Search Results for "yaml"
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Showing 43 open source projects for "yaml"
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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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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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Nerve
The Simple Agent Development Kit
...Define agents using a clean YAML format: system prompt, task, tools, and variables — all in one file. -
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Claude Platform CLI
The CLI for the Claude API
...It provides access to API resources through structured subcommands, making it useful for both interactive exploration and automated workflows. The CLI simplifies API requests by supporting typed flags, piped YAML or JSON input, and inline file references instead of manually writing complex JSON. Users can format, filter, and transform responses directly in the terminal using built-in output controls and GJSON queries. It also supports authentication through interactive login, API keys, profiles, and workspace switching for flexible development environments. ... -
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Buzz
A hive mind communication platform
...Agents receive their own identities and memberships, allowing them to answer questions, review patches, manage workspaces, and run tools without impersonating users. YAML workflows can respond to messages, reactions, schedules, and webhooks while preserving execution traces. Buzz provides a Tauri desktop client, browser access, a JSON-oriented CLI, MCP support, and ACP integrations for popular coding agents. Teams can run their own relay and keep the workspace, history, automation, and repositories under their control. -
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ant CLI
ant CLI - Command line tool for Anthropic Claude API
...It exposes every API resource as a structured subcommand, making it useful for both hands-on exploration and automated workflows. The ant CLI simplifies API requests by allowing users to build request bodies with typed flags, piped YAML or JSON, stdin input, and inline file references instead of manually writing complex JSON. It also includes built-in output formatting, response filtering, and GJSON-based transformation options so users can inspect and reuse API responses more efficiently. With support for interactive login, API keys, profiles, workspace switching, and authentication status checks, the ant CLI is built for flexible development environments. ... -
Cut Data Warehouse Costs by 54%BigQuery delivers 54% lower TCO with exabyte scale and flexible pricing. Free migration tools handle the SQL translation automatically.
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NeMo Automodel
Pytorch Distributed native training library for LLMs/VLMs
...Its DTensor-native SPMD approach lets the same training code scale from one GPU to large multi-node clusters by changing configuration. Hugging Face integration provides broad model compatibility without requiring format conversion. YAML recipes and CLI overrides keep experiments concise while preserving reproducibility. The library supports composable parallelism, optimized kernels, MoE acceleration, mixed precision, sequence packing, and asynchronous checkpointing. Jobs can run through interactive environments, Slurm, SkyPilot, or Kubernetes-based workflows. It targets both rapid research experiments and high-performance large-scale fine-tuning. -
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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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TorchDistill
A coding-free framework built on PyTorch
torchdistill (formerly kdkit) offers various state-of-the-art knowledge distillation methods and enables you to design (new) experiments simply by editing a declarative yaml config file instead of Python code. Even when you need to extract intermediate representations in teacher/student models, you will NOT need to reimplement the models, which often change the interface of the forward, but instead specify the module path(s) in the yaml file. In addition to knowledge distillation, this framework helps you design and perform general deep learning experiments (WITHOUT coding) for reproducible deep learning studies. i.e., it enables you to train models without teachers simply by excluding teacher entries from a declarative yaml config file. -
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Docker Agent
AI Agent Builder and Runtime by Docker Engineering
Docker Agent is an open-source multi-agent runtime developed by Docker that enables developers to define, run, and orchestrate AI agents using simple declarative configuration files instead of traditional code-heavy approaches. It introduces a YAML-based configuration model where users describe agent behavior, tools, models, and interaction logic in a single file, significantly reducing complexity in building AI systems. The runtime supports multi-agent collaboration, allowing specialized agents to delegate tasks to each other and operate as coordinated systems rather than isolated units. ... -
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Midscene
Vision-based AI framework for cross-platform UI automation tasks
...Developers can describe tasks such as clicking buttons, filling forms, or extracting information, and the system interprets these commands to interact with the interface accordingly. Midscene.js includes SDKs, scripting options, and integration capabilities that allow automation workflows to be written in JavaScript, TypeScript, or YAML-based scripts. Midscene also provides debugging and development tools. -
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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10
OpenShell
OpenShell is the safe, private runtime for autonomous AI agents.
