Search Results for "mod-apache-snmp" - Page 9
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Showing 940 open source projects for "mod-apache-snmp"
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SageMaker Hugging Face Inference Toolkit
Library for serving Transformers models on Amazon SageMaker
...The Hugging Face Inference Toolkit allows user to override the default methods of the HuggingFaceHandlerService. SageMaker Hugging Face Inference Toolkit is licensed under the Apache 2.0 License. -
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Ideogram 4
Open image model at the forefront of design
Ideogram 4 is an open-weight text-to-image model focused on high-quality visual generation, design control, and accurate text rendering inside images. It is built for users who need more than generic image generation, especially when layout, typography, composition, color, and language understanding matter. The project introduces a structured JSON prompting workflow that gives creators more explicit control over scene details and visual constraints. It can also accept plain-text prompts,... -
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Clawbolt
The AI Assistant that actually does things for the trades
Clawbolt is an open-source messaging-first AI assistant built specifically for contractors, tradespeople, and service businesses that prefer managing work through chat instead of traditional dashboards. The platform allows users to interact with an AI assistant through iMessage, SMS, RCS, Telegram, and related messaging channels to handle tasks such as estimates, invoices, scheduling, reminders, and client communication. Clawbolt combines large language model orchestration with memory... -
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macai
All-in-one native macOS AI chat application
macai is a native macOS AI chat application that consolidates access to multiple AI providers into a single, polished desktop interface. It is built specifically for macOS using Swift and SwiftUI, delivering a lightweight and responsive experience that integrates seamlessly with the operating system. The app supports a wide range of providers, including OpenAI, Anthropic, Google Gemini, xAI, Perplexity, and Ollama, allowing users to switch between local and cloud-based models without... -
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Cognita
Open source RAG framework for building scalable modular AI apps
Cognita is an open source framework designed to help developers build, organize, and deploy Retrieval-Augmented Generation (RAG) applications in a structured and production-ready way. It addresses the gap between quick experimentation in notebooks and the complexity of deploying scalable AI systems by introducing a modular and API-driven architecture. Cognita provides reusable components such as parsers, data loaders, embedders, retrievers, and query controllers, allowing teams to customize... -
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NVIDIA PhysicsNeMo
Open-source deep-learning framework for building and training
NVIDIA PhysicsNeMo is an open-source deep learning framework designed for building artificial intelligence models that incorporate physical laws and scientific knowledge into machine learning workflows. The framework focuses on the emerging field of physics-informed machine learning, where neural networks are used alongside physical equations to model complex scientific systems. PhysicsNeMo provides modular Python components that allow developers to create scalable training and inference... -
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MarkPDFDown
A high-quality PDF to Markdown tool based on large language model
MarkPDFdown is an open-source document processing tool designed to convert PDF files into structured Markdown output that can be easily used for documentation, content pipelines, and AI processing workflows. The project focuses on extracting text, formatting, and structural information from complex PDF documents and transforming that information into clean Markdown that preserves the original hierarchy of headings, paragraphs, tables, and lists. By producing Markdown rather than raw text,... -
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Hugging Face Skills
Definitions for AI/ML tasks like dataset creation
Hugging Face Skills is a repository of standardized task definitions that package instructions, scripts, and resources so coding agents can reliably perform AI and machine learning workflows. Each skill is a self-contained folder with structured metadata and guidance that tells an agent how to execute tasks such as dataset creation, model training, evaluation, or Hub operations. The project is designed to be interoperable across major agent ecosystems, including Claude Code, OpenAI Codex,... -
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UltraRAG
Less Code, Lower Barrier, Faster Deployment
UltraRAG 2.0 is a low-code, MCP-enabled RAG framework that aims to lower the barrier to building complex retrieval pipelines for research and production. It provides end-to-end recipes—from encoding and indexing corpora to deploying retrievers and LLMs—so users can reproduce baselines and iterate rapidly. The toolkit comes with built-in support for popular RAG datasets, large corpora, and canonical baselines, plus documentation that walks from “quick start” to debugging and case analysis. It... -
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GLM-4
GLM-4 series: Open Multilingual Multimodal Chat LMs
GLM-4 is a family of open models from ZhipuAI that spans base, chat, and reasoning variants at both 32B and 9B scales, with long-context support and practical local-deployment options. The GLM-4-32B-0414 models are trained on ~15T high-quality data (including substantial synthetic reasoning data), then post-trained with preference alignment, rejection sampling, and reinforcement learning to improve instruction following, coding, function calling, and agent-style behaviors. The... -
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DeepEval is a simple-to-use, open-source LLM evaluation framework, for evaluating and testing large-language model systems. It is similar to Pytest but specialized for unit testing LLM outputs. DeepEval incorporates the latest research to evaluate LLM outputs based on metrics such as G-Eval, hallucination, answer relevancy, RAGAS, etc., which uses LLMs and various other NLP models that run locally on your machine for evaluation. Whether your application is implemented via RAG or fine-tuning,...
