Search Results for "unit-api" - Page 20
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Showing 1154 open source projects for "unit-api"
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Agentic Commerce Protocol (ACP)
Interaction model for connecting buyers to complete purchases
...The repository organizes the spec as human-readable RFCs plus machine-readable OpenAPI and JSON Schema definitions, along with worked examples and a changelog so integrators can track breaking changes. Practically, ACP defines three main pieces; a Product Feed for discovery, an Agentic Checkout API for stateful, in-conversation checkout, and a Delegated Payment flow so a merchant’s existing PSP securely handles payment credentials and settlement. Merchants remain the merchant-of-record—orders, fraud controls, payment authorization/capture, refunds, and post-purchase communication all stay on their systems while the agent surfaces status to the buyer. -
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LiteRT
LiteRT, successor to TensorFlow Lite
LiteRT is Google's next-generation on-device machine learning framework and the successor to TensorFlow Lite, designed for high-performance AI and generative AI deployment across edge devices. It provides efficient model conversion, optimization, and runtime execution while leveraging hardware acceleration from CPUs, GPUs, and NPUs. LiteRT supports a wide range of platforms, including Android, iOS, Linux, macOS, Windows, web environments, and IoT devices. The framework simplifies on-device... -
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Deep Java Library (DJL)
An engine-agnostic deep learning framework in Java
Deep Java Library (DJL) is an open-source, high-level, engine-agnostic Java framework for deep learning. DJL is designed to be easy to get started with and simple to use for Java developers. DJL provides native Java development experience and functions like any other regular Java library. You don't have to be a machine learning/deep learning expert to get started. You can use your existing Java expertise as an on-ramp to learn and use machine learning and deep learning. You can use your... -
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infinite-canvas
Infinite Canvas Workbench for AI creation integrates AI generation
...Users can work across multiple canvases, drag and scale nodes, connect ideas visually, use a minimap, undo changes, and import or export work. The project supports OpenAI-compatible API connections for text-to-image, image-to-image, reference editing, text chat, audio generation, and video generation. It also includes a canvas assistant that can discuss selected nodes, use upstream context, generate new outputs, and place results back onto the canvas. The project is still in active development and is better suited for personal or local deployment than stable public multi-user production use. -
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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abtop
Like htop, but for AI coding agents. Monitor Claude Code & Codex CLI
...The dashboard helps developers track token usage, context window percentage, rate limits, child processes, open ports, and multiple active profiles. It is read-only, so it does not require API keys or authentication and does not control the agents it observes. abtop is especially useful for developers running several agents across projects who need quick visibility into cost, quota pressure, context growth, and orphaned processes. Its main value is bringing operational observability to AI coding-agent workflows directly inside the terminal. -
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GenericAgent
Self-evolving autonomous agent framework
The GenericAgent project is a flexible framework for building autonomous AI agents that can operate across diverse tasks and environments. It is designed around modularity, allowing developers to define agents with interchangeable components such as tools, memory systems, and reasoning strategies. The architecture emphasizes generality, enabling the same agent framework to be adapted for different domains including coding, research, and task automation. It integrates with modern language... -
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Superglue
Builds integrations and tools from natural language
Superglue is an AI-powered integration platform that enables developers to build production-grade tools and workflows using natural language, abstracting away the complexity of connecting APIs, databases, and external systems. It functions as a universal integration layer that allows users to define workflows in plain language, which are then translated into executable pipelines capable of interacting with multiple services. One of its defining features is its ability to handle... -
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Datapizza AI
Build reliable Gen AI solutions without overhead
Datapizza AI is a lightweight framework for building modular, multi-agent AI systems that collaborate to solve complex tasks through orchestration and tool usage. The project focuses on simplicity and transparency, enabling developers to construct agent-based workflows without the heavy abstractions and dependencies often found in larger AI frameworks. It provides a flexible architecture where individual agents can be assigned specialized roles, such as web search, reasoning, or... -
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CGraph
A general, three-party dependency-free, cross-platform
CGraph is a high-performance, cross-platform Directed Acyclic Graph (DAG) framework implemented in pure C++ with no third-party dependencies, designed for building complex task pipelines and parallel execution workflows. It allows developers to model computational processes as graph structures, where nodes represent tasks and edges define dependencies, enabling efficient scheduling and execution. The framework includes a pipeline system that supports sequential and parallel execution,... -
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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clip-retrieval
Easily compute clip embeddings and build a clip retrieval system
clip-retrieval is an open-source toolkit designed to build large-scale semantic search systems for images and text by leveraging CLIP embeddings to enable multimodal retrieval. It allows developers to compute embeddings for both images and text efficiently and then index them for fast similarity search across massive datasets. The system is optimized for performance and scalability, capable of processing tens or even hundreds of millions of embeddings using GPU acceleration. It includes... -
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OpenHome Abilities
Open-source abilities for OpenHome agents
...Each ability is intentionally simple in structure, centering on a single main.py file that contains the core Python logic, which lowers the barrier to building and sharing custom behaviors. The system is meant to support a wide range of voice-driven actions, from API calls and media playback to quiz flows, device control, and multi-turn conversations, so it functions as a practical extension framework rather than a narrow template library. The repository includes official abilities maintained by the OpenHome team as well as community-contributed ones, creating both a stable baseline and a path for outside developers to publish their own work. -
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qxresearch-event-1
Python hands on tutorial with 50+ Python Application
...The repository contains dozens of small programs, many implemented with minimal lines of code, covering topics such as machine learning, graphical user interfaces, computer vision, and API integration. Each example is designed to illustrate a single concept or application in a clear and concise manner so that learners can quickly understand the underlying logic. The project emphasizes practical experimentation, allowing beginners to modify and extend the example programs to explore new ideas. Many of the examples are accompanied by video explanations that guide learners through the code and demonstrate how the programs work in practice. -
