Unstract is a no-code platform that enables users to launch APIs and ETL pipelines to structure unstructured documents. With Unstract, users can go beyond co-pilots by enabling machine-to-machine automation. Unstract's Prompt Studio provides a simple, no-code approach to creating prompts for LLMs, vector databases, embedding models, and text extractors. Users can then configure Prompt Studio projects as API deployments or ETL pipelines to automate critical business processes that involve complex documents. Unstract supports a wide range of LLM providers, vector databases, embeddings, text extractors, ETL sources, and ETL destinations, providing users with the flexibility to choose the best tools for their needs.

Hashbrown is a lightweight and efficient hashing library for Python, designed to provide easy-to-use cryptographic hashing functions for secure data storage and transmission. It supports a variety of hashing algorithms, including MD5, SHA-1, SHA-256, and SHA-512, allowing users to generate hash values for strings, files, and other data types. With Hashbrown, developers can quickly implement data integrity checks, password hashing, digital signatures, and other security features in their Python applications.

Doris is a lightweight and user-friendly data visualization tool designed for quick and easy exploration of datasets. It provides a simple interface for users to upload their data and generate interactive visualizations without the need for coding. With Doris, users can easily create charts, graphs, and dashboards to analyze and present their data in a visually appealing way. The tool supports various data formats and offers customization options to tailor visualizations to specific needs. Whether you are a data analyst, researcher, or student, Doris simplifies the process of data exploration and presentation.

Opencode.nvim is a Neovim plugin that provides a simple and efficient way to browse, search, and open files in a project. It enhances the file navigation experience by offering features like fuzzy finding, file preview, and quick access to frequently used files. With Opencode.nvim, users can easily navigate through their project files, jump to specific locations, and manage their workflow more effectively. The plugin is designed to improve productivity and streamline the development process by simplifying file handling tasks within Neovim.

SQLBot is a versatile tool for executing SQL queries and managing databases. It provides a user-friendly interface for interacting with databases, allowing users to easily query, insert, update, and delete data. SQLBot supports various database systems such as MySQL, PostgreSQL, and SQLite, making it a valuable tool for developers, data analysts, and database administrators. With SQLBot, users can streamline their database management tasks and improve their productivity by quickly accessing and manipulating data without the need for complex SQL commands.

Aiounifi is a Python library that provides a simple interface for interacting with the Unifi Controller API. It allows users to easily manage their Unifi network devices, such as access points, switches, and gateways, through automated scripts or applications. With Aiounifi, users can retrieve device information, perform configuration changes, monitor network performance, and more, all through a convenient and efficient API wrapper. This library simplifies the process of integrating Unifi network management into custom solutions, making it ideal for network administrators, developers, and enthusiasts looking to automate and streamline their network operations.

LLMs is a universal LLM API transformation server designed to standardize requests and responses between different LLM providers such as Anthropic, Gemini, and Deepseek. It uses a modular transformer system to handle provider-specific API formats, supporting real-time streaming responses and converting data into standardized formats. The server transforms requests and responses to and from unified formats, enabling seamless communication between various LLM providers.

Cellm is an Excel extension that allows users to leverage Large Language Models (LLMs) like ChatGPT within cell formulas. It enables users to extract AI responses to text ranges, making it useful for automating repetitive tasks that involve data processing and analysis. Cellm supports various models from Anthropic, Mistral, OpenAI, and Google, as well as locally hosted models via Llamafiles, Ollama, or vLLM. The tool is designed to simplify the integration of AI capabilities into Excel for tasks such as text classification, data cleaning, content summarization, entity extraction, and more.

This repository contains a collection of various tools and utilities that can be used for different purposes. It includes scripts, programs, and resources to assist with tasks related to software development, data analysis, automation, and more. The tools are designed to be versatile and easy to use, providing solutions for common challenges faced by developers and users alike.

The mcp-fundamentals repository is a collection of fundamental concepts and examples related to microservices, cloud computing, and DevOps. It covers topics such as containerization, orchestration, CI/CD pipelines, and infrastructure as code. The repository provides hands-on exercises and code samples to help users understand and apply these concepts in real-world scenarios. Whether you are a beginner looking to learn the basics or an experienced professional seeking to refresh your knowledge, mcp-fundamentals has something for everyone.

Repomix is a powerful tool that packs your entire repository into a single, AI-friendly file. It is designed to format your codebase for easy understanding by AI tools like Large Language Models (LLMs), Claude, ChatGPT, and Gemini. Repomix offers features such as AI optimization, token counting, simplicity in usage, customization options, Git awareness, and security-focused checks using Secretlint. It allows users to pack their entire repository or specific directories/files using glob patterns, and even supports processing remote Git repositories. The tool generates output in plain text, XML, or Markdown formats, with options for including/excluding files, removing comments, and performing security checks. Repomix also provides a global configuration option, custom instructions for AI context, and a security check feature to detect sensitive information in files.

