Search Results for "model-builder"
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Showing 165 open source projects for "model-builder"
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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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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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Model Explorer
A modern model graph visualizer and debugger
Model Explorer is a visual tool for exploring, debugging, and optimizing ML models deployed on edge devices. Developed by Google AI Edge, it offers a browser-based interface to inspect layer-wise performance, memory usage, and inference timing of TensorFlow Lite and other supported models. It’s a powerful utility for developers optimizing models for constrained environments. -
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dsh-our-free-model
Simply install this plugin in your dsh
dsh-our-free-model is a plugin and developing standalone service that connects dsh to multiple publicly available or account-backed AI model gateways. It discovers available models dynamically instead of relying on a fixed local catalog. The plugin can expose models through an OpenAI-compatible local endpoint for use by other software. It includes model availability checks, regional-status handling, configurable reasoning budgets, and local performance measurements. ... -
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Netron
Visualizer for neural network, deep learning, machine learning models
...Netron has experimental support for TensorFlow, PyTorch, TorchScript, OpenVINO, Torch, Arm NN, BigDL, Chainer, CNTK, Deeplearning4j, MediaPipe, ML.NET, scikit-learn, TensorFlow.js. There is an extense variety of sample model files to download or open using the browser version. It is supported by macOS, Windows, Linux, Python Server and browser. -
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Model Context Protocol (MCP) Servers
Model Context Protocol Servers
The Model Context Protocol (MCP) is an open protocol that enables seamless integration between LLM applications and external data sources and tools. Whether you’re building an AI-powered IDE, enhancing a chat interface, or creating custom AI workflows, MCP provides a standardized way to connect LLMs with the context they need. -
PRTG Catches Network Issues Before They Cause DowntimeReactive troubleshooting usually means hearing about a problem from frustrated users, not your monitoring tool. PRTG sets threshold-based alerts across devices, servers and applications, notifying your team by email, SMS or push the moment a metric crosses a set limit. That means catching a failing disk or overloaded server before it becomes an outage and getting time back from firefighting. Start a free trial and set your first alerts today.
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Odysseus
Self-hosted AI workspace from PewDiePie
Odysseus is a self-hosted AI workspace designed for running language-model workflows on user-controlled infrastructure. It provides an interface for chat, agents, tools, research, model serving, email, and other AI-assisted productivity tasks. The project emphasizes local-first and privacy-first operation, with no telemetry by default. It is built for users who want a personal AI environment rather than a fully hosted commercial assistant. -
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Kokoro
An inference library for Kokoro-82M
Kokoro is an open-weight text-to-speech model and inference library built around the lightweight Kokoro-82M model. It is designed to generate high-quality speech from text while staying fast, compact, and cost-efficient compared with larger TTS systems. The project is useful for developers who want deployable speech synthesis without depending on a closed platform. It can be installed as a Python package and used in applications, scripts, experiments, or production workflows. ... -
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NOFX
Open source AI trading OS for autonomous multi-model trading systems
NOFX is an open source AI-powered trading operating system designed to automate financial trading workflows using autonomous AI agents. It acts as an infrastructure layer that transforms market data into AI-driven trade decisions and execution. Instead of requiring users to manually configure machine learning models, data sources, and API integrations, the system allows AI components to perceive market conditions, select models, and perform trading actions automatically. It supports running... -
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Open WebUI
User-friendly AI Interface
...Additionally, Open WebUI offers a Progressive Web App (PWA) for mobile devices, providing offline access and a native app-like experience. The platform also includes a Model Builder, allowing users to create custom models from base Ollama models directly within the interface. With over 156,000 users, Open WebUI is a versatile solution for deploying and managing AI models in a secure, offline environment. -
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TikTok MCP
Model Context Protocol (MCP) with TikTok integration
The TikTok MCP integrates TikTok access into AI applications like Claude AI via TikNeuron. It enables analysis and interaction with TikTok content to determine virality factors and extract video content. -
Custom VMs From 1 to 96 vCPUs With 99.95% UptimeLive migration and automatic failover keep workloads online through maintenance. One free e2-micro VM every month.
