RTutor
Chat with your data via AI. https://RTutor.ai
Stars: 302
RTutor is an AI-based app that generates and tests R code by translating natural language into R scripts using API calls to OpenAI's ChatGPT. It executes the scripts within the Shiny platform, generating R Markdown source files and HTML reports. The tool features GPT-4 for accurate code, comprehensive EDA reports, and a chat window for code explanation, making it ideal for learning R and statistics.
README:
Hosted at RTutor.ai. Contact Steven Ge on LinkedIn or Twitter.
RTutor is an AI-based app that can quickly generate and test R code. Powered by API calls to OpenAI's ChatGPT or other models, RTutor translates natural languages into R scripts, which are then executed within the Shiny platform. An R Markdown source file and HTML report can be generated.
Highly recommend users to watch this 10-min YouTube video.
- GPT-4 becomes the default, providing more accurate code.
- Comprehensive EDA reports.
- Chat window that helps explain code, result, error messages, and statistics in general. This makes RTutor a great platform for learning R and statistics.
This repository is updated frequently, sometimes a few times a day. We suggest users reinstall everytime before using it, so that you always have the most recent version.
- Update R and RStudio to the most recent version.
- Install the RTutor package
if (!require("remotes")) {
install.packages("remotes")
}
library(remotes)
#voice input package heyshiny
install_github("jcrodriguez1989/heyshiny", dependencies = TRUE)
install_github("gexijin/RTutor")
- Install other R packages. If you want to use additional R package for analyzing your data, you should install these in your computer too.
- Create a personal account at OpenAI.
- After logging in, click on Personal from top left.
- Click Manage Account and then Billing, where you can add Payment methods and set Usage limits. $3-$5 per month is more than enough for most people.
- Click on API keys to create a new key, which can be copied.
There are several ways to do this.
- After the app is started, you can click on Settings and paste the API key.
- You can also save this key as a text file called api_key.txt in the working directory.
- Finally, you can create an environment variable called OPEN_API_KEY. Instructions for Windows, Mac, and Linux.
library(RTutor)
run_app()
(CC BY-NC 3.0) Non-commercial use.
See this report generated by RTutor after in a typical session.
RTutor also generates comprehensive reports for exploratory data analysis (EDA).
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for RTutor
Similar Open Source Tools
RTutor
RTutor is an AI-based app that generates and tests R code by translating natural language into R scripts using API calls to OpenAI's ChatGPT. It executes the scripts within the Shiny platform, generating R Markdown source files and HTML reports. The tool features GPT-4 for accurate code, comprehensive EDA reports, and a chat window for code explanation, making it ideal for learning R and statistics.
ComfyUI-Tara-LLM-Integration
Tara is a powerful node for ComfyUI that integrates Large Language Models (LLMs) to enhance and automate workflow processes. With Tara, you can create complex, intelligent workflows that refine and generate content, manage API keys, and seamlessly integrate various LLMs into your projects. It comprises nodes for handling OpenAI-compatible APIs, saving and loading API keys, composing multiple texts, and using predefined templates for OpenAI and Groq. Tara supports OpenAI and Grok models with plans to expand support to together.ai and Replicate. Users can install Tara via Git URL or ComfyUI Manager and utilize it for tasks like input guidance, saving and loading API keys, and generating text suitable for chaining in workflows.
litlytics
LitLytics is an affordable analytics platform leveraging LLMs for automated data analysis. It simplifies analytics for teams without data scientists, generates custom pipelines, and allows customization. Cost-efficient with low data processing costs. Scalable and flexible, works with CSV, PDF, and plain text data formats.
chat-with-notes
Chat-with-Notes is a Flask web application that enables users to upload text files, view their content, and engage with an AI chatbot for discussions. The application prioritizes privacy by utilizing a locally hosted Ollama Llama 3.1 (8B) model for AI responses, ensuring data security. Users can upload files during conversations, clear chat history, and export chat logs. The tool operates locally, requiring Python 3.x, pip, Git, and a locally running Ollama Llama 3.1 (8B) model as prerequisites.
Open_Data_QnA
Open Data QnA is a Python library that allows users to interact with their PostgreSQL or BigQuery databases in a conversational manner, without needing to write SQL queries. The library leverages Large Language Models (LLMs) to bridge the gap between human language and database queries, enabling users to ask questions in natural language and receive informative responses. It offers features such as conversational querying with multiturn support, table grouping, multi schema/dataset support, SQL generation, query refinement, natural language responses, visualizations, and extensibility. The library is built on a modular design and supports various components like Database Connectors, Vector Stores, and Agents for SQL generation, validation, debugging, descriptions, embeddings, responses, and visualizations.
langdrive
LangDrive is an open-source AI library that simplifies training, deploying, and querying open-source large language models (LLMs) using private data. It supports data ingestion, fine-tuning, and deployment via a command-line interface, YAML file, or API, with a quick, easy setup. Users can build AI applications such as question/answering systems, chatbots, AI agents, and content generators. The library provides features like data connectors for ingestion, fine-tuning of LLMs, deployment to Hugging Face hub, inference querying, data utilities for CRUD operations, and APIs for model access. LangDrive is designed to streamline the process of working with LLMs and making AI development more accessible.
