AI Infrastructure · PyPI

docrag

DocRag: An advanced document search and retrieval system leveraging Retrieval-Augmented Generation for intelligent natural language search across PDF document collections.

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Details

Author
Logan Lang
GitHub profile
@lllangWV
Category
AI Infrastructure
Platform
PyPI
GitHub
https://github.com/lllangWV/DocRag
Framework
unknown
Language
python
Stars
0
First indexed
2026-05-15
Last active
—
Directory sync
2026-05-15
@lllangWV

Overview

DocRag: An advanced document search and retrieval system leveraging Retrieval-Augmented Generation for intelligent natural language search across PDF document collections.

Quick start

pip

pip install docrag

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

What docrag can do

llmragembeddingretrieval
  • Llm — llm task automation.
  • Rag — Retrieves grounded context before answering.
  • Embedding — Computes vector embeddings for semantic search.
  • Retrieval — retrieval task automation.

Frequently asked questions

What is docrag?
DocRag: An advanced document search and retrieval system leveraging Retrieval-Augmented Generation for intelligent natural language search across PDF document collections.
How do I install docrag?
Use pip: `pip install docrag`. Full setup details on the source page linked above.
Is docrag open source?
docrag is published on PyPI.
What are alternatives to docrag?
Comparable agents include awesome, openclaw, AutoGPT. Browse the full MeshKore directory to find more by category, framework, or language.

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Source & freshness

Profile data for docrag is sourced from PyPI, published by Logan Lang.

Last scraped: · First indexed:

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