Showing 1075 open source projects for "unit-api"

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  • 1
    AppAgent

    AppAgent

    Multimodal Agents as Smartphone Users, an LLM-based multimodal agent

    AppAgent is an open-source multimodal agent framework designed to enable large language models to operate smartphone applications through natural interactions with graphical user interfaces. The system allows an AI agent to interpret visual information from the screen and translate natural language instructions into actions such as tapping, swiping, and navigating between application screens. Instead of requiring backend access to application APIs, the framework interacts with apps the same...
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  • 2
    TimesFM

    TimesFM

    Pretrained time-series foundation model developed by Google Research

    ...It provides a decoder-only model approach to forecasting, aiming for strong performance even in zero-shot or low-data settings where traditional models often struggle. The project includes code and an inference API intended to make it practical to run forecasts programmatically, with options to use different backends such as Torch or Flax depending on your environment and performance needs. Newer releases emphasize expanded context handling and more flexible forecasting outputs, including quantile forecasting so users can get uncertainty estimates rather than only point predictions. ...
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  • 3
    Secure OpenClaw

    Secure OpenClaw

    A personal 24x7 AI assistant like OpenClaw

    Secure-OpenClaw is an open-source project designed to transform your everyday messaging apps like WhatsApp, Telegram, Signal, and iMessage into a 24×7 personal AI assistant that can respond to queries, run tasks, remember context, and interact with external services. Unlike a traditional chatbot that lives in a browser or API dashboard, Secure-OpenClaw runs locally or on your chosen infrastructure and listens for messages on channels you already use, giving you an always-on interface to a powerful agent. It leverages Claude and other models to interpret messages and is built to manage persistent memory, scheduled reminders, and integration with hundreds of third-party apps to automate workflows without leaving your chat. ...
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  • 4
    Dash Data Agent

    Dash Data Agent

    Self-learning data agent that grounds its answers in layers of content

    Dash is a self-learning data agent built by the Agno AI community that generates grounded answers to English queries over structured data by synthesizing SQL and reasoning based on six layers of context, improving automatically with each run. It sidesteps common limitations of simple text-to-SQL agents by incorporating multiple context layers — including schema structure, human annotations, known query patterns, institutional knowledge from docs, machine-discovered error patterns, and live...
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    AWS Agent Skills

    AWS Agent Skills

    AWS Skills for Agents

    ...Instead of streaming giant documentation sets or relying on episodic web search, this project compresses AWS best practices, usage patterns, edge cases, and real-world engineering guides into pre-structured skill definitions that are token-efficient and tailored for reasoning. The skills cover critical AWS services such as IAM, Lambda, DynamoDB, S3, API Gateway, EKS, and many more, letting agents offer actionable advice on infrastructure as code, debugging, security configurations, and architectural workflows. Skills are kept up to date with weekly documentation checks, ensuring they reflect current AWS patterns and service changes.
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  • 6
    mgrep

    mgrep

    A calm, CLI-native way to semantically grep everything, like code

    This project is a modern, semantic search tool that brings the simplicity of traditional command-line grep to the world of natural language and multimodal content, enabling users to search across codebases, documents, PDFs, and even images using meaning-aware queries. Built with a focus on calm CLI experiences, it lets you index and query your local files with semantic understanding, delivering results that are relevant to your intent rather than simple pattern matches, which is especially...
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  • 7
    Agent Reinforcement Trainer

    Agent Reinforcement Trainer

    Train multi-step agents for real-world tasks using GRPO

    Agent Reinforcement Trainer, or ART is an open-source reinforcement learning framework tailored to training large language model agents through experience, making them more reliable and performant on multi-turn, multi-step tasks. Instead of just manually crafting prompts or relying on supervised fine-tuning, ART uses techniques like Group Relative Policy Optimization (GRPO) to let agents learn from environmental feedback and reward signals. The framework is designed to integrate easily with...
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  • 8
    CoAI.Dev

    CoAI.Dev

    Next Generation AI One-Stop Internationalization Solution

    CoAI.Dev is an open-source “one-stop” AIGC web application that combines a modern chat-first UI with a full backend for running, managing, and monetizing multiple AI model providers from one place. It is designed to support a wide range of LLM and image-generation backends (including OpenAI-compatible endpoints), while also providing an admin dashboard for user, subscription, and pricing controls, so it can be operated as a self-hosted AI product rather than just a personal playground. The...
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  • 9
    Quotio