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Machine Learning Zoomcamp
Learn ML engineering for free in 4 months
...The course also introduces more advanced topics including decision trees, ensemble methods, and neural networks. Later modules focus on practical engineering topics such as containerization with Docker, API development with FastAPI, and scaling machine learning services using Kubernetes and cloud platforms. The repository includes lecture materials, assignments, and projects that allow learners to gain hands-on experience implementing machine learning pipelines. -
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Jina-Serve
Build multimodal AI applications with cloud-native stack
Jina Serve is an open-source framework designed for building, deploying, and scaling AI services and machine learning pipelines in production environments. The framework allows developers to create microservices that expose machine learning models through APIs that communicate using protocols such as HTTP, gRPC, and WebSockets. It is built with a cloud-native architecture that supports deployment on local machines, containerized environments, or large orchestration platforms such as... -
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Grounded Docs
Open-Source Alternative to Context7, Nia, and Ref.Tools
Grounded Docs is an open-source implementation of a Model Context Protocol server designed to expose documentation and structured information as tools that AI agents can query. The project allows language models and agent frameworks to retrieve and interact with documentation through standardized MCP interfaces. By acting as an intermediary layer between documentation sources and AI tools, the server enables models to access structured documentation in a consistent and machine-readable... -
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llama.vim
Vim plugin for LLM-assisted code/text completion
...Instead of relying on remote AI services, the plugin is designed to work with locally running LLM inference engines such as llama.cpp. This approach allows developers to benefit from AI-assisted coding features while maintaining full control over their data and avoiding external API dependencies. The plugin focuses on simplicity and performance, providing fast completions and editing assistance even on consumer-grade hardware. By integrating AI functionality directly into Vim workflows, the tool enables developers to write and edit code more efficiently while staying within a familiar development interface. -
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Aix-DB
Based on the LangChain/LangGraph framework
...The platform supports multiple types of data sources and provides an end-to-end pipeline that includes intent recognition, SQL generation, database execution, and visual presentation of results. Its architecture includes multiple layers such as a web interface, API gateway, AI service layer, and data storage layer that support relational databases, vector stores, graph databases, and file systems. -
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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... -
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ANE Training
Training neural networks on Apple Neural Engine via APIs
ANE Training is an experimental research project that demonstrates how to train neural networks directly on Apple’s Neural Engine by leveraging reverse-engineered private APIs that are normally inaccessible to developers. The repository implements a from-scratch transformer training pipeline capable of running both forward and backward passes on ANE hardware without relying on CoreML, Metal, or GPU acceleration. It explores the internal software stack of the Apple Neural Engine by... -
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Pinchtab
High-performance browser automation bridge and orchestrator
Pinchtab is a lightweight browser automation backend built specifically for AI agents that need efficient, programmatic web control. Implemented as a small standalone HTTP server, it allows any agent or script to interact with web pages using simple API calls instead of heavyweight browser frameworks. The tool emphasizes accessibility-first snapshots that dramatically reduce token usage compared to screenshot-based approaches, making it cost-effective for large-scale automation. It launches and manages its own Chrome instance while remaining framework-agnostic, so it can be used with any language or agent system. ... -
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IronClaw
IronClaw is OpenClaw inspired but focused on privacy & security
IronClaw is a security-first, open-source personal AI assistant built in Rust and designed to keep your data fully under your control. It operates on the principle that your AI should work for you, not external vendors, ensuring all data is stored locally, encrypted, and never shared. The platform emphasizes transparency, offering auditable code with no hidden telemetry or data harvesting. IronClaw runs untrusted tools inside isolated WebAssembly (WASM) sandboxes with strict capability-based... -
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TONL
TONL (Token-Optimized Notation Language)
...It provides a serialization format that significantly reduces token usage compared with traditional JSON, which can result in lower costs and more efficient prompt size utilization in LLM-driven systems. TONL isn’t just a format — it includes a rich API for querying, indexing, modifying, and streaming data, along with tools for schema validation and TypeScript code generation. The platform comes with a complete command-line interface that supports interactive dashboards and cross-platform usage in browsers and server environments, and its high test coverage gives developers confidence in stability. -
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SERA CLI
A tool to use the Ai2 Open Coding Agents Soft-Verified Agents
SERA CLI is a command-line tool created by AllenAI to enable developers to interact with the SERA (Soft-Verified Efficient Repository Agents) model family using Claude Code as the execution front end. It provides a convenient interface for deploying, testing, and using SERA models without needing to write scaffold code from scratch, acting as both a proxy and utility wrapper to simplify workflows that involve large agent models. Through sera-cli, users can connect to local or cloud-hosted... -
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RamaLama
Simplifies the local serving of AI models from any source
...Developers can use familiar container commands to pull, run, and interact with AI models from any source, treating models similarly to how container images are handled in OCI workflows. RamaLama supports multiple model registries and offers a REST API or chatbot interface for interacting with running models, making it flexible for local development, testing, or integration into larger systems. -
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D4RL
Collection of reference environments, offline reinforcement learning
...Researchers can load a dataset for a given task (e.g., maze navigation, manipulation) and apply their algorithm without the need to collect fresh transitions, which accelerates experimentation and comparison. The API is based on Gymnasium (via gym.make) and each environment also exposes a method get_dataset() that returns the offline data to learn from. The repository emphasizes open science, reproducibility, and benchmarking at scale, making it easier to compare algorithms on equal footing.
