nateraw/sqlcoder-70b-alpha 🔢📝✓ → 📝
Example Output
Output
SELECT c.address, SUM(s.quantity) AS total_sales FROM sales s JOIN customers c ON s.customer_id = c.customer_id GROUP BY c.address ORDER BY total_sales DESC NULLS LAST;
Performance Metrics
7.14s
Prediction Time
7.14s
Total Time
All Input Parameters
{
"top_k": 50,
"top_p": 0.95,
"question": "Do we get more sales from customers in New York compared to customers in San Francisco? Give me the total sales for each city, and the difference between the two.",
"do_sample": false,
"temperature": 0,
"max_new_tokens": 512,
"table_metadata": "CREATE TABLE products (\n product_id INTEGER PRIMARY KEY, -- Unique ID for each product\n name VARCHAR(50), -- Name of the product\n price DECIMAL(10,2), -- Price of each unit of the product\n quantity INTEGER -- Current quantity in stock\n);\n\nCREATE TABLE customers (\n customer_id INTEGER PRIMARY KEY, -- Unique ID for each customer\n name VARCHAR(50), -- Name of the customer\n address VARCHAR(100) -- Mailing address of the customer\n);\n\nCREATE TABLE salespeople (\n salesperson_id INTEGER PRIMARY KEY, -- Unique ID for each salesperson \n name VARCHAR(50), -- Name of the salesperson\n region VARCHAR(50) -- Geographic sales region \n);\n\nCREATE TABLE sales (\n sale_id INTEGER PRIMARY KEY, -- Unique ID for each sale\n product_id INTEGER, -- ID of product sold\n customer_id INTEGER, -- ID of customer who made purchase\n salesperson_id INTEGER, -- ID of salesperson who made the sale\n sale_date DATE, -- Date the sale occurred \n quantity INTEGER -- Quantity of product sold\n);\n\nCREATE TABLE product_suppliers (\n supplier_id INTEGER PRIMARY KEY, -- Unique ID for each supplier\n product_id INTEGER, -- Product ID supplied\n supply_price DECIMAL(10,2) -- Unit price charged by supplier\n);\n\n-- sales.product_id can be joined with products.product_id\n-- sales.customer_id can be joined with customers.customer_id \n-- sales.salesperson_id can be joined with salespeople.salesperson_id\n-- product_suppliers.product_id can be joined with products.product_id",
"prompt_template": "### Task\nGenerate a SQL query to answer [QUESTION]{question}[/QUESTION]\n\n### Instructions\n- If you cannot answer the question with the available database schema, return 'I do not know'\n\n### Database Schema\nThe query will run on a database with the following schema:\n{table_metadata}\n\n### Answer\nGiven the database schema, here is the SQL query that answers [QUESTION]{question}[/QUESTION]\n[SQL]\n"
}
Input Parameters
- top_k
- The number of highest probability tokens to consider for generating the output. If > 0, only keep the top k tokens with highest probability (top-k filtering).
- top_p
- A probability threshold for generating the output. If < 1.0, only keep the top tokens with cumulative probability >= top_p (nucleus filtering). Nucleus filtering is described in Holtzman et al. (http://arxiv.org/abs/1904.09751).
- question (required)
- The question to answer with a SQL query.
- do_sample
- Whether or not to use sampling; otherwise use greedy decoding.
- temperature
- The value used to modulate the next token probabilities.
- max_new_tokens
- The maximum number of tokens the model should generate as output.
- table_metadata (required)
- The database schema to use when generating the SQL query.
- prompt_template
- The template used to format the prompt before passing it to the model. For no template, you can set this to `{prompt}`.
Output Schema
Output
Example Execution Logs
=== Formatted Prompt === ### Task Generate a SQL query to answer [QUESTION]Do we get more sales from customers in New York compared to customers in San Francisco? Give me the total sales for each city, and the difference between the two.[/QUESTION] ### Instructions - If you cannot answer the question with the available database schema, return 'I do not know' ### Database Schema The query will run on a database with the following schema: CREATE TABLE products ( product_id INTEGER PRIMARY KEY, -- Unique ID for each product name VARCHAR(50), -- Name of the product price DECIMAL(10,2), -- Price of each unit of the product quantity INTEGER -- Current quantity in stock ); CREATE TABLE customers ( customer_id INTEGER PRIMARY KEY, -- Unique ID for each customer name VARCHAR(50), -- Name of the customer address VARCHAR(100) -- Mailing address of the customer ); CREATE TABLE salespeople ( salesperson_id INTEGER PRIMARY KEY, -- Unique ID for each salesperson name VARCHAR(50), -- Name of the salesperson region VARCHAR(50) -- Geographic sales region ); CREATE TABLE sales ( sale_id INTEGER PRIMARY KEY, -- Unique ID for each sale product_id INTEGER, -- ID of product sold customer_id INTEGER, -- ID of customer who made purchase salesperson_id INTEGER, -- ID of salesperson who made the sale sale_date DATE, -- Date the sale occurred quantity INTEGER -- Quantity of product sold ); CREATE TABLE product_suppliers ( supplier_id INTEGER PRIMARY KEY, -- Unique ID for each supplier product_id INTEGER, -- Product ID supplied supply_price DECIMAL(10,2) -- Unit price charged by supplier ); -- sales.product_id can be joined with products.product_id -- sales.customer_id can be joined with customers.customer_id -- sales.salesperson_id can be joined with salespeople.salesperson_id -- product_suppliers.product_id can be joined with products.product_id ### Answer Given the database schema, here is the SQL query that answers [QUESTION]Do we get more sales from customers in New York compared to customers in San Francisco? Give me the total sales for each city, and the difference between the two.[/QUESTION] [SQL] ======================== Setting `pad_token_id` to `eos_token_id`:2 for open-end generation.
Version Details
- Version ID
d6cd1065e6982faeb224e9ccdd0811afd9e104623383268eeb2d7a5c7e7bd3b3- Version Created
- February 8, 2024