Search Results for "prototype"
Sort By:
Showing 82 open source projects for "prototype"
View related business solutions-
Veeam Data Platform v13.1 - Get Your Free TrialTry Veeam Data Platform today. Experience the unified platform that's secure by design, portable by default, and proven to recover clean, fast, and anywhere.
-
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.
-
1
Magentic UI
A research prototype of a human-centered web agent
Magentic-UI is a research prototype developed by Microsoft that serves as a human-centered interface powered by a multi-agent system. It enables users to automate complex web tasks, such as browsing, form filling, and data analysis, while maintaining control over the process. The system emphasizes transparency and user involvement, making it suitable for tasks requiring both automation and human oversight. -
2
AI App Lab
Implementing large models into scenario-based applications
...It includes a high-level SDK called Arkitect, which provides workflows and tools for integrating models, plugins, and multimodal capabilities such as text, image, and voice processing. The repository also contains a large collection of prototype applications that demonstrate how AI can be applied to scenarios such as customer service, education, content generation, and mobile automation. These examples allow developers to quickly replicate and customize solutions for their own business needs. -
3
TUUI
A desktop MCP client designed as a tool unitary utility integration
...It also represents a bold experiment in creating a complete project using AI. Many components within the project have been directly converted or generated from the prototype project through AI. Given the considerations regarding the quality and safety of AI-generated content, this project employs strict syntax checks and naming conventions. Therefore, for any further development, please ensure that you use the linting tools I've set up to check and automatically fix syntax issues. -
4
TypeAgent Python
Structured RAG: ingest, index, query
...This design allows the system to combine the flexibility of language models with the reliability of traditional programming logic. The repository is intended primarily as a research prototype and sample code rather than a production-ready framework, allowing developers to experiment with building AI agents that maintain structured memory and perform tasks through defined actions. -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
-
5
Bolt.new
Prompt, run, edit, and deploy full-stack web applications
...Bolt.new is designed to significantly lower the barrier to entry for software creation, making it accessible not only to developers but also to product managers, designers, and non-technical users who want to quickly prototype or launch applications. -
6
Kiro
Kiro is an agentic IDE that works alongside you from prototype
Kiro is an agentic AI-powered integrated development environment and command-line tool designed to help developers move from early-stage prototypes to production-ready software through structured, spec-driven development. Unlike traditional AI coding assistants that rely heavily on ad hoc prompts, Kiro transforms natural language input into formalized requirements, architectural plans, and step-by-step implementation tasks, ensuring clarity and maintainability throughout the development... -
7
AgentOps
Python SDK for agent monitoring, LLM cost tracking, benchmarking, etc.
...Visually track events such as LLM calls, tools, and multi-agent interactions. Rewind and replay agent runs with point-in-time precision. Keep a full data trail of logs, errors, and prompt injection attacks from prototype to production. Native integrations with the top agent frameworks. -
8
Nestia
NestJS Helper + AI Chatbot Development
...One of its defining advantages is its focus on performance optimization, offering dramatically faster runtime validation and serialization compared to traditional libraries commonly used in NestJS environments. Nestia also integrates advanced capabilities such as automatic end-to-end test generation and mock server simulation, allowing developers to test and prototype applications with minimal manual setup. -
9
Pruna AI
Pruna is a model optimization framework built for developers
...It is ideal for companies or teams looking to reduce reliance on external APIs while maintaining speed, cost-efficiency, and full control over their data and AI stack. With a focus on extensibility and observability, Pruna empowers engineers to scale LLM applications from prototype to production securely and reliably. -
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.
-
10
ComfyUI-LTXVideo
LTX-Video Support for ComfyUI
...Instead of writing code to apply effects, transitions, edits, and data flows, users can assemble nodes that represent video inputs, transformations, and outputs, letting them prototype and automate video production pipelines visually. This integration empowers non-programmers and rapid-iteration teams to harness the performance of LTX-Video while maintaining the clarity and flexibility of a dataflow graph model. It supports nodes for common video operations like trimming, layering, color grading, and generative augmentations, making it suitable for everything from simple clip edits to complex sequences with conditional behavior. -
11
Gradient Bang
Gradient Bang is an online multiplayer universe
...Rather than functioning as a traditional application or API, it is conceptualized as an “online multiplayer universe” in which participants can explore, trade, battle, and collaborate while interacting with AI agents as active entities within the system. The project serves both as a prototype and a conceptual playground for testing how conversational AI systems behave when embedded into dynamic, game-like environments rather than static chat interfaces. It leverages the broader Pipecat architecture for multimodal and conversational AI orchestration, meaning that interactions can potentially extend beyond text into voice, events, and real-time systems. -
12
baoyu-design
Run Claude Design locally as an Agent Skill
baoyu-design is an Agent Skill that lets local coding agents produce polished visual design artifacts. It packages Claude Design-style methodology for environments such as Cursor, Claude Code, Codex, Claude Desktop, and other file-capable agents. The skill can generate UI mockups, prototypes, wireframes, landing pages, dashboards, mobile app screens, and slide decks as self-contained HTML. It keeps outputs inside the local project, so artifacts can be versioned, edited, previewed, and... -
13
AutoBE
AI Vibe Coding Agent of TS backend server
...It analyzes what the user wants, creates specifications, designs database structure, defines API documentation, writes end-to-end tests, and generates implementation logic. The project is aimed at moving from prototype to production more quickly while keeping generated code buildable and verifiable. It uses an agentic workflow supported by compiler-friendly checks and test generation, which helps reduce the risk of incomplete AI output. AutoBE can be explored through a local playground where users chat with agents and manage sessions. Its main value is giving developers and non-programmers a structured way to generate backend systems from requirements while still producing documentation and tests. -
