Best AI tools for< Pull Live Data >

Superjoin is an AI-powered tool that allows users to automatically pull data from various tools into Google Sheets without the need for writing any code. It offers features like one-click connectors, auto-refresh schedules, data preview, and the ability to send report screenshots to Slack and Email. Superjoin is loved by thousands of users across hundreds of companies for its efficiency in automating workflows and data management.

OSS Insight is an AI tool that provides deep insight into developers and repositories on GitHub, offering information about stars, pull requests, issues, pushes, comments, and reviews. It utilizes artificial intelligence to analyze data and provide valuable insights to users. The tool ranks repositories, tracks trending repositories, and offers real-time information about GitHub events. Additionally, it offers features like data exploration, collections, live blog, API integration, and widgets.

Fine is an AI-powered software development tool that automates mundane and complex tasks, allowing developers to focus on driving innovation. Its AI agents integrate seamlessly into your team and toolset, transforming your development workflow by automating tasks such as transforming Jira tickets into pull requests, streamlining code reviews, and simplifying migrations.

What The Diff is an AI-powered code review assistant that helps you to write pull request descriptions, send out summarized notifications, and refactor minor issues during the review. It uses natural language processing to understand the changes in your code and generate clear and concise descriptions. What The Diff also provides rich summary notifications that are easy for non-technical stakeholders to understand, and it can generate beautiful changelogs that you can share with your team or the public.

TextUnbox is an AI-powered tool that allows users to extract text from images, generate images from text descriptions, translate text, remove image backgrounds, and more. It supports over 20 languages and can be used in the browser or integrated into custom solutions using its REST API.

CodeRabbit is an innovative AI code review platform that streamlines and enhances the development process. By automating reviews, it dramatically improves code quality while saving valuable time for developers. The system offers detailed, line-by-line analysis, providing actionable insights and suggestions to optimize code efficiency and reliability. Trusted by hundreds of organizations and thousands of developers daily, CodeRabbit has processed millions of pull requests. Backed by CRV, CodeRabbit continues to revolutionize the landscape of AI-assisted software development.

Tusk is an AI-powered tool designed to prevent regressions and increase test coverage by generating unit and integration tests with codebase context. It reads codebase and documentation to suggest test cases, helping engineers catch edge cases that may be missed. Tusk seamlessly integrates into GitHub and CI/CD pipelines, offering features like mock services, non-blocking checks, user-centric interface design, personalization, integration with third-party APIs, and scalable architecture for high performance.

PYQ is an AI-powered platform that helps businesses automate document-related tasks, such as data extraction, form filling, and system integration. It uses natural language processing (NLP) and machine learning (ML) to understand the content of documents and perform tasks accordingly. PYQ's platform is designed to be easy to use, with pre-built automations for common use cases. It also offers custom automation development services for more complex needs.

Coursable is an AI-powered student workspace designed to enhance learning experiences. It leverages artificial intelligence to provide personalized study recommendations, track progress, and offer interactive learning tools. With Coursable, students can access a virtual study companion that adapts to their learning style and pace, making studying more efficient and engaging. The platform aims to revolutionize traditional learning methods by incorporating AI technology to support students in achieving their academic goals.

Korbit is an AI-powered code review tool that helps developers write better code, faster. It integrates directly into your GitHub PR workflow and provides instant feedback on your code, identifying issues and providing actionable recommendations. Korbit also provides valuable insights into code quality, project status, and developer performance, helping you to boost your productivity and elevate your code.

Gitya is an AI-powered GitHub assistant designed to streamline your GitHub workflow by automating minor tasks and enhancing productivity. With features like GitHub App integration, AI-enhanced automation, PR management, and ticket automation, Gitya aims to help users spend less time on busywork and more time on high-impact engineering tasks. Users have praised Gitya for its ability to reduce time spent on bug fixes and PR management, ultimately leading to increased project efficiency and success.

Weekly Github Insights is an AI-powered platform that provides users with a comprehensive summary of their latest GitHub activities from the past 7 days. It aims to keep users informed and motivated by compiling their weekly GitHub journey. The platform is built by @rohan_2502 using @aceternitylabs, @github APIs, and @OpenAI.

GPTConsole is an AI-powered platform that helps developers build production-ready applications faster and more efficiently. Its AI agents can generate code for a variety of applications, including web applications, AI applications, and landing pages. GPTConsole also offers a range of features to help developers build and maintain their applications, including an AI agent that can learn your entire codebase and answer your questions, and a CLI tool for accessing agents directly from the command line.

