CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework

This contains script that reimplements KAPING framework (Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering, Baek et al. 2023)

Powerful Auto Research powered by LangChain, and Anthropic.

A Survey of Multimodal Retrieval-Augmented Generation

Your personalized museum tour guide!

Tiledesk Server is the main API component of the Tiledesk platform 🚀 Tiledesk is an open-source alternative to Voiceflow, allowing you to build advanced LLM-powered agents with easy human-in-the-loop (HITL) when necessary.

React Agentic RAG app using LlamaIndex and OpenAI

The Tiledesk Automation Engine: Your open-source solution for multichannel workflow automation. An alternative to Voiceflow, Botpress, Stack AI, Flowise, Gumloop, VectorShift, Lyzr AI

Anthropic-SQL-Agent powered by LangChain, Anthropic

QA With Jupyter NoteBook(.ipynb) powered by LangChain & Anthropic

AI chatbot for PDF documents

RAG for Competitive Programming (rag_4_cpr) is a Retrieval-Augmented Generation (RAG) system designed to assist with solving competitive programming problems efficiently. The project aims to combine retrieval-based techniques with advanced LLM reasoning to deliver optimal solutions.

This is the official repository contains the code, data, and models of the paper titled "XL-HeadTags: Leveraging Multimodal Retrieval Augmentation for the Multilingual Generation of News Headlines and Tags", accepted for publication in Findings of the 62nd Annual Meeting of the Association for Computational Linguistics (ACL’24).

Self-corrective RAG Technical Documentation Assistant built with LangGraph, FastAPI, ChromaDB, and Groq.

Retrieval Augmented Generation

Repository dedicated to Term Project of UofT Intelligent Agents

Addresses supply chain risk per scheduled delivery item by adding new context with respect to weather conditions and local security or environmental news, which is passed through AI models to calculate delivery risk, while offering advisory on next steps.