Search Results for "cloud system" - Page 2
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Showing 138 open source projects for "cloud system"
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Ship Agents FasterGemini Enterprise Agent Platform lets you rapidly build, scale, govern and optimize production-ready agents grounded in your organization's data. The platform enables developers to build custom or pre-built agents for virtually any use case. New customers get $300 in free credits.
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$300 Free Credits for Your Google Cloud ProjectsLaunch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
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Ollamac
Mac app for Ollama
...The application focuses on delivering a lightweight and responsive experience that integrates seamlessly with the macOS ecosystem. Because the models run locally, the system enables private AI workflows without sending data to external APIs or cloud services. Ollamac supports different Ollama models and provides features designed to improve usability such as syntax highlighting and configurable settings. -
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Casibase
Open-source enterprise-level AI knowledge base and MCP
Casibase is an open-source AI cloud platform designed to function as an enterprise knowledge base, container management system, and collaboration environment for AI-driven applications. The project combines knowledge management, messaging, and forum features with large language model integration to create an interactive platform for storing and querying domain-specific knowledge. -
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SmythOS
Cloud-native runtime for agentic AI
SmythOS SRE (Smyth Runtime Environment) is an open-source runtime and development platform designed for building and operating production-grade AI agents. It provides a foundational infrastructure layer that functions similarly to an operating system for agentic AI systems, managing resources such as language models, storage, vector databases, and caching through a unified interface. Developers can use the runtime to create, deploy, and orchestrate intelligent agents across local machines, cloud environments, or hybrid infrastructures without rewriting their application logic. ... -
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AgentForge
Extensible AGI Framework
AgentForge is a framework for creating and deploying AI agents that can perform autonomous decision-making and task execution. It enables developers to define agent behaviors, train models, and integrate AI-powered automation into various applications. -
Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Supertonic
Lightning-fast, on-device TTS, running natively via ONNX
Supertonic is a lightning-fast, on-device text-to-speech system built around ONNX Runtime for maximum speed and portability. It focuses on running entirely locally, eliminating the need for cloud APIs and providing low latency and strong privacy guarantees, even on constrained devices like Raspberry Pi boards and e-readers. The core model is highly compact at around 66 million parameters, yet benchmarks show it can generate speech up to 167× faster than real time on modern consumer hardware and significantly outpace popular cloud TTS APIs in throughput and real-time factor. ... -
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DeepSeek-OCR
Contexts Optical Compression
...It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body text, interpreting tables, or recognizing handwritten versus printed words. It supports local deployment, enabling organizations concerned about privacy or latency to run the pipeline on-premises rather than send sensitive documents to third-party cloud services. ... -
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Project NOMAD
Self-contained, offline survival computer with tools, knowledge, & AI
Project N.O.M.A.D. (Node for Offline Media, Archives, and Data) is a self-contained, offline-first knowledge and education server designed to run on local hardware. It combines AI, educational resources, and critical information tools into a single platform accessible through a web browser. Built as a containerized system managed via Docker, it orchestrates multiple applications through a centralized “Command Center” interface. NOMAD enables users to access offline Wikipedia, AI chat, maps,... -
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Claude Code Video Vision
Give Claude the ability to watch and understand videos
...The system dynamically adapts how much data it extracts based on the user’s query, adjusting frame rate, resolution, and time windows to optimize both performance and token efficiency. It supports multiple backends for audio processing, including local and cloud-based options, enabling flexible deployment depending on privacy or performance requirements. -
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vLLM Semantic Router
System Level Intelligent Router for Mixture-of-Models at Cloud
Semantic Router is an open-source system designed to intelligently route requests across multiple large language models based on the semantic meaning and complexity of user queries. Instead of sending every prompt to the same model, the system analyzes the intent and reasoning requirements of the request and dynamically selects the most appropriate model to process it. This approach allows developers to combine multiple models with different strengths, such as lightweight models for simple... -
Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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TuyaOpen
Next-gen AI+IoT framework for T2/T3/T5AI/ESP32/and more
...The platform provides a cross-platform C and C++ software development kit that supports a wide range of hardware platforms including Tuya microcontrollers, ESP32 boards, Raspberry Pi devices, and other embedded systems. It offers a unified development environment where developers can build devices capable of communicating with IoT cloud services while integrating AI capabilities and intelligent automation features. The system includes built-in networking support for communication protocols such as Wi-Fi, Bluetooth, and Ethernet, allowing devices to connect securely to remote services and applications. TuyaOpen also integrates with Tuya’s broader cloud ecosystem, enabling developers to manage device authentication, firmware updates, device activation, and remote monitoring from centralized services. -
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MAI-UI
Real-World Centric Foundation GUI Agents
...Developed by Tongyi-MAI (Alibaba’s research initiative), the MAI-UI models are multimodal agents trained to understand user instructions and corresponding screenshots, grounding those instructions to on-screen elements and generating sequences of GUI actions such as taps, swipes, text input, and system commands. Unlike traditional UI frameworks, MAI-UI emphasizes realistic deployment by supporting agent–user interaction (clarifying ambiguous instructions), integration with external tool APIs using MCP calls, and a device–cloud collaboration mechanism that dynamically routes computation to on-device or cloud models based on task state and privacy constraints. -
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Google Agent Skills
Agent Skills for Google products and technologies
