README.md

metadata

title: Semantic Integrity Analysis
emoji: 🤖
colorFrom: blue
colorTo: green
sdk: streamlit
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Semantic Integrity Analysis

Legal document analysis web app with authentication, upload, line-level issue detection, and final narrative summary.

Current Architecture

• backend/: Flask API + SQLite auth + document analysis pipeline
• frontend/: Multi-page static UI
• ui/: Streamlit path (separate from current web flow)
• analysis/: Core analyzer logic

Active User Flow

1. index.html -> Login / Sign up
2. upload.html -> Upload up to 2 reference files + final file, then run cross-verification analysis
3. issues.html -> Line-level issue analysis (duplication, inconsistency, contradiction)
4. summary.html ->
   • Detailed document summary (Page 1, Page 2, ... style)
   • Page-wise summary cards
   • Top findings
5. dashboard.html ->
   • Line error table (exact page/line)
   • Reference vs Final mismatch explanation + rectify action

Features

• Auth endpoints (register, login) with SQLite
• Upload support: PDF, DOCX, TXT
• Cross verification: optional 1-2 reference documents + required final document
• Detection categories:
  • Duplication
  • Inconsistency
  • Contradiction
• Vendor/Vendee extraction
• Narrative detailedSummary + page summaries + line-level dashboard

Backend Setup

cd backend
python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python3 app.py

Backend default: http://127.0.0.1:5000

Frontend Setup

cd frontend
python3 -m http.server 8080

Open: http://127.0.0.1:8080/index.html

API Endpoints

• GET /api/health
• POST /api/register
• POST /api/login
• POST /api/analyze

Alias routes also available:

• GET /health
• POST /register
• POST /login
• POST /analyze

Analyze Response (important keys)

• summary
• pageSummaries
• detailedSummary
• findings
• lineIssues

Deployment (GitHub + Render)

1) Push repository

git add .
git commit -m "Project setup and web flow"
git branch -M main
git remote add origin https://github.com/<your-username>/<your-repo>.git
git push -u origin main

2) Deploy backend on Render (Web Service)

• Root directory: backend
• Build command:

pip install -r requirements.txt

• Start command:

gunicorn app:app

3) Deploy frontend (static)

• Option A: Render Static Site (root frontend)
• Option B: GitHub Pages for frontend/

Notes

• Current frontend + backend flow does not require merged_tinyllama_instruction.
• Streamlit path under ui/ may use local TinyLlama model path.
• If analysis output changes are not visible, restart backend and re-run upload. (Create README.md)