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what is prag-personal-rag fr?

subrat-dwi/prag-personal-rag — explained in plain English

Analysis updated 2026-05-18

1PythonAudience · generalComplexity · 4/5LicenseSetup · hard

tl;dr

PRAG is a personal RAG assistant that lets you ask natural-language questions about your own documents, photos, and files and get cited answers back.

vibe map

mindmap
  root((prag))
    What it does
      Chat with personal docs
      Cited answers
      Google Drive sync
      OCR for scans
    Tech stack
      Python
      FastAPI
      Qdrant
      Docker
    Use cases
      Find personal facts
      Interview prep
      Document Q and A
    Search
      Semantic search
      Keyword search
      Query correction

Code map

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filefunction / class

what do people make with this?

VIBE 1

Ask PRAG for personal facts like ID numbers or dates buried across old documents and photos.

VIBE 2

Sync a Google Drive folder of personal files so PRAG stays up to date as documents change.

VIBE 3

Generate a quick professional summary or intro for interviews from your own stored documents.

what's the stack?

PythonFastAPILangChainQdrantDocker

how it stacks up fr

subrat-dwi/prag-personal-rag0xustaz/streamgatea-bissell/unleash-lite
Stars111
LanguagePythonPythonPython
Setup difficultyhardhardhard
Complexity4/54/54/5
Audiencegeneraldeveloperresearcher

Figures from each repo's GitHub metadata at analysis time.

how do i run it?

Difficulty · hard time til it works · 1h+

Needs Ollama models, Qdrant Cloud, and Google Drive credentials configured before first use.

MIT license: use freely for any purpose, including commercial use, as long as you keep the copyright notice.

in plain english

PRAG is a personal assistant that answers questions about you using your own documents. The idea is simple: instead of digging through old files, photos, messages, and emails to find something like your college roll number or the exact date you started an internship, you just ask PRAG and it looks it up for you. You feed it your personal documents in formats like PDF, Word files, images, markdown, and plain text. For scanned documents or photos, it uses OCR to pull out the text, then cleans up any messy results with a language model. It can also sync directly with Google Drive, checking file checksums so it only reprocesses files that actually changed, and removing old data automatically when a file is deleted. When you ask a question, PRAG combines two kinds of search: one based on meaning, which catches questions phrased differently than the original document, and one based on exact keyword matching, which is better for things like ID numbers or specific terms. It also tries to correct spelling mistakes in your question and figures out whether you are asking for a plain fact or something that needs pulling information together from multiple places. Every answer includes a citation showing which document it came from, along with a link back to the file in Google Drive if it is stored there. The language model itself can run locally through Ollama for privacy, or switch to a faster hosted option for deployment, changed with a single setting. The whole system, including its web interface that installs like a mobile app, is packaged with Docker so it can be set up the same way locally or in production.

prompts (copy fr)

prompt 1
Set up PRAG locally with Docker and Ollama, then ask it to summarize my technical experience from my uploaded documents.
prompt 2
Configure PRAG's Google Drive sync so it automatically re-ingests files when they change.
prompt 3
Explain how PRAG's hybrid search combines semantic and keyword matching to answer factual questions.
prompt 4
Show me how PRAG extracts text from a scanned certificate image using OCR.

Frequently asked questions

what is prag-personal-rag fr?

PRAG is a personal RAG assistant that lets you ask natural-language questions about your own documents, photos, and files and get cited answers back.

What language is prag-personal-rag written in?

Mainly Python. The stack also includes Python, FastAPI, LangChain.

What license does prag-personal-rag use?

MIT license: use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is prag-personal-rag to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is prag-personal-rag for?

Mainly general.

peek the repo → explain another one

This repo across BitVibe Labs

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