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Published directory entries matching your search.
Guild is a vendor-neutral control plane for AI agents. It lets engineering teams manage, govern, and share agents in production, with security and observability built in. Features include scoped credentials, action approval, policy enforcement, tracing, and evaluations. It supports any model or framework and provides a shared agent catalog and CLI access.
Helicone AI supports deploying, serving, monitoring, or operating AI and machine-learning systems.
Humanloop was a development platform for LLM applications that provided management and evaluation of AI applications. The team announced it is joining Anthropic, and the Humanloop platform is to be sunset on September 8th, 2025. A migration guide covers exporting Files, Versions, Logs and Evaluations.
Hydrosphere Mist is a serverless proxy for Spark clusters. It offers a functional programming framework and deployment model for Spark applications, with a REST HTTP and messaging API for Scala and Python Spark jobs. Sessions are managed across EMR, Hortonworks, Cloudera, DC/OS and vanilla Spark clusters.
This repository provides a hyperparameter optimization implementation for machine learning algorithms, accompanying a paper on hyperparameter optimization theory and practice. It includes sample code for regression and classification problems using the Boston-Housing and MNIST datasets, covering algorithms such as random forest, SVM, KNN and artificial neural networks.
Infer.NET is a framework for running Bayesian inference in graphical models. It can be used for machine learning problems such as classification, recommendation or clustering, and for probabilistic programming. It is published as open source on GitHub under the MIT license and available as NuGet packages.
A 2003 book by David J.C. MacKay published by Cambridge University Press, covering information theory, inference, and learning algorithms. The site offers corrections, software, and downloadable figures. It lists a price of £35.00 or $60.00.
An archived educational course repository for learning about LLMs, LLMOps and vector databases by designing, training and deploying a real-time financial advisor LLM system. It includes source code, video and reading materials, and covers a training pipeline using QLoRA and a streaming pipeline ingesting financial news. The repository was archived by its owner and is read-only.
Build multimodal AI services via cloud native technologies · Model Serving · Generative AI · Neural Search · Cloud Native.
Kaito is the Kubernetes AI Toolchain Operator, an operator suite that automates LLM inference, fine-tuning and RAG engine deployment in a Kubernetes cluster. It simplifies the CRD API and provides optimized preset configurations for inference engine scheduling parameters. Workspaces are the basic CRD for managing inference and tuning workloads, and all vLLM-supported models can be run.
Kubeflow Katib is a Kubernetes-native project for automated machine learning (AutoML). It supports hyperparameter tuning, early stopping and neural architecture search, and is agnostic to machine learning frameworks, natively supporting frameworks such as TensorFlow, PyTorch and XGBoost. Training jobs can use any Kubernetes Custom Resources, with out-of-box support for Kubeflow Training Operator, Argo Workflows and Tekton Pipelines. A Python SDK simplifies creating tuning jobs.
Respan is an AI gateway that routes requests to over 1,000 models through one API endpoint, with automatic fallbacks, response caching, and spending limits. It also provides built-in observability for tracing LLM calls, tool calls, and agent steps, plus automated evaluations and security testing for masking PII and red-teaming agents before launch.
Kubernetes custom resource definition for serving ML models on arbitrary frameworks.
Kitaru is an open-source, self-hosted tool providing replay-based evaluations for AI agents. It records or imports production runs as sessions and replays them against a changed model, prompt, or code, with tool calls answered from the recording. It is available for Python and TypeScript and comes from the team behind ZenML.
Knowledge3D (K3D) is a sovereign GPU-native reference implementation for the W3C PM-KR specification. It aims to unify web knowledge representation by allowing humans and AI to consume the same procedural knowledge from a single source, addressing fragmentation across fonts, embeddings, metadata, and renderings.
KServe is a standardized distributed generative and predictive AI inference platform for scalable, multi-framework deployment on Kubernetes. It is a Cloud Native Computing Foundation incubating project. The platform supports backends such as vLLM and llm-d for serving LLMs, and multi-framework predictive serving. Standalone installation on standard Kubernetes is described as more lightweight but without canary deployment or request-based autoscaling with scale-to-zero.
Kubeflow is described as the cloud native AI platform, composed of modular open source projects forming a Kubernetes-native stack for data and AI workloads. Its subprojects include Kubeflow Pipelines for building and deploying portable machine learning workflows, Kubeflow Trainer for distributed AI training and LLM fine-tuning, Kubeflow Katib for automated machine learning, Kubeflow Notebooks for interactive development environments, and Kubeflow Hub for indexing models and metadata. It is a Cloud Native Computing Foundation project.
KubeStellar Console is an open-source multi-cluster Kubernetes management dashboard. It allows users to monitor clusters, deploy workloads, manage GPU resources, and troubleshoot with AI-powered missions across all your Kubernetes environments.
Laminar is an open-source observability platform purpose-built for AI agents. It provides OpenTelemetry-native tracing with a one-line SDK setup, plain-English signals that alert in Slack, and an SDK and CLI for running evals. It is written in Rust with 20x trace compression, and can be used via a managed platform or self-hosted with Docker Compose.
FastAPI framework to build production-grade LLM applications.
LanceDB is a developer-friendly open-source embedded retrieval library for multimodal AI. It emphasizes searching more and managing less. The project tagline is 'Search More; Manage Less.' It is available on GitHub.
An archived, read-only repository that provided a way to deploy LangChain apps using Jina and FastAPI, wrapping apps as services on Jina AI Cloud. The README notes the project is no longer maintained and that it could deploy apps on a user's own infrastructure.
LangKit is an open-source toolkit for monitoring large language models (LLMs). It extracts signals from LLM prompts and responses, and offers features such as text quality assessment, relevance metrics, and sentiment analysis to support LLM observability.
LangWatch is a platform for evaluating large language models and testing AI agents. The open-source project is hosted on the GitHub platform under the langwatch organization as the langwatch/langwatch repository.
