Best AI tools for< Disable Autoscroll >

The website is an AI tool called ChatGPT that offers browser extensions to search chat history, pin chats, and disable autoscroll. ChatGPT uses advanced natural language processing to enhance chat experiences by providing users with convenient features to manage their conversations effectively.

Lion Accountability Browser is the first AI-powered accountability browser with built-in parental controls. It utilizes cutting-edge Artificial Intelligence and Machine Learning to accurately detect explicit websites and images in real-time. Users can track their browsing history, blacklist adult websites, fine-tune detection levels, and disable images and media for a safer online experience. The browser aims to promote responsible web browsing and help users build good online habits.

OpenRead is an AI-powered research tool that offers a seamless research experience by providing access to a vast repository of over 300 million papers and trillions of web sources. It allows users to search for papers in real-time, gain valuable insights, and explore trending research topics effortlessly. With features like paper Espresso, Paper Q&A, and related Paper Graph, OpenRead aims to enhance research productivity and knowledge organization. The tool also offers the ability to disable web support for focused tasks and remembers chat history for easy reference.

Trifacta API Documentation provides reference information on all of the available endpoints for each product edition. This website does not factor disabled features or your specific account permissions. To review API documentation for the endpoints to which your account has access, please select Help menu > API Documentation from the Trifacta application menu.

ChatGPT-VSCode is a Visual Studio Code integration that allows users to prompt OpenAI's GPT-4, GPT-3.5, GPT-3, and Codex models within the editor. It offers features like using improved models via OpenAI API Key, Azure OpenAI Service deployments, generating commit messages, storing conversation history, explaining and suggesting fixes for compile-time errors, viewing code differences, and more. Users can customize prompts, quick fix problems, save conversations, and export conversation history. The extension is designed to enhance developer experience by providing AI-powered assistance directly within VS Code.

GPTel is a simple Large Language Model chat client for Emacs, with support for multiple models and backends. It's async and fast, streams responses, and interacts with LLMs from anywhere in Emacs. LLM responses are in Markdown or Org markup. Supports conversations and multiple independent sessions. Chats can be saved as regular Markdown/Org/Text files and resumed later. You can go back and edit your previous prompts or LLM responses when continuing a conversation. These will be fed back to the model. Don't like gptel's workflow? Use it to create your own for any supported model/backend with a simple API.

LARS is an application that enables users to run Large Language Models (LLMs) locally on their devices, upload their own documents, and engage in conversations where the LLM grounds its responses with the uploaded content. The application focuses on Retrieval Augmented Generation (RAG) to increase accuracy and reduce AI-generated inaccuracies. LARS provides advanced citations, supports various file formats, allows follow-up questions, provides full chat history, and offers customization options for LLM settings. Users can force enable or disable RAG, change system prompts, and tweak advanced LLM settings. The application also supports GPU-accelerated inferencing, multiple embedding models, and text extraction methods. LARS is open-source and aims to be the ultimate RAG-centric LLM application.

Flowise is a tool that allows users to build customized LLM flows with a drag-and-drop UI. It is open-source and self-hostable, and it supports various deployments, including AWS, Azure, Digital Ocean, GCP, Railway, Render, HuggingFace Spaces, Elestio, Sealos, and RepoCloud. Flowise has three different modules in a single mono repository: server, ui, and components. The server module is a Node backend that serves API logics, the ui module is a React frontend, and the components module contains third-party node integrations. Flowise supports different environment variables to configure your instance, and you can specify these variables in the .env file inside the packages/server folder.

RestAI is an AIaaS (AI as a Service) platform that allows users to create and consume AI agents (projects) using a simple REST API. It supports various types of agents, including RAG (Retrieval-Augmented Generation), RAGSQL (RAG for SQL), inference, vision, and router. RestAI features automatic VRAM management, support for any public LLM supported by LlamaIndex or any local LLM supported by Ollama, a user-friendly API with Swagger documentation, and a frontend for easy access. It also provides evaluation capabilities for RAG agents using deepeval.