    Quotio

    Stop juggling AI accounts. Quotio is a beautiful native macOS menu bar

    Quotio is a native macOS menu bar application designed to unify and manage multiple AI service accounts and quota usage in one consolidated interface. It works alongside a local proxy server (CLIProxyAPI) and helps developers who use various AI coding assistants such as Claude, Gemini, OpenAI Codex, Qwen, and others — avoiding the hassle of juggling tokens, keys, and rate limits across different providers. Through real-time dashboard views, users can monitor request traffic, token...
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  • 10
    VibeKit

    VibeKit

    Run Claude Code, Gemini, Codex in a clean, isolated sandbox

    Vibekit is an open-source toolkit focused on rapid prototyping and building of AI-driven experiences, particularly those that integrate multimodal inputs, reactive interfaces, and context-aware behaviors. It provides a set of abstractions and utilities that let developers connect generative models to UI frameworks, sensors, event streams, and external services without having to build plumbing from scratch. Instead of treating AI models as black boxes behind simple prompts, Vibekit encourages...
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  • 11
    Open Model Zoo

    Open Model Zoo

    Pre-trained Deep Learning models and demos

    ...In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. Tools in the repository also help automate model downloads and other tasks, making it easier to incorporate these models into production systems or custom solutions.
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  • 12
    StatsForecast

    StatsForecast

    Fast forecasting with statistical and econometric models

    StatsForecast is a Python library for time-series forecasting that delivers a suite of classical statistical and econometric forecasting models optimized for high performance and scalability. It is designed not just for academic experiments but for production-level time-series forecasting, meaning it handles forecasting for many series at once, efficiently, reliably, and with minimal overhead. The library implements a broad set of models, including AutoARIMA, ETS, CES, Theta, plus a battery...
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  • 13
    WorldGen

    WorldGen

    Generate Any 3D Scene in Seconds

    WorldGen is an AI model and library that can generate full 3D scenes in a matter of seconds from either text prompts or reference images. It is designed to create interactive environments suitable for games, simulations, robotics research, and virtual reality, rather than just static 3D assets. The core idea is that you describe a world in natural language and WorldGen produces a navigable 3D scene that you can freely explore in 360 degrees, with loop closure so that the space remains...
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  • 14
    Agently 4

    Agently 4

    Build GenAI application quick and easy

    ...With Agently, one can define agents that call different models, chain tasks, trigger workflows based on events, and switch models with minimal code changes. It abstracts away boilerplate around model API calls, tool usage, prompt management, and workflow state. The project aims at production-grade GenAI application development rather than just one-off scripts — you’ll find examples of news gathering, agentic workflows, control systems, etc. It is licensed under Apache-2.0, allowing commercial use and modification. Because it's built in Python, it integrates easily with existing data pipelines, databases, and agent architectures.
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  • 15
    Firecrawl MCP Server

    Firecrawl MCP Server

    Adds powerful web scraping and search to Cursor and Claude

    ...It exposes tools for single-page scrape, multi-URL batch jobs, site discovery, and search enrichment, returning cleaned, structured content suitable for downstream LLM reasoning. The server is designed to run with Firecrawl’s hosted API or self-hosted deployments, making it flexible for enterprise data-governance requirements. Built-in behaviors include JavaScript rendering, automatic retries, and streamable HTTP so long pages and large crawls can flow incrementally into agents. Because it’s an MCP server, clients get typed inputs/outputs and standardized error handling rather than ad-hoc prompt instructions. ...
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  • 16
    Kodu

    Kodu

    Kodu is an autonomous coding agent that lives in your IDE

    ...It includes conversation history, diff previews, and code-generation templates for repetitive tasks. The project also focuses on openness—developers can extend it with plugins, API configurations, and custom model backends to use Anthropic’s Claude or other compatible LLM APIs.
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  • 17
    ChatGLM3

    ChatGLM3

    ChatGLM3 series: Open Bilingual Chat LLMs | Open Source Bilingual Chat

    ...It keeps the series’ smooth dialog and low deployment cost while adding native tool use (function calling), a built-in code interpreter, and agent-style workflows. The family includes base and long-context variants (8K/32K/128K). The repo ships Python APIs, CLI and web demos (Gradio/Streamlit), an OpenAI-format API server, and a compact fine-tuning kit. Quantization (4/8-bit), CPU/MPS support, and accelerator backends (TensorRT-LLM, OpenVINO, chatglm.cpp) enable lightweight local or edge deployment.
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  • 18
    MCP Hub

