task_categories:text-generation task_categories:text2text-generation size_categories:n<1K format:parquet modality:text library:datasets library:pandas library:mlcroissant library:polars library:distilabel region:us synthetic distilabel rlaif datacraft
---
size_categories: n<1K
task_categories:
- text-generation
- text2text-generation
dataset_info:
  features:
  - name: prompt
    dtype: string
  - name: completion
    dtype: string
  - name: system_prompt
    dtype: string
  splits:
  - name: train
    num_bytes: 459379
    num_examples: 100
  download_size: 121371
  dataset_size: 459379
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
tags:
- synthetic
- distilabel
- rlaif
- datacraft
---

<p align="left">
  <a href="https://github.com/argilla-io/distilabel">
    <img src="https://raw.githubusercontent.com/argilla-io/distilabel/main/docs/assets/distilabel-badge-light.png" alt="Built with Distilabel" width="200" height="32"/>
  </a>
</p>

# Dataset Card for my-distiset-81e4c2a2

This dataset has been created with [distilabel](https://distilabel.argilla.io/).



## Dataset Summary

This dataset contains a `pipeline.yaml` which can be used to reproduce the pipeline that generated it in distilabel using the `distilabel` CLI:

```console
distilabel pipeline run --config "https://huggingface.co/datasets/raduqus/my-distiset-81e4c2a2/raw/main/pipeline.yaml"
```

or explore the configuration:

```console
distilabel pipeline info --config "https://huggingface.co/datasets/raduqus/my-distiset-81e4c2a2/raw/main/pipeline.yaml"
```

## Dataset structure

The examples have the following structure per configuration:


<details><summary> Configuration: default </summary><hr>

```json
{
    "completion": "Based on your interests, skills, and preferences, I\u0027ll generate four new tasks for you. Here are the tasks in JSON format:\n\n```json\n[\n  {\n    \"title\": \"Code a Python Script for a Simple Calculator\",\n    \"description\": \"Use your Python skills to create a simple calculator that performs basic arithmetic operations.\",\n    \"enjoyment\": {\n      \"fun\": 4,\n      \"challenging\": 2,\n      \"easy\": 2,\n      \"boring\": 1\n    },\n    \"characteristics\": {\n      \"solitary\": 3,\n      \"quick\": 4\n    },\n    \"skills\": [\"Problem Solving\", \"Python\"]\n  },\n  {\n    \"title\": \"Read a Science Fiction Novel\",\n    \"description\": \"Choose a science fiction novel and dedicate some time to reading it.\",\n    \"enjoyment\": {\n      \"fun\": 4,\n      \"social\": 1,\n      \"boring\": 1\n    },\n    \"characteristics\": {\n      \"indoor\": 2,\n      \"quick\": 2\n    },\n    \"skills\": [\"Reading\"]\n  },\n  {\n    \"title\": \"Plan a Hike for the Upcoming Weekend\",\n    \"description\": \"Use your hiking experience to plan a hike for the upcoming weekend, considering the terrain, weather, and any necessary gear.\",\n    \"enjoyment\": {\n      \"fun\": 4,\n      \"outdoors\": 4,\n      \"social\": 1\n    },\n    \"characteristics\": {\n      \"solitary\": 2,\n      \"quick\": 2\n    },\n    \"skills\": [\"Hiking\", \"Problem Solving\"]\n  },\n  {\n    \"title\": \"Organize Your Bookshelf\",\n    \"description\": \"Use your household management skills to organize your bookshelf, making sure everything is tidy and in its place.\",\n    \"enjoyment\": {\n      \"fun\": 3,\n      \"easy\": 3,\n      \"boring\": 1\n    },\n    \"characteristics\": {\n      \"indoor\": 2,\n      \"quick\": 3\n    },\n    \"skills\": [\"Household Management\"]\n  }\n]\n```\n\nThese tasks cater to your interests in Python, reading, and hiking, and consider your skills in problem-solving and household management. The tasks are designed to be enjoyable, with a mix of solitary and social aspects, and are quick to complete.",
    "prompt": "I\u0027d like to generate new tasks based on my interests in \"Learning Python\", \"Reading\", and \"Hiking\". I\u0027ve completed the task of \"Room Cleaning\". I have a moderate level of skill in \"Household Management\" and a high level of skill in \"Problem Solving\". Here are my preferred enjoyment levels for different task characteristics: \n- Easy: 3\n- Challenging: 2\n- Boring: 1\n- Fun: 4\n- Social: 2\n- Solitary: 3]\n- Time-consuming: 1\n- Quick: 4\n- Outdoors: 3\n- Indoors: 2\n\nI\u0027d like to generate 4 new tasks based on my skills and interests. \n\n",
    "system_prompt": "You are an AI assistant designed to provide personalized task recommendations based on user interests and past experiences. Your purpose is to analyze user input and suggest relevant tasks that align with their preferences and facilitate skill development, productivity, and enjoyment. Provide tailored recommendations, taking into account the user\u0027s interests, strengths, and past task history, to help them make the most of their time and abilities. User questions are direct and concise in a strict format of the following prompt.\n\nPrompt :\n\"\"\"\nYou are an advanced task recommendation assistant. Based on the provided user interests and previous tasks, generate up to 3-4 new tasks in JSON format. Ensure the tasks are diverse, relevant to the interests, and align with the style of the previous tasks.\nUser Interests:\n\n[ \"Interest 1\", \"Interest 2\", \"Interest 3\" ]\nPrevious Tasks:\n\n[ { \"title\": \"Room Cleaning\", \"description\": \"Need to clean the clothes room and sort things out there.\" }, { \"title\": \"{Insert title of previous task}\", \"description\": \"{Insert description of previous task}\" } // Add as needed ]\nOutput Instructions:\n\nGenerate a JSON array containing 3-4 new tasks in the following format:\n\n[\n  {\n    \"title\": \"Task Title 1\",\n    \"description\": \"Task Description 1\"\n  },\n  {\n    \"title\": \"Task Title 2\",\n    \"description\": \"Task Description 2\"\n  },\n  {\n    \"title\": \"Task Title 3\",\n    \"description\": \"Task Description 3\"\n  }\n]\n\nOnly provide the JSON array as output.\n\"\"\"\n"
}
```

This subset can be loaded as:

```python
from datasets import load_dataset

ds = load_dataset("raduqus/my-distiset-81e4c2a2", "default")
```

Or simply as it follows, since there's only one configuration and is named `default`: 

```python
from datasets import load_dataset

ds = load_dataset("raduqus/my-distiset-81e4c2a2")
```


</details>




