ScrapeGraphAI is a web scraping Python library that utilizes LLM and direct graph logic to create scraping pipelines for websites and local documents. It offers various standard scraping pipelines like SmartScraperGraph, SearchGraph, SpeechGraph, and ScriptCreatorGraph. Users can extract information by specifying prompts and input sources. The library supports different LLM APIs such as OpenAI, Groq, Azure, and Gemini, as well as local models using Ollama. ScrapeGraphAI is designed for data exploration and research purposes, providing a versatile tool for extracting information from web pages and generating outputs like Python scripts, audio summaries, and search results.

ScaleLLM is a cutting-edge inference system engineered for large language models (LLMs), meticulously designed to meet the demands of production environments. It extends its support to a wide range of popular open-source models, including Llama3, Gemma, Bloom, GPT-NeoX, and more. ScaleLLM is currently undergoing active development. We are fully committed to consistently enhancing its efficiency while also incorporating additional features. Feel free to explore our **_Roadmap_** for more details. ## Key Features * High Efficiency: Excels in high-performance LLM inference, leveraging state-of-the-art techniques and technologies like Flash Attention, Paged Attention, Continuous batching, and more. * Tensor Parallelism: Utilizes tensor parallelism for efficient model execution. * OpenAI-compatible API: An efficient golang rest api server that compatible with OpenAI. * Huggingface models: Seamless integration with most popular HF models, supporting safetensors. * Customizable: Offers flexibility for customization to meet your specific needs, and provides an easy way to add new models. * Production Ready: Engineered with production environments in mind, ScaleLLM is equipped with robust system monitoring and management features to ensure a seamless deployment experience.

OptScale is an open-source FinOps and MLOps platform that provides cloud cost optimization for all types of organizations and MLOps capabilities like experiment tracking, model versioning, ML leaderboards.

VNVE is a Visual Novel Video Editor that allows users to create visual novel videos in their browser with AI-powered rapid creation. It offers a low-cost production solution for converting textual content into videos, creating interactive videos for gaming experiences, and making video teasers for novels and short video dramas. The tool is a pure front-end Typescript implementation powered by PixiJS + WebCodecs, and users can also create videos programmatically using the npm package. VNVE is tailored specifically for visual novels, focusing on text content and simplifying the video creation process for users.

Mistral Typescript Client is an SDK for Mistral AI API, providing Chat Completion and Embeddings APIs. It allows users to create chat completions, upload files, create agent completions, create embedding requests, and more. The SDK supports various JavaScript runtimes and provides detailed documentation on installation, requirements, API key setup, example usage, error handling, server selection, custom HTTP client, authentication, providers support, standalone functions, debugging, and contributions.

SynapseML (previously known as MMLSpark) is an open-source library that simplifies the creation of massively scalable machine learning (ML) pipelines. It provides simple, composable, and distributed APIs for various machine learning tasks such as text analytics, vision, anomaly detection, and more. Built on Apache Spark, SynapseML allows seamless integration of models into existing workflows. It supports training and evaluation on single-node, multi-node, and resizable clusters, enabling scalability without resource wastage. Compatible with Python, R, Scala, Java, and .NET, SynapseML abstracts over different data sources for easy experimentation. Requires Scala 2.12, Spark 3.4+, and Python 3.8+.

vnc-lm is a Discord bot designed for messaging with language models. Users can configure model parameters, branch conversations, and edit prompts to enhance responses. The bot supports various providers like OpenAI, Huggingface, and Cloudflare Workers AI. It integrates with ollama and LiteLLM, allowing users to access a wide range of language model APIs through a single interface. Users can manage models, switch between models, split long messages, and create conversation branches. LiteLLM integration enables support for OpenAI-compatible APIs and local LLM services. The bot requires Docker for installation and can be configured through environment variables. Troubleshooting tips are provided for common issues like context window problems, Discord API errors, and LiteLLM issues.

Pixeltable is a Python library designed for ML Engineers and Data Scientists to focus on exploration, modeling, and app development without the need to handle data plumbing. It provides a declarative interface for working with text, images, embeddings, and video, enabling users to store, transform, index, and iterate on data within a single table interface. Pixeltable is persistent, acting as a database unlike in-memory Python libraries such as Pandas. It offers features like data storage and versioning, combined data and model lineage, indexing, orchestration of multimodal workloads, incremental updates, and automatic production-ready code generation. The tool emphasizes transparency, reproducibility, cost-saving through incremental data changes, and seamless integration with existing Python code and libraries.

