Search Results for "ace-step"
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Showing 18 open source projects for "ace-step"
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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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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OpenAI Quickstart Node
Node.js example app from the OpenAI API quickstart tutorial
...The project is a practical starting point for building AI-powered applications, serving as a foundation for experimentation and integration into larger projects. It simplifies onboarding by offering step-by-step setup instructions and ready-to-use code snippets that can be adapted for custom needs. -
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RAG from Scratch
Demystify RAG by building it from scratch
RAG From Scratch is an educational open-source project designed to teach developers how retrieval-augmented generation systems work by building them step by step. Instead of relying on complex frameworks or cloud services, the repository demonstrates the entire RAG pipeline using transparent and minimal implementations. The project walks through key concepts such as generating embeddings, building vector databases, retrieving relevant documents, and integrating the retrieved context into language model prompts. ... -
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AI Agents From Scratch
Demystify AI agents by building them yourself. Local LLMs
AI Agents from Scratch is an educational repository designed to teach developers how to build autonomous AI agents using large language models and modern AI frameworks. The project walks through the process of constructing agents step by step, beginning with simple prompt-based interactions and gradually introducing more advanced capabilities such as planning, tool use, and memory. The repository provides example implementations that demonstrate how language models can interact with external systems, perform reasoning tasks, and execute structured workflows. It focuses on explaining the architecture of agent systems rather than simply providing finished code, making it useful for developers who want to understand how AI agents actually work internally. ... -
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Easy-Vibe
Tutorial on Product Prototype, AI Capability Integration
...The project provides a structured curriculum that guides learners from having no programming experience to building fully functional AI-integrated applications. Instead of focusing only on theoretical concepts, Easy-Vibe emphasizes practical, step-by-step tutorials that demonstrate how to transform product ideas into working software using modern AI coding tools and development workflows. The learning path is divided into progressive stages that cover beginner concepts, full-stack development, and advanced multi-platform application development. Throughout the curriculum, learners explore topics such as prompt engineering, AI tool integration, product prototyping, and deployment strategies for AI-enabled applications. -
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Agent Skills
Skills for AI coding agents
...In this repository, each skill adheres to the Agent Skills specification, meaning they’re defined as folders with a SKILL.md file (containing task descriptions and step-by-step guidance) and can include helper scripts and reference material that the agent can execute or consult when invoked. The goal of the project is to make it easy for AI assistants like Claude Code, OpenCode, Cursor, Codex, and others that support this open ecosystem to automatically apply best practices or perform concrete actions when a relevant user intent is detected. ... -
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MCP Shrimp Task Manager
Shrimp Task Manager is a task tool built for AI Agents
Shrimp Task Manager is an MCP server that converts natural-language requests into structured development tasks with dependencies, status, and style/format rules—built for agents that reason step-by-step. It emphasizes chain-of-thought and reflection loops, allowing an assistant to plan, refine, and re-prioritize work like a human project assistant. The server exposes typed tools so clients can create tasks, link prerequisites, record progress, and enforce writing or coding standards for consistent output. It ships with a web/GUI experience and works smoothly inside MCP-capable IDEs, making it useful as both a personal organizer and a programmable task substrate for software projects. ... -
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BMad Method
Breakthrough Method for Agile Ai Driven Development
BMad Method is a comprehensive AI-driven software development framework that structures the entire lifecycle of building applications through coordinated agent workflows and agile methodologies. It transforms AI from a reactive assistant into a structured team of specialized roles such as product manager, architect, developer, and QA, each operating within predefined workflows. The system guides users through phases including analysis, planning, solution design, and implementation, ensuring... -
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Rivet
Visual AI IDE for building agents with prompt chains and graphs
Rivet is an open source visual AI programming environment designed to help developers build complex AI agents using a node-based interface and prompt chaining workflows. It provides a desktop application that allows users to visually construct and debug AI logic as interconnected graphs, making it easier to manage sophisticated interactions between language models and external tools. Rivet also includes a TypeScript library that enables these visual graphs to be executed and integrated... -
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Scribe.js
JavaScript OCR and text extraction for images and PDFs
