---
license: cc-by-sa-4.0
size_categories:
- 10K<n<100K
task_categories:
- question-answering
dataset_info:
- config_name: angular
  features:
  - name: _id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
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    - name: url
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- config_name: godot
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    struct:
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- config_name: langchain
  features:
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  - name: text
    dtype: string
  - name: metadata
    struct:
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    - name: start_byte
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    - name: url
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- config_name: laravel
  features:
  - name: _id
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  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: end_byte
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    - name: start_byte
      dtype: int64
    - name: url
      dtype: string
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  - name: train
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    num_examples: 52351
  download_size: 39525810
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- config_name: yolo
  features:
  - name: _id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: end_byte
      dtype: int64
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      dtype: int64
    - name: url
      dtype: string
  splits:
  - name: train
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    num_examples: 27207
  download_size: 42140310
  dataset_size: 134629730
configs:
- config_name: angular
  data_files:
  - split: train
    path: angular/train-*
- config_name: godot
  data_files:
  - split: train
    path: godot/train-*
- config_name: langchain
  data_files:
  - split: train
    path: langchain/train-*
- config_name: laravel
  data_files:
  - split: train
    path: laravel/train-*
- config_name: yolo
  data_files:
  - split: train
    path: yolo/train-*
---

# Dataset Card for FreshStack (Corpus)

[Homepage](https://fresh-stack.github.io) | 
[Repository](https://github.com/fresh-stack/freshstack) |
[Paper](https://arxiv.org/abs/2504.13128)

FreshStack is a holistic framework to construct challenging IR/RAG evaluation datasets that focuses on search across niche and recent topics.

This dataset (October 2024) contains the query, nuggets, answers and nugget-level relevance judgments of 5 niche topics focused on software engineering and machine learning. 

The queries and answers (accepted) are taken from Stack Overflow, GPT-4o generates the nuggets and labels the relevance between each nugget and a given document list.

This repository contains the corpus of GitHub chunked documents of five niche topics in freshstack. The queries, answers and nuggets can be found [here](https://huggingface.co/datasets/freshstack/queries-oct-2024).

## Dataset Structure

To access the data using HuggingFace `datasets`:
```
topic='langchain'  # or any of the 5 topics
freshstack = datasets.load_dataset('freshstack/corpus-oct-2024', topic)

# train set
for data in freshstack['train']:
  doc_id = data['_id']
  doc_text = data['text'] 
```

## Dataset Statistics 
The following table contains the number of documents (`#D`) and the number of GitHub repositories used (`#G`) in the FreshStack collection.

| Topic | Versions | Domain | Train |        |
|:----:|:-----:|:-----:|:-----:|:------:|
|            |     |     | **#D**| **#G** |
|  langchain | -   |Machine Learning     | 49,514  | 10 |
|  yolo      | v7 & v8 | Computer Vision      | 27,207  | 5  |
|  laravel   | 10 & 11 | Back-end Development | 52,351  | 9  |
|  angualar  | 16, 17 & 18 | Front-end Development| 117,288 | 4  |
|  godot     | 4 | Game Development     | 25,482  | 6  |

## Dataset Licenses

The FreshStack datasets are provided under the CC-BY-SA 4.0 license.

> The original GitHub repositories used for constructing the corpus may contain non-permissive licenses; we advise the reader to check the licenses for each repository carefully.