SageMaker - Make Anything Bot

AI-Powered Creation Assistance Platform

The SageMaker-Make Anything Bot is an AI-powered platform designed to streamline the process of creating projects by providing users with personalized step-by-step guidance, smart material recommendations, and curated tutorial videos. Leveraging Google Gemini Vision Pro, Python Django, and Generative AI, this tool reduces search time, improves user engagement, and enhances the overall creation experience.

Video Demo link : https://youtu.be/Vm9a1Mh63VU

Features

• Personalized Step-by-Step Guidance:
  The bot provides users with detailed instructions tailored to their specific projects, ensuring smooth workflows and reducing confusion.

• Smart Material Recommendations:
  Uses Generative AI and vector databases to recommend the best materials and tools based on user input, optimizing the creation process.

• Dynamic Cart Integration:
  Automatically adds the required items to the user's cart, minimizing the chance of missing out on necessary materials.

• Video Tutorials & Support:
  Offers curated tutorial videos to guide users through the entire process, ensuring they have the resources needed to complete their projects.

• Real-Time API Integration:
  Integrates with live APIs to adapt to user preferences and provide updated recommendations, ensuring a personalized experience.

• Creative Empowerment:
  Empowers users to turn their ideas into reality, enhancing engagement by an estimated 30% and boosting project completion rates.

Technology Stack

• Frontend:

  • Streamlit: For an interactive and user-friendly interface.

• Backend:

  • Django & JavaScript: Powering robust data handling and dynamic functionalities.
  • SQL Database: Efficient data management for user projects, materials, and recommendations.

• AI/ML Technologies:

  • Google Gemini 1.5 Pro Vision LLM: For enhanced natural language understanding and product/material recognition.
  • Hugging Face Word Embeddings: Enabling similarity search and context-aware recommendations.
  • ChromaDB: For storing and searching vectorized data efficiently.

Installation

1. Clone the repository:

   git clone https://github.com/your-repo/sagemaker.git

2.Install dependencies:

 
 pip install -r requirements.txt

3.Set up environment variables in a .env file:
```bash
 touch .enV

4.Run the Streamlit application:
```bash
streamlit run app.py