phoenix
flyte
phoenix | flyte | |
---|---|---|
4 | 31 | |
2,730 | 4,853 | |
13.2% | 3.8% | |
9.9 | 9.8 | |
7 days ago | 4 days ago | |
Jupyter Notebook | Go | |
GNU General Public License v3.0 or later | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
phoenix
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First 15 Open Source Advent projects
11. Phoenix by Arize AI | Github | tutorial
- Show HN: Phoenix OSS β Applying LLM Spans, Traces, and Evals for AI Insights
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I'll build your AI app for you free of charge(Yes, there's a catch).
Happy to explain more. This package has a great umap visualization that helps explain the context, but building it off clusters established in batch is less useful than an event driven response.
- ML Observability in a Notebook
flyte
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First 15 Open Source Advent projects
9. Flyte by Union AI | Github | tutorial
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Flyte 1.10: Self-hosted solution to build production-grade data and ML pipelines; now ships with monorepo, new agents and sensors, eager workflows and more π (4.1k stars on GitHub)
GitHub: https://github.com/flyteorg/flyte
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Flyte: Open-source orchestrator for building production-grade ML pipelines
This is actually but a link to Flyte, this is a link to the documentation for the Flyte integration in LangChain, a separate product.
Flyte's homepage is https://flyte.org/
- Flyte: Advanced workflow orchestration alternative to Apache Airflow
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Orchestration: Thoughts on Dagster, Airflow and Prefect?
Anyone tried Flyte?
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Flyte 1.6.0: Self-hosted solution to build production-grade data and ML pipelines; now ships with PyTorch elastic training, image specification without dockerfile, enhanced task execution insights and more π (3.4k stars on GitHub)
Website: https://flyte.org/
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Flyte(v1.5.0) - Self-hosted solution to build production-grade data and ML pipelines; now ships with streaming support, pod templates, partial tasks and more π (3.2k stars on GitHub)
Flyte is an open source orchestration tool for managing the workflow of machine learning and AI projects. It runs on top of Kubernetes.
- Flyte: Open-Source Kubernetes-Native ML Orchestrator Implemented in Go
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What is MLOps and how to get started? | MLOps series | Deploying ML in production
I have a question though, what is your opinion on https://flyte.org. My pipeline uses this and itβll be interesting to get your perspectives on itβs capabilities.
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Github alternative for ML?
Have you looked at flyte.org. It aims to bring "versioning", "compute" and "reproducibility" together in one package.
What are some alternatives?
dev-gpt - Your Virtual Development Team
metaflow - :rocket: Build and manage real-life ML, AI, and data science projects with ease!
OpenLLM - Run any open-source LLMs, such as Llama 2, Mistral, as OpenAI compatible API endpoint in the cloud.
argo - Workflow Engine for Kubernetes
MetaGPT - π The Multi-Agent Framework: First AI Software Company, Towards Natural Language Programming
temporal - Temporal service
EVAL - EVAL(Elastic Versatile Agent with Langchain) will execute all your requests. Just like an eval method!
kubeflow - Machine Learning Toolkit for Kubernetes
dvclive - π Log and track ML metrics, parameters, models with Git and/or DVC
Celery-Kubernetes-Operator - An operator to manage celery clusters on Kubernetes (Work in Progress)
aider - aider is AI pair programming in your terminