| configs: | |
| - config_name: documents | |
| data_files: | |
| - split: train | |
| path: seed/documents.json | |
| - config_name: chunks | |
| data_files: | |
| - split: train | |
| path: seed/chunks.json | |
| - config_name: satellites | |
| data_files: | |
| - split: train | |
| path: seed/satellites.json | |
| license: mit | |
| task_categories: | |
| - question-answering | |
| - text-retrieval | |
| tags: | |
| - space | |
| - nasa | |
| - esa | |
| - rag | |
| pretty_name: Space Mission Intelligence Data | |
| # Space Mission Intelligence Data | |
| Seed data for the Space Mission Intelligence Agent RAG pipeline. | |
| ## Configurations | |
| - **documents** — 40 documents (NASA technical reports, ESA mission papers, arXiv preprints) | |
| - **chunks** — 2,590 text chunks with 1024-dim embeddings (sentence-transformers) | |
| - **satellites** — satellite orbital data (TLE-derived) | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| docs = load_dataset("JuanCastillo29/space-mission-intelligence-data", "documents") | |
| chunks = load_dataset("JuanCastillo29/space-mission-intelligence-data", "chunks") | |
| ``` | |