
-    "sql": "SELECT increment_id, CONCAT(customer_firstname, ' ', customer_lastname) AS customer_name, grand_total FROM sales_order WHERE status = 'canceled';",
-    "sql_execute_result": [
-      [
-        "000000001",
-        "Veronica Costello",
-        "36.3900"
-      ],
-      [
-        "000000003",
-        "Brian Smith",
-        "160.2500"
-      ],
-      [
-        "000000005",
-        "Grace Nguyen",
-        "137.0000"
-      ],
-      [
-        "000000006",
-        "John Doe",
-        "53.0000"
-      ],
-      [
-        "000000007",
-        "Adam Garcia",
-        "108.2500"
-      ],
-      [
-        "000000008",
-        "Bob Johnson",
-        "146.0000"
-      ],
-      [
-        "000000010",
-        "Matt Baker",
-        "107.6000"
-      ],
-      [
-        "000000012",
-        "Jane Smith",
-        "113.8000"
-      ],
-      [
-        "000000014",
-        "Bob Jones",
-        "85.2000"
-      ],
-      [
-        "000000015",
-        "Sarah Miller",
-        "61.0000"
-      ],
-      [
-        "000000018",
-        "Sophie Taylor",
-        "105.0000"
-      ],
-      [
-        "000000019",
-        "Julia Williams",
-        "214.6000"
-      ],
-      [
-        "000000025",
-        "John Doe",
-        "204.2500"
-      ],
-      [
-        "000000026",
-        "Lucy Garcia",
-        "216.0000"
-      ],
-      [
-        "000000029",
-        "Lucy Garcia",
-        "98.4000"
-      ],
-      [
-        "000000030",
-        "Alex Martin",
-        "67.0000"
-      ],
-      [
-        "000000038",
-        "Jason Miller",
-        "52.2000"
-      ],
-      [
-        "000000039",
-        "Sarah Miller",
-        "218.8500"
-      ],
-      [
-        "000000040",
-        "Lisa Kim",
-        "74.0000"
-      ],
-      [
-        "000000041",
-        "Mary Martin",
-        "161.2500"
-      ],
-      [
-        "000000042",
-        "Michael Nguyen",
-        "211.6000"
-      ],
-      [
-        "000000044",
-        "Lisa Green",
-        "155.0000"
-      ],
-      [
-        "000000046",
-        "Samantha Jones",
-        "139.0000"
-      ],
-      [
-        "000000049",
-        "Alexander Thomas",
-        "205.0000"
-      ],
-      [
-        "000000052",
-        "Brian Smith",
-        "48.0000"
-      ],
-      [
-        "000000056",
-        "Adam Garcia",
-        "198.6000"
-      ],
-      [
-        "000000058",
-        "John Lee",
-        "199.1000"
-      ],
-      [
-        "000000059",
-        "John Smith",
-        "95.4000"
-      ],
-      [
-        "000000060",
-        "Jennifer White",
-        "60.0000"
-      ],
-      [
-        "000000063",
-        "Alex Martin",
-        "196.0000"
-      ],
-      [
-        "000000066",
-        "Samantha Jones",
-        "162.2000"
-      ],
-      [
-        "000000067",
-        "Lily Potter",
-        "194.7600"
-      ],
-      [
-        "000000068",
-        "John Smith",
-        "211.8000"
-      ],
-      [
-        "000000072",
-        "Jennifer White",
-        "178.0000"
-      ],
-      [
-        "000000074",
-        "Adam Garcia",
-        "67.8000"
-      ],
-      [
-        "000000076",
-        "Jane Smith",
-        "72.0000"
-      ],
-      [
-        "000000077",
-        "Alex Johnson",
-        "104.0000"
-      ],
-      [
-        "000000080",
-        "Grace Nguyen",
-        "37.5000"
-      ],
-      [
-        "000000081",
-        "Samantha Jones",
-        "183.5900"
-      ],
-      [
-        "000000085",
-        "Grace Nguyen",
-        "203.0000"
-      ],
-      [
-        "000000086",
-        "John Doe",
-        "105.4000"
-      ],
-      [
-        "000000088",
-        "Samantha Jones",
-        "168.8000"
-      ],
-      [
-        "000000094",
-        "Alex Johnson",
-        "64.0000"
-      ],
-      [
-        "000000095",
-        "John Smith",
-        "64.0000"
-      ],
-      [
-        "000000098",
-        "Julia Williams",
-        "223.6000"
-      ],
-      [
-        "000000101",
-        "Sarah Miller",
-        "199.8000"
-      ],
-      [
-        "000000103",
-        "Jane Smith",
-        "71.5000"
-      ],
-      [
-        "000000106",
-        "John Lee",
-        "99.0000"
-      ],
-      [
-        "000000107",
-        "John Smith",
-        "45.0000"
-      ],
-      [
-        "000000108",
-        "Alex Johnson",
-        "75.0000"
-      ],
-      [
-        "000000109",
-        "Jason Miller",
-        "136.4000"
-      ],
-      [
-        "000000110",
-        "Julia Williams",
-        "104.0000"
-      ],
-      [
-        "000000111",
-        "Lily Potter",
-        "217.1200"
-      ],
-      [
-        "000000117",
-        "John Lee",
-        "196.8000"
-      ],
-      [
-        "000000118",
-        "Brian Smith",
-        "29.0000"
-      ],
-      [
-        "000000120",
-        "Matt Baker",
-        "112.0000"
-      ],
-      [
-        "000000122",
-        "Alexander Thomas",
-        "123.2000"
-      ],
-      [
-        "000000123",
-        "Olivia Lee",
-        "209.0000"
-      ],
-      [
-        "000000124",
-        "Sophie Taylor",
-        "193.6400"
-      ],
-      [
-        "000000126",
-        "Grace Nguyen",
-        "207.0000"
-      ],
-      [
-        "000000129",
-        "Olivia Lee",
-        "151.0000"
-      ],
-      [
-        "000000132",
-        "Samantha Jones",
-        "161.8000"
-      ],
-      [
-        "000000134",
-        "Daniel Jackson",
-        "64.0000"
-      ],
-      [
-        "000000135",
-        "Jennifer White",
-        "141.0000"
-      ],
-      [
-        "000000136",
-        "Lily Potter",
-        "208.2000"
-      ],
-      [
-        "000000141",
-        "Matt Baker",
-        "167.0000"
-      ],
-      [
-        "000000142",
-        "Julia Williams",
-        "87.0000"
-      ],
-      [
-        "000000143",
-        "Brian Smith",
-        "95.0000"
-      ],
-      [
-        "000000144",
-        "John Smith",
-        "171.0000"
-      ],
-      [
-        "000000149",
-        "Ava Brown",
-        "34.0000"
-      ],
-      [
-        "000000151",
-        "David Lee",
-        "217.2000"
-      ],
-      [
-        "000000152",
-        "Alex Johnson",
-        "223.0000"
-      ],
-      [
-        "000000153",
-        "Jane Doe",
-        "180.8000"
-      ],
-      [
-        "000000157",
-        "Sarah Miller",
-        "44.0000"
-      ],
-      [
-        "000000159",
-        "Daniel Jackson",
-        "29.0000"
-      ],
-      [
-        "000000162",
-        "Olivia Lee",
-        "152.2000"
-      ],
-      [
-        "000000165",
-        "Alex Martin",
-        "202.6000"
-      ],
-      [
-        "000000167",
-        "Julia Williams",
-        "38.6000"
-      ],
-      [
-        "000000168",
-        "Bob Jones",
-        "146.0000"
-      ],
-      [
-        "000000170",
-        "Olivia Lee",
-        "66.0000"
-      ],
-      [
-        "000000171",
-        "Samantha Nguyen",
-        "220.0000"
-      ],
-      [
-        "000000172",
-        "Adam Garcia",
-        "64.0000"
-      ],
-      [
-        "000000173",
-        "Alex Martin",
-        "94.2000"
-      ],
-      [
-        "000000174",
-        "Emma Davis",
-        "45.8000"