    MCP Hub

    An MCP client for Neovim that seamlessly integrates MCP servers

    mcphub.nvim is an MCP (Model Context Protocol) client plugin for Neovim that seamlessly integrates MCP servers into your editing workflow with an intuitive interface for managing, testing, and using MCP servers with your favorite chat plugins. Create your first MCP capable agent you need only 6 lines of code. Works with any langchain-supported LLM that supports tool calling (OpenAI, Anthropic, Groq, LLama etc.) Explore MCP capabilities and generate starter code with the interactive code...
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  • 19
    OpenCompass

    OpenCompass

    OpenCompass is an LLM evaluation platform

    ...OpenCompass is a one-stop platform for large model evaluation, aiming to provide a fair, open, and reproducible benchmark for large model evaluation. Pre-support for 20+ HuggingFace and API models, a model evaluation scheme of 50+ datasets with about 300,000 questions, comprehensively evaluating the capabilities of the models in five dimensions. One line command to implement task division and distributed evaluation, completing the full evaluation of billion-scale models in just a few hours. Support for zero-shot, few-shot, and chain-of-thought evaluations, combined with standard or dialogue type prompt templates, to easily stimulate the maximum performance of various models.
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  • 20
    node-red-contrib-custom-chatgpt
    ...Install with the built-in Node-RED Palette manager. When editing the properties of the node, to get your OPENAI_API_KEY log in to ChatGPT. Create a new secret key" then copy and paste the "API key" into the node API_KEY property value. msg.payload should be a well-written prompt that provides enough information for the model to know what you want and how it should respond. Its success generally depends on the complexity of the task and quality of your prompt. A good rule of thumb is to think about how you would write a word problem for a middle schooler to solve. msg.payload should be a well-written prompt that provides enough information for the model to know what you want and how it should respond.
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  • 21
    Opacus

    Opacus

    Training PyTorch models with differential privacy

    ...Vectorized per-sample gradient computation that is 10x faster than micro batching. Supports most types of PyTorch models and can be used with minimal modification to the original neural network. Open source, modular API for differential privacy research. Everyone is welcome to contribute. ML practitioners will find this to be a gentle introduction to training a model with differential privacy as it requires minimal code changes. Differential Privacy researchers will find this easy to experiment and tinker with, allowing them to focus on what matters.
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  • 22
    Metarank

    Metarank

    A low code Machine Learning service that personalizes articles

    ...Ingest historical item listings, clicks and item metadata so Metarank can find hidden dependencies in the data using our simple JSON format.No Machine Learning experience is required, run our CLI tool with a set of features in a YAML configuration. Run Metarank API service, feed it with real-time events and receive a personalized ranking for your items that will boost conversion, click-through rate or any other business-critical metric you define.
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  • 23
    tf2onnx

    tf2onnx

    Convert TensorFlow, Keras, Tensorflow.js and Tflite models to ONNX

    tf2onnx converts TensorFlow (tf-1.x or tf-2.x), keras, tensorflow.js and tflite models to ONNX via command line or python API. Note: tensorflow.js support was just added. While we tested it with many tfjs models from tfhub, it should be considered experimental. TensorFlow has many more ops than ONNX and occasionally mapping a model to ONNX creates issues. tf2onnx will use the ONNX version installed on your system and installs the latest ONNX version if none is found.
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  • 24
    Deepchecks

    Deepchecks

    Test Suites for validating ML models & data

    ...To run a specific single check, all you need to do is import it and then to run it with the required (check-dependent) input parameters. More details about the existing checks and the parameters they can receive can be found in our API Reference. An ordered collection of checks, that can have conditions added to them. The Suite enables displaying a concluding report for all of the Checks that ran.
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  • 25
    DALI

    DALI

    A GPU-accelerated library containing highly optimized building blocks

    The NVIDIA Data Loading Library (DALI) is a library for data loading and pre-processing to accelerate deep learning applications. It provides a collection of highly optimized building blocks for loading and processing image, video and audio data. It can be used as a portable drop-in replacement for built-in data loaders and data iterators in popular deep learning frameworks. Deep learning applications require complex, multi-stage data processing pipelines that include loading, decoding,...
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