Prediction

Model

nateraw/defog-sqlcoder-7b-2:ced935b5

enm65blbgntnxuhsewbxdy2qoq

Status

Succeeded

Source

Web

Hardware

A40 (Large)

Total duration

2.6s

Created

almost 2 years ago

Webhook

–

Input

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.
table_metadata: 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
max_new_tokens: 512
temperature: 0
top_p: 0.9
top_k: 50
presence_penalty: 0
frequency_penalty: 0
prompt_template: ### Task Generate a SQL query to answer [QUESTION]{question}[/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: {table_metadata} ### Answer Given the database schema, here is the SQL query that answers [QUESTION]{question}[/QUESTION] [SQL]

{
  "frequency_penalty": 0,
  "max_new_tokens": 512,
  "presence_penalty": 0,
  "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]",
  "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.",
  "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",
  "temperature": 0,
  "top_k": 50,
  "top_p": 0.9
}

Install Replicate’s Node.js client library:

npm install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MbK**********************************

This is your API token. Keep it to yourself.

Import and set up the client:

import Replicate from "replicate";

const replicate = new Replicate({
  auth: process.env.REPLICATE_API_TOKEN,
});

Run nateraw/defog-sqlcoder-7b-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

const output = await replicate.run(
  "nateraw/defog-sqlcoder-7b-2:ced935b577fb52644d933f77e2ff8902744e4c58a2f50023b3a1db80b7a75806",
  {
    input: {
      frequency_penalty: 0,
      max_new_tokens: 512,
      presence_penalty: 0,
      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]",
      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.",
      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",
      temperature: 0,
      top_k: 50,
      top_p: 0.9
    }
  }
);

console.log(output);

To learn more, take a look at the guide on getting started with Node.js.

Install Replicate’s Python client library:

pip install replicate

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MbK**********************************

This is your API token. Keep it to yourself.

Import the client:

import replicate

Run nateraw/defog-sqlcoder-7b-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

output = replicate.run(
    "nateraw/defog-sqlcoder-7b-2:ced935b577fb52644d933f77e2ff8902744e4c58a2f50023b3a1db80b7a75806",
    input={
        "frequency_penalty": 0,
        "max_new_tokens": 512,
        "presence_penalty": 0,
        "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]",
        "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.",
        "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",
        "temperature": 0,
        "top_k": 50,
        "top_p": 0.9
    }
)

# The nateraw/defog-sqlcoder-7b-2 model can stream output as it's running.
# The predict method returns an iterator, and you can iterate over that output.
for item in output:
    # https://replicate.com/nateraw/defog-sqlcoder-7b-2/api#output-schema
    print(item, end="")

To learn more, take a look at the guide on getting started with Python.

Set the REPLICATE_API_TOKEN environment variable:

export REPLICATE_API_TOKEN=r8_MbK**********************************

This is your API token. Keep it to yourself.

Run nateraw/defog-sqlcoder-7b-2 using Replicate’s API. Check out the model's schema for an overview of inputs and outputs.

curl -s -X POST \
  -H "Authorization: Bearer $REPLICATE_API_TOKEN" \
  -H "Content-Type: application/json" \
  -H "Prefer: wait" \
  -d $'{
    "version": "nateraw/defog-sqlcoder-7b-2:ced935b577fb52644d933f77e2ff8902744e4c58a2f50023b3a1db80b7a75806",
    "input": {
      "frequency_penalty": 0,
      "max_new_tokens": 512,
      "presence_penalty": 0,
      "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]",
      "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.",
      "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",
      "temperature": 0,
      "top_k": 50,
      "top_p": 0.9
    }
  }' \
  https://api.replicate.com/v1/predictions

To learn more, take a look at Replicate’s HTTP API reference docs.