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MCP Mongo Server
A Model Context Protocol Server for MongoDB
A Model Context Protocol server that provides access to MongoDB databases, enabling Large Language Models to inspect collection schemas and execute MongoDB operations. -
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MCP Server Amazon Bedrock
Model Context Procotol(MCP) server for using Amazon Bedrock
The Amazon Bedrock MCP Server is an MCP server that integrates with Amazon Bedrock's Nova Canvas model for AI image generation. It allows users to generate high-quality images from text descriptions using Amazon's AI capabilities. -
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Box MCP Server
A Box model context protocol server to search, read and access files
Box MCP Server is a Model Context Protocol (MCP) server designed to facilitate searching, reading, and accessing files stored on the Box cloud storage platform. It enables seamless integration with Box, allowing for efficient file management and retrieval through MCP-compatible clients. -
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MCP Server Playwright
MCP server for browser automation using Playwright
An MCP (Model Context Protocol) server that leverages Playwright to provide browser automation capabilities, enabling large language models (LLMs) to interact with web pages, take screenshots, and execute JavaScript within a real browser environment. -
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iOS Simulator MCP
MCP server for interacting with the iOS simulator
The iOS Simulator MCP Server is a Model Context Protocol implementation that allows interaction with iOS simulators. It enables users to retrieve information about simulators, control UI interactions, and inspect UI elements, facilitating automated testing and development workflows. -
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DocsGPT
Private AI agents, assistants and search over your own documents
...It ingests PDFs, Office files, scanned pages (OCR), web pages and repositories, syncs Google Drive, SharePoint, Confluence, GitHub and S3, and answers with citations to the source passage. Agents call tools, APIs and MCP servers with per-action approval; a visual builder chains AI steps, conditions and code into workflows; agents can produce DOCX, XLSX, PPTX and PDF files. Models: OpenAI, Anthropic, Google and others, or local via Ollama, llama.cpp or vLLM. Vectors: pgvector, Qdrant, Milvus, Elasticsearch, MongoDB Atlas or FAISS. Install with one line (curl -fsSL https://docs.ac/install | bash), or deploy with Docker Compose or Kubernetes, including fully air-gapped. ... -
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MCP YouTube
A Model-Context Protocol Server for YouTube
The YouTube MCP Server uses yt-dlp to download subtitles from YouTube videos and connects to claude.ai via the Model Context Protocol. It enables AI assistants to summarize YouTube videos by accessing their subtitles. -
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MCP JetBrains
A model context protocol server to work with JetBrains IDEs
The JetBrains MCP Server is a Model Context Protocol (MCP) server designed to integrate seamlessly with JetBrains IDEs such as IntelliJ, PyCharm, WebStorm, and Android Studio. It facilitates enhanced communication between Large Language Models (LLMs) and the development environment, enabling AI-driven code assistance and automation. -
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Upscayl
Free and Open Source AI Image Upscaler for Linux, MacOS and Windows
...You can also download the flatpak version and double-click the flatpak file to install via Store but wait for the full release, we'll be pushing it to Flathub for easy access. Upscayl uses AI models to enhance your images by guessing what the details could be. It uses Real-ESRGAN (and more in the future) model to achieve this. The CLI tool is called real-esrgan-ncnn-vulkan and it's available on the Real-ESRGAN repository. -
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Easy DataSet
A powerful tool for creating datasets for LLM fine-tuning
...The system includes automated question-generation capabilities, hierarchical label trees, and answer generation pipelines that use LLM APIs to produce coherent paired data with customizable templates. Beyond dataset creation, Easy-dataset also provides a built-in evaluation system with model testing and blind-test features, helping teams validate model performance using curated test sets. -
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AgentQL MCP
Model Context Protocol server that integrates AgentQL's data
The AgentQL MCP Server is a Model Context Protocol (MCP) server that integrates AgentQL's data extraction capabilities, enabling users to extract structured data from web pages using natural language prompts. -
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MCP Server and GW
An MCP stdio to HTTP SSE transport gateway with example server
mcp-server-and-gw is a Model Context Protocol (MCP) gateway that bridges standard input/output to HTTP Server-Sent Events (SSE) transport. It includes an example MCP server and client, facilitating the development and testing of MCP implementations. This tool is particularly useful for integrating MCP servers with applications like Claude Desktop that may not natively support remote server connections. -
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LoLLMs WEBUI
Local AI WebUI for running and managing large language models offlineA
...It provides users with a centralized environment to interact with multiple AI models, making it suitable for experimentation, development, and personal use. lollms-webui emphasizes offline capability, allowing users to maintain privacy and control over their data while still accessing advanced AI features. It integrates model management tools that help users download, configure, and switch between different language models with ease. It is built to be user-friendly while still offering advanced customization options for power users who want deeper control over model behavior. Additionally, it supports extensibility through plugins or modular components, enabling users to expand functionality as needed. ... -
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MLflow
Open source platform for the machine learning lifecycle
MLflow is a platform to streamline machine learning development, including tracking experiments, packaging code into reproducible runs, and sharing and deploying models. MLflow offers a set of lightweight APIs that can be used with any existing machine learning application or library (TensorFlow, PyTorch, XGBoost, etc), wherever you currently run ML code (e.g. in notebooks, standalone applications or the cloud). -
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civitai
Open platform for sharing and discovering Stable Diffusion models
...Civitai encourages collaboration by allowing users to publish their models, explore models created by others, and learn from the techniques used in the community. It also supports user accounts, model browsing, and interaction features that help creators showcase their work and receive feedback from other users. Developers can deploy the project to run their own instance of the platform and integrate with its available API to retrieve models. -
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Context7 Platform
Up-to-date code documentation for LLMs and AI code editors
Context7 is a system that aims to inject fresh, version-specific documentation and code snippets into language model prompts, thereby avoiding reliance on outdated training data or hallucinated APIs. It’s designed to integrate with tools that support the Model Context Protocol (MCP), such as Cursor, Windsurf, and other LLM clients. When a user writes a prompt and appends something like “use context7,” the system detects the libraries or frameworks being asked about, fetches the latest docs/snippets from the source repositories, filters and packages relevant context, and injects them into the LLM’s prompt to guide it toward accurate, up-to-date code. ...
