| --- |
| 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 |
| } |
| } |
