Search Results for "extract-xiso"
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Showing 8 open source projects for "extract-xiso"
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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1
Stagehand
An AI web browsing framework focused on simplicity and extensibility
...Each Stagehand function takes in an atomic instruction, such as act("click the login button") or extract("find the red shoes"), generates the appropriate Playwright code to accomplish that instruction, and executes it. -
2
designlang
Extract any website's complete design system with one command
...The system includes accessibility analysis features, such as WCAG compliance checks and CSS health audits, helping developers improve usability and standards compliance. It can be used via CLI or browser extension, making it flexible for different workflows. Overall, design-extract automates the process of reverse-engineering design systems, significantly accelerating frontend development. -
3
Skyvern
Automate browser-based workflows with LLMs and Computer Vision
...Support for proxies, with support for country, state, or even precise zip-code level targeting. Skyvern understands how to solve CAPTCHAs to complete complicated workflows. Support for authenticating into user accounts, including support for 2FA/TOTP. Extract data from workflows in any schema of your choice including CSV or JSON. Automate procurement pipelines, breeze through government forms, and complete workflows in any language. -
4
Cheat on Content
Workflow that turns every post into a calibrated experiment
...It is aimed at creators, marketers, and operators who want to build a repeatable system for learning from every published piece. Its value is strongest for people who already create consistently but need a better way to extract insight from their output. -
AI-powered service management for IT and enterprise teamsGive your IT, operations, and business teams the ability to deliver exceptional services—without the complexity. Maximize operational efficiency with refreshingly simple, AI-powered Freshservice.
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5
Dendrite
Tools to build web AI agents that can authenticate
Dendrite Python SDK is a toolkit for building web AI agents that can authenticate, interact with, and extract data from any website, facilitating web automation tasks. -
6
Android Use
Automate native Android apps with AI using accessibility APIs
...It fills a gap in automation tooling by focusing on mobile-first workflows where traditional browser or desktop-based automation doesn’t work; such as logistics, gig work, field operations, and other industries reliant on phones or tablets. The project works by using Android’s accessibility API to extract structured UI state (as XML) from the device, which is then fed to a large language model (LLM) like OpenAI’s models for decision-making, and actions are executed via the Android Debug Bridge (ADB). This approach bypasses expensive vision-based models and provides faster, cheaper automation with fine-grained interaction capabilities (for example, tapping buttons, typing text, navigating screens). -
7
ReMe
Memory Management Kit for Agents
ReMe is a memory management kit for AI agents that gives them structured, persistent memory capabilities, enabling agents to extract, store, and reuse information across sessions, tasks, and interactions. It is designed to support long-running agent workflows where context matters and working memory alone isn’t enough, helping agents remember user preferences, task histories, and relevant past observations. The toolkit provides APIs to offload large, ephemeral outputs to external storage and reload them on demand, which reduces memory bloat and keeps active context concise. ... -
8
cognee
Deterministic LLMs Outputs for AI Applications and AI Agents
...Any kind of data works; unstructured text or raw media files, PDFs, tables, presentations, JSON files, and so many more. Add small or large files, or many files at once. We map out a knowledge graph from all the facts and relationships we extract from your data. Then, we establish graph topology and connect related knowledge clusters, enabling the LLM to "understand" the data.
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