🚀 AI Projects Portfolio

This repository contains 4 AI-powered projects, each demonstrating different capabilities of Large Language Models (LLMs) and integrations with tools, APIs, and UIs.
All projects use Gradio for interactive frontends and integrate with OpenAI / Ollama / LangChain as needed.

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1️⃣ Proj1 — 🌐 AI Brochure Generator

Description:
Scrapes a company website, intelligently selects relevant pages (About, Careers, etc.), and generates a beautiful brochure in Markdown in any language.

Key Features:

• 🌍 Web scraping with BeautifulSoup
• 🤖 OpenAI GPT models & Ollama integration
• 📜 JSON link filtering using LLM reasoning
• 🎨 Gradio UI for easy interaction

Screenshot:

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2️⃣ Proj2 — ✈️ FlightAI Assistant

Description:
A conversational assistant for an airline that:

• Answers travel questions ✈️
• Generates city images 🎨
• Checks ticket prices 💰
• Shows ticket availability 🎟️

Key Features:

• 🛠️ Custom function calling tools (price, image, availability)
• 🖼️ DALLE-3 city illustrations
• 💬 Context-aware short replies
• 📱 Gradio chat interface with image output

Screenshot:

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3️⃣ Proj3 — 💻 Python/Cobol → C++ High-Performance Converter

Description:
Converts Python or COBOL code into optimized C++ for maximum speed.
Includes execution capabilities for both original and converted code.

Key Features:

• 🔄 GPT-powered code translation
• ⚡ High-performance C++ generation with -Ofast
• ▶️ Built-in execution for Python, COBOL, and C++
• 🖥️ Gradio UI for conversion & execution

Screenshot:

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4️⃣ Proj4 — 📚 RAG AI Assistant with Chroma & LangChain

Description:
A Retrieval-Augmented Generation (RAG) assistant that answers questions using documents from a knowledge base.
Includes 2D & 3D vector visualizations of embeddings.

Key Features:

• 🧠 LangChain + Chroma vector DB integration
• 📊 Plotly visualizations of embeddings (TSNE)
• 💬 Conversational memory for context retention
• 🖥️ Gradio chat interface

Screenshot:

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🛠️ Tech Stack

• Language: Python 🐍
• Frameworks & Libraries:
  • Gradio, LangChain, BeautifulSoup
  • OpenAI API, Ollama, ChromaDB
  • Plotly, Matplotlib, Scikit-learn

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🎓 Credits

These projects were developed as part of the course:
LLM Engineering: Master AI, Large Language Models & Agents
by Ed Donner

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📌 How to Run

1. Clone the repo

git clone https://github.com/SionAlin/LLM_Engineering.git

2. Add your OpenAI API key to .env

OPENAI_API_KEY=sk-yourkeyhere

3. Navigate to the desired project folder and run:

jupyter notebook Main.ipynb

or

python Main.py