PromptClip is a tool that allows developers to create video clips using LLM prompts. Users can upload videos from various sources, prompt the video in natural language, use different LLM models, instantly watch the generated clips, finetune the clips, and add music or image overlays. The tool provides a seamless way to extract specific moments from videos based on user queries, making video editing and content creation more efficient and intuitive.

Ling is a MoE LLM provided and open-sourced by InclusionAI. It includes two different sizes, Ling-Lite with 16.8 billion parameters and Ling-Plus with 290 billion parameters. These models show impressive performance and scalability for various tasks, from natural language processing to complex problem-solving. The open-source nature of Ling encourages collaboration and innovation within the AI community, leading to rapid advancements and improvements. Users can download the models from Hugging Face and ModelScope for different use cases. Ling also supports offline batched inference and online API services for deployment. Additionally, users can fine-tune Ling models using Llama-Factory for tasks like SFT and DPO.

Eval-Scope is a framework designed to support the evaluation of large language models (LLMs) by providing pre-configured benchmark datasets, common evaluation metrics, model integration, automatic evaluation for objective questions, complex task evaluation using expert models, reports generation, visualization tools, and model inference performance evaluation. It is lightweight, easy to customize, supports new dataset integration, model hosting on ModelScope, deployment of locally hosted models, and rich evaluation metrics. Eval-Scope also supports various evaluation modes like single mode, pairwise-baseline mode, and pairwise (all) mode, making it suitable for assessing and improving LLMs.

Composio is a production-ready toolset for AI agents that enables users to integrate AI agents with various agentic tools effortlessly. It provides support for over 100 tools across different categories, including popular softwares like GitHub, Notion, Linear, Gmail, Slack, and more. Composio ensures managed authorization with support for six different authentication protocols, offering better agentic accuracy and ease of use. Users can easily extend Composio with additional tools, frameworks, and authorization protocols. The toolset is designed to be embeddable and pluggable, allowing for seamless integration and consistent user experience.

TiddlyWiki Starter Kit is a pre-configured setup for TiddlyWiki, utilizing Tailwind CSS for responsive design and providing multiple wiki support for different purposes. It offers quick operations with keyboard shortcuts, simplified configuration through editing the .env file, and one-click installation using npm create command.

AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and seamlessly allow human participation. They can operate in various modes that employ combinations of LLMs, human inputs, and tools.

Sailor is a suite of open language models tailored for South-East Asia (SEA), focusing on languages such as Indonesian, Thai, Vietnamese, Malay, and Lao. Developed with careful data curation, Sailor models are designed to understand and generate text across diverse linguistic landscapes of the SEA region. Built from Qwen 1.5, Sailor encompasses models of varying sizes, spanning from 0.5B to 7B versions for different requirements. Benchmarking results demonstrate Sailor's proficiency in tasks such as question answering, commonsense reasoning, reading comprehension, and more in SEA languages.

CopilotKit is an open-source framework for building, deploying, and operating fully custom AI Copilots, including in-app AI chatbots, AI agents, and AI Textareas. It provides a set of components and entry points that allow developers to easily integrate AI capabilities into their applications. CopilotKit is designed to be flexible and extensible, so developers can tailor it to their specific needs. It supports a variety of use cases, including providing app-aware AI chatbots that can interact with the application state and take action, drop-in replacements for textareas with AI-assisted text generation, and in-app agents that can access real-time application context and take action within the application.

ScrapeGraphAI is a web scraping Python library that utilizes LLM and direct graph logic to create scraping pipelines for websites and local documents. It offers various standard scraping pipelines like SmartScraperGraph, SearchGraph, SpeechGraph, and ScriptCreatorGraph. Users can extract information by specifying prompts and input sources. The library supports different LLM APIs such as OpenAI, Groq, Azure, and Gemini, as well as local models using Ollama. ScrapeGraphAI is designed for data exploration and research purposes, providing a versatile tool for extracting information from web pages and generating outputs like Python scripts, audio summaries, and search results.

ScrapeGraphAI is a Python library that uses Large Language Models (LLMs) and direct graph logic to create web scraping pipelines for websites, documents, and XML files. It allows users to extract specific information from web pages by providing a prompt describing the desired data. ScrapeGraphAI supports various LLMs, including Ollama, OpenAI, Gemini, and Docker, enabling users to choose the most suitable model for their needs. The library provides a user-friendly interface through its `SmartScraper` class, which simplifies the process of building and executing scraping pipelines. ScrapeGraphAI is open-source and available on GitHub, with extensive documentation and examples to guide users. It is particularly useful for researchers and data scientists who need to extract structured data from web pages for analysis and exploration.

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.

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 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 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 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 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 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 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.