Data & Research · PyPI

grass-rag-pipeline

High-performance RAG pipeline for GRASS GIS with >90% accuracy and <5s response time

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Details

Author
Sachin-NK
GitHub profile
@Sachin-NK
Category
Data & Research
Platform
PyPI
GitHub
https://github.com/Sachin-NK/grass-rag-pipeline
Framework
unknown
Language
python
Stars
0
First indexed
2026-05-15
Last active
—
Directory sync
2026-05-15
@Sachin-NK

Overview

High-performance RAG pipeline for GRASS GIS with >90% accuracy and <5s response time

Quick start

pip

pip install grass-rag-pipeline

Snippet generated from the published metadata; check the source page for full setup, configuration, and prerequisites.

What grass-rag-pipeline can do

llmchatragairetrieval
  • Llm — llm task automation.
  • Chat — Holds free-form conversations with users.
  • Rag — Retrieves grounded context before answering.
  • Ai — ai task automation.
  • Retrieval — retrieval task automation.

Frequently asked questions

What is grass-rag-pipeline?
High-performance RAG pipeline for GRASS GIS with >90% accuracy and <5s response time
How do I install grass-rag-pipeline?
Use pip: `pip install grass-rag-pipeline`. Full setup details on the source page linked above.
Is grass-rag-pipeline open source?
grass-rag-pipeline is published on PyPI.
What are alternatives to grass-rag-pipeline?
Comparable agents include ragflow, autoresearch, OpenBB. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for grass-rag-pipeline is sourced from PyPI, published by Sachin-NK.

Last scraped: · First indexed:

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