Powerful Auto Research powered by LangChain, and Anthropic.
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Updated
Jul 16, 2024 - Python
Powerful Auto Research powered by LangChain, and Anthropic.
This contains script that reimplements KAPING framework (Knowledge-Augmented Language Model Prompting for Zero-Shot Knowledge Graph Question Answering, Baek et al. 2023)
React Agentic RAG app using LlamaIndex and OpenAI
Anthropic-SQL-Agent powered by LangChain, Anthropic
Your personalized museum tour guide!
QA With Jupyter NoteBook(.ipynb) powered by LangChain & Anthropic
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).
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.
Repository dedicated to Term Project of UofT Intelligent Agents
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