Intelligent AI Platform for Automobile Component Management

link to github repository: link

You can view the full presentation by: clicking here

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Introduction

• Introduction
  • Objective
• Technical Pipeline / Project Architecture
  • 1. Global Project Architecture
    • 1. Data Collection & Preprocessing
    • 2. Knowledge Base Creation
    • 3. Benchmarking & Integration of LLM / RAG Models
    • 4. Automatic Document Generation
    • 5. Development of the Web Platform
  • 2. Key Application Features
    • Technologies & Tools

Challenges

• Main Challenges Encountered in the Project
• Data Labeling and Preparation
• Model Performance and Comparison
• Project Summary - Impact and Solutions

Data Extraction

• PDF Processing Pipeline Documentation
  • Overview
  • Docling: Next‑Generation Document Processing
    • Overview
    • Architecture
    • 🔧 Key Features
    • 🚀 Installation
    • 📦 Usage
    • 📁 Supported File Types
• 📄 PDF Data Extraction docling
  • 🧠 Goal
  • ✅ 📄 Code: PDF Extraction for DocLing Annotation
  • 🔎 Output
  • 🧠 How to Use with DocLing
  • ✅ Summary
  • 🧠 Final Notes
  • Practice
• 📄 PDF Data Extraction and Structuring Tool (Custom Scripts)
  • 🧩 Overview
  • 🌍 Primary Use Case
  • 🔁 Workflow Summary
  • 📦 Key Features
  • ⚙️ Prerequisites
  • 🔍 Function-by-Function Explanation
    • Key Libraries Used
    • Split_pdf(input_pdf_path)
    • Summarize_table(table)
    • Extract_image_caption(page, bbox, nlp)
    • Extract_content(pdf_path, page_num, nlp)
    • Save_txt_and_md(base_name, page_number, content)
    • Process_pdf(pdf_path)
    • Clean_generated_files(base_name, total_pages)
    • 🧠 How This Supports LLMs and RAG
    • 🔬 Example Pipeline: LLM + RAG
    • 📚 Technologies Used
  • Practice

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link to github repository: link

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• Realized by: MAALOUF

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