...Developed by NVIDIA, it provides sandboxed execution spaces that protect system resources, credentials, and data from unauthorized access. Each agent runs inside a containerized sandbox governed by declarative YAML security policies that control network access, file permissions, and process behavior. The platform includes a gateway service that manages sandbox lifecycles and routes AI inference requests through controlled providers. OpenShell also features a privacy-aware routing system that prevents sensitive information from leaving the sandbox environment. ... -
11
OSMO
The developer-first platform for scaling complex Physical AI workloads
...It was originally built internally at NVIDIA to support robotics and embodied AI systems, where workflows span multiple stages such as data generation, training, simulation, and hardware testing. The platform addresses what NVIDIA refers to as the “three computer problem” by unifying these stages into a single pipeline defined through simple YAML configurations. It enables users to orchestrate tasks across Kubernetes clusters, automatically managing dependencies, scheduling, and resource allocation without requiring deep infrastructure expertise. -
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Rill
Fast SQL-based BI tool for real-time dashboards and analytics
...With an embedded in-memory database powered by DuckDB or ClickHouse, queries run in milliseconds, enabling real-time exploration and analysis. Rill supports local and remote data sources such as CSV, Parquet, S3, and GCS, making it flexible across environments. Its BI-as-code model combines SQL, YAML configuration, Git version control, and CLI tools, allowing teams to build, manage, and deploy analytics workflows efficiently. Automatic data profiling and responsive query updates help users understand datasets instantly. Interactive dashboards come with opinionated defaults, so teams can focus on insights instead of setup, while metrics layers standardize business logic for consistent reporting across dashboards, APIs, and AI systems. -
13
Bear Stone Smart Home
Custom Home Assistant configuration with automations and scripts setup
...It includes configuration files that manage entities such as lights, sensors, switches, and media devices, enabling centralized automation and monitoring. It demonstrates how to structure Home Assistant YAML files for scalability and maintainability in a real-world deployment. Bear Stone Smart Home also showcases custom automations and scripts designed to improve convenience, energy efficiency, and overall smart home behavior. Additionally, it may include examples of dashboards and user interface customization to enhance usability and visualization of home data. ... -
14
DocETL
A system for agentic LLM-powered data processing and ETL
...Instead of relying on single prompts or ad-hoc scripts, DocETL provides a declarative pipeline framework that breaks complex document analysis tasks into manageable operations that can be optimized and orchestrated automatically. Pipelines are typically defined using a low-code YAML interface, giving users full control over prompts and processing steps while still simplifying workflow creation. -
15
Halo
Framework built by White Circle for training large language
...Performance features include FlashAttention, DeepEP, Liger kernels, Grouped GEMM, BF16 optimizers, LoRA, and QLoRA. RL rollouts can run through vLLM or SGLang while overlapping with training. Halo also provides Docker images, YAML recipes, checkpoint tools, dataset utilities, benchmarks, and agent-oriented technical documentation. -
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Prompt Poet
Streamlines and simplifies prompt design for both developers
...The project focuses on transforming prompt engineering into a structured design process rather than ad-hoc string manipulation within application code. It allows developers and non-technical users to build prompts using templated configurations based on YAML and Jinja2, which makes prompts easier to compose, reuse, and modify across different environments. By separating prompt structure from program logic, Prompt Poet encourages iterative prompt design and experimentation without requiring constant changes to application code. The framework supports dynamic prompts that adapt to runtime data, allowing developers to inject variables, context, and examples directly into templates. ... -
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Omnigent
A meta-harness for all your AI agents
Omnigent is a meta-harness for managing many AI agents through one shared layer. It works with Claude Code, Codex, Cursor, Pi, and custom YAML-defined agents, so users can swap or combine agent runtimes without rebuilding their workflows. Sessions can move across terminal, browser, desktop, and mobile interfaces while keeping messages, files, terminals, and subagents in sync. The platform supports collaboration, shared live sessions, co-driving, conversation forking, and remote access from deployed servers. ... -