Funcchain is a Python library that allows you to easily write cognitive systems by leveraging Pydantic models as output schemas and LangChain in the backend. It provides a seamless integration of LLMs into your apps, utilizing OpenAI Functions or LlamaCpp grammars (json-schema-mode) for efficient structured output. Funcchain compiles the Funcchain syntax into LangChain runnables, enabling you to invoke, stream, or batch process your pipelines effortlessly.

OpenSSA is an open-source framework for creating efficient, domain-specific AI agents. It enables the development of Small Specialist Agents (SSAs) that solve complex problems in specific domains. SSAs tackle multi-step problems that require planning and reasoning beyond traditional language models. They apply OODA for deliberative reasoning (OODAR) and iterative, hierarchical task planning (HTP). This "System-2 Intelligence" breaks down complex tasks into manageable steps. SSAs make informed decisions based on domain-specific knowledge. With OpenSSA, users can create agents that process, generate, and reason about information, making them more effective and efficient in solving real-world challenges.

SeaGOAT is a local search tool that leverages vector embeddings to enable you to search your codebase semantically. It is designed to work on Linux, macOS, and Windows and can process files in various formats, including text, Markdown, Python, C, C++, TypeScript, JavaScript, HTML, Go, Java, PHP, and Ruby. SeaGOAT uses a vector database called ChromaDB and a local vector embedding engine to provide fast and accurate search results. It also supports regular expression/keyword-based matches. SeaGOAT is open-source and licensed under an open-source license, and users are welcome to examine the source code, raise concerns, or create pull requests to fix problems.

NoneBotPluginNaturelGPT is a plugin for NoneBot that enhances the GPT chat AI with more human-like characteristics. It supports multiple customizable personalities, preset sharing, and various features to improve chat interactions. Users can create personalized chat experiences, enable context-aware conversations, and benefit from features like long-term memory, user-specific impressions, and data persistence. The plugin also allows for personality switching, custom trigger words, content blocking, and more. It offers extensive capabilities for enhancing chat interactions and enabling AI to actively participate in conversations.

Langflow is an open-source Python-powered visual framework designed for building multi-agent and RAG applications. It is fully customizable, language model agnostic, and vector store agnostic. Users can easily create flows by dragging components onto the canvas, connect them, and export the flow as a JSON file. Langflow also provides a command-line interface (CLI) for easy management and configuration, allowing users to customize the behavior of Langflow for development or specialized deployment scenarios. The tool can be deployed on various platforms such as Google Cloud Platform, Railway, and Render. Contributors are welcome to enhance the project on GitHub by following the contributing guidelines.

The AI-Gateway repository explores the AI Gateway pattern through a series of experimental labs, focusing on Azure API Management for handling AI services APIs. The labs provide step-by-step instructions using Jupyter notebooks with Python scripts, Bicep files, and APIM policies. The goal is to accelerate experimentation of advanced use cases and pave the way for further innovation in the rapidly evolving field of AI. The repository also includes a Mock Server to mimic the behavior of the OpenAI API for testing and development purposes.

TiDB.AI is a conversational search RAG (Retrieval-Augmented Generation) app based on TiDB Serverless Vector Storage. It provides an out-of-the-box and embeddable QA robot experience based on knowledge from official and documentation sites. The platform features a Perplexity-style Conversational Search page with an advanced built-in website crawler for comprehensive coverage. Users can integrate an embeddable JavaScript snippet into their website for instant responses to product-related queries. The tech stack includes Next.js, TypeScript, Tailwind CSS, shadcn/ui for design, TiDB for database storage, Kysely for SQL query building, NextAuth.js for authentication, Vercel for deployments, and LlamaIndex for the RAG framework. TiDB.AI is open-source under the Apache License, Version 2.0.

sfdx-hardis is a toolbox for Salesforce DX, developed by Cloudity, that simplifies tasks which would otherwise take minutes or hours to complete manually. It enables users to define complete CI/CD pipelines for Salesforce projects, backup metadata, and monitor any Salesforce org. The tool offers a wide range of commands that can be accessed via the command line interface or through a Visual Studio Code extension. Additionally, sfdx-hardis provides Docker images for easy integration into CI workflows. The tool is designed to be natively compliant with various platforms and tools, making it a versatile solution for Salesforce developers.