Hexabot
Hexabot Community Edition is an open-source chatbot solution designed for flexibility and customization, offering powerful text-to-action capabilities. It allows users to create and manage AI-powered, multi-channel, and multilingual chatbots with ease. The platform features an analytics dashboard, multi-channel support, visual editor, plugin system, NLP/NLU management, multi-lingual support, CMS integration, user roles & permissions, contextual data, subscribers & labels, and inbox & handover functionalities. The directory structure includes frontend, API, widget, NLU, and docker components. Prerequisites for running Hexabot include Docker and Node.js. The installation process involves cloning the repository, setting up the environment, and running the application. Users can access the UI admin panel and live chat widget for interaction. Various commands are available for managing the Docker services. Detailed documentation and contribution guidelines are provided for users interested in contributing to the project.
supervisely
Supervisely is a computer vision platform that provides a range of tools and services for developing and deploying computer vision solutions. It includes a data labeling platform, a model training platform, and a marketplace for computer vision apps. Supervisely is used by a variety of organizations, including Fortune 500 companies, research institutions, and government agencies.
doc2plan
doc2plan is a browser-based application that helps users create personalized learning plans by extracting content from documents. It features a Creator for manual or AI-assisted plan construction and a Viewer for interactive plan navigation. Users can extract chapters, key topics, generate quizzes, and track progress. The application includes AI-driven content extraction, quiz generation, progress tracking, plan import/export, assistant management, customizable settings, viewer chat with text-to-speech and speech-to-text support, and integration with various Retrieval-Augmented Generation (RAG) models. It aims to simplify the creation of comprehensive learning modules tailored to individual needs.
stride-gpt
STRIDE GPT is an AI-powered threat modelling tool that leverages Large Language Models (LLMs) to generate threat models and attack trees for a given application based on the STRIDE methodology. Users provide application details, such as the application type, authentication methods, and whether the application is internet-facing or processes sensitive data. The model then generates its output based on the provided information. It features a simple and user-friendly interface, supports multi-modal threat modelling, generates attack trees, suggests possible mitigations for identified threats, and does not store application details. STRIDE GPT can be accessed via OpenAI API, Azure OpenAI Service, Google AI API, or Mistral API. It is available as a Docker container image for easy deployment.
pathway
Pathway is a Python data processing framework for analytics and AI pipelines over data streams. It's the ideal solution for real-time processing use cases like streaming ETL or RAG pipelines for unstructured data. Pathway comes with an **easy-to-use Python API** , allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: **you can use it in both development and production environments, handling both batch and streaming data effectively**. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a **scalable Rust engine** based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with **Docker and Kubernetes**. You can install Pathway with pip: `pip install -U pathway` For any questions, you will find the community and team behind the project on Discord.
reductstore
ReductStore is a high-performance time series database designed for storing and managing large amounts of unstructured blob data. It offers features such as real-time querying, batching data, and HTTP(S) API for edge computing, computer vision, and IoT applications. The database ensures data integrity, implements retention policies, and provides efficient data access, making it a cost-effective solution for applications requiring unstructured data storage and access at specific time intervals.
crawlee-python
Crawlee-python is a web scraping and browser automation library that covers crawling and scraping end-to-end, helping users build reliable scrapers fast. It allows users to crawl the web for links, scrape data, and store it in machine-readable formats without worrying about technical details. With rich configuration options, users can customize almost any aspect of Crawlee to suit their project's needs.
twinny
Twinny is a free and private AI extension for Visual Studio Code that offers AI-based code completion and code discussion features. It provides real-time code suggestions, function explanations, test generation, refactoring requests, and more. Twinny operates both online and offline, supports customizable API endpoints, conforms to OpenAI API standards, and offers various customization options for prompt templates, API providers, model names, and more. It is compatible with multiple APIs and allows users to accept code solutions directly in the editor, create new documents from code blocks, and copy generated code solution blocks. Twinny is open-source under the MIT license and welcomes contributions from the community.
OpenDAN-Personal-AI-OS
OpenDAN is an open source Personal AI OS that consolidates various AI modules for personal use. It empowers users to create powerful AI agents like assistants, tutors, and companions. The OS allows agents to collaborate, integrate with services, and control smart devices. OpenDAN offers features like rapid installation, AI agent customization, connectivity via Telegram/Email, building a local knowledge base, distributed AI computing, and more. It aims to simplify life by putting AI in users' hands. The project is in early stages with ongoing development and future plans for user and kernel mode separation, home IoT device control, and an official OpenDAN SDK release.
Local-Multimodal-AI-Chat
Local Multimodal AI Chat is a multimodal chat application that integrates various AI models to manage audio, images, and PDFs seamlessly within a single interface. It offers local model processing with Ollama for data privacy, integration with OpenAI API for broader AI capabilities, audio chatting with Whisper AI for accurate voice interpretation, and PDF chatting with Chroma DB for efficient PDF interactions. The application is designed for AI enthusiasts and developers seeking a comprehensive solution for multimodal AI technologies.