...The system helps bridge the gap between documentation and actionable agent behavior. -
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SwanLab
An open-source, modern-design AI training tracking and visualization
...It provides a modern user interface for visualizing results, enabling teams to compare runs, track model performance trends, and collaborate on machine learning research. SwanLab supports both cloud and self-hosted deployments, allowing organizations to run the system privately or integrate it into shared development environments. The platform integrates with a wide range of machine learning frameworks including PyTorch, Transformers, Keras, and other widely used training ecosystems. -
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Gemma Chat
Local AI chat + coding agent for Apple Silicon, powered by Gemma 4
...The project enables users to interact with AI through a chat interface while also supporting code generation and editing workflows. It emphasizes privacy and independence by avoiding cloud dependencies, allowing all interactions and data to remain local. The system integrates model selection and execution directly into the app, giving users control over performance and behavior. It is particularly aligned with the “vibe coding” approach, where users iteratively build and modify projects through conversational prompts. ... -
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PrivateGPT
Interact with your documents using the power of GPT
PrivateGPT is a production-ready, privacy-first AI system that allows querying of uploaded documents using LLMs, operating completely offline in your own environment. It provides contextual generative AI capabilities without sending data externally. Now maintained under Zylon.ai with enterprise deployment options (air gapped, cloud, or on-prem). -
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ClaraVerse
Claraverse is a opesource privacy focused ecosystem to replace ChatGPT
ClaraVerse is an open-source private AI workspace designed to give users a unified environment for interacting with large language models, building automations, and managing AI-driven tasks in a self-hosted environment. The platform combines chat interfaces, workflow automation, and long-running task management into a single application that can connect to both local and cloud-based AI models. Users can integrate models from multiple providers such as OpenAI, Anthropic, Google, or locally hosted systems like Ollama and LM Studio, enabling flexibility in how AI capabilities are deployed and managed. The system includes a visual workflow builder that allows users to create automation pipelines where AI tools interact with external services, APIs, or datasets. ... -
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text-extract-api
Document (PDF, Word, PPTX ...) extraction and parse API
...The architecture is designed to be lightweight and easily deployable, making it suitable for both local installations and cloud environments. -
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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 changing tools. It includes advanced features such as multimodal capabilities, image generation, search integration, and reasoning workflows, making it more than just a simple chat client. ... -
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PaddleOCR-json
OCR offline image text recognition command line windows program
PaddleOCR-json is an OCR engine based on the PaddleOCR project that provides a command-line interface and tools for extracting text from images and exporting results in structured JSON format. It wraps the PaddleOCR models, which are capable of detecting and recognizing text in a wide variety of languages and layouts, into a self-contained executable that can be run locally without needing a deep learning environment configured manually. This makes it practical for developers or system... -
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Hyprnote
Local-first AI Notepad for Private Meetings
Hyprnote is an open-source, privacy-first AI notepad app designed for taking notes during meetings—transcribing audio (microphone and system) and generating context-rich summaries using on-device AI models like Whisper and HyprLLM, all without any data leaving your machine.(turn0search7, turn0search1). Listens to your meetings while you write. Crafts smart summaries based on your quick notes. Runs completely offline using open-source models like Whisper or HyprLLM. Use approved third-party... -
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NVIDIA NeMo Framework
Scalable generative AI framework built for researchers and developers
NVIDIA NeMo is a scalable, cloud-native generative AI framework aimed at researchers and PyTorch developers working on large language models, multimodal models, and speech AI (ASR and TTS), with growing support for computer vision. It provides collections of domain-specific modules and reference implementations that make it easier to pre-train, fine-tune, and deploy very large models on multi-GPU and multi-node infrastructure. -
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Colab-MCP
An MCP server for interacting with Google Colab
Colab-MCP is an open-source Model Context Protocol server developed by Google that enables AI agents to directly interact with and control Google Colab environments programmatically, transforming Colab into a fully automated, agent-accessible workspace. Instead of relying on manual notebook usage, the system allows MCP-compatible agents to execute code, manage files, install dependencies, and orchestrate entire development workflows within Colab’s cloud infrastructure. This approach bridges the gap between local AI agents and remote high-performance compute environments, allowing users to offload heavy workloads such as machine learning training, data analysis, and dependency-heavy tasks to Colab’s GPU and TPU resources. ... -
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Browserbase MCP Server
Allow LLMs to control a browser with Browserbase and Stagehand
...The system supports multiple AI models and integrates seamlessly into agent workflows, making it suitable for applications such as web scraping, testing, and intelligent automation. It also includes advanced capabilities such as screenshot capture, DOM analysis, and session persistence, enabling complex interactions across multiple browsing sessions. -
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AutoTrain Advanced
Faster and easier training and deployments
...It supports a wide range of tasks including text classification, sequence-to-sequence modeling, token classification, sentence embedding training, and large language model fine-tuning. The system integrates closely with the Hugging Face ecosystem and allows developers to train models using datasets hosted on the Hugging Face Hub. AutoTrain Advanced can run locally or in cloud environments, making it adaptable to different computational setups. By automating tasks such as model configuration, hyperparameter selection, and training pipelines, the project significantly reduces the technical barrier to building AI systems. -
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PicoLM
Run a 1-billion parameter LLM on a $10 board with 256MB RAM
...This makes PicoLM particularly suitable for edge computing, offline AI applications, and embedded AI devices that cannot rely on cloud resources.
