devMaLoba/ShopyMall---AI-Powered-Shopping-Assistant

ShopyMall is a next-generation e-commerce aggregator built for convenience. It unifies the shopping experience by aggregating real-time search results from Kenya's top e-commerce platforms (Jumia, Jiji, Kilimall, etc.) and uses Generative AI (Llama 3.3) to provide intelligent buying recommendations. # 🛍️ ShopyMall — AI-Powered Shopping Assistant ShopyMall is an AI-driven e-commerce aggregator built for Kenya and the world. It unifies product discovery by aggregating real-time search results from Kenya’s leading online marketplaces and applying Generative AI to recommend the best purchase options. Instead of hopping between multiple platforms, users search once and receive intelligent, value-based recommendations. ## 🚀 Key Features ### 🔎 Unified Product Search Search across multiple Kenyan e-commerce platforms from a single interface, including: 1.Jumia 2.Jiji 3.Kilimall 4.Masoko 5.Oraimo ### ⚡ Real-Time Data Fetching Live product pricing Availability status Vendor-specific results Fetched directly from vendor sites at query time. ### 🤖 AI-Driven Recommendations Powered by byllm and Meta Llama 3.3 (70B Instruct) Analyzes: -Price competitiveness -Vendor reliability -Overall value for money -Returns a clear best-deal recommendation, not just raw results ### 🛡️ Fault-Tolerant Design Smart fallbacks ensure graceful degradation The application remains stable even if a vendor site is unavailable ## 🧠 Built with Jac Entirely implemented using the Jac programming language Demonstrates seamless integration of: -Python libraries -Web scraping -GenAI workflows -Embedded frontend logic ## 🛠️ Tech Stack Layer | Technology ``` Language Jaclang AI / LLM byllm + Meta Llama 3.3-70B-Instruct Frontend React (embedded via Jac) Backend Jac Walkers + Python Data Fetching requests, BeautifulSoup4 ``` ## 📦 Installation & Setup 1️⃣ Clone the Repository ``` git clone github.com cd ShopyMall---AI-Powered-Shopping-Assistant ``` 2️⃣ Create & Activate a Virtual Environment ``` python3 -m venv venv source venv/bin/activate ``` 3️⃣ Install Dependencies ``` pip install -r requirements.txt ``` 4️⃣ Configure Environment Variables ``` Export your Hugging Face API key (with access to Llama 3.3): ex …