| --- |
| 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 `.m2` files 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: |
| ```json |
| { |
| "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. |