SellScale is an AI-powered prospecting tool designed to assist revenue organizations in launching campaigns, engaging with prospects, and obtaining feedback on products. It helps users in setting up conference meetings, launching new products, and reaching out to potential customers effectively. The tool is built with design partners and customers, offering features such as quickly launching campaigns based on recent news, gearing up for product launches, getting feedback from early adopters, and personalizing outreach messages using AI technology. SellScale aims to ensure proper deliverability of emails, enable users to pull contacts from various data providers, and enhance messaging to resonate with the target audience.

Maverick is an incremental layer of automated code review for GitHub pull requests. It helps catch small issues that may go unnoticed, providing feedback via GitHub review comments. Maverick is a free tool that monitors selected repositories and assists developers in improving code quality.

Trag is an AI-powered tool designed to review pull requests in minutes, empowering engineering teams to save time and focus on building products. With Trag, users can create custom patterns for code review, ensuring best practices are followed and bugs are caught early. The tool offers features like autofix with AI, monitoring progress, connecting multiple repositories, pull request review, analytics, and team workspaces. Trag stands out from traditional linters by providing complex code understanding, semantic code analysis, predictive bug detection, and refactoring suggestions. It aims to streamline code reviews and help teams ship faster with AI-powered reviews.

Elessar is an AI-powered platform designed to enhance engineering productivity by providing automatic documentation, reporting, and visibility for development teams. It seamlessly integrates with existing ecosystems, generates pull request changelogs, automates Notion documentation, offers Slack bot functionality, provides VS Code extension for easy code understanding, and links with Linear for issue tracking. Elessar ensures data privacy and security by following SOC II compliant policies and encrypting data at rest and in transit. It does not use data for training AI models. With Elessar, organizations can streamline communication, improve visibility, and boost productivity.

Maige is an open-source infrastructure designed to run natural language workflows on your codebase. It allows users to connect their repository, define rules for handling issues and pull requests, and monitor the workflow execution through a dashboard. Maige leverages AI capabilities to label, assign, comment, review code, and execute simple code snippets, all while being customizable and flexible with the GitHub API.

Greptile is an AI tool designed to assist developers in code review processes. It integrates with GitHub to review pull requests and identify bugs, antipatterns, and other issues in the codebase. By leveraging AI technology, Greptile aims to streamline the code review process and improve code quality.

ChainAware.ai is an AI-powered blockchain super tool designed for both users and businesses. It offers a range of features such as Wallet Auditor, Fraud Detector, and Rug Pull Detector to enhance security and trust in blockchain transactions. The tool provides predictive AI capabilities to prevent fraud and identify potential risks before they occur. Additionally, it offers business solutions including account-based user acquisition, web3 user analytics, and crypto fraud detection with AI. ChainAware.ai aims to revolutionize the way users interact with blockchain technology by providing advanced tools and services powered by artificial intelligence.

The Artificial Intelligence Incident Database (AIID) is a collection of incidents involving the development and use of artificial intelligence (AI). The database is designed to help researchers, policymakers, and the public understand the potential risks and benefits of AI, and to inform the development of policies and practices to mitigate the risks and promote the benefits of AI. The AIID is a collaborative project involving researchers from the University of California, Berkeley, the University of Washington, and the University of Toronto.

Arena-Hard-Auto-v0.1 is an automatic evaluation tool for instruction-tuned LLMs. It contains 500 challenging user queries. The tool prompts GPT-4-Turbo as a judge to compare models' responses against a baseline model (default: GPT-4-0314). Arena-Hard-Auto employs an automatic judge as a cheaper and faster approximator to human preference. It has the highest correlation and separability to Chatbot Arena among popular open-ended LLM benchmarks. Users can evaluate their models' performance on Chatbot Arena by using Arena-Hard-Auto.

The Conversational Azure OpenAI Accelerator is a tool designed to provide rapid, no-cost custom demos tailored to customer use cases, from internal HR/IT to external contact centers. It focuses on top use cases of GenAI conversation and summarization, plus live backend data integration. The tool automates conversations across voice and text channels, providing a valuable way to save money and improve customer and employee experience. By combining Azure OpenAI + Cognitive Search, users can efficiently deploy a ChatGPT experience using web pages, knowledge base articles, and data sources. The tool enables simultaneous deployment of conversational content to chatbots, IVR, voice assistants, and more in one click, eliminating the need for in-depth IT involvement. It leverages Microsoft's advanced AI technologies, resulting in a conversational experience that can converse in human-like dialogue, respond intelligently, and capture content for omni-channel unified analytics.

