JASS Document Intelligence Studio

Universal Local-First Document & File Research Workspace

JASS Document Intelligence Studio is a local-first research workspace for importing, cataloguing, inspecting, searching, organizing and studying files on your own computer.

It is designed as part of JASS Digital Lab and follows a simple principle:

Bring your files together. Understand them. Organize them. Research them.

The application uses a local SQLite database and does not require a cloud service for its core library functions.

✨ What It Does

JASS Document Intelligence Studio provides a unified library for many different kinds of files.

Universal Import

The application can import:

PDF
DOCX
TXT
Markdown
CSV
TSV
JSON
XML
HTML
YAML
RTF
Python
JavaScript
TypeScript
C / C++
Java
SQL
PowerShell
Shell scripts
CSS
Logs
Configuration files
Images
Audio
Video
Other file types

The important design principle is:

A file does not have to be fully understood to be preserved in the library.

Supported formats receive appropriate extraction and/or preview. Other formats can still be catalogued and retained as library items.

🖼️ Image Support

Images are first-class library items.

Supported image formats include:

PNG
JPG / JPEG
GIF
BMP
WebP
TIFF
SVG
ICO

Images can be imported into the library and viewed through the application's image workspace.

PDF documents can also have their embedded images extracted and displayed.

📄 Document Support

PDF

PDF support includes:

Text extraction
Page count
PDF page thumbnails
Visual page rendering
Page navigation
Embedded image extraction
Image gallery
Searchable extracted text

DOCX

DOCX files can be imported and their text extracted for research and searching.

Text & Markdown

TXT and Markdown files are imported directly and become searchable library content.

🔎 Research Search

Search across the local document library using:

Filename
Extracted text
Category
Tags
Notes

The Research Search workspace provides:

Matching documents
Match counts
Context snippets
Quick opening of matching documents

There is also a Find function for searching within the currently open document.

🗂️ Research Collections

Documents can be organized into research collections such as:

Project Athena
Punjabi Language
Mizo Research
Literature
AI Research
HRTK
Personal Research

Collections do not move or modify the original files.

They simply provide a logical research organization layer.

⭐ Favorites

Important documents can be added to a personal reading list.

Features include:

Add to Favorites
Remove from Favorites
Favorites workspace
Persistent favorite status

This makes it easy to maintain a focused set of documents for current research.

🏷️ Metadata & Organization

Each library item can have:

Category
Tags
Research notes
Collections
Relationships

Built-in categories include:

Research
Literature
Language
Technical
Project
Data
Reference
Personal
Other

🔗 Document Relationships

Documents can be connected to one another using relationships such as:

Related to
References
Derived from
Part of
Supports
Uses

For example:

RAG Research Paper
        │
        ├── References → Project Athena
        │
        └── Supports → Retrieval Notes

This provides the foundation for a future research knowledge graph.

📊 Document Statistics

The Statistics workspace provides information such as:

Filename
File type
Category
Collections
File size
Pages
Word count
Character count
Extracted images
Import time
Modification time
SHA-1 checksum
Original file path

🔐 Local-First Design

JASS Document Intelligence Studio is designed around local processing.

Core principles

Local-first
Offline-friendly
Privacy-conscious
SQLite-based
Original files are never modified
No mandatory cloud service
User-controlled document library

The database is stored by default under:

~/JASS/DocumentIntelligenceStudio/

On Windows this normally resolves to:

C:\Users\<username>\JASS\DocumentIntelligenceStudio\

The primary database is:

jass_documents.db

🧠 Current Architecture

                     JASS Document Intelligence Studio
                                  │
                                  ▼
                         Universal File Import
                                  │
             ┌────────────────────┼────────────────────┐
             ▼                    ▼                    ▼
        Documents              Images          Media / Other
             │                    │                    │
             └────────────────────┼────────────────────┘
                                  ▼
                           SQLite Library
                                  │
              ┌───────────────────┼───────────────────┐
              ▼                   ▼                   ▼
           Search             Collections         Metadata
              │                   │                   │
              ├──────────────┬────┴────┬──────────────┤
              ▼              ▼         ▼              ▼
          Favorites      Relations   Notes          Tags
                                  │
                                  ▼
                           Research Workspace

🛠️ Technology Stack

Python
PySide6
SQLite
PyMuPDF
python-docx

The application is designed as a lightweight desktop application rather than a browser-dependent research service.