PulsarRPAPro is a powerful robotic process automation (RPA) tool designed to automate repetitive tasks and streamline business processes. It offers a user-friendly interface for creating and managing automation workflows, allowing users to easily automate tasks without the need for extensive programming knowledge. With features such as task scheduling, data extraction, and integration with various applications, PulsarRPAPro helps organizations improve efficiency and productivity by reducing manual work and human errors. Whether you are a small business looking to automate simple tasks or a large enterprise seeking to optimize complex processes, PulsarRPAPro provides the flexibility and scalability to meet your automation needs.

Dexto is a lightweight runtime for creating and running AI agents that turn natural language into real-world actions. It serves as the missing intelligence layer for building AI applications, standalone chatbots, or as the reasoning engine inside larger products. Dexto features a powerful CLI and Web UI for running AI agents, supports multiple interfaces, allows hot-swapping of LLMs from various providers, connects to remote tool servers via the Model Context Protocol, is config-driven with version-controlled YAML, offers production-ready core features, extensibility for custom services, and enables multi-agent collaboration via MCP and A2A.

The dbt MCP Server is a Model Context Protocol server that provides tools to interact with dbt. It allows users to provide AI agents with context of their project in dbt Core, dbt Fusion, and dbt Platform. The server architecture enables agents to connect to various tools, and users can refer to the documentation for more details on its capabilities. Users can also contribute to the project by following the instructions in the CONTRIBUTING.md file.

Agent Lightning is a lightweight and efficient tool for automating repetitive tasks in the field of data analysis and machine learning. It provides a user-friendly interface to create and manage automated workflows, allowing users to easily schedule and execute data processing, model training, and evaluation tasks. With its intuitive design and powerful features, Agent Lightning streamlines the process of building and deploying machine learning models, making it ideal for data scientists, machine learning engineers, and AI enthusiasts looking to boost their productivity and efficiency in their projects.

nndeploy is a tool that allows you to quickly build your visual AI workflow without the need for frontend technology. It provides ready-to-use algorithm nodes for non-AI programmers, including large language models, Stable Diffusion, object detection, image segmentation, etc. The workflow can be exported as a JSON configuration file, supporting Python/C++ API for direct loading and running, deployment on cloud servers, desktops, mobile devices, edge devices, and more. The framework includes mainstream high-performance inference engines and deep optimization strategies to help you transform your workflow into enterprise-level production applications.

Unstract is a no-code platform that enables users to launch APIs and ETL pipelines to structure unstructured documents. With Unstract, users can go beyond co-pilots by enabling machine-to-machine automation. Unstract's Prompt Studio provides a simple, no-code approach to creating prompts for LLMs, vector databases, embedding models, and text extractors. Users can then configure Prompt Studio projects as API deployments or ETL pipelines to automate critical business processes that involve complex documents. Unstract supports a wide range of LLM providers, vector databases, embeddings, text extractors, ETL sources, and ETL destinations, providing users with the flexibility to choose the best tools for their needs.

The mslearn-knowledge-mining repository contains lab files for Azure AI Knowledge Mining modules. It provides resources for learning and implementing knowledge mining techniques using Azure AI services. The repository is designed to help users explore and understand how to leverage AI for knowledge mining purposes within the Azure ecosystem.

Nous is an open-source TypeScript platform for autonomous AI agents and LLM based workflows. It aims to automate processes, support requests, review code, assist with refactorings, and more. The platform supports various integrations, multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It offers advanced features like reasoning/planning, memory and function call history, hierarchical task decomposition, and control-loop function calling options. Nous is designed to be a flexible platform for the TypeScript community to expand and support different use cases and integrations.

This repository focuses on the application of Large Language Models (LLMs) in the field of finance. It provides insights and knowledge about how LLMs can be utilized in various scenarios within the finance industry, particularly in generating AI agents. The repository aims to explore the potential of LLMs to enhance financial processes and decision-making through the use of advanced natural language processing techniques.

Docq is a private and secure GenAI tool designed to extract knowledge from business documents, enabling users to find answers independently. It allows data to stay within organizational boundaries, supports self-hosting with various cloud vendors, and offers multi-model and multi-modal capabilities. Docq is extensible, open-source (AGPLv3), and provides commercial licensing options. The tool aims to be a turnkey solution for organizations to adopt AI innovation safely, with plans for future features like more data ingestion options and model fine-tuning.

