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MaintAI β€” Equipment Troubleshooting Assistant

Client Demo Β· Advanced Multimodal RAG Β· Industry Standard

AI-powered assistant that lets maintenance technicians ask technical questions and get accurate, cited answers from equipment manuals. Supports scanned PDFs, troubleshooting photos, and global web fallback.


πŸ›  Features

  • Multimodal Analysis: Upload photos of machine errors or screens for instant troubleshooting context.
  • Role-Based Access (RBAC): Secure Login for Admins (Uploads/Deletes) and Technicians (Chat-only).
  • Multilingual OCR: Supports 12+ languages (ZH, JA, KO, EN, HI, etc.) via PaddleOCR.
  • Global Search Fallback: If manuals don't have the answer, one-click search queries the web for industrial solutions.
  • Hyper-Fast Inference: Running on Llama 3.3 70B via Groq's LPU engine for near-instant responses.

πŸ— Technology Stack

Layer Technology Why
LLM Groq Β· Llama 3.3 70B Sub-second inference at industrial scale
OCR PaddleOCR + PyMuPDF High-precision extraction from diagrams and scanned text
Vector DB ChromaDB Native, on-premise storage for data privacy
Auth JWT + FastAPI Security Secure, role-based technician verification
Backend FastAPI (Python) High-performance async RAG architecture
Frontend React 18 Modern, responsive dashboard with SSE streaming

πŸš€ Deployment Guide

Option 1: Quick Start (Local)

  1. Environment: Create a .env file from .env.example and add your GROQ_API_KEY.
  2. Dependencies:
    # Backend
    cd backend && pip install -r requirements.txt
    python -m uvicorn app.main:app --reload
    
    # Frontend (Separate terminal)
    cd frontend && npm install && npm run dev
    

Option 2: Docker / Hugging Face Spaces

This project includes a unified Dockerfile in the root and is pre-configured for Hugging Face Spaces.

docker build -t maintai .
docker run -p 7860:7860 --env-file .env maintai

πŸ’‘ Demo Flow

  1. Login: Choose a role.
    • Admin: admin / admin (Can upload/edit library)
    • Technician: technician / tech (Secure chat access)
  2. Upload: Add an equipment manual in the Manuals tab.
  3. Chat: Ask a question or paste a screenshot.
  4. Web Search: If the manual is insufficient, click the Globe Icon to fetch live maintenance data.

πŸ“‚ Project Structure

maintai-demo/
β”œβ”€β”€ Dockerfile              Unified multi-stage build (HF Ready)
β”œβ”€β”€ .gitignore              Protects project secrets & local DB
β”œβ”€β”€ backend/
β”‚   β”œβ”€β”€ requirements.txt    RAG, OCR, & Search dependencies
β”‚   └── app/
β”‚       β”œβ”€β”€ services/auth.py  JWT & Role-based logic
β”‚       β”œβ”€β”€ services/rag.py   ChromaDB + Groq + Web Fallback
β”‚       └── main.py           FastAPI Entrypoint (serves Static UI)
└── frontend/
    └── src/
        β”œβ”€β”€ App.jsx         Multimodal Dashboard UI
        └── lib/api.js      Auth-aware API client

πŸ”’ Security & Privacy

  • Local Processing: Manuals are stored and indexed locally (ChromaDB); data never leaves your infrastructure except for LLM inference.
  • LOTO Warnings: The system is prompted to prioritize safety and Lockout-Tagout protocols.
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