Update README.md

Author: mkswagger

README.md

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-# Llama Scholar : Transform WhatsApp into Your Smart Study Assistant with Llama models
+# Llama Scholar : Transform WhatsApp into Your Smart Study Assistant with Llama models 
 
 ## Problem Statement
 
@@ -19,5 +19,47 @@ The implementation of a WhatsApp bot involves utilizing Qdrant for efficient dat
 ![WhatsApp Image 2024-10-20 at 09 07 09](https://github.com/user-attachments/assets/743bb59f-080c-4de3-8970-c3d15aa60337)
 
 ## Tech Stack
+BackEnd: 
+- WhatsApp Business API
+- Ma-nish whatsapp wrapper
+- Python 
+- FastAPI
+- Llama3 models 
+- AWS BedRock 
+- Tune AI 
+- Qdrant
+
+FrontEnd: 
+- RemixJS
+- Tailwind CSS
+- Aceternity UI
+
+## Data Sources
+
+The project uses a combination of:
+- User-provided data (images, notes, presentations)
+- Stored educational content in the vector database
+- Generated content from Llama models
+- Data is collected through user interactions on WhatsApp and processed using Llama models. The system emphasizes data privacy and secure storage in the vector database.
+
+## Video Demo
+
+
+https://github.com/user-attachments/assets/e3f5d3d5-1120-45fd-93f2-5351c6cbb0f9
+
+
+## USP of Our Solution
+
+The solution's USP integrates cutting edge tools like  Qdrant for fast, personalized content retrieval, Tune AI  for optimized model performance, and a multimodal approach using LLaMA models. Leveraging WhatsApp, a platform widely used by students for real-time messaging, group chats, and multimedia sharing, it delivers dynamic content processing—text, images, and voice.
+Offering real-time summarization, image extraction, and personalized study tools, it enhances productivity and streamlines learning, providing an efficient, AI-powered support system within a familiar and accessible communication platform.
+
+## Future Scope 
+
+The solution has significant potential for scaling:
+- Adding more varied range of features into the bot 
+- Integration with more educational platforms and resources
+- Development of subject-specific modules for targeted learning
+- Potential for adaptation to professional training and lifelong learning contexts
+