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ABHINAV
ABHINAV

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NEXORA — On-Device AI Workspace

What I Built
I built NEXORA — On-Device AI Workspace, a fully offline, zero-cloud desktop application built to maximize personal productivity while letting you be gloriously lazy.

Instead of jumping between SaaS subscriptions, API key management, rate limits, and tab clutter, NEXORA aggregates model inference, document search, mathematical execution, and capital weather forecasting into a single unified dashboard.

It lets you submit long, dense PDFs or text documents and ask questions directly using local vector embeddings. You get back concise, page-cited answers without ever reading through endless pages or worrying about your private data leaving your computer.

Demo
Here is a glimpse of NEXORA running locally on a personal laptop:

Code
Below is the complete, single-file implementation for app.py:

app.py - Google Drive

favicon drive.google.com

How I Built It
NEXORA relies on open-source software and open-weight models at every step:

Local LLM & Embedding Execution: Driven by Ollama, which runs an open-weight model (localmind) alongside open embedding weights (nomic-embed-text) locally on port 11434.

On-Device Vector RAG Engine: Document processing uses PyMuPDF (pymupdf) to extract and chunk text locally. Chunks are passed to nomic-embed-text to generate embeddings, and similarity scoring is calculated with NumPy (numpy) using cosine vector product distance.

Streamlit Desktop UI: Built using Streamlit, styled with a custom dark high-contrast theme (#0d1117) inspired by GitHub dark mode.

Why Does Open Innovation Matter?
Open innovation is the backbone of NEXORA. Using open-weight models locally offers crucial advantages:

Complete Data Privacy & Offline Capability: Sensitive financial, academic, or personal documents never leave your machine. You can analyze private contracts or read confidential papers on an airplane with Wi-Fi turned off.

Zero API Bills: Once downloaded, running open weights costs $0 per million tokens. You can summarize hundreds of documents without worrying about pay-per-token API charges.

Full Speed Transparency: Every response displays execution specs—total wall time, pure generation time, exact token generation counts, and generation speed (tokens/sec).

The Lazy Payoff
NEXORA embodies the "Slow and Steady" sloth mentality:

Zero Manual Reading: Drop a 50-page PDF, ask a question, and receive page-cited answers instantly.

No Internet Dependency: Works completely offline without needing cloud services or API connections.

Set Up Once, Run Forever: Spin up Ollama, run Streamlit, and your local workspace handles tasks automatically.

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