18
kagent
Kubernetes native framework for building AI agents
Kagent is a Kubernetes-native framework for building, deploying, and operating AI agents as first-class cloud-native workloads. It models core agent concepts declaratively using Kubernetes custom resources, so teams can manage agents similarly to other platform components via YAML, controllers, and standard cluster workflows. In kagent’s design, an “Agent” represents a system prompt plus a set of tools and other agents, along with an LLM configuration, making the agent definition portable and repeatable across environments. It supports multiple model providers through a dedicated configuration resource, allowing teams to switch providers or run mixed environments while keeping the agent spec stable. ... -
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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), parameter efficient fine-tuning (PEFT), 4-bit quantization (QLoRA), and larger-than-memory datasets. ... -
20
DESIGN.md
A format specification for describing a visual identity
design.md is an open specification created by Google Labs that defines a standardized way to describe design systems for AI coding agents. It allows developers to encode visual identity elements such as colors, typography, spacing, and components in a structured format. The file combines machine-readable design tokens with human-readable explanations, enabling agents to generate consistent user interfaces aligned with a brand. By providing persistent design context, it eliminates the need to... -
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GitHub Agentic Workflows
GitHub Agentic Workflows
...By writing intent in markdown files, a developer can quickly generate .yml Actions workflows that perform tasks such as summarizing issues, automating triage, generating reports, or maintaining documentation, all without manually crafting YAML logic from scratch. The system emphasizes safety and guardrails, running agents in sandboxed environments with minimal permissions by default, and using “safe outputs” to constrain what the workflow can write back into the repository. It includes tooling for compiling, testing, and iterating on agentic workflows locally and integrates with GitHub’s existing Actions ecosystem. -
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ticket
Fast, powerful, git-native ticket tracking in a single bash script
ticket is a lightweight, git-native ticket management tool implemented as a single Bash script that brings powerful issue tracking directly into your Git workflows without requiring a database or complex setup. It stores each ticket as a Markdown file with YAML frontmatter, making them human-readable and easy to version control alongside your code, while also allowing IDEs to jump straight to ticket definitions. The CLI provides common subcommands to create, list, edit, close, and manage dependencies between tickets, enabling clear hierarchical task structures and visual dependency trees. ... -
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Open Interpreter
A natural language interface for computers
Open Interpreter is an open-source tool that provides a natural-language interface for interacting with your computer. It lets large language models (LLMs) run code locally (Python, JavaScript, shell, etc.), enabling you to ask your computer to do tasks like data analysis, file manipulation, browsing, etc. in human terms (“chat with your computer”), with safeguards. Runs locally or via configured remote LLM servers/inference backends, giving flexibility to use models you trust or have... -
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Aerosolve
A machine learning package built for humans
Aerosolve is an open-source machine learning library developed by Airbnb, designed for interpretable and human-friendly modeling. Built around sparse, human-intuitive features (like geography, pricing), it supports feature quantization, interaction specification, and rule-based priors—enabling domain experts to contribute directly to model behavior. -
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ChatTTS webUI & API
A simple native web interface that uses ChatTTS to synthesize text
ChatTTS-ui is a local web interface and API wrapper around the ChatTTS speech synthesis system, designed to make advanced TTS models easy to use from a browser. It runs a small backend server (Python + Torch + ffmpeg) and exposes a simple webpage where you can type text, adjust parameters, and generate audio. The project supports Chinese, English, and mixed text with digits and control symbols, making it suitable for bilingual content and numerically heavy text like announcements or prompts....
