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1. Semantic-RAG Semantic-RAG Public

   Advanced Retrieval-Augmented Generation (RAG) system for processing and retrieving semi-structured data from PDF documents using state-of-the-art NLP techniques.

   Python

2. Multi-Agent-RAG Multi-Agent-RAG Public

   Multi-agent RAG system using AutoGen for document-focused tasks in medical education, leveraging LangChain, ChromaDB, and OpenAI embeddings.

   Python 3

3. Multi-Agent-LLM Multi-Agent-LLM Public

   Multi-agent LLM project using LlamaIndex for document-specific QA, summarization, and top-level query orchestration with reranking and dynamic query planning.

   Python 2

4. Multimodal-RAG Multimodal-RAG Public

   Multimodal RAG using LangChain and Vertex AI for advanced document search and Q&A over text and images. Leverage Google's Gemini models for enhanced knowledge retrieval.

   Python 2

5. Anthropic-Multi-Modal Anthropic-Multi-Modal Public

   This project demonstrates how to use Anthropic's MultiModal LLMs, specifically Claude 3 Opus and Claude 3 Sonnet, for image reasoning and structured output parsing.

   Python 2

6. Text-to-Video-3D Text-to-Video-3D Public

   This project leverages VQGAN (Vector Quantized Generative Adversarial Networks) and CLIP (Contrastive Language-Image Pre-training) to create video frames from textual descriptions. By applying vari…

   Python 1