Earth2Studio is a Python-based package designed to enable users to quickly get started with AI weather and climate models. It provides access to pre-trained models, diagnostic tools, data sources, IO utilities, perturbation methods, and sample workflows for building custom weather prediction workflows. The package aims to empower users to explore AI-driven meteorology through modular components and seamless integration with other Nvidia packages like Modulus.

This repository contains the training and inference code needed to replicate the winning solution to the AI Mathematical Olympiad - Progress Prize 1. It consists of fine-tuning DeepSeekMath-Base 7B, high-quality training datasets, a self-consistency decoding algorithm, and carefully chosen validation sets. The training methodology involves Chain of Thought (CoT) and Tool Integrated Reasoning (TIR) training stages. Two datasets, NuminaMath-CoT and NuminaMath-TIR, were used to fine-tune the models. The models were trained using open-source libraries like TRL, PyTorch, vLLM, and DeepSpeed. Post-training quantization to 8-bit precision was done to improve performance on Kaggle's T4 GPUs. The project structure includes scripts for training, quantization, and inference, along with necessary installation instructions and hardware/software specifications.

Frigate Home Assistant Integration provides a rich media browser with thumbnails and navigation, sensor entities for camera FPS, detection FPS, process FPS, skipped FPS, and objects detected, binary sensor entities for object motion, camera entities for live view and object detected snapshot, switch entities for clips, detection, snapshots, and improve contrast, and support for multiple Frigate instances. It offers easy installation via HACS and manual installation options for advanced users. Users need to configure the `mqtt` integration for Frigate to work. Additionally, media browsing and a companion Lovelace card are available for enhanced user experience. Refer to the main Frigate documentation for detailed installation instructions and usage guidance.

AutoFlow is an open source graph rag based knowledge base tool built on top of TiDB Vector and LlamaIndex and DSPy. It features a Perplexity-style Conversational Search page and an Embeddable JavaScript Snippet for easy integration into websites. The tool allows for comprehensive coverage and streamlined search processes through sitemap URL scraping.

Modus is an open-source, serverless framework for building APIs powered by WebAssembly. It simplifies integrating AI models, data, and business logic with sandboxed execution. Modus extracts metadata, compiles code with optimizations, caches compiled modules, prepares invocation plans, generates API schema, and activates endpoints. Users query the endpoint, and Modus loads compiled code into a sandboxed environment, runs code securely, queries data and AI models, and responds via API. It provides a production-ready scalable endpoint for AI-enabled apps, optimized for sub-second response times. Modus supports programming languages like AssemblyScript and Go, and can be hosted on Hypermode or any platform. Developed by Hypermode as an open-source project, Modus welcomes external contributions.

Janus is a series of unified multimodal understanding and generation models, including Janus-Pro, Janus, and JanusFlow. Janus-Pro is an advanced version that improves both multimodal understanding and visual generation significantly. Janus decouples visual encoding for unified multimodal understanding and generation, surpassing previous models. JanusFlow harmonizes autoregression and rectified flow for unified multimodal understanding and generation, achieving comparable or superior performance to specialized models. The models are available for download and usage, supporting a broad range of research in academic and commercial communities.

AIGES is a core component of the Athena Serving Framework, designed as a universal encapsulation tool for AI developers to deploy AI algorithm models and engines quickly. By integrating AIGES, you can deploy AI algorithm models and engines rapidly and host them on the Athena Serving Framework, utilizing supporting auxiliary systems for networking, distribution strategies, data processing, etc. The Athena Serving Framework aims to accelerate the cloud service of AI algorithm models and engines, providing multiple guarantees for cloud service stability through cloud-native architecture. You can efficiently and securely deploy, upgrade, scale, operate, and monitor models and engines without focusing on underlying infrastructure and service-related development, governance, and operations.

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Helps disabled people globally find and claim their benefits.

Due to OpenAI's policy, the original GPT's code execution has been disabled, making it non-functional. We're creating a compliant, functional GPT. Thanks for your understanding.由于OpenAI政策，原GPT代码执行被禁，因而不再能正常使用。我将在另一个链接上重建一个更加合规、功能正常的GPT，搜索本应用的英文名即可。感谢您的理解。