For similar tasks
Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.
sorrentum
Sorrentum is an open-source project that aims to combine open-source development, startups, and brilliant students to build machine learning, AI, and Web3 / DeFi protocols geared towards finance and economics. The project provides opportunities for internships, research assistantships, and development grants, as well as the chance to work on cutting-edge problems, learn about startups, write academic papers, and get internships and full-time positions at companies working on Sorrentum applications.
tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
zep-python
Zep is an open-source platform for building and deploying large language model (LLM) applications. It provides a suite of tools and services that make it easy to integrate LLMs into your applications, including chat history memory, embedding, vector search, and data enrichment. Zep is designed to be scalable, reliable, and easy to use, making it a great choice for developers who want to build LLM-powered applications quickly and easily.
telemetry-airflow
This repository codifies the Airflow cluster that is deployed at workflow.telemetry.mozilla.org (behind SSO) and commonly referred to as "WTMO" or simply "Airflow". Some links relevant to users and developers of WTMO: * The `dags` directory in this repository contains some custom DAG definitions * Many of the DAGs registered with WTMO don't live in this repository, but are instead generated from ETL task definitions in bigquery-etl * The Data SRE team maintains a WTMO Developer Guide (behind SSO)
mojo
Mojo is a new programming language that bridges the gap between research and production by combining Python syntax and ecosystem with systems programming and metaprogramming features. Mojo is still young, but it is designed to become a superset of Python over time.
pandas-ai
PandasAI is a Python library that makes it easy to ask questions to your data in natural language. It helps you to explore, clean, and analyze your data using generative AI.
databend
Databend is an open-source cloud data warehouse that serves as a cost-effective alternative to Snowflake. With its focus on fast query execution and data ingestion, it's designed for complex analysis of the world's largest datasets.
For similar jobs
lollms-webui
LoLLMs WebUI (Lord of Large Language Multimodal Systems: One tool to rule them all) is a user-friendly interface to access and utilize various LLM (Large Language Models) and other AI models for a wide range of tasks. With over 500 AI expert conditionings across diverse domains and more than 2500 fine tuned models over multiple domains, LoLLMs WebUI provides an immediate resource for any problem, from car repair to coding assistance, legal matters, medical diagnosis, entertainment, and more. The easy-to-use UI with light and dark mode options, integration with GitHub repository, support for different personalities, and features like thumb up/down rating, copy, edit, and remove messages, local database storage, search, export, and delete multiple discussions, make LoLLMs WebUI a powerful and versatile tool.
Azure-Analytics-and-AI-Engagement
The Azure-Analytics-and-AI-Engagement repository provides packaged Industry Scenario DREAM Demos with ARM templates (Containing a demo web application, Power BI reports, Synapse resources, AML Notebooks etc.) that can be deployed in a customer’s subscription using the CAPE tool within a matter of few hours. Partners can also deploy DREAM Demos in their own subscriptions using DPoC.
minio
MinIO is a High Performance Object Storage released under GNU Affero General Public License v3.0. It is API compatible with Amazon S3 cloud storage service. Use MinIO to build high performance infrastructure for machine learning, analytics and application data workloads.
mage-ai
Mage is an open-source data pipeline tool for transforming and integrating data. It offers an easy developer experience, engineering best practices built-in, and data as a first-class citizen. Mage makes it easy to build, preview, and launch data pipelines, and provides observability and scaling capabilities. It supports data integrations, streaming pipelines, and dbt integration.
AiTreasureBox
AiTreasureBox is a versatile AI tool that provides a collection of pre-trained models and algorithms for various machine learning tasks. It simplifies the process of implementing AI solutions by offering ready-to-use components that can be easily integrated into projects. With AiTreasureBox, users can quickly prototype and deploy AI applications without the need for extensive knowledge in machine learning or deep learning. The tool covers a wide range of tasks such as image classification, text generation, sentiment analysis, object detection, and more. It is designed to be user-friendly and accessible to both beginners and experienced developers, making AI development more efficient and accessible to a wider audience.
tidb
TiDB is an open-source distributed SQL database that supports Hybrid Transactional and Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.
airbyte
Airbyte is an open-source data integration platform that makes it easy to move data from any source to any destination. With Airbyte, you can build and manage data pipelines without writing any code. Airbyte provides a library of pre-built connectors that make it easy to connect to popular data sources and destinations. You can also create your own connectors using Airbyte's no-code Connector Builder or low-code CDK. Airbyte is used by data engineers and analysts at companies of all sizes to build and manage their data pipelines.
labelbox-python
Labelbox is a data-centric AI platform for enterprises to develop, optimize, and use AI to solve problems and power new products and services. Enterprises use Labelbox to curate data, generate high-quality human feedback data for computer vision and LLMs, evaluate model performance, and automate tasks by combining AI and human-centric workflows. The academic & research community uses Labelbox for cutting-edge AI research.