📦 Installation

Create a Python environment and install the required packages:

pip install PySide6 PyMuPDF python-docx

Then run:

python jass_document_intelligence_studio_v0_7.py

💻 Typical Workflow

1. Import

Bring research material into the library:

PDF
DOCX
TXT
Markdown
Images
CSV
JSON
Code
Media
Other files

2. Inspect

Open a document and inspect:

Text
PDF Pages
Images
Statistics

3. Organize

Add:

Category
Tags
Notes
Collections
Favorites
Relationships

4. Search

Use:

Library Search
Research Search
Find in Document

5. Build Research Collections

For example:

Project Athena
│
├── Architecture papers
├── RAG research
├── AI provider documentation
├── Retrieval experiments
└── Personal research notes

🚧 Current Scope

JASS Document Intelligence Studio v0.7 is primarily a file intelligence, organization and research workspace.

It already provides the foundation for more advanced document intelligence.

Available now

Universal file import
Local SQLite library
PDF rendering
PDF text extraction
PDF image extraction
Image import and viewing
DOCX extraction
Text/Markdown extraction
Search
Research Search
Collections
Favorites
Tags
Notes
Relationships
Categories
Statistics
Duplicate detection
Text export
Local/offline operation

Planned / Future Direction

The architecture can evolve toward:

OCR
Image-to-text extraction
Semantic search
Embeddings
Vector databases
RAG
Document summarization
AI-assisted research
Question answering over documents
Citation-aware answers
Knowledge graph features
Athena integration
Local AI providers
Document classification
Multimodal research

The goal is to add these capabilities incrementally without turning the application into an unnecessarily heavy platform.

🔗 Relationship to Project Athena

JASS Document Intelligence Studio can serve as a practical document research foundation for Project Athena.

A possible future architecture is:

JASS Document Intelligence Studio
              │
              ▼
       Document Library
              │
              ▼
       Document Intelligence
              │
       ┌──────┴──────┐
       ▼             ▼
   Retrieval       AI/RAG
       │             │
       └──────┬──────┘
              ▼
        Project Athena

This keeps document ingestion and organization useful independently while allowing Athena to consume the resulting knowledge layer later.

🎯 Design Philosophy

Library First. Intelligence Second.

The first responsibility of the application is to build a reliable local library.

AI capabilities come afterward.

This approach provides:

Better control of personal research material
Clear document provenance
Local organization before AI processing
Easier debugging
Modular development
Reduced dependence on external services

🔒 Data Safety

The application calculates a SHA-1 checksum for imported files to help identify duplicates.

Removing a document from the library does not delete the original file.

The application stores references and extracted research data in its local database while leaving the source file untouched.

🌱 JASS Digital Lab

JASS Document Intelligence Studio is part of JASS Digital Lab — a personal software laboratory focused on:

AI & Machine Learning
Knowledge Systems
Language & Literature
Data Research
Document Intelligence
Creative Computing
Legacy Software Modernization
Desktop Software

The broader philosophy is:

Build useful software locally, preserve knowledge, and modernize what matters.

📌 Project Status

Version: 0.7

Status: Active Development

Platform: Desktop

Primary language: Python

GUI: PySide6

Database: SQLite

Architecture: Local-first

👤 Author

SinghJasvir · Fanu2

Independent Software Builder
JASS Digital Lab

📄 License

Add the project's preferred license here when finalized.

JASS Digital Lab

AI · Knowledge · Language · Data · Creative Computing

Name		Name	Last commit message	Last commit date
README.md		README.md
jass_document_intelligence_studio_v0_7.py		jass_document_intelligence_studio_v0_7.py

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