Sophia is an open-source TypeScript platform designed for autonomous AI agents and LLM based workflows. It aims to automate processes, review code, assist with refactorings, and support various integrations. The platform offers features like advanced autonomous agents, reasoning/planning inspired by Google's Self-Discover paper, memory and function call history, adaptive iterative planning, and more. Sophia supports multiple LLMs/services, CLI and web interface, human-in-the-loop interactions, flexible deployment options, observability with OpenTelemetry tracing, and specific agents for code editing, software engineering, and code review. It provides a flexible platform for the TypeScript community to expand and support various use cases and integrations.

Upsonic offers a cutting-edge enterprise-ready framework for orchestrating LLM calls, agents, and computer use to complete tasks cost-effectively. It provides reliable systems, scalability, and a task-oriented structure for real-world cases. Key features include production-ready scalability, task-centric design, MCP server support, tool-calling server, computer use integration, and easy addition of custom tools. The framework supports client-server architecture and allows seamless deployment on AWS, GCP, or locally using Docker.

ClearML is an auto-magical suite of tools designed to streamline AI workflows. It includes modules for experiment management, MLOps/LLMOps, data management, model serving, and more. ClearML offers features like experiment tracking, model serving, orchestration, and automation. It supports various ML/DL frameworks and integrates with Jupyter Notebook and PyCharm for remote debugging. ClearML aims to simplify collaboration, automate processes, and enhance visibility in AI projects.

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.

Skyvern automates browser-based workflows using LLMs and computer vision. It provides a simple API endpoint to fully automate manual workflows, replacing brittle or unreliable automation solutions. Traditional approaches to browser automations required writing custom scripts for websites, often relying on DOM parsing and XPath-based interactions which would break whenever the website layouts changed. Instead of only relying on code-defined XPath interactions, Skyvern adds computer vision and LLMs to the mix to parse items in the viewport in real-time, create a plan for interaction and interact with them. This approach gives us a few advantages: 1. Skyvern can operate on websites it’s never seen before, as it’s able to map visual elements to actions necessary to complete a workflow, without any customized code 2. Skyvern is resistant to website layout changes, as there are no pre-determined XPaths or other selectors our system is looking for while trying to navigate 3. Skyvern leverages LLMs to reason through interactions to ensure we can cover complex situations. Examples include: 1. If you wanted to get an auto insurance quote from Geico, the answer to a common question “Were you eligible to drive at 18?” could be inferred from the driver receiving their license at age 16 2. If you were doing competitor analysis, it’s understanding that an Arnold Palmer 22 oz can at 7/11 is almost definitely the same product as a 23 oz can at Gopuff (even though the sizes are slightly different, which could be a rounding error!) Want to see examples of Skyvern in action? Jump to #real-world-examples-of- skyvern

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.

Vanna is an open-source Python framework for SQL generation and related functionality. It uses Retrieval-Augmented Generation (RAG) to train a model on your data, which can then be used to ask questions and get back SQL queries. Vanna is designed to be portable across different LLMs and vector databases, and it supports any SQL database. It is also secure and private, as your database contents are never sent to the LLM or the vector database.

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.

Avalonia-Assistant is an open-source desktop intelligent assistant that aims to provide a user-friendly interactive experience based on the Avalonia UI framework and the integration of Semantic Kernel with OpenAI or other large LLM models. By utilizing Avalonia-Assistant, you can perform various desktop operations through text or voice commands, enhancing your productivity and daily office experience.

Marvin is a lightweight AI toolkit for building natural language interfaces that are reliable, scalable, and easy to trust. Each of Marvin's tools is simple and self-documenting, using AI to solve common but complex challenges like entity extraction, classification, and generating synthetic data. Each tool is independent and incrementally adoptable, so you can use them on their own or in combination with any other library. Marvin is also multi-modal, supporting both image and audio generation as well using images as inputs for extraction and classification. Marvin is for developers who care more about _using_ AI than _building_ AI, and we are focused on creating an exceptional developer experience. Marvin users should feel empowered to bring tightly-scoped "AI magic" into any traditional software project with just a few extra lines of code. Marvin aims to merge the best practices for building dependable, observable software with the best practices for building with generative AI into a single, easy-to-use library. It's a serious tool, but we hope you have fun with it. Marvin is open-source, free to use, and made with 💙 by the team at Prefect.

Activepieces is an open source replacement for Zapier, designed to be extensible through a type-safe pieces framework written in Typescript. It features a user-friendly Workflow Builder with support for Branches, Loops, and Drag and Drop. Activepieces integrates with Google Sheets, OpenAI, Discord, and RSS, along with 80+ other integrations. The list of supported integrations continues to grow rapidly, thanks to valuable contributions from the community. Activepieces is an open ecosystem; all piece source code is available in the repository, and they are versioned and published directly to npmjs.com upon contributions. If you cannot find a specific piece on the pieces roadmap, please submit a request by visiting the following link: Request Piece Alternatively, if you are a developer, you can quickly build your own piece using our TypeScript framework. For guidance, please refer to the following guide: Contributor's Guide