[EMNLP '25] A web app and Python API for multi-modal RAG framework to ground LLMs on high-fidelity materials informatics. An agentic materials scientist powered by @materialsproject, @langchain-ai, and @openai https://aclanthology.org/2025.emnlp-main.1280/

RAG Agent System - Spring AI + React + Multi-modal Document Parsing + Hybrid Vector Retrieval

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Awesome papers in Large Language Models (LLM). They focus on state-of-the-art LLM methods, such as algorithms, system, SFT, RL, Multi-modal LLMs, MOE, Quantization, and Applications (RAG, agent, coding).

A multi modal RAG chatbot using Vertex AI SDK, Gemini, Langchain and Chainlit

"Enterprise-grade hierarchical agentic RAG for multi-modal reasoning"

A multimodal RAG-based generative AI digital assistant that combines text generation, vision QA, and code generation.

M3ARAG = Multi-Modal Multi-Agent RAG system for comprehensive document understanding through specialized AI agents processing PDFs, Office docs, and web content with iterative quality improvement.

Data scientist lab run in Google Colab or locally in Anaconda using JupyterLab to experiment in creating AI agents in python using various Open Source and Frontier LLM models. Projects include RAG, inference, function calling and multi-modal techniques.

A Multi-Modal Agentic RAG pipeline designed to handle unstructured documents containing tables, charts, and images. It integrates Docling and ElasticSearch for structured indexing, and leverages LangGraph for agent-based reasoning and dynamic query reformulation.

A simple MultiModal RAG Agent on Text and Tables using LangChain and Docling.

A comprehensive medical image analysis pipeline for dermatological question answering using multi-modal large language models, featuring fine-tuning, reasoning layers, and agentic RAG systems.

Production-ready multi-agent AI systems using Modal, LLaMA, RAG, vector databases, and autonomous workflows.

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Building a Multi-Modal AI Agent with an Enhanced Retrieval Augmented Generation(RAG) System for Web Search, Stock and Cryptocurrency Investment Analysis.

Multi-agent AI movie recommendation system - 6 LangGraph agents (profile analysis, content intelligence, context-aware, serendipity, adversarial critic, explainability) with RAG, ChromaDB vector search, multi-modal embeddings, and a React + FastAPI stack. Supports group recommendations, Letterboxd import, and real-time cinema news.

Multi Modal Agent using Deepgram and Groq LPU's and Sentence Transformers for Vector Embeddings, ChromaDB for persistent vector db storage and BM25 with ColBERT reranking for hybrid search for RAG context management

A multi-modal AI system combining image captioning, VQA, RAG, and agent-driven reasoning with FastAPI backend and Gradio/React/PyQt frontends. Features BLIP-2, LLaVA, Qwen-VL, and text-based adventure game integration.

A next-generation, zero-code, hyper-scalable autonomous AI agent swarm orchestration ecosystem. Leverage multi-modal LLM reasoning like Claude, GPT Codex, or Local Ollama, and asynchronous RAG memory layers to deploy an entire decentralized AI software agency, managed natively through enterprise chat platforms (Discord, Slack, Telegram, WhatsApp).

Multi-Agent multi-modal RAG System

Agentic Video RAG - Multi-modal video understanding with AI agents

End-To-End Multi-Modal RAG Using both basic and Agentic workflows

Multi-modal RAG agent that processes video/audio to answer questions with precise timestamps.

An intelligent RAG+AGENT knowledge base system supporting multi-modal data, secure permissions, and advanced retrieval.

MemU is an agentic memory framework for LLM and AI agent backends: it ingests multi-modal data, extracts and organizes it into structured memory and supports both RAG and LLM-based retrieval.

An AI-Agent-Driven Medical Assistant Platform combining Multi-Modal AI and Retrieval Augmented Generation (RAG) for comprehensive intelligent medical assistance, enhanced diagnostics, and streamlined workflow automation.

I have learned and worked with Python, Git, Docker, Pydantic, LLMs, Agents, RAG, LangChain, LangGraph, and Multi-Modal AI, and can build, deploy, and scale real-world AI applications.

Black-bot is a simplified, plug-and-play RAG chatbot template for learning or production. Multi-agent, multi-modal (text, PDF, image/OCR), N18N (multilingual) support. Run offline (Ollama) or cloud (OpenAI). Python, LangChain, Gradio. Easy to extend!

Built an autonomous multi-agent research system using CrewAI & Streamlit. Features multi-modal RAG (Text+Vision), live web search, & hybrid LLMs. Optimized chart analysis with custom vision pipelines and secure data isolation to generate professional enterprise reports from proprietary PDFs.

This repository benchmarks FuriosaAI RNGD on LLM tasks like RAG Chatbots, translation, summarization, and multi-modal agents. It provides unified APIs and configurable pipelines for seamless comparisons between GPU and NPU environments, enabling efficient performance evaluation.