|
|
--- |
|
|
license: mit |
|
|
task_categories: |
|
|
- question-answering |
|
|
- text-retrieval |
|
|
language: |
|
|
- en |
|
|
tags: |
|
|
- mulesoft |
|
|
- documentation |
|
|
- embeddings |
|
|
- rag |
|
|
- api-integration |
|
|
size_categories: 10K<n<100K |
|
|
configs: |
|
|
- config_name: default |
|
|
data_files: dataset.parquet |
|
|
default: true |
|
|
--- |
|
|
|
|
|
# mulesoft-documentation-embeddings |
|
|
|
|
|
MuleSoft Documentation Embeddings for RAG Applications |
|
|
|
|
|
## Dataset Information |
|
|
|
|
|
- **Version**: 1.0.0 |
|
|
- **Created**: 2025-09-16T02:41:16.352809 |
|
|
- **Source**: Vector Database |
|
|
- **License**: MIT |
|
|
- **Language**: en |
|
|
|
|
|
## Task Categories |
|
|
|
|
|
question-answering, retrieval, knowledge-base |
|
|
|
|
|
## Dataset Statistics |
|
|
|
|
|
### SkillPilotDataSet_v11 |
|
|
|
|
|
- **Total Objects**: 6430 |
|
|
- **Unique Properties**: 13 |
|
|
- **Knowledge Sources**: mulesoft, user_defined_docs |
|
|
- **Average Content Length**: 5079 characters |
|
|
|
|
|
## Dataset Schema |
|
|
|
|
|
The dataset contains the original document properties with the following fields: |
|
|
|
|
|
- `author`: Document author |
|
|
- `chunk_id`: Unique chunk identifier |
|
|
- `chunk_index`: Position of chunk in document |
|
|
- `document_id`: Source document identifier |
|
|
- `entities`: Extracted entities |
|
|
- `keywords`: Document keywords |
|
|
- `knowledge_source`: Source of knowledge (mulesoft, user_defined_docs) |
|
|
- `page_content`: Main text content |
|
|
- `relationships`: Entity relationships |
|
|
- `source_url`: Original document URL |
|
|
- `tags`: Document tags |
|
|
- `title`: Document title |
|
|
- `total_chunks`: Total number of chunks in document |
|
|
- `vector`: Embedding vector (3072 dimensions from OpenAI text-embedding-3-large) |
|
|
|
|
|
## RAG Configuration |
|
|
|
|
|
This dataset was created using the following RAG (Retrieval-Augmented Generation) configuration: |
|
|
|
|
|
### Embedding Model |
|
|
- **Model Type**: OpenAI |
|
|
- **Model ID**: text-embedding-3-large |
|
|
- **Embedding Dimensions**: 3072 |
|
|
- **Provider**: OpenAI |
|
|
|
|
|
### Chunking Configuration |
|
|
- **Chunk Size**: 2048 characters |
|
|
- **Chunk Overlap**: 256 characters |
|
|
|
|
|
### Technical Details |
|
|
- **Vector Database**: Vector Database |
|
|
- **Collection**: SkillPilotDataSet_v11 |
|
|
- **Total Vectors**: 6430 |
|
|
- **Vector Distance**: Cosine similarity |
|
|
|
|
|
## Usage |
|
|
|
|
|
This dataset can be used for: |
|
|
- Question answering systems |
|
|
- Retrieval-augmented generation (RAG) |
|
|
- Knowledge base construction |
|
|
- Technical interview preparation |
|
|
- AI assistant training |
|
|
|
|
|
## Files |
|
|
|
|
|
- `dataset.parquet`: Dataset in Parquet format (recommended for large datasets) |
|
|
- `README.md`: This documentation file |
|
|
|
|
|
## Citation |
|
|
|
|
|
If you use this dataset, please cite: |
|
|
|
|
|
```bibtex |
|
|
@dataset{{mulesoft_documentation_embeddings, |
|
|
title={{MuleSoft Documentation Embeddings}}, |
|
|
author={{Bassem Elsodany}}, |
|
|
year={{2025}}, |
|
|
url={{https://huggingface.co/datasets/BassemE/mulesoft-documentation-embeddings}} |
|
|
}} |
|
|
``` |
|
|
|
