3 个仓库
Infrastructure for exposing AI orchestration workflows as accessible web services.
Distinct from AI Services: Focuses on serving the orchestration workflow itself rather than individual model inference or general AI services
Explore 3 awesome GitHub repositories matching artificial intelligence & ml · AI Workflow Serving. Refine with filters or upvote what's useful.
JARVIS is a system for large language model task orchestration, deployment management, and automation benchmarking. It utilizes a task orchestrator to decompose complex requests into actionable steps and coordinates various expert models to synthesize final responses. The project includes an AI model deployment manager to handle the local deployment of expert models across different hardware scales. It further provides an AI workflow API consisting of web endpoints used to trigger automated task workflows and retrieve results from model selection stages. The framework incorporates an automat
Creates web endpoints to trigger AI workflows and retrieve intermediate results from model selection stages.
Mmlspark is a distributed framework for executing machine learning models, data transformations, and AI service integrations across Apache Spark clusters. It functions as a distributed machine learning library and pipeline orchestrator, allowing users to integrate pre-trained cognitive services and custom models into large-scale batch and streaming workflows. The project is distinguished by its ability to incorporate external AI services and web APIs directly into big data pipelines for text and vision analysis. It provides a scalable model training framework that coordinates gradient boostin
Exposes distributed computations as low-latency web services for real-time inference.
Olares is a comprehensive suite of self-hosted identity, storage, AI, and orchestration services designed for private infrastructure management. It functions as a Kubernetes home server orchestrator, enabling the deployment of containerized applications, AI models, and GPU resources on local hardware to replace third-party cloud services. The platform distinguishes itself through a combination of self-hosted AI infrastructure for running large language models and image generators, alongside a decentralized identity manager that uses cryptographic keys and OIDC for trustless authentication. It
Hosts AI models to coordinate complex agent tasks and provide retrieval-augmented generation as a web service.