-      ],
-      [
-        "000000175",
-        "Katie Wong",
-        "205.6400"
-      ],
-      [
-        "000000176",
-        "Lisa Kim",
-        "37.0000"
-      ],
-      [
-        "000000177",
-        "Alex Martin",
-        "76.0000"
-      ],
-      [
-        "000000178",
-        "Lisa Kim",
-        "64.0000"
-      ],
-      [
-        "000000180",
-        "Samantha Jones",
-        "135.2000"
-      ],
-      [
-        "000000183",
-        "Grace Nguyen",
-        "201.6000"
-      ],
-      [
-        "000000185",
-        "Sarah Miller",
-        "37.0000"
-      ],
-      [
-        "000000191",
-        "Alex Martin",
-        "95.0000"
-      ],
-      [
-        "000000193",
-        "Bob Jones",
-        "224.4000"
-      ],
-      [
-        "000000194",
-        "David Lee",
-        "94.0000"
-      ],
-      [
-        "000000195",
-        "Lisa Kim",
-        "133.0000"
-      ],
-      [
-        "000000198",
-        "Katie Wong",
-        "96.0000"
-      ],
-      [
-        "000000204",
-        "Lucy Garcia",
-        "44.0000"
-      ],
-      [
-        "000000206",
-        "Alexander Thomas",
-        "62.0000"
-      ],
-      [
-        "000000209",
-        "Daniel Jackson",
-        "39.0000"
-      ],
-      [
-        "000000210",
-        "John Lee",
-        "228.9900"
-      ],
-      [
-        "000000211",
-        "Sophie Taylor",
-        "107.4000"
-      ],
-      [
-        "000000212",
-        "Sophie Taylor",
-        "68.0000"
-      ],
-      [
-        "000000219",
-        "Alexander Thomas",
-        "223.0000"
-      ],
-      [
-        "000000220",
-        "Jane Doe",
-        "153.4000"
-      ],
-      [
-        "000000221",
-        "Brian Smith",
-        "76.0000"
-      ],
-      [
-        "000000222",
-        "Jane Smith",
-        "185.0000"
-      ],
-      [
-        "000000224",
-        "Matt Baker",
-        "73.0000"
-      ],
-      [
-        "000000226",
-        "Jane Smith",
-        "54.0000"
-      ],
-      [
-        "000000227",
-        "Bob Johnson",
-        "27.0000"
-      ],
-      [
-        "000000229",
-        "Sarah Miller",
-        "55.0000"
-      ],
-      [
-        "000000232",
-        "Samantha Jones",
-        "143.0000"
-      ],
-      [
-        "000000234",
-        "Lily Potter",
-        "50.0000"
-      ],
-      [
-        "000000241",
-        "Alex Johnson",
-        "44.0000"
-      ],
-      [
-        "000000242",
-        "Olivia Lee",
-        "183.0000"
-      ],
-      [
-        "000000244",
-        "Alex Johnson",
-        "89.0000"
-      ],
-      [
-        "000000245",
-        "Jane Doe",
-        "37.5000"
-      ],
-      [
-        "000000246",
-        "Jane Smith",
-        "74.0000"
-      ],
-      [
-        "000000248",
-        "Alexander Thomas",
-        "192.0000"
-      ],
-      [
-        "000000249",
-        "Samantha Jones",
-        "125.0000"
-      ],
-      [
-        "000000252",
-        "Ava Brown",
-        "65.0000"
-      ],
-      [
-        "000000254",
-        "Michael Nguyen",
-        "145.5000"
-      ],
-      [
-        "000000255",
-        "Lisa Kim",
-        "34.0000"
-      ],
-      [
-        "000000259",
-        "Jane Doe",
-        "189.6000"
-      ],
-      [
-        "000000261",
-        "Lily Potter",
-        "192.0000"
-      ],
-      [
-        "000000265",
-        "Daniel Jackson",
-        "94.0000"
-      ],
-      [
-        "000000266",
-        "Samantha Jones",
-        "183.1900"
-      ],
-      [
-        "000000267",
-        "Julia Williams",
-        "117.0000"
-      ],
-      [
-        "000000271",
-        "Jane Smith",
-        "77.0000"
-      ],
-      [
-        "000000272",
-        "Michael Nguyen",
-        "82.0000"
-      ],
-      [
-        "000000273",
-        "John Smith",
-        "190.0000"
-      ],
-      [
-        "000000275",
-        "Alexander Thomas",
-        "195.4000"
-      ],
-      [
-        "000000278",
-        "Jason Miller",
-        "37.0000"
-      ],
-      [
-        "000000279",
-        "Samantha Nguyen",
-        "44.0000"
-      ],
-      [
-        "000000280",
-        "Daniel Jackson",
-        "71.5000"
-      ],
-      [
-        "000000283",
-        "Bob Jones",
-        "154.8000"
-      ],
-      [
-        "000000289",
-        "Daniel Jackson",
-        "194.5000"
-      ],
-      [
-        "000000290",
-        "Julia Williams",
-        "53.0000"
-      ],
-      [
-        "000000291",
-        "Adam Garcia",
-        "43.4000"
-      ],
-      [
-        "000000292",
-        "Jason Miller",
-        "121.0000"
-      ],
-      [
-        "000000293",
-        "John Doe",
-        "208.0000"
-      ],
-      [
-        "000000294",
-        "Alexander Thomas",
-        "171.0000"
-      ],
-      [
-        "000000296",
-        "Lily Potter",
-        "23.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the label for the order status 'pending_payment'?",
-    "answer": [
-      "Pending Payment"
-    ],
-    "sql": "SELECT label FROM sales_order_status WHERE status = 'pending_payment';",
-    "sql_execute_result": [
-      [
-        "Pending Payment"
-      ]
-    ]
-  },
-  {
-    "question": "Determine the country ISO-3 code for the country with ISO-2 code 'PG'.",
-    "answer": [
-      "PNG"
-    ],
-    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'PG';",
-    "sql_execute_result": [
-      [
-        "PNG"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total number of items ordered in order with increment ID '000000287'.",
-    "answer": [
-      "1.0000"
-    ],
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE increment_id = '000000287';",
-    "sql_execute_result": [
-      [
-        "1.0000"
-      ]
-    ]
-  },
-  {
-    "question": "What is the value description for attribute option with ID 77?",
-    "answer": [
-      "Reflective"
-    ],
-    "sql": "SELECT value FROM eav_attribute_option_value WHERE option_id = 77;",
-    "sql_execute_result": [
-      [
-        "Reflective"
-      ]
-    ]
-  },
-  {
-    "question": "Which customer has the billing address in Beverly Hills?",
-    "answer": [
-      "Jane Smith",
-      "Alex Johnson",
-      "Julie Nguyen"
-    ],
-    "sql": "SELECT CONCAT(firstname, ' ', lastname) FROM customer_address_entity WHERE city = 'Beverly Hills';",
-    "sql_execute_result": [
-      [
-        "Jane Smith"
-      ],
-      [
-        "Alex Johnson"
-      ],
-      [
-        "Julie Nguyen"
-      ]
-    ]
-  },
-  {
-    "question": "What is the shipping method used for order with increment ID '000000114'?",
-    "answer": [
-      "flatrate_flatrate"
-    ],
-    "sql": "SELECT shipping_method FROM sales_order WHERE increment_id = '000000114';",
-    "sql_execute_result": [
-      [
-        "flatrate_flatrate"
-      ]
-    ]
-  },
-  {
-    "question": "Identify the name of the customer who placed the order with increment ID '000000023'.",
-    "answer": [
-      "Alex Martin"
-    ],
-    "sql": "SELECT CONCAT(customer_firstname, ' ', customer_lastname) AS customer_name FROM sales_order WHERE increment_id = '000000023';",
-    "sql_execute_result": [
-      [
-        "Alex Martin"
-      ]
-    ]
-  },
-  {
