AI Developer for OCR and LLM-Based Repair Advisory System

Project Specification: AI-Powered Repair Advice System Project Overview The goal of this project is to develop an AI-powered repair advice system that extracts and processes repair information from structured PDFs (repair manuals, operator manuals, and parts manuals) for automotive and heavy equipment industries. The system will use AWS Textract for OCR and a fine-tuned LLM to generate chatbot responses. The chatbot will also retrieve relevant images extracted from the PDFs. The system will be available on Android, iOS, and Web platforms. System Requirements 1. Input Data Document Types: Repair manuals, operator manuals, parts manuals. Formats: Scanned PDFs. Content Types: Text, tables, diagrams, and images. 2. Output Format Chatbot Response: Users can query the chatbot for repair guidance. Image Retrieval: Extracted images related to the query will be displayed alongside the response. Multi-Platform Availability: The chatbot will be accessible on Android, iOS, and Web applications. 3. Subscription Model & Payment Integration Monthly Subscription Model: Users will be required to subscribe to access premium repair advice and features. Payment Integration: The system will support Stripe and PayPal for secure payment processing. Free Trial: Option to offer a free trial before requiring payment. User Management: Subscription status tracking and automated billing reminders. Technology Stack 1. Cloud Services AWS Textract – Extracts text, tables, and forms from scanned PDFs. AWS S3 – Stores processed documents and extracted images. AWS Lambda (Optional) – For serverless execution. AWS API Gateway – Exposes the chatbot API. 2. AI & NLP Components Fine-tuned LLM (GPT-4, Llama 2, or Mistral-7B) – Generates repair advice. Hugging Face Transformers – For fine-tuning and deploying an open-source LLM. LangChain – For chatbot query handling. 3. Image Processing PyMuPDF (fitz) – Extracts images from PDF manuals. PIL (Pillow) – Processes images before storage. 4. Backend & API Development FastAPI – Builds the chatbot API. Boto3 – Integrates with AWS services. OpenAI API (if using GPT-4) – Provides chatbot responses. Stripe & PayPal APIs – Handles payment processing. 5. Frontend Chatbot UI React.js – Web-based chatbot interface. React Native – Mobile app development for Android & iOS. Axios – API request handling. Stripe & PayPal SDKs – Enables payment processing in apps. Step-by-Step Development Plan Step 1: Document Processing Upload repair manuals to AWS S3. Run AWS Textract to extract text and tables. Use PyMuPDF to extract images from PDFs. Store extracted text and images in a database (DynamoDB or PostgreSQL). Step 2: AI Model Development Prepare training data from repair manuals (question-answer format). Fine-tune LLM (GPT-4, Llama 2, or Mistral-7B) for industry-specific repair knowledge. Deploy the trained model using Hugging Face or OpenAI API. Step 3: Chatbot API Development Develop API with FastAPI to handle user queries. Retrieve relevant repair advice from the AI model. Search extracted images based on query keywords. Return both text and image results to the frontend. Step 4: Mobile & Web App Development Develop a React.js-based web chatbot. Develop a React Native mobile app for Android and iOS. Integrate API with both mobile and web interfaces. Implement Stripe & PayPal for handling subscriptions. Ensure cross-platform synchronization for a seamless user experience. Step 5: Deployment & Integration Deploy API using AWS Lambda or EC2. Expose API via AWS API Gateway. Deploy the mobile and web applications. Implement subscription billing and automated payment reminders. Conduct user testing and optimization. Expected Deliverables Fully functional chatbot API for repair advice. Automated document processing system with AWS Textract. Fine-tuned AI model trained on repair manuals. Extracted images stored in AWS S3 for retrieval. Frontend chatbot for Web, Android, and iOS. Subscription-based model integrated with Stripe and PayPal. Complete documentation on system usage and maintenance. Additional Notes The service provider should have experience in AWS, LLM fine-tuning, OCR processing, chatbot development, and mobile app development. Secure payment handling and compliance with PCI-DSS for Stripe and PayPal integration. Scalability and security measures should be implemented for future expansion. The chatbot should be optimized to understand domain-specific repair queries accurately.