HolmesGPT is an open-source DevOps assistant powered by OpenAI or any tool-calling LLM of your choice. It helps in troubleshooting Kubernetes, incident response, ticket management, automated investigation, and runbook automation in plain English. The tool connects to existing observability data, is compliance-friendly, provides transparent results, supports extensible data sources, runbook automation, and integrates with existing workflows. Users can install HolmesGPT using Brew, prebuilt Docker container, Python Poetry, or Docker. The tool requires an API key for functioning and supports OpenAI, Azure AI, and self-hosted LLMs.

Kheish is an open-source, multi-role agent designed for complex tasks that require structured, step-by-step collaboration with Large Language Models (LLMs). It acts as an intelligent agent that can request modules on demand, integrate user feedback, switch between specialized roles, and deliver refined results. By harnessing multiple 'sub-agents' within one framework, Kheish tackles tasks like security audits, file searches, RAG-based exploration, and more.

GenAI Agents is a comprehensive repository for developing and implementing Generative AI (GenAI) agents, ranging from simple conversational bots to complex multi-agent systems. It serves as a valuable resource for learning, building, and sharing GenAI agents, offering tutorials, implementations, and a platform for showcasing innovative agent creations. The repository covers a wide range of agent architectures and applications, providing step-by-step tutorials, ready-to-use implementations, and regular updates on advancements in GenAI technology.

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.

Google GenerativeAI (Gemini) is an unofficial C# .Net SDK based on REST APIs for accessing Google Gemini models. It offers a complete rewrite of the previous SDK with improved performance, flexibility, and ease of use. The SDK seamlessly integrates with LangChain.net, providing easy methods for JSON-based interactions and function calling with Google Gemini models. It includes features like enhanced JSON mode handling, function calling with code generator, multi-modal functionality, Vertex AI support, multimodal live API, image generation and captioning, retrieval-augmented generation with Vertex RAG Engine and Google AQA, easy JSON handling, Gemini tools and function calling, multimodal live API, and more.

DeepEval is a simple-to-use, open-source LLM evaluation framework specialized for unit testing LLM outputs. It incorporates various metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., and runs locally on your machine for evaluation. It provides a wide range of ready-to-use evaluation metrics, allows for creating custom metrics, integrates with any CI/CD environment, and enables benchmarking LLMs on popular benchmarks. DeepEval is designed for evaluating RAG and fine-tuning applications, helping users optimize hyperparameters, prevent prompt drifting, and transition from OpenAI to hosting their own Llama2 with confidence.

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)

AI Town is a virtual town where AI characters live, chat, and socialize. This project provides a deployable starter kit for building and customizing your own version of AI Town. It features a game engine, database, vector search, auth, text model, deployment, pixel art generation, background music generation, and local inference. You can customize your own simulation by creating characters and stories, updating spritesheets, changing the background, and modifying the background music.

The Missing Persons 2024 Antifinance Bill Demonstrations Kenya database is an AI-powered platform designed to track and identify individuals who have gone missing during the ongoing protests. It aims to assist in reuniting families by providing a centralized online resource for all Kenyans. The platform allows for crowdsourced information upload, monitoring disappearances, and tracking unidentified bodies to create a comprehensive database. Key features include a user-friendly interface, AI-powered search, real-time updates, secure handling of data, and detailed reporting.

DBRX is a large language model trained by Databricks and made available under an open license. It is a Mixture-of-Experts (MoE) model with 132B total parameters and 36B live parameters, using 16 experts, of which 4 are active during training or inference. DBRX was pre-trained for 12T tokens of text and has a context length of 32K tokens. The model is available in two versions: a base model and an Instruct model, which is finetuned for instruction following. DBRX can be used for a variety of tasks, including text generation, question answering, summarization, and translation.

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.