-    "question": "What is the stock quantity for the product with ID 1819?",
-    "answer": [
-      "0.0000"
-    ],
-    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 1819;",
-    "sql_execute_result": [
-      [
-        "0.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the name of the store with store ID 0.",
-    "answer": [
-      "Admin"
-    ],
-    "sql": "SELECT name FROM store WHERE store_id = 0;",
-    "sql_execute_result": [
-      [
-        "Admin"
-      ]
-    ]
-  },
-  {
-    "question": "What is the default name for the region with region ID 273?",
-    "answer": [
-      "Essonne"
-    ],
-    "sql": "SELECT default_name FROM directory_country_region WHERE region_id = 273;",
-    "sql_execute_result": [
-      [
-        "Essonne"
-      ]
-    ]
-  },
-  {
-    "question": "What is the sort order for the attribute option with option ID 134?",
-    "answer": [
-      "18"
-    ],
-    "sql": "SELECT sort_order FROM eav_attribute_option WHERE option_id = 134;",
-    "sql_execute_result": [
-      [
-        18
-      ]
-    ]
-  },
-  {
-    "question": "Find the attribute ID for the integer value with value ID 9019.",
-    "answer": [
-      "93"
-    ],
-    "sql": "SELECT attribute_id FROM catalog_product_entity_int WHERE value_id = 9019;",
-    "sql_execute_result": [
-      [
-        93
-      ]
-    ]
-  },
-  {
-    "question": "Is the store with code 'default' active?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT is_active FROM store WHERE code = 'default';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "What is the value for the product attribute with entity ID 1263 and attribute ID 97?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_int WHERE entity_id = 1263 AND attribute_id = 97;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the region code for the region named 'Cremona'.",
-    "answer": [
-      "CR"
-    ],
-    "sql": "SELECT code FROM directory_country_region WHERE default_name = 'Cremona';",
-    "sql_execute_result": [
-      [
-        "CR"
-      ]
-    ]
-  },
-  {
-    "question": "What is the website ID associated with the store named 'Default Store View'?",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT website_id FROM store WHERE name = 'Default Store View';",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Find the product ID of the product with stock ID 1 and item ID 412.",
-    "answer": [
-      "412"
-    ],
-    "sql": "SELECT product_id FROM cataloginventory_stock_item WHERE item_id = 412 AND stock_id = 1;",
-    "sql_execute_result": [
-      [
-        412
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for customer with ID 45?",
-    "answer": [
-      "amanda.kim@gmail.com"
-    ],
-    "sql": "SELECT email FROM customer_grid_flat WHERE entity_id = 45;",
-    "sql_execute_result": [
-      [
-        "amanda.kim@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "Find the full billing address for customer 'Bob Johnson'.",
-    "answer": [
-      "123 Main St Richardson Texas 75080"
-    ],
-    "sql": "SELECT billing_full FROM customer_grid_flat WHERE name = 'Bob Johnson';",
-    "sql_execute_result": [
-      [
-        "123 Main St Richardson Texas 75080"
-      ]
-    ]
-  },
-  {
-    "question": "What is the ISO-3 code for the country with ISO-2 code 'TM'?",
-    "answer": [
-      "TKM"
-    ],
-    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'TM';",
-    "sql_execute_result": [
-      [
-        "TKM"
-      ]
-    ]
-  },
-  {
-    "question": "List all rating options for rating ID 4.",
-    "answer": [
-      "16",
-      "1",
-      "1",
-      "17",
-      "2",
-      "2",
-      "18",
-      "3",
-      "3",
-      "19",
-      "4",
-      "4",
-      "20",
-      "5",
-      "5"
-    ],
-    "sql": "SELECT option_id, code, value FROM rating_option WHERE rating_id = 4;",
-    "sql_execute_result": [
-      [
-        16,
-        "1",
-        1
-      ],
-      [
-        17,
-        "2",
-        2
-      ],
-      [
-        18,
-        "3",
-        3
-      ],
-      [
-        19,
-        "4",
-        4
-      ],
-      [
-        20,
-        "5",
-        5
-      ]
-    ]
-  },
-  {
-    "question": "How many units of 'Impulse Duffle' were ordered in January 2023?",
-    "answer": [
-      "2.0000",
-      "2.0000"
-    ],
-    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Impulse Duffle' AND period = '2023-01-01';",
-    "sql_execute_result": [
-      [
-        "2.0000"
-      ],
-      [
-        "2.0000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sort order for the attribute option with ID 179.",
-    "answer": [
-      "19"
-    ],
-    "sql": "SELECT sort_order FROM eav_attribute_option WHERE option_id = 179;",
-    "sql_execute_result": [
-      [
-        19
-      ]
-    ]
-  },
-  {
-    "question": "What is the billing telephone number for customer 'John Smith'?",
-    "answer": [
-      "2058812302",
-      "2145551212"
-    ],
-    "sql": "SELECT billing_telephone FROM customer_grid_flat WHERE name = 'John Smith';",
-    "sql_execute_result": [
-      [
-        "2058812302"
-      ],
-      [
-        "2145551212"
-      ]
-    ]
-  },
-  {
-    "question": "Find the store ID associated with the 'Autumn Pullie-S-Green' product in April 2023.",
-    "answer": [
-      "0",
-      "1"
-    ],
-    "sql": "SELECT store_id FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Autumn Pullie-S-Green' AND period = '2023-04-01';",
-    "sql_execute_result": [
-      [
-        0
-      ],
-      [
-        1
-      ]
-    ]
-  },
-  {
-    "question": "Which country has the ISO-3 code 'CIV'?",
-    "answer": [
-      "CI"
-    ],
-    "sql": "SELECT country_id FROM directory_country WHERE iso3_code = 'CIV';",
-    "sql_execute_result": [
-      [
-        "CI"
-      ]
-    ]
-  },
-  {
-    "question": "Get the billing city for customer with email 'isabella.santos@gmail.com'.",
-    "answer": [
-      "Miami"
-    ],
-    "sql": "SELECT billing_city FROM customer_grid_flat WHERE email = 'isabella.santos@gmail.com';",
-    "sql_execute_result": [
-      [
-        "Miami"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address of the customer for the shipping address on order with ID 123?",
-    "answer": [
-      "soccerfanatic22@gmail.com"
-    ],
-    "sql": "SELECT email FROM sales_order_address WHERE parent_id = 123 AND address_type = 'shipping';",
-    "sql_execute_result": [
-      [
-        "soccerfanatic22@gmail.com"
-      ]
-    ]
-  },
-  {
-    "question": "Find the SKU and name of the product with entity ID 392.",
-    "answer": [
-      "Jupiter All-Weather Trainer -L-Blue"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE entity_id = 392 AND attribute_id = 73;",
-    "sql_execute_result": [
-      [
-        "Jupiter All-Weather Trainer -L-Blue"
-      ]
-    ]
-  },
-  {
-    "question": "What is the status label for the status 'pending' in the sales order status table?",
-    "answer": [
-      "Pending"
-    ],
-    "sql": "SELECT label FROM sales_order_status WHERE status = 'pending';",
-    "sql_execute_result": [
-      [
-        "Pending"
-      ]
-    ]
-  },
-  {
-    "question": "What is the option value for the option ID 52 in the attribute option value table?",
-    "answer": [
-      "Gray"
-    ],