...In addition to simple text extraction, Scribe.js supports writing or injecting a high-quality invisible text layer back into PDFs, effectively making them searchable and improving usability for indexing or accessibility. It is written in modern ECMAScript Modules (ESM), so it can be imported in both browser and Node.js environments without a build step, though browser usage requires same-origin hosting of the files. -
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Claude HUD
A Claude Code plugin that shows what's happening
...This plugin was designed to reduce cognitive load and make agentic workflows more transparent, helping developers diagnose stalled tasks, understand resource usage, and manage multi-step reasoning sequences more effectively. It installs with zero configuration and appears immediately in Claude Code, making it helpful for both newcomers and seasoned users who want better situational awareness without interrupting their workflow. -
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Lemon AI
Full-stack Open-source Self-Evolving General AI Agent
LemonAI is an open-source full-stack framework for building autonomous AI agents capable of performing complex tasks such as research, programming, data analysis, and document processing. The platform is designed to run primarily on local infrastructure, providing a privacy-focused alternative to cloud-dependent agent platforms. It integrates with local large language models through tools such as Ollama, vLLM, and other model runtimes while also allowing optional connections to external... -
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browserable
Open source and self-hostable browser automation library for AI agents
...The project provides tools that allow automated agents to navigate websites, click buttons, fill out forms, and extract information from pages without manual scripting of each step. Built primarily in JavaScript, the framework offers both a developer-friendly SDK and a REST API that allow integration with AI applications and automation pipelines. It is designed to be self-hostable, which means developers can deploy and run it on their own infrastructure without relying on third-party services. The platform enables the creation of browser-based agents capable of performing complex online workflows such as data collection, research tasks, and automated interactions with web platforms. -
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LLM Course
Course to get into Large Language Models (LLMs)
LLM Course is a hands-on, notebook-driven path for learning how large language models work in practice, from data curation to training, fine-tuning, evaluating, and deploying. It emphasizes reproducible experiments: each step is demonstrated with runnable code, clear dependencies, and references to commonly used open-source models and libraries. Learners get exposure to multiple adaptation strategies—LoRA/QLoRA, instruction fine-tuning, and alignment techniques—so they can choose approaches that fit their hardware and budgets. The materials also cover inference optimization and quantization to make serving LLMs feasible on commodity GPUs or even CPUs, which is crucial for side projects and startups. ... -
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dashAI
dashAI: an interactive platform for training, evaluating and deploying
...The platform guides users through a complete, traceable workflow — data ingestion → visual exploration → preprocessing → model training → evaluation → explainability — without writing a single line of code. Each step is explicit and reversible, keeping the user in control rather than delegating decisions to an opaque pipeline. -
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Transformer Explainer
Learn How LLM Transformer Models Work with Interactive Visualization
Transformer Explainer is an interactive visualization tool created to help users understand how transformer-based language models operate internally. The platform runs a lightweight GPT-2 model directly in the user’s browser and allows users to experiment with text prompts while observing the model’s internal operations. Through visual diagrams and interactive interfaces, the tool reveals how tokens are processed through layers such as embeddings, attention mechanisms, and feed-forward... -
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LaVague
Framework for building AI agents that automate complex web tasks
...It implements the concept of a Large Action Model framework, allowing agents to interpret a user-provided objective and translate it into a sequence of actions performed in a browser. These agents can navigate web pages, retrieve information, fill out forms, and execute multi-step workflows automatically. LaVague is centered around a World Model that analyzes the current webpage state and determines the next set of instructions, combined with an Action Engine that converts those instructions into executable automation code. It can use browser automation tools such as Selenium or Playwright to interact with websites programmatically. ... -
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DreamTime
Use artificial intelligence to create images
...Open files or folders from your computer, you can also open files from Instagram and the web. Vitamined with editing tools for any case, you can also make the process fully automatic. Powerful working method that allows you to edit the algorithm step by step and obtain results that only a human could achieve. -
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Sklearn TensorFlow
Sklearn and TensorFlow: A Practical Guide to Machine Learning
...The material covers topics ranging from basic machine learning theory to deep learning techniques and model evaluation, enabling learners to build and experiment with models step by step.
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