Datasets:
File size: 1,689 Bytes
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dataset_info:
features:
- name: prompt
dtype: string
- name: tool
dtype: string
- name: args
struct:
- name: a
dtype: float64
- name: b
dtype: float64
splits:
- name: train
num_bytes: 2617582
num_examples: 20000
download_size: 999433
dataset_size: 2617582
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
tags:
- function-calling
- agent
- synthetic
- mathematics
- nlp
---
# Simple Calculator: Agentic Function-Calling Dataset
## Overview
This dataset contains **20,000 highly structured, synthetically generated examples** designed to train Large Language Models (LLMs) in agentic tool-calling and parameter extraction. It focuses on mapping diverse natural language mathematical queries—ranging from direct commands to conversational word problems—into deterministic, executable JSON structures for a calculator tool.
## Dataset Structure
The dataset trains models to isolate numerical entities and identify the correct mathematical operation required to solve the user's prompt.
### Schema
* **`prompt`** *(string)*: The natural language input (e.g., "If I have a 200 bill and I want to split it with 3 friends").
* **`tool`** *(string)*: The target target routing function (`add`, `subtract`, `multiply`, or `divide`).
* **`args`** *(struct)*: The extracted numerical parameters.
* **`a`** *(float64)*: The first numerical operand.
* **`b`** *(float64)*: The second numerical operand.
### Data Example
```json
{
"prompt": "A factory produces 45.5 items per hour. How many items does it make in 8 hours?",
"tool": "multiply",
"args": {
"a": 45.5,
"b": 8.0
}
} |