-    "sql": "SELECT value FROM eav_attribute_option_value WHERE option_id = 52;",
-    "sql_execute_result": [
-      [
-        "Gray"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence value for the most recent invoice.",
-    "answer": [
-      "2"
-    ],
-    "sql": "SELECT sequence_value FROM sequence_invoice_1 ORDER BY sequence_value DESC LIMIT 1;",
-    "sql_execute_result": [
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the product with attribute ID 106 and store ID 0 in the catalog product entity varchar table?",
-    "answer": [
-      "container2"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_varchar WHERE attribute_id = 106 AND store_id = 0 LIMIT 1;",
-    "sql_execute_result": [
-      [
-        "container2"
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve the postcode for the billing address of order with ID 127.",
-    "answer": [
-      "60606"
-    ],
-    "sql": "SELECT postcode FROM sales_order_address WHERE parent_id = 127 AND address_type = 'billing';",
-    "sql_execute_result": [
-      [
-        "60606"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name associated with the attribute option value ID 66?",
-    "answer": [
-      "Shoulder"
-    ],
-    "sql": "SELECT value FROM eav_attribute_option_value WHERE value_id = 66;",
-    "sql_execute_result": [
-      [
-        "Shoulder"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total number of quotes for the customer with email 'john.smith.xyz@gmail.com'.",
-    "answer": [
-      "26"
-    ],
-    "sql": "SELECT COUNT(*) FROM sales_order_address WHERE email = 'john.smith.xyz@gmail.com';",
-    "sql_execute_result": [
-      [
-        26
-      ]
-    ]
-  },
-  {
-    "question": "What is the label for the sales order status 'paypal_canceled_reversal'?",
-    "answer": [
-      "PayPal Canceled Reversal"
-    ],
-    "sql": "SELECT label FROM sales_order_status WHERE status = 'paypal_canceled_reversal';",
-    "sql_execute_result": [
-      [
-        "PayPal Canceled Reversal"
-      ]
-    ]
-  },
-  {
-    "question": "What is the name of the region with code 'VD' in Switzerland?",
-    "answer": [
-      "Vaud"
-    ],
-    "sql": "SELECT default_name FROM directory_country_region WHERE code = 'VD' AND country_id = 'CH';",
-    "sql_execute_result": [
-      [
-        "Vaud"
-      ]
-    ]
-  },
-  {
-    "question": "Find the entity type associated with meta ID 5 in the sales sequence meta table.",
-    "answer": [
-      "order"
-    ],
-    "sql": "SELECT entity_type FROM sales_sequence_meta WHERE meta_id = 5;",
-    "sql_execute_result": [
-      [
-        "order"
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve the description for the product with entity ID 508.",
-    "answer": [
-      "<p>Like it's v-neck counterpart, the crew-neck Atomic Tee will get you to your goal and beyond with its many load-bearing features: ultra-lightweight, moisture-wicking Cocona&reg; fabric, chafe-free flatlock seams and an ergonomic cut that moves with your body.</p>\n<p>&bull; Red polyester tee.<br />&bull; Crew neckline. <br />&bull; Cocona&reg; performance fabric. <br />&bull; Machine wash/dry.</p>"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 508 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>Like it's v-neck counterpart, the crew-neck Atomic Tee will get you to your goal and beyond with its many load-bearing features: ultra-lightweight, moisture-wicking Cocona&reg; fabric, chafe-free flatlock seams and an ergonomic cut that moves with your body.</p>\n<p>&bull; Red polyester tee.<br />&bull; Crew neckline. <br />&bull; Cocona&reg; performance fabric. <br />&bull; Machine wash/dry.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "What is the ISO3 code for the country with ISO2 code 'IT'?",
-    "answer": [
-      "ITA"
-    ],
-    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'IT';",
-    "sql_execute_result": [
-      [
-        "ITA"
-      ]
-    ]
-  },
-  {
-    "question": "Find the sequence table associated with the meta ID 8 for shipments.",
-    "answer": [
-      "sequence_shipment_1"
-    ],
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE meta_id = 8 AND entity_type = 'shipment';",
-    "sql_execute_result": [
-      [
-        "sequence_shipment_1"
-      ]
-    ]
-  },
-  {
-    "question": "What is the next sequence value for invoice in store ID 1?",
-    "answer": [
-      "2"
-    ],
-    "sql": "SELECT sequence_value FROM sequence_invoice_1 ORDER BY sequence_value DESC LIMIT 1;",
-    "sql_execute_result": [
-      [
-        2
-      ]
-    ]
-  },
-  {
-    "question": "How many regions are in the country with ID 'EC'?",
-    "answer": [
-      "24"
-    ],
-    "sql": "SELECT default_name FROM directory_country_region WHERE country_id = 'EC';",
-    "sql_execute_result": [
-      [
-        "Azuay"
-      ],
-      [
-        "Bol\u00edvar"
-      ],
-      [
-        "Ca\u00f1ar"
-      ],
-      [
-        "Carchi"
-      ],
-      [
-        "Chimborazo"
-      ],
-      [
-        "Cotopaxi"
-      ],
-      [
-        "El Oro"
-      ],
-      [
-        "Esmeraldas"
-      ],
-      [
-        "Gal\u00e1pagos"
-      ],
-      [
-        "Guayas"
-      ],
-      [
-        "Imbabura"
-      ],
-      [
-        "Loja"
-      ],
-      [
-        "Los R\u00edos"
-      ],
-      [
-        "Manab\u00ed"
-      ],
-      [
-        "Morona Santiago"
-      ],
-      [
-        "Napo"
-      ],
-      [
-        "Orellana"
-      ],
-      [
-        "Pastaza"
-      ],
-      [
-        "Pichincha"
-      ],
-      [
-        "Santa Elena"
-      ],
-      [
-        "Santo Domingo de los Ts\u00e1chilas"
-      ],
-      [
-        "Sucumb\u00edos"
-      ],
-      [
-        "Tungurahua"
-      ],
-      [
-        "Zamora Chinchipe"
-      ]
-    ]
-  },
-  {
-    "question": "What are the attribute IDs linked to the product entity ID 654 in the catalog product entity text table?",
-    "answer": [
-      "75",
-      "139",
-      "152",
-      "155",
-      "156"
-    ],
-    "sql": "SELECT attribute_id FROM catalog_product_entity_text WHERE entity_id = 654;",
-    "sql_execute_result": [
-      [
-        75
-      ],
-      [
-        139
-      ],
-      [
-        152
-      ],
-      [
-        155
-      ],
-      [
-        156
-      ]
-    ]
-  },
-  {
-    "question": "Retrieve the full description text for the product with entity ID 517.",
-    "answer": [
-      "<p>The Balboa Persistence Tee is a must-have for any athlete, Philadelphia or elsewhere. We took the best of performance apparel, cut the fluff and boiled it down to the basics for a lightweight, quick-drying t-shirt.</p>\n<p>&bull; Crew neckline. <br />&bull; Semi-fitted. <br />&bull; Cocona&reg; performance fabric. <br />&bull; Machine wash/dry.</p>"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 517 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>The Balboa Persistence Tee is a must-have for any athlete, Philadelphia or elsewhere. We took the best of performance apparel, cut the fluff and boiled it down to the basics for a lightweight, quick-drying t-shirt.</p>\n<p>&bull; Crew neckline. <br />&bull; Semi-fitted. <br />&bull; Cocona&reg; performance fabric. <br />&bull; Machine wash/dry.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "What is the sequence table for creditmemo in store ID 0?",