14
claurst
Your favorite Terminal Coding Agent, now in Rust
...It is likely intended as a lightweight but extensible platform for experimenting with agent behavior and orchestration. The project may also emphasize simplicity, making it accessible for developers who want to prototype agent systems quickly. -
15
AutoGluon
AutoGluon: AutoML for Image, Text, and Tabular Data
AutoGluon enables easy-to-use and easy-to-extend AutoML with a focus on automated stack ensembling, deep learning, and real-world applications spanning image, text, and tabular data. Intended for both ML beginners and experts, AutoGluon enables you to quickly prototype deep learning and classical ML solutions for your raw data with a few lines of code. Automatically utilize state-of-the-art techniques (where appropriate) without expert knowledge. Leverage automatic hyperparameter tuning, model selection/ensembling, architecture search, and data processing. Easily improve/tune your bespoke models and data pipelines, or customize AutoGluon for your use-case. ... -
16
OmAgent
Build multimodal language agents for fast prototype and production
OmAgent is an open-source Python framework designed to simplify the development of multimodal language agents that can reason, plan, and interact with different types of data sources. The framework provides abstractions and infrastructure for building AI agents that operate on text, images, video, and audio while maintaining a relatively simple interface for developers. Instead of forcing developers to implement complex orchestration logic manually, the system manages task scheduling, worker... -
17
Deta Surf
Personal AI Notebooks. Organize files & webpages and generate notes
...The platform provides a streamlined development environment where developers can test models, run experiments, and deploy small AI services with minimal infrastructure overhead. It focuses on simplicity and speed, allowing developers to prototype ideas quickly without managing complex cloud configurations. Surf integrates modern AI workflows such as prompt-based applications, lightweight APIs, and automated deployment pipelines. The platform is particularly useful for developers who want to experiment with AI models locally while maintaining the option to deploy them in production environments later. ... -
18
MemOS
AI memory OS for LLM and Agent systems
MemOS is an experimental operating system and runtime built around the concept of memory-centric computing, where memory objects are first-class citizens and program execution is organized around efficient, persistent memory access rather than traditional process and file system boundaries. The project explores rethinking system abstractions by tightly coupling computation with memory objects so that programs can operate on large datasets without expensive serialization or context switching.... -
19
Open-AutoGLM
An open phone agent model & framework
Open-AutoGLM is an open-source framework and model designed to empower autonomous mobile intelligent assistants by enabling AI agents to understand and interact with phone screens in a multimodal manner, blending vision and language capability to control real devices. It aims to create an “AI phone agent” that can perceive on-screen content, reason about user goals, and execute sequences of taps, swipes, and text input via automated device control interfaces like ADB, enabling hands-off... -
20
eve
The Framework for Building Agents
...Eve supports durable execution, sandboxed compute, human-in-the-loop approvals, subagents, long-running work, and Vercel-native deployment. It also fits into agent templates and app workflows, such as Slack agents or persisted chat experiences. It is useful for developers who want to move from prototype agents to production-ready agents with clearer structure, safer execution, and cloud deployment built into the framework. -
21
Agent Stack
Deploy and share agents with open infrastructure
Agent Stack is an open infrastructure platform designed to take AI agents from prototype to production, no matter how they were built. It includes a runtime environment, multi-tenant web UI, catalog of agents, and deployment flow that seeks to remove vendor lock-in and provide greater autonomy. Under the hood it’s built on the “Agent2Agent” (A2A) protocol, enabling interoperability between different agent ecosystems, runtime services, and frameworks. -
22
GenMedia Creative Studio
AI generative media user experience highlighting use of APIs
...The project is built to showcase multimodal creation across text, image, video, speech, and music from one deployable interface. It is useful for creators, marketers, developers, and technical teams that want to prototype media-generation experiences using Google Cloud services. The repository also includes experiments and MCP-related materials for connecting generative media capabilities to agent workflows. It is not an officially supported Google product, so it is best treated as a reference implementation and creative sandbox rather than a managed commercial service. -
23
AntV Infographic
Declarative engine for generating AI-powered infographic visuals
...It also includes a built-in editor that allows users to refine and adjust generated infographics interactively after creation. With a large library of predefined templates and themes, AntV Infographic helps users rapidly prototype and produce consistent visual content. -
24
Avalanche
End-to-End Library for Continual Learning based on PyTorch
Avalanche is an end-to-end Continual Learning library based on Pytorch, born within ContinualAI with the unique goal of providing a shared and collaborative open-source (MIT licensed) codebase for fast prototyping, training and reproducible evaluation of continual learning algorithms. Avalanche can help Continual Learning researchers in several ways. This module maintains a uniform API for data handling: mostly generating a stream of data from one or more datasets. It contains all the major... -
25
FastRTC
The python library for real-time communication
...This makes it particularly well suited for building real-time voice (or video) interfaces for applications such as AI assistants, live chat, or collaborative audio/video tools. FastRTC also integrates nicely with UI frameworks (e.g. via a web demo using Gradio), so developers can rapidly prototype and deploy real-time streaming applications without deep knowledge of low-level WebRTC internals. Because voice-enabled AI agents often involve many moving parts (speech-to-text, text processing, text-to-speech, streaming, session/chat management), FastRTC helps by handling the streaming aspect, leaving the rest to be plugged in modularly.
