Search Results for "cloud" - Page 2
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Showing 34 open source projects for "cloud"
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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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8 Monitoring Tools in One APM. Install in 5 Minutes.AppSignal works out of the box for Ruby, Elixir, Node.js, Python, and more. 30-day free trial, no credit card required.
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Acontext
Context data platform for building observable, self-learning AI agents
Acontext is a cloud-native context data platform designed to support the development and operation of advanced AI agents. It provides a unified system to store and manage contexts, multimodal messages, artifacts, and task workflows, enabling developers to engineer context effectively for their agent products. The platform observes agent tasks and user feedback in real time, offering robust observability into workflows and helping teams understand how agents perform over time. -
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Klavis AI
MCP integration platforms for AI agents to use tools at any scale
Klavis AI is a Y Combinator X25-backed open-source infrastructure platform that enables AI agents to reliably connect with external tools and services at scale through Model Context Protocol (MCP). Founded by ex-Google DeepMind and ex-Lyft engineers, Klavis provides 50+ production-ready MCP servers with enterprise OAuth support for GitHub, Slack, Gmail, Salesforce, Linear, Notion, and more. The flagship product Strata solves tool overload through progressive discovery, achieving +13% higher... -
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LLocalSearch
LLocalSearch is a completely locally running search aggregator
...The system allows users to submit natural language questions, after which a chain of LLM-driven agents recursively searches for relevant information and compiles a response. Unlike many AI search tools, LLocalSearch operates without requiring external cloud APIs or proprietary services, making it suitable for privacy-focused or offline environments. The architecture integrates local language models with external tools such as search engines, enabling the system to gather up-to-date information while keeping model execution on local hardware. The tool also exposes the internal reasoning process of its agents so users can observe how queries are expanded and how results are retrieved during the search process. -
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aqueduct LLM
Aqueduct allows you to run LLM and ML workloads on any infrastructure
...You can connect Aqueduct to your existing cloud infrastructure (docs), and Aqueduct will seamlessly move your code from your laptop to the cloud or between different cloud infrastructure layers. Aqueduct provides a single interface to running machine learning tasks on your existing cloud infrastructure — Kubernetes, Spark, Lambda, etc. From the same Python API, you can run code across any or all of these systems seamlessly and gain visibility into how your code is performing. -
Our Free Plans just got better! | Auth0You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
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cortex
Production infrastructure for machine learning at scale
...Developers can define machine learning pipelines as code using declarative configuration files, which simplifies the process of managing complex ML workflows. The platform supports integration with cloud environments and container orchestration systems so that applications can scale dynamically based on demand. It is designed to help teams focus on building machine learning logic rather than managing infrastructure details. -
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VideoSrt
Windows-GUI
...Recognize video/audio speech to generate subtitle files (support Chinese-English translation, bilingual subtitles) Extract speech text from video/audio. Batch translation, filter processing/encoding SRT subtitle files. Using the Alibaba Cloud speech recognition interface, the accuracy is high, and the standard Mandarin/English recognition rate is over 95%. Video recognition does not need to upload the original video, which is convenient, fast and time-saving. -
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Kite
Primary Kite repo, private bits replaced with XXXXXXX
...It has been lightly adapted for publication here by replacing private information with XXXXXXX. As a result, many components here may not work out of the box. We used a variety of infrastructure, on a mix of cloud platforms, depending on what was most economical, though it was mostly on AWS. You should be able to develop, build, and test Kite entirely on your local machine. However, we do have cloud instances & VMs available for running larger jobs and for testing our cloud services. We bundle a lot of pre-computed datasets & machine learning models into the Kite app through the use of a custom filemap & encoding on top of go-bindata. ... -
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The Google Cloud Developer's Cheat Sheet
Cheat sheet for Google Cloud developers
Every product in the Google Cloud family described in <=4 words (with liberal use of hyphens and slashes) by the Google Developer Relations Team. This list only includes products that are publicly available. There are several products in pre-release/private-alpha that will not be included until they go public beta or GA. Many of these products have a free tier. There is also a free trial that will enable you try almost everything. -
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Docker Machine
Machine management for a container-centric world
Docker Machine is a tool that lets you install Docker Engine on virtual hosts, and manage the hosts with docker-machine commands. You can use Machine to create Docker hosts on your local Mac or Windows box, on your company network, in your data center, or on cloud providers like Azure, AWS, or DigitalOcean. Using docker-machine commands, you can start, inspect, stop, and restart a managed host, upgrade the Docker client and daemon, and configure a Docker client to talk to your host. Point the Machine CLI at a running, managed host, and you can run docker commands directly on that host. For example, run docker-machine env default to point to a host called default, follow on-screen instructions to complete env setup, and run docker ps, docker run hello-world, and so forth. ... -
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