-    "answer": [
-      "sequence_creditmemo_0"
-    ],
-    "sql": "SELECT sequence_table FROM sales_sequence_meta WHERE meta_id = 3 AND store_id = 0;",
-    "sql_execute_result": [
-      [
-        "sequence_creditmemo_0"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for customer with ID 5?",
-    "answer": [
-      "helloworld@yahoo.com"
-    ],
-    "sql": "SELECT customer_email FROM sales_order WHERE customer_id = 5 LIMIT 1;",
-    "sql_execute_result": [
-      [
-        "helloworld@yahoo.com"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were found for customer 'Grace Nguyen'?",
-    "answer": [
-      "15"
-    ],
-    "sql": "SELECT entity_id FROM sales_order WHERE customer_firstname = 'Grace' AND customer_lastname = 'Nguyen';",
-    "sql_execute_result": [
-      [
-        5
-      ],
-      [
-        11
-      ],
-      [
-        16
-      ],
-      [
-        32
-      ],
-      [
-        65
-      ],
-      [
-        80
-      ],
-      [
-        85
-      ],
-      [
-        114
-      ],
-      [
-        126
-      ],
-      [
-        166
-      ],
-      [
-        183
-      ],
-      [
-        189
-      ],
-      [
-        300
-      ],
-      [
-        307
-      ],
-      [
-        308
-      ]
-    ]
-  },
-  {
-    "question": "What is the status of the order with increment ID '000000248'?",
-    "answer": [
-      "canceled"
-    ],
-    "sql": "SELECT status FROM sales_order WHERE increment_id = '000000248';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total grand total for orders with the status 'complete'?",
-    "answer": [
-      "20625.5000"
-    ],
-    "sql": "SELECT SUM(grand_total) AS total_grand_total FROM sales_order WHERE status = 'complete';",
-    "sql_execute_result": [
-      [
-        "20625.5000"
-      ]
-    ]
-  },
-  {
-    "question": "Find the text description for product with entity ID 1599.",
-    "answer": [
-      "<p>A heavenly soft and stylish eco garment, the Electra Bra Top is perfect for wearing on its own as a hot yoga top or layered under a tank.</p>\n<p>&bull; Gray rouched bra top.<br />&bull; Attractive back straps feature contrasting motif fabric.<br />&bull; Interior bra top is lined with breathable mesh.<br />&bull; Elastic underband for superior support.<br />&bull; Removable cup inserts.<br />&bull; Chafe-free flat lock seams provide added comfort.</p>"
-    ],
-    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 1599 AND attribute_id = 75;",
-    "sql_execute_result": [
-      [
-        "<p>A heavenly soft and stylish eco garment, the Electra Bra Top is perfect for wearing on its own as a hot yoga top or layered under a tank.</p>\n<p>&bull; Gray rouched bra top.<br />&bull; Attractive back straps feature contrasting motif fabric.<br />&bull; Interior bra top is lined with breathable mesh.<br />&bull; Elastic underband for superior support.<br />&bull; Removable cup inserts.<br />&bull; Chafe-free flat lock seams provide added comfort.</p>"
-      ]
-    ]
-  },
-  {
-    "question": "Find the total quantity ordered for customer with email 'avidreader99@yahoo.com'.",
-    "answer": [
-      "3.0000"
-    ],
-    "sql": "SELECT total_qty_ordered FROM sales_order WHERE customer_email = 'avidreader99@yahoo.com' LIMIT 1;",
-    "sql_execute_result": [
-      [
-        "3.0000"
-      ]
-    ]
-  },
-  {
-    "question": "How many order statuses were found?",
-    "answer": [
-      "12"
-    ],
-    "sql": "SELECT label FROM sales_order_status;",
-    "sql_execute_result": [
-      [
-        "Canceled"
-      ],
-      [
-        "Closed"
-      ],
-      [
-        "Complete"
-      ],
-      [
-        "Suspected Fraud"
-      ],
-      [
-        "On Hold"
-      ],
-      [
-        "Payment Review"
-      ],
-      [
-        "PayPal Canceled Reversal"
-      ],
-      [
-        "PayPal Reversed"
-      ],
-      [
-        "Pending"
-      ],
-      [
-        "Pending Payment"
-      ],
-      [
-        "Pending PayPal"
-      ],
-      [
-        "Processing"
-      ]
-    ]
-  },
-  {
-    "question": "What is the shipping method for order ID 199?",
-    "answer": [
-      "flatrate_flatrate"
-    ],
-    "sql": "SELECT shipping_method FROM sales_order WHERE entity_id = 199;",
-    "sql_execute_result": [
-      [
-        "flatrate_flatrate"
-      ]
-    ]
-  },
-  {
-    "question": "What is the email address for the customer with ID 31?",
-    "answer": [
-      "jason.miller@yahoo.com"
-    ],
-    "sql": "SELECT customer_email FROM sales_order_grid WHERE customer_id = 31;",
-    "sql_execute_result": [
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ],
-      [
-        "jason.miller@yahoo.com"
-      ]
-    ]
-  },
-  {
-    "question": "How many orders were found for the customer with email 'john.smith.xyz@gmail.com'?",
-    "answer": [
-      "13"
-    ],
-    "sql": "SELECT increment_id FROM sales_order_grid WHERE customer_email = 'john.smith.xyz@gmail.com';",
-    "sql_execute_result": [
-      [
-        "000000009"
-      ],
-      [
-        "000000059"
-      ],
-      [
-        "000000068"
-      ],
-      [
-        "000000079"
-      ],
-      [
-        "000000093"
-      ],
-      [
-        "000000095"
-      ],
-      [
-        "000000096"
-      ],
-      [
-        "000000107"
-      ],
-      [
-        "000000115"
-      ],
-      [
-        "000000144"
-      ],
-      [
-        "000000217"
-      ],
-      [
-        "000000257"
-      ],
-      [
-        "000000273"
-      ]
-    ]
-  },
-  {
-    "question": "Find the status of the order with increment ID '000000152'.",
-    "answer": [
-      "canceled"
-    ],
-    "sql": "SELECT status FROM sales_order_grid WHERE increment_id = '000000152';",
-    "sql_execute_result": [
-      [
-        "canceled"
-      ]
-    ]
-  },
-  {
-    "question": "What is the total quantity shipped for the shipment with increment ID '000000003'?",
-    "answer": [
-      "2.0000"
-    ],
-    "sql": "SELECT total_qty FROM sales_shipment WHERE increment_id = '000000003';",
-    "sql_execute_result": [
-      [
-        "2.0000"
-      ]
-    ]
-  },
-  {
-    "question": "List all reviews for the product with ID 1990.",
-    "answer": [
-      "296",
-      "297"
-    ],
-    "sql": "SELECT review_id FROM review WHERE entity_pk_value = 1990;",
-    "sql_execute_result": [
-      [
-        296
-      ],
-      [
-        297
-      ]
-    ]
-  },
-  {
-    "question": "What is the rating value for the review with ID 59?",
-    "answer": [
-      "4"
-    ],
-    "sql": "SELECT value FROM rating_option_vote WHERE review_id = 59;",
-    "sql_execute_result": [
-      [
-        4
-      ]
-    ]
-  },
-  {
-    "question": "Find the store name for the order with increment ID '000000013'.",
-    "answer": [
-      "Main Website\nMain Website Store\nDefault Store View"
-    ],
-    "sql": "SELECT store_name FROM sales_order_grid WHERE increment_id = '000000013';",
-    "sql_execute_result": [
-      [
-        "Main Website\nMain Website Store\nDefault Store View"
-      ]
-    ]
-  },
-  {
-    "question": "What is the shipping method for the order with ID 68?",
-    "answer": [
-      "Flat Rate - Fixed"
-    ],
-    "sql": "SELECT shipping_information FROM sales_order_grid WHERE entity_id = 68;",
