🛍️ ShopSmart.AI - Intelligent Shopping Assistant Powered by AIMLAPI and CrewAI

Welcome to the ShopSmart.AI repository!
This project is an Intelligent Shopping Assistant, built for the Execute: AI Genesis Hackathon 2025.
It enhances shopping experiences using multi-agent collaboration and end-to-end AI services via AIMLAPI, providing personalized product recommendations, review analysis, and voice interaction — all in one place.

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📚 Table of Contents

1. Overview
2. Features
3. Tech Stack & Gen AI Capabilities
4. Setup and Installation
5. Usage
6. Contributing
7. License

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🚀 Overview

ShopSmart.AI uses intelligent agents built with CrewAI and entirely powered by AIMLAPI services:

• Product search and structured extraction (name, price, image URL, rating, etc.)
• LLM-based reasoning and recommendations
• Voice-to-text input handling (Whisper via AIMLAPI)
• Review summarization using RAG with embeddings (via AIMLAPI)

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✨ Features

• Personalized Recommendations: Suggests best-fit products based on user queries and preferences.
• Multi-Agent System: Intelligent agents collaborate using CrewAI for product search, analysis, and summarization.
• Voice & Text Input Support: Users can interact via typing or speaking (speech recognition powered by AIMLAPI).
• Product Search & Comparison: Searches across platforms and compares multiple products.
• Review Summarization: Summarizes user reviews to assist in faster, smarter decision-making using RAG.
• Updated Product Information: Retrieves product Name, Price, Image URL, Ratings, Reviews, and more in real-time.
• Powered Entirely by AIMLAPI: All LLM, embeddings, retrievals, and speech-to-text functionalities handled via AIMLAPI.
• User-Friendly Interface: Built with Streamlit for seamless and simple interaction.

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🛠️ Technologies, Tools & Gen AI Capabilities Mapping

Component	Purpose	Gen AI Capability Demonstrated
AIMLAPI - LLM	Provides reasoning, analysis, product recommendations	✅ Natural Language Understanding ✅ Structured Output Generation
AIMLAPI - Embeddings	Semantic vector search and document retrieval for RAG	✅ Semantic Search ✅ Retrieval-Augmented Generation (RAG)
AIMLAPI - Whisper (Speech-to-Text)	Converts user voice input into text	✅ Voice Recognition ✅ Conversational Interface
AIMLAPI - Web Search + Scraping	Retrieves product details (Name, Price, Image URL, Ratings, etc.)	✅ Information Retrieval ✅ Structured Data Extraction
CrewAI	Orchestrates multiple AI agents for workflow management	✅ Multi-Agent Collaboration
Streamlit	Web application interface for user interaction	✅ Real-time User Interaction
Python (Colab / Local)	Programming environment for prototyping and deployment	✅ Experimentation and Development

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🛠️ Setup and Installation

Follow these steps to set up and run the project locally:

1. Clone the Repository:

   git clone https://github.com/SheemaMasood381/Intelligent-Shopping-Assistant-with-CrewAi.git
   cd Intelligent-Shopping-Assistant-with-CrewAi

2. Create a Virtual Environment (Optional but recommended):

   python3 -m venv venv
   source venv/bin/activate   # For Linux/Mac
   venv\Scripts\activate      # For Windows

3. Install Required Dependencies:

   pip install -r requirements.txt

4. Run the Application:

   python app.py

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Streamlit App for Smart Product Recommendations

🚀 Usage

After setting up:

Run the Streamlit App:

streamlit run app.py

Interact with the Assistant:

• Enter a text query (e.g., "Find me a budget smartphone under $300")
• Or Speak your query directly (Speech Recognition enabled via AIMLAPI Whisper)

View recommended products with:

• Name
• Price
• Image
• Ratings
• Summarized reviews

Get smart recommendations generated by CrewAI agents and LLMs.

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🤝 Contributing

Contributions are welcome! Please fork the repo and submit a pull request.

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📜 License

This project is licensed under the MIT License.

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📩 Contact

• Email: sheemamasood381@gmail.com | mmasood04@gmail.com
• GitHub: SheemaMasood381

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