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Superduper
Superduper: Integrate AI models and machine learning workflows
Superduper is a Python-based framework for building end-2-end AI-data workflows and applications on your own data, integrating with major databases. It supports the latest technologies and techniques, including LLMs, vector-search, RAG, and multimodality as well as classical AI and ML paradigms. Developers may leverage Superduper by building compositional and declarative objects that out-source the details of deployment, orchestration versioning, and more to the Superduper engine. This... -
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Ludwig AI
Low-code framework for building custom LLMs, neural networks
Declarative deep learning framework built for scale and efficiency. Ludwig is a low-code framework for building custom AI models like LLMs and other deep neural networks. Declarative YAML configuration file is all you need to train a state-of-the-art LLM on your data. Support for multi-task and multi-modality learning. Comprehensive config validation detects invalid parameter combinations and prevents runtime failures. Automatic batch size selection, distributed training (DDP, DeepSpeed),... -
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Flowly AI
Flowly is 100x faster than OpenClaw
Flowly is an open-source personal AI assistant that runs locally on your machine and connects to multiple communication platforms like Telegram, WhatsApp, Discord, and Slack. It acts as a centralized AI system that can perform tasks such as web browsing, file management, command execution, scheduling, and more—all while keeping your data private. Designed for flexibility, Flowly supports multiple AI providers and models through LiteLLM, allowing users to customize how their assistant... -
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FastKoko
Dockerized FastAPI wrapper for Kokoro-82M text-to-speech model
FastKoko is a self-hosted text-to-speech server built around the Kokoro-82M model and exposed through a FastAPI backend. It is designed to be easy to deploy via Docker, with separate CPU and GPU images so that users can choose between pure CPU inference and NVIDIA GPU acceleration. The project exposes an OpenAI-compatible speech endpoint, which means existing code that talks to the OpenAI audio API can often be pointed at a Kokoro-FastAPI instance with minimal changes. It supports multiple... -
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Google DeepMind GraphCast and GenCast
Global weather forecasting model using graph neural networks and JAX
GraphCast, developed by Google DeepMind, is a research-grade weather forecasting framework that employs graph neural networks (GNNs) to generate medium-range global weather predictions. The repository provides complete example code for running and training both GraphCast and GenCast, two models introduced in DeepMind’s research papers. GraphCast is designed to perform high-resolution atmospheric simulations using the ERA5 dataset from ECMWF, while GenCast extends the approach with... -
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Seldon Core
An MLOps framework to package, deploy, monitor and manage models
The de facto standard open-source platform for rapidly deploying machine learning models on Kubernetes. Seldon Core, our open-source framework, makes it easier and faster to deploy your machine learning models and experiments at scale on Kubernetes. Seldon Core serves models built in any open-source or commercial model building framework. You can make use of powerful Kubernetes features like custom resource definitions to manage model graphs. And then connect your continuous integration and... -
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Brax
Massively parallel rigidbody physics simulation
Brax is a fast and fully differentiable physics engine for large-scale rigid body simulations, built on JAX. It is designed for research in reinforcement learning and robotics, enabling efficient simulations and gradient-based optimization. -
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SkyPilot
SkyPilot: Run AI and batch jobs on any infra
SkyPilot is a framework for running AI and batch workloads on any infra, offering unified execution, high cost savings, and high GPU availability. Run AI and batch jobs on any infra (Kubernetes or 12+ clouds). Get unified execution, cost savings, and high GPU availability via a simple interface. -
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Google Antigravity SDK
Python library for building agents that leverages Google Antigravity
Google Antigravity SDK for Python is a Python library for building AI agents powered by Antigravity and Gemini. It provides a secure, scalable, and stateful infrastructure layer so developers can focus on agent behavior instead of manually implementing the full agent loop. The SDK includes a high-level Agent class for quick setup, as well as lower-level conversation and connection abstractions for more controlled workflows. It supports streaming responses, stateful sessions, custom Python... -
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Wanwu AI Agent Platform
Enterprise AI agent platform for workflows, models, and RAG apps
Wanwu is an enterprise-grade AI agent development platform designed to help organizations build and deploy intelligent applications at scale. It provides a multi-tenant environment that enables teams to create AI agents, orchestrate workflows, and implement retrieval-augmented generation systems within a unified framework. Wanwu integrates large language models with business process automation, allowing developers to design complex, production-ready AI solutions tailored to enterprise needs.... -
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Pixeltable
Data Infrastructure providing an approach to multimodal AI workloads
Pixeltable is an open-source Python data infrastructure framework designed to support the development of multimodal AI applications. The system provides a declarative interface for managing the entire lifecycle of AI data pipelines, including storage, transformation, indexing, retrieval, and orchestration of datasets. Unlike traditional architectures that require multiple tools such as databases, vector stores, and workflow orchestrators, Pixeltable unifies these functions within a... -
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Awesome LLM Apps
Collection of awesome LLM apps with AI Agents and RAG using OpenAI
Awesome LLM Apps is a community-curated directory of interesting, practical, and innovative applications built on or around large language models, serving as a discovery hub for developers, researchers, and enthusiasts. The list spans a wide range of categories including productivity tools, creative assistants, utilities, education platforms, research frameworks, and niche vertical apps, showcasing how generative models are being used across domains. Each entry includes a brief description,... -
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Marvin
A batteries-included library for building AI-powered software
Meet Marvin: a batteries-included library for building AI-powered software. Marvin's job is to integrate AI directly into your codebase by making it look and feel like any other function. Marvin introduces a new concept called AI Functions. These functions differ from conventional ones in that they don’t rely on source code, but instead generate their outputs on-demand through AI. With AI functions, you don't have to write complex code for tasks like extracting entities from web pages,... -
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Every Code
Local AI coding agent CLI with multi-agent orchestration tools
Every Code (often referred to simply as Code) is a fast, local AI-powered coding agent designed to run directly in the terminal environment. It is a community-driven fork of the Codex CLI, with a strong emphasis on improving real-world developer ergonomics and workflows. Every Code enhances the traditional coding assistant model by introducing multi-agent orchestration, allowing multiple AI agents to collaborate, compare solutions, and refine outputs in parallel. It supports integration with...