🌟 Real-Time Research & Media Assistant

🚀 Inspiration

Imagine a real-time, all-in-one research and media assistant where users can seamlessly upload or link various content—videos, images, PDFs—and receive instant, cross-referenced insights.

🔹 Use Case: A student preparing for a presentation can:
✔️ Extract key points from research papers 📄
✔️ Get summarized video breakdowns 🎥
✔️ Generate custom visuals for slides 🎨

All within a single session!

🔍 What It Does

Our platform utilizes advanced semantic search algorithms to analyze and retrieve relevant data from a diverse content repository. Here's how it works:

🎯 Semantic Search & Contextual Understanding

• The system performs a semantic search to fetch relevant content, using it as references to enhance LLM outputs.
  

🤖 Multi-Agent System for Smart Processing

• Understands user input and dynamically assigns the right agent for the task.
  
• Handles various formats including images, YouTube links, and PDFs.
  

📽️ Video Summarization

• Fetches metadata via YouTube API.
  
• Uses LLMs to generate concise and relevant summaries.
  

🖼️ Image & Document Analysis

• Extracts and summarizes text from images & PDFs.
  
• Ensures a comprehensive, multi-format experience.
  

🎨 AI-Generated Visuals

• Uses Stable Diffusion to generate images from text.
  
• Stores generated images on Pinata (IPFS).
  

💬 Chat History & Memory

• Maintains a comprehensive chat history for context continuity.
  
• Enables users to reference past interactions seamlessly.
  

🛠️ Tech Stack

Built using cutting-edge technologies:

✅ Next.js – Frontend framework for a smooth UI/UX
✅ Langchain & LangGraph – Powering AI workflows
✅ Pinecone – Vector search for fast retrieval
✅ Hugging Face API – Advanced LLM processing
✅ Pinata (IPFS) – Decentralized storage for images
✅ Firebase – Authentication & database management

🚀 Bringing research and media processing into a new era!

Built With

• huggingface
• langchain
• langgraph
• next
• node.js
• pinecone