Output

 SELECT c.city, SUM(s.quantity) AS total_sales, SUM(CASE WHEN c.city = 'New York' THEN s.quantity ELSE 0 END) - SUM(CASE WHEN c.city = 'San Francisco' THEN s.quantity ELSE 0 END) AS difference_in_sales FROM sales s JOIN customers c ON s.customer_id = c.customer_id GROUP BY c.city ORDER BY total_sales DESC NULLS LAST;

{
  "id": "enm65blbgntnxuhsewbxdy2qoq",
  "model": "nateraw/defog-sqlcoder-7b-2",
  "version": "ced935b577fb52644d933f77e2ff8902744e4c58a2f50023b3a1db80b7a75806",
  "input": {
    "frequency_penalty": 0,
    "max_new_tokens": 512,
    "presence_penalty": 0,
    "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]",
    "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.",
    "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",
    "temperature": 0,
    "top_k": 50,
    "top_p": 0.9
  },
  "logs": "INFO 02-11 03:18:28 async_llm_engine.py:431] Received request bdd2a2c68ac94d98bf8ecdd2fea93e0d: prompt: \"### Task\\nGenerate 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]\\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:\\nCREATE 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\\n\\n### Answer\\nGiven 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]\\n[SQL]\", prefix_pos: None,sampling params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.0, top_p=1.0, top_k=-1, min_p=0.0, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=['</s>'], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=512, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True), prompt token ids: None, lora_request: None.\nINFO 02-11 03:18:28 llm_engine.py:877] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 5.2 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 1.0%, CPU KV cache usage: 0.0%\nINFO 02-11 03:18:31 async_llm_engine.py:110] Finished request bdd2a2c68ac94d98bf8ecdd2fea93e0d.\ngeneration took 2.463s",
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    ""
  ],
  "data_removed": false,
  "error": null,
  "source": "web",
  "status": "succeeded",
  "created_at": "2024-02-11T03:18:28.589237Z",
  "started_at": "2024-02-11T03:18:28.626848Z",
  "completed_at": "2024-02-11T03:18:31.215272Z",
  "urls": {
    "cancel": "https://api.replicate.com/v1/predictions/enm65blbgntnxuhsewbxdy2qoq/cancel",
    "get": "https://api.replicate.com/v1/predictions/enm65blbgntnxuhsewbxdy2qoq",
    "stream": "https://streaming-api.svc.us.c.replicate.net/v1/streams/cqx75gzmdt4seyemtjrhvc7futhse6ltxok2obugalrrl6vao2wa"
  },
  "metrics": {
    "predict_time": 2.588424,
    "total_time": 2.626035
  }
}

Generated in

2.6 seconds

Tweak it Report

INFO 02-11 03:18:28 async_llm_engine.py:431] Received request bdd2a2c68ac94d98bf8ecdd2fea93e0d: prompt: "### Task\nGenerate 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]\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:\nCREATE 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\n\n### Answer\nGiven 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]\n[SQL]", prefix_pos: None,sampling params: SamplingParams(n=1, best_of=1, presence_penalty=0.0, frequency_penalty=0.0, repetition_penalty=1.0, temperature=0.0, top_p=1.0, top_k=-1, min_p=0.0, use_beam_search=False, length_penalty=1.0, early_stopping=False, stop=['</s>'], stop_token_ids=[], include_stop_str_in_output=False, ignore_eos=False, max_tokens=512, logprobs=None, prompt_logprobs=None, skip_special_tokens=True, spaces_between_special_tokens=True), prompt token ids: None, lora_request: None. INFO 02-11 03:18:28 llm_engine.py:877] Avg prompt throughput: 0.0 tokens/s, Avg generation throughput: 5.2 tokens/s, Running: 1 reqs, Swapped: 0 reqs, Pending: 0 reqs, GPU KV cache usage: 1.0%, CPU KV cache usage: 0.0% INFO 02-11 03:18:31 async_llm_engine.py:110] Finished request bdd2a2c68ac94d98bf8ecdd2fea93e0d. generation took 2.463s