Datasets:
metadata
task_categories:
- text-retrieval
language:
- en
- code
tags:
- macaulay2
- rag
- documentation
- vector-database
pretty_name: Macaulay2 RAG Chunks
license: gpl-2.0
Macaulay2 RAG Chunks
A comprehensive knowledge base extracted directly from the official Macaulay2 source code and documentation packages (M2/Macaulay2/packages). Designed to be ingested into Vector Databases (e.g., ChromaDB, FAISS) for Retrieval-Augmented Generation (RAG).
📊 Dataset Statistics
- Total Chunks: 15,711
- Size: ~45MB
- Code Density: ~85% of chunks contain executable Macaulay2 examples.
- Source: Parsed from 2,208
.m2files using a custom AST/Regex-aware parser (https://gitlab.com/frupniew/llm_macaulay/src/extract_m2_docs_v2.py) that groups documentation per mathematical symbol.
🏷️ Metadata & Filtering
Each chunk is enriched with metadata to allow for highly targeted retrieval:
{
"id": "chunk_8492",
"symbol": "primaryDecomposition",
"package": "PrimaryDecomposition",
"has_code": true,
"headline": "compute the primary decomposition of an ideal",
"usage": "primaryDecomposition I",
"example_code": "R = QQ[x,y,z]; I = ideal(x^2, x*y); primaryDecomposition I"
}
This structure allows RAG pipelines to filter out purely theoretical text when the user explicitly asks for code implementation, or filter by specific algebraic packages (e.g., Schubert2).
🧩 Recommended Embedding Model
Tested and optimized with sentence-transformers/all-MiniLM-L6-v2 for a balance of semantic mathematical understanding and low-latency retrieval.