OpenWebUI Tools provides a collection of plugins for OpenWebUI to enhance large language models with external tool access. It includes a web browsing and search module for live data retrieval, a Python REPL and terminal executor for on-the-fly code running, file system readers/writers for document access, and utilities for parsing PDFs or formatting JSON. These tools operate within the OpenWebUI front-end, letting users interactively call functions and combine AI reasoning with real-world actions for richer conversational and task-oriented experiences.

Sequel is an AI-driven platform that offers immediate insights from your data. Designed for both technical and non-technical users, Sequel transforms natural language queries into SQL, retrieves the data, and provides visualizations and insights. It seamlessly connects with a wide range of databases, eliminating the hassle of writing detailed SQL queries while ensuring up-to-date and accurate business intelligence.

X Search Assistant is an AI-powered tool designed to help users craft advanced Twitter searches. With this tool, you don't need to memorize complex search operators. Simply type your query in plain English, and the LLM (Large Language Model) will generate the corresponding search query for Twitter. You can choose from a variety of supported LLMs and customize them according to your needs. The tool also provides shortcuts and flags to enhance your search efficiency, making Twitter research easier and more effective.

AChat.dev is a developer-centric platform that allows users to create, test and deploy AI chat agents with advanced capabilities. It supports persistent conversation memory so agents remember past interactions, dynamic function calls to external APIs for real-time data retrieval, and role-based multi-agent collaboration. Built on Python and Node.js SDKs, it includes templating for quick setup, plugin architecture for extensibility, and monitoring dashboards to track agent performance. AChat.dev ensures GDPR-compliant data handling and can scale across cloud and on-premise environments.

Bind provides a suite of customizable Generative AI models and AI agents designed to facilitate real-time data interaction and retrieval from various systems. These tools allow businesses to optimize their workflows, enhance operational efficiency, and gain deeper insights from their data. Bind focuses on delivering tailored solutions that meet the specific needs of each client, ensuring they can harness the full potential of AI technologies. Whether it's through AI-driven customer engagement or data analysis, Bind's offerings are aimed at driving innovation and growth.

The Gemini Agent Cookbook is a curated open-source toolkit offering a variety of hands-on examples for constructing intelligent agents powered by Google’s Gemini language models. It includes sample code for orchestrating multi-step reasoning chains, dynamically invoking external APIs, integrating toolkits for data retrieval, and managing conversation flows. The cookbook demonstrates best practices for error handling, context management, and prompt engineering, supporting use cases like autonomous chatbots, task automation, and decision support systems. It guides developers through building custom agents that can interpret user requests, fetch real-time data, perform computations, and generate formatted outputs. By following these recipes, engineers can accelerate agent prototyping and deploy robust AI-driven applications in diverse domains.

Liner is an AI-powered tool designed to help users acquire knowledge faster by finding, summarizing, and organizing information. It supports research productivity by offering instant answers, real-time information, and credible sources. With Liner, users can highlight and comment on web content, summarize documents and webpages, and dive deeply into any topic. The tool caters explicitly to researchers, students, and professionals who regularly deal with extensive information and need a reliable solution to streamline their workflows.

Neon Azure AI Agent is an open-source demonstration showing how to build an AI-driven database assistant using Azure OpenAI and Neon Postgres. The agent parses natural language inputs, generates optimized SQL queries, executes them on a serverless Postgres instance, and returns formatted results. Developers can use this repository to quickly prototype conversational data applications, learn integrated Azure AI and Neon DB workflows, and extend the agent with custom functions or data sources for tailored solutions.