-    "sql_execute_result": [
-      [
-        "Flat Rate - Fixed"
-      ]
-    ]
-  },
-  {
-    "question": "Find the status for the review with ID 263.",
-    "answer": [
-      "1"
-    ],
-    "sql": "SELECT status_id FROM review WHERE review_id = 263;",
-    "sql_execute_result": [
-      [
-        1
-      ]
-    ]
-  }
-]
\ No newline at end of file
diff --git a/random_sample/requirements.txt b/random_sample/requirements.txt
new file mode 100644
index 0000000..78204fa
--- /dev/null
+++ b/random_sample/requirements.txt
@@ -0,0 +1,3 @@
+mysql-connector==2.2.9
+openai
+dotenv
\ No newline at end of file
diff --git a/random_sample/tes1.json b/random_sample/tes1.json
new file mode 100644
index 0000000..a3ac9d7
--- /dev/null
+++ b/random_sample/tes1.json
@@ -0,0 +1,1088 @@
+[
+  {
+    "question": "What is the email address for the customer with ID 8?",
+    "sql": "SELECT email FROM customer_entity WHERE entity_id = 8;",
+    "answer": [
+      "marym@gmail.com"
+    ],
+    "sql_execute_result": [
+      [
+        "marym@gmail.com"
+      ]
+    ]
+  },
+  {
+    "question": "How many products are in the category with ID 32?",
+    "sql": "SELECT product_id FROM catalog_category_product WHERE category_id = 32;",
+    "answer": [
+      "247"
+    ],
+    "sql_execute_result": [
+      [
+        725
+      ],
+      [
+        726
+      ],
+      [
+        727
+      ],
+      [
+        728
+      ],
+      [
+        729
+      ],
+      [
+        730
+      ],
+      [
+        731
+      ],
+      [
+        732
+      ],
+      [
+        733
+      ],
+      [
+        734
+      ],
+      [
+        735
+      ],
+      [
+        736
+      ],
+      [
+        737
+      ],
+      [
+        738
+      ],
+      [
+        739
+      ],
+      [
+        740
+      ],
+      [
+        741
+      ],
+      [
+        742
+      ],
+      [
+        743
+      ],
+      [
+        744
+      ],
+      [
+        745
+      ],
+      [
+        746
+      ],
+      [
+        747
+      ],
+      [
+        748
+      ],
+      [
+        749
+      ],
+      [
+        750
+      ],
+      [
+        751
+      ],
+      [
+        752
+      ],
+      [
+        753
+      ],
+      [
+        754
+      ],
+      [
+        755
+      ],
+      [
+        756
+      ],
+      [
+        757
+      ],
+      [
+        758
+      ],
+      [
+        759
+      ],
+      [
+        760
+      ],
+      [
+        761
+      ],
+      [
+        762
+      ],
+      [
+        763
+      ],
+      [
+        764
+      ],
+      [
+        765
+      ],
+      [
+        766
+      ],
+      [
+        767
+      ],
+      [
+        768
+      ],
+      [
+        769
+      ],
+      [
+        770
+      ],
+      [
+        771
+      ],
+      [
+        772
+      ],
+      [
+        773
+      ],
+      [
+        774
+      ],
+      [
+        775
+      ],
+      [
+        776
+      ],
+      [
+        777
+      ],
+      [
+        778
+      ],
+      [
+        779
+      ],
+      [
+        780
+      ],
+      [
+        781
+      ],
+      [
+        782
+      ],
+      [
+        783
+      ],
+      [
+        784
+      ],
+      [
+        785
+      ],
+      [
+        786
+      ],
+      [
+        787
+      ],
+      [
+        788
+      ],
+      [
+        789
+      ],
+      [
+        790
+      ],
+      [
+        791
+      ],
+      [
+        792
+      ],
+      [
+        793
+      ],
+      [
+        794
+      ],
+      [
+        795
+      ],
+      [
+        796
+      ],
+      [
+        797
+      ],
+      [
+        798
+      ],
+      [
+        799
+      ],
+      [
+        800
+      ],
+      [
+        801
+      ],
+      [
+        802
+      ],
+      [
+        803
+      ],
+      [
+        804
+      ],
+      [
+        805
+      ],
+      [
+        806
+      ],
+      [
+        807
+      ],
+      [
+        808
+      ],
+      [
+        809
+      ],
+      [
+        810
+      ],
+      [
+        811
+      ],
+      [
+        812
+      ],
+      [
+        813
+      ],
+      [
+        814
+      ],
+      [
+        815
+      ],
+      [
+        816
+      ],
+      [
+        817
+      ],
+      [
+        818
+      ],
+      [
+        819
+      ],
+      [
+        820
+      ],
+      [
+        821
+      ],
+      [
+        822
+      ],
+      [
+        823
+      ],
+      [
+        824
+      ],
+      [
+        825
+      ],
+      [
+        826
+      ],
+      [
+        827
+      ],
+      [
+        828
+      ],
+      [
+        829
+      ],
+      [
+        830
+      ],
+      [
+        831
+      ],
+      [
+        832
+      ],
+      [
+        833
+      ],
+      [
+        834
+      ],
+      [
+        835
+      ],
+      [
+        836
+      ],
+      [
+        837
+      ],
+      [
+        838
+      ],
+      [
+        839
+      ],
+      [
+        840
+      ],
+      [
+        841
+      ],
+      [
+        842
+      ],
+      [
+        843
+      ],
+      [
+        844
+      ],
+      [
+        845
+      ],
+      [
+        846
+      ],
+      [
+        847
+      ],
+      [
+        848
+      ],
+      [
+        849
+      ],
+      [
+        850
+      ],
+      [
+        851
+      ],
+      [
+        852
+      ],
+      [
+        853
+      ],
+      [
+        854
+      ],
+      [
+        855
+      ],
+      [
+        856
+      ],
+      [
+        857
+      ],
+      [
+        858
+      ],
+      [
+        859
+      ],
+      [
+        860
+      ],
+      [
+        861
+      ],
+      [
+        862
+      ],
+      [
+        863
+      ],
+      [
+        864
+      ],
+      [
+        865
+      ],
+      [
+        866
+      ],
+      [
+        867
+      ],
+      [
+        868
+      ],
+      [
+        869
+      ],
+      [
+        870
+      ],
+      [
+        871
+      ],
+      [
+        872
+      ],
+      [
+        873
+      ],
+      [
+        874
+      ],
+      [
+        875
+      ],
+      [
+        876
+      ],
+      [
+        877
+      ],
+      [
+        878
+      ],
+      [
+        879
+      ],
+      [
+        880
+      ],
+      [
+        1813
+      ],
+      [
+        1814
+      ],
+      [
+        1815
+      ],
+      [
+        1816
+      ],
+      [
+        1817
+      ],
+      [
+        1818
+      ],
+      [
+        1819
+      ],
+      [
+        1820
+      ],
+      [
+        1821
+      ],
+      [
+        1822
+      ],
+      [
+        1823
+      ],
+      [
+        1824
+      ],
+      [
+        1825
+      ],
+      [
+        1826
+      ],
+      [
+        1827
+      ],
+      [
+        1828
+      ],
+      [
+        1829
+      ],
+      [
+        1830
+      ],
+      [
+        1831
+      ],
+      [
+        1832
+      ],
+      [
+        1833
+      ],
+      [
+        1834
+      ],
+      [
+        1835
+      ],
+      [
+        1836
+      ],
+      [
+        1837
+      ],
+      [
+        1838
+      ],
+      [
+        1839
+      ],
+      [
+        1840
+      ],
+      [
+        1841
+      ],
+      [
+        1842
+      ],