LEADS is a lightweight embedded assisted driving system designed to simplify the development of instrumentation, control, and analysis systems for racing cars. It is written in Python and C/C++ with impressive performance. The system is customizable and provides abstract layers for component rearrangement. It supports hardware components like Raspberry Pi and Arduino, and can adapt to various hardware types. LEADS offers a modular structure with a focus on flexibility and lightweight design. It includes robust safety features, modern GUI design with dark mode support, high performance on different platforms, and powerful ESC systems for traction control and braking. The system also supports real-time data sharing, live video streaming, and AI-enhanced data analysis for driver training. LEADS VeC Remote Analyst enables transparency between the driver and pit crew, allowing real-time data sharing and analysis. The system is designed to be user-friendly, adaptable, and efficient for racing car development.

The Amazon Transcribe Live Call Analytics (LCA) with Agent Assist Sample Solution is designed to help contact centers assess and optimize caller experiences in real time. It leverages Amazon machine learning services like Amazon Transcribe, Amazon Comprehend, and Amazon SageMaker to transcribe and extract insights from contact center audio. The solution provides real-time supervisor and agent assist features, integrates with existing contact centers, and offers a scalable, cost-effective approach to improve customer interactions. The end-to-end architecture includes features like live call transcription, call summarization, AI-powered agent assistance, and real-time analytics. The solution is event-driven, ensuring low latency and seamless processing flow from ingested speech to live webpage updates.

Databend is an open-source cloud data warehouse built in Rust, offering fast query execution and data ingestion for complex analysis of large datasets. It integrates with major cloud platforms, provides high performance with AI-powered analytics, supports multiple data formats, ensures data integrity with ACID transactions, offers flexible indexing options, and features community-driven development. Users can try Databend through a serverless cloud or Docker installation, and perform tasks such as data import/export, querying semi-structured data, managing users/databases/tables, and utilizing AI functions.

An open-source AI assistant for taking meeting notes that captures live meeting audio, transcribes it in real-time, and generates summaries while ensuring user privacy. Perfect for teams to focus on discussions while automatically capturing and organizing meeting content without external servers or complex infrastructure. Features include modern UI, real-time audio capture, speaker diarization, local processing for privacy, and more. The tool also offers a Rust-based implementation for better performance and native integration, with features like live transcription, speaker diarization, and a rich text editor for notes. Future plans include database connection for saving meeting minutes, improving summarization quality, and adding download options for meeting transcriptions and summaries. The backend supports multiple LLM providers through a unified interface, with configurations for Anthropic, Groq, and Ollama models. System architecture includes core components like audio capture service, transcription engine, LLM orchestrator, data services, and API layer. Prerequisites for setup include Node.js, Python, FFmpeg, and Rust. Development guidelines emphasize project structure, testing, documentation, type hints, and ESLint configuration. Contributions are welcome under the MIT License.

The MiniAiLive Face Recognition LivenessDetection Server SDK provides system integrators with fast, flexible, and extremely precise facial recognition that can be deployed across various scenarios, including security, access control, public safety, fintech, smart retail, and home protection. The SDK is fully on-premise, meaning all processing happens on the hosting server, and no data leaves the server. The project structure includes bin, cpp, flask, model, python, test_image, and Dockerfile directories. To set up the project on Linux, download the repo, install system dependencies, and copy libraries into the system folder. For Windows, contact MiniAiLive via email. The C++ example involves replacing the license key in main.cpp, building the project, and running it. The Python example requires installing dependencies and running the project. The Python Flask example involves replacing the license key in app.py, installing dependencies, and running the project. The Docker Flask example includes building the docker image and running it. To request a license, contact MiniAiLive. Contributions to the project are welcome by following specific steps. An online demo is available at https://demo.miniai.live. Related products include MiniAI-Face-Recognition-LivenessDetection-AndroidSDK, MiniAI-Face-Recognition-LivenessDetection-iOS-SDK, MiniAI-Face-LivenessDetection-AndroidSDK, MiniAI-Face-LivenessDetection-iOS-SDK, MiniAI-Face-Matching-AndroidSDK, and MiniAI-Face-Matching-iOS-SDK. MiniAiLive is a leading AI solutions company specializing in computer vision and machine learning technologies.

This GPT can generate code for you. For now it creates full-stack apps using Typescript. Just describe the feature you want and you will get a link to the Github code pull request and the live app deployed.

Assists with code review, pull requests, and writing tests.

Clear, brief GitHub aid, for you

Git specialist offering university-level teaching and guidance.

Expert at fetching repository information from GitHub, Hugging Face. and you local repositories

Friendly GIT Assistant/Expert !

主动且直观的 Git 和 GitHub 中文学习助手。