Vectara's RAG-Enhanced Customer Service Bot Platform
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Updated
Nov 9, 2023 - Python
Vectara's RAG-Enhanced Customer Service Bot Platform
Dive into LangChain, a powerful platform that lets you interact with your data like never before. This guide offers insights on its unique capabilities, helping you tap into your data in conversational ways.
EMNLP'2023: Retrieval-Generation Alignment for End-to-End Task-Oriented Dialogue System
"Chat with Databases using RAG" is a cutting-edge project that seamlessly integrates natural language inputs with database interactions. By leveraging advanced techniques like RAG and few-shot learning, it generates SQL queries from plain text and retrieves human-like responses from the database, revolutionizing the way we interact with data.
Takes in a users question and returns an answer along with URL resources.
Just training on langchain to improve RAG skills
An app allowing to upload files (ppt, doc, pdf, zip) and RAG on their content
VirtuTA is an AI teaching assistant that delivers quick, accurate responses to student queries directly on Piazza. Powered by agentic workflows, Google Gemini, and Langchain, it automates both conceptual and logistical course queries.
Unleash the power of LLMs over your data 🦙 ~ Exploring Different QA Engines
YouTube Video Summarizer and Q&A CLI using Perplexity AI & ChatGPT-4, built with langchain
A generative AI based smart information retrieval system featuring Hybrid Contextual Search,
An AI assistant for patent related queries
Experimenting with retrieval augmented generation (RAG) with the LangChain framework to identify tablets/capsules by their text description
Personal task management tool to schedule or reschedule incomplete tasks, while understanding user's needs.
Applications that can reason. Powered by LangChain.
A playground for anything related to retrieval augmented generation (RAG)
A generative AI app that responds to Phasmophobia-related queries.
CodeChat: Enabling interaction with codebases present in GitHub repositories. Seamlessly explore, query, and discuss code with a powerful RAG pipeline, making coding intuitive and efficient
Homework 3 for the machine learning class at Tsinghua University (fall term 23/24)
Add a description, image, and links to the retrieval-augmented-generation topic page so that developers can more easily learn about it.
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