+      [
+        1843
+      ],
+      [
+        1844
+      ],
+      [
+        1845
+      ],
+      [
+        1846
+      ],
+      [
+        1847
+      ],
+      [
+        1848
+      ],
+      [
+        1849
+      ],
+      [
+        1850
+      ],
+      [
+        1851
+      ],
+      [
+        1852
+      ],
+      [
+        1853
+      ],
+      [
+        1854
+      ],
+      [
+        1855
+      ],
+      [
+        1856
+      ],
+      [
+        1857
+      ],
+      [
+        1858
+      ],
+      [
+        1859
+      ],
+      [
+        1860
+      ],
+      [
+        1861
+      ],
+      [
+        1862
+      ],
+      [
+        1863
+      ],
+      [
+        1864
+      ],
+      [
+        1865
+      ],
+      [
+        1866
+      ],
+      [
+        1867
+      ],
+      [
+        1868
+      ],
+      [
+        1869
+      ],
+      [
+        1870
+      ],
+      [
+        1871
+      ],
+      [
+        1872
+      ],
+      [
+        1873
+      ],
+      [
+        1874
+      ],
+      [
+        1875
+      ],
+      [
+        1876
+      ],
+      [
+        1877
+      ],
+      [
+        1878
+      ],
+      [
+        1879
+      ],
+      [
+        1880
+      ],
+      [
+        1881
+      ],
+      [
+        1882
+      ],
+      [
+        1883
+      ],
+      [
+        1884
+      ],
+      [
+        1885
+      ],
+      [
+        1886
+      ],
+      [
+        1887
+      ],
+      [
+        1888
+      ],
+      [
+        1889
+      ],
+      [
+        1890
+      ],
+      [
+        1891
+      ],
+      [
+        1892
+      ],
+      [
+        1893
+      ],
+      [
+        1894
+      ],
+      [
+        1895
+      ],
+      [
+        1896
+      ],
+      [
+        1897
+      ],
+      [
+        1898
+      ],
+      [
+        1899
+      ],
+      [
+        1900
+      ],
+      [
+        1901
+      ],
+      [
+        1902
+      ],
+      [
+        1903
+      ]
+    ]
+  },
+  {
+    "question": "What is the SKU for the product with entity ID 1805?",
+    "sql": "SELECT sku FROM catalog_product_entity WHERE entity_id = 1805;",
+    "answer": [
+      "WT09-M-Yellow"
+    ],
+    "sql_execute_result": [
+      [
+        "WT09-M-Yellow"
+      ]
+    ]
+  },
+  {
+    "question": "How many orders have been placed by the customer named 'Jane Doe'?",
+    "sql": "SELECT COUNT(*) FROM sales_order WHERE customer_id = 46;",
+    "answer": [
+      "0"
+    ],
+    "sql_execute_result": [
+      [
+        0
+      ]
+    ]
+  },
+  {
+    "question": "What is the total quantity of product with SKU 'BRT-001' currently in stock?",
+    "sql": "SELECT qty FROM cataloginventory_stock_item WHERE product_id = 1805;",
+    "answer": [
+      "100.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "100.0000"
+      ]
+    ]
+  },
+  {
+    "question": "Find the description of the product with entity ID 764.",
+    "sql": "SELECT value FROM catalog_product_entity_text WHERE entity_id = 764 AND attribute_id = 75;",
+    "answer": [
+      "<p>Turn the corner and open it up -- your driveway is two blocks away. The Supernova Sport Pant gets you there with key features like moisture-wicking LumaTech&trade; fabric and mesh ventilation. Side seam pockets ensure total convenience during rest periods.</p>\n<p>&bull; Dark heather gray straight leg cotton pants.<br />&bull; Relaxed fit. <br />&bull; Internal drawstring. <br />&bull; Machine wash/dry.</p>"
+    ],
+    "sql_execute_result": [
+      [
+        "<p>Turn the corner and open it up -- your driveway is two blocks away. The Supernova Sport Pant gets you there with key features like moisture-wicking LumaTech&trade; fabric and mesh ventilation. Side seam pockets ensure total convenience during rest periods.</p>\n<p>&bull; Dark heather gray straight leg cotton pants.<br />&bull; Relaxed fit. <br />&bull; Internal drawstring. <br />&bull; Machine wash/dry.</p>"
+      ]
+    ]
+  },
+  {
+    "question": "What is the billing address for the order with parent ID 279?",
+    "sql": "SELECT CONCAT(street, ', ', city, ', ', region, ', ', postcode, ', ', country_id) FROM sales_order_address WHERE parent_id = 279 AND address_type = 'billing';",
+    "answer": [
+      "123 Main St, Dallas, Texas, 75201, US"
+    ],
+    "sql_execute_result": [
+      [
+        "123 Main St, Dallas, Texas, 75201, US"
+      ]
+    ]
+  },
+  {
+    "question": "How many units of the product with SKU 'WS08-XS-Blue' are in stock?",
+    "sql": "SELECT qty FROM cataloginventory_stock_item JOIN catalog_product_entity ON cataloginventory_stock_item.product_id = catalog_product_entity.entity_id WHERE catalog_product_entity.sku = 'WS08-XS-Blue';",
+    "answer": [
+      "3"
+    ],
+    "sql_execute_result": [
+      [
+        "3.0000"
+      ]
+    ]
+  },
+  {
+    "question": "Which customer groups are available?",
+    "sql": "SELECT customer_group_code FROM customer_group;",
+    "answer": [
+      "NOT LOGGED IN",
+      "General",
+      "Wholesale",
+      "Retailer"
+    ],
+    "sql_execute_result": [
+      [
+        "NOT LOGGED IN"
+      ],
+      [
+        "General"
+      ],
+      [
+        "Wholesale"
+      ],
+      [
+        "Retailer"
+      ]
+    ]
+  },
+  {
+    "question": "What is the price including tax for 'Iris Workout Top'?",
+    "sql": "SELECT price_incl_tax FROM sales_invoice_item WHERE name = 'Iris Workout Top';",
+    "answer": [
+      "31.3900"
+    ],
+    "sql_execute_result": [
+      [
+        "31.3900"
+      ]
+    ]
+  },
+  {
+    "question": "Find the region name for region ID 1023 in the US locale.",
+    "sql": "SELECT name FROM directory_country_region_name WHERE region_id = 1023 AND locale = 'en_US';",
+    "answer": [
+      "\u015bwi\u0119tokrzyskie"
+    ],
+    "sql_execute_result": [
+      [
+        "\u015bwi\u0119tokrzyskie"
+      ]
+    ]
+  },
+  {
+    "question": "How many unique billing addresses for orders shipped to California were found?",
+    "sql": "SELECT CONCAT(street, ', ', city, ', ', region, ', ', postcode, ', ', country_id) FROM sales_order_address WHERE region = 'California' AND address_type = 'billing';",
+    "answer": [
+      "7"
+    ],
+    "sql_execute_result": [
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "789 W Olympic Blvd, Los Angeles, California, 90015, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "123 Malibu Beach Road, Malibu, California, 90265, US"
+      ],
+      [
+        "456 Beverly Hills Blvd, Beverly Hills, California, 90210, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "321 Maple Avenue, Oakland, California, 94602, US"
+      ],
+      [
+        "789 Rodeo Drive, Beverly Hills, California, 90212, US"
+      ],
+      [
+        "456 Hollywood Blvd, Los Angeles, California, 90028, US"
+      ]
+    ]
+  }
+]
\ No newline at end of file
diff --git a/random_sample/test1.json b/random_sample/test1.json
new file mode 100644
index 0000000..3bd8edb
--- /dev/null
+++ b/random_sample/test1.json
@@ -0,0 +1,282 @@
+[
+  {
+    "question": "What is the total income amount for orders completed on February 14, 2022, in store 1?",
+    "sql": "SELECT total_income_amount FROM sales_order_aggregated_created WHERE period = '2022-02-14' AND store_id = 1 AND order_status = 'complete';",
+    "answer": [
+      "240.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "240.0000"
+      ]
+    ]
+  },
+  {
+    "question": "Find the email address for the shipping address with entity ID 197.",
+    "sql": "SELECT email FROM sales_order_address WHERE entity_id = 197;",
+    "answer": [
+      "janesmith456@yahoo.com"
+    ],
+    "sql_execute_result": [
+      [
+        "janesmith456@yahoo.com"
+      ]
+    ]
+  },
+  {
+    "question": "What is the name of the product with ID 16 that was a bestseller in March 2023?",
+    "sql": "SELECT product_name FROM sales_bestsellers_aggregated_monthly WHERE product_id = 16 AND period = '2023-03-01';",
+    "answer": [
+      "Dual Handle Cardio Ball"
+    ],
+    "sql_execute_result": [
+      [
+        "Dual Handle Cardio Ball"
+      ],
+      [
+        "Dual Handle Cardio Ball"
+      ]
+    ]
+  },
+  {
+    "question": "What is the value associated with the attribute option ID 80?",
+    "sql": "SELECT value FROM eav_attribute_option_value WHERE option_id = 80;",
+    "answer": [
+      "Men"
+    ],
+    "sql_execute_result": [
+      [
+        "Men"
+      ]
+    ]
+  },
+  {
+    "question": "Find the percentage rating for the review with ID 219.",
+    "sql": "SELECT percent FROM rating_option_vote WHERE review_id = 219;",
+    "answer": [
+      "100"
+    ],
+    "sql_execute_result": [
+      [
+        100
+      ]
+    ]
+  },
+  {
+    "question": "What is the total shipping amount for orders completed on July 1, 2022, in store 0?",
+    "sql": "SELECT total_shipping_amount FROM sales_order_aggregated_created WHERE period = '2022-07-01' AND store_id = 0 AND order_status = 'complete';",
+    "answer": [
+      "15.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "15.0000"
+      ]
+    ]
+  },
+  {
+    "question": "What is the product price for the 'Zoe Tank-S-Yellow' that was a bestseller in January 2023?",
+    "sql": "SELECT product_price FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Zoe Tank-S-Yellow' AND period = '2023-01-01';",
+    "answer": [
+      "29.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "29.0000"
+      ],
+      [
+        "29.0000"
+      ]
+    ]
+  },
+  {
+    "question": "Find the total quantity ordered for orders that were canceled on February 24, 2023, in store 1.",
+    "sql": "SELECT total_qty_ordered FROM sales_order_aggregated_created WHERE period = '2023-02-24' AND store_id = 1 AND order_status = 'canceled';",
+    "answer": [
+      "5.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "5.0000"
+      ]
+    ]
+  },
+  {
+    "question": "What is the region associated with the sales order address with entity ID 228?",
+    "sql": "SELECT region FROM sales_order_address WHERE entity_id = 228;",
+    "answer": [
+      "Massachusetts"
+    ],
+    "sql_execute_result": [
+      [
+        "Massachusetts"
+      ]
+    ]
+  },
+  {
+    "question": "Find the rating position for the product 'Sinbad Fitness Tank-M-Blue' in October 2022.",
+    "sql": "SELECT rating_pos FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Sinbad Fitness Tank-M-Blue' AND period = '2022-10-01';",
+    "answer": [
+      "5",
+      "2"
+    ],
+    "sql_execute_result": [
+      [
+        5
+      ],
+      [
+        2
+      ]
+    ]
+  },
+  {
+    "question": "What is the ISO-3 code for the country with ISO-2 code 'VC'?",
+    "sql": "SELECT iso3_code FROM directory_country WHERE iso2_code = 'VC';",
+    "answer": [
+      "VCT"
+    ],
+    "sql_execute_result": [
+      [
+        "VCT"
+      ]
+    ]
+  },
+  {
+    "question": "How many orders were completed on 2022-01-17 in the default store?",
+    "sql": "SELECT orders_count FROM sales_order_aggregated_created WHERE period = '2022-01-17' AND store_id = 0 AND order_status = 'complete';",
+    "answer": [
+      "2"
+    ],
+    "sql_execute_result": [
+      [
+        2
+      ]
+    ]
+  },
+  {
+    "question": "Find the total quantity ordered for the product 'Gobi HeatTec\u00ae Tee-XS-Orange' in April 2023.",
+    "sql": "SELECT qty_ordered FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Gobi HeatTec&reg; Tee-XS-Orange' AND period = '2023-04-01';",
+    "answer": [
+      "4.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "2.0000"
+      ],
+      [
+        "2.0000"
+      ]
+    ]
+  },
+  {
+    "question": "What is the product price for 'Cora Parachute Pant-29-Blue' in April 2023?",
+    "sql": "SELECT product_price FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Cora Parachute Pant-29-Blue' AND period = '2023-04-01';",
+    "answer": [
+      "60.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "60.0000"
+      ],
+      [
+        "60.0000"
+      ]
+    ]
+  },
+  {
+    "question": "List all countries that have an ISO-2 code starting with 'F'.",
+    "sql": "SELECT country_id FROM directory_country WHERE iso2_code LIKE 'F%';",
+    "answer": [
+      "FI",
+      "FJ",
+      "FK",
+      "FM",
+      "FO",
+      "FR"
+    ],
+    "sql_execute_result": [
+      [
+        "FI"
+      ],
+      [
+        "FJ"
+      ],
+      [
+        "FK"
+      ],
+      [
+        "FM"
+      ],
+      [
+        "FO"
+      ],
+      [
+        "FR"
+      ]
+    ]
+  },
+  {
+    "question": "What is the rating position of 'Lando Gym Jacket-XS-Green' in May 2022?",
+    "sql": "SELECT rating_pos FROM sales_bestsellers_aggregated_monthly WHERE product_name = 'Lando Gym Jacket-XS-Green' AND period = '2022-05-01';",
+    "answer": [
+      "5",
+      "18"
+    ],
+    "sql_execute_result": [
+      [
+        5
+      ],
+      [
+        18
+      ]
+    ]
+  },
+  {
+    "question": "How many products have a value of '2' for attribute ID 136 in the default store?",
+    "sql": "SELECT COUNT(*) FROM catalog_product_entity_int WHERE attribute_id = 136 AND store_id = 0 AND value = 2;",
+    "answer": [
+      "2038"
+    ],
+    "sql_execute_result": [
+      [
+        2038
+      ]
+    ]
+  },
+  {
+    "question": "Find the period for the order with ID 1003.",
+    "sql": "SELECT period FROM sales_order_aggregated_created WHERE id = 1003;",
+    "answer": [
+      "2023-01-13"
+    ],
+    "sql_execute_result": [
+      [
+        "2023-01-13"
+      ]
+    ]
+  },
+  {
+    "question": "What is the total income amount for orders on 2022-09-23 in store ID 1?",
+    "sql": "SELECT total_income_amount FROM sales_order_aggregated_created WHERE period = '2022-09-23' AND store_id = 1;",
+    "answer": [
+      "210.0000"
+    ],
+    "sql_execute_result": [
+      [
+        "210.0000"
+      ]
+    ]
+  },
+  {
+    "question": "Find the sequence value for the latest shipment entry.",
+    "sql": "SELECT sequence_value FROM sequence_shipment_1 ORDER BY sequence_value DESC LIMIT 1;",
+    "answer": [
+      "3"
+    ],
+    "sql_execute_result": [
+      [
+        3
+      ]
+    ]
+  }
+]
\ No newline at end of file
diff --git a/scripts/portforward.sh b/scripts/portforward.sh
index 7ab957b..032c8e0 100644
--- a/scripts/portforward.sh
+++ b/scripts/portforward.sh
@@ -1,5 +1,5 @@
 # 用于将网站的mysql端口转发到本地，保证稳定性
 autossh -M 0 -f -N -o "ServerAliveInterval 30" \
         -o "ServerAliveCountMax 3" \
-        -L 23306:localhost:23306 yuyr@g14_jump2
+        -L 23306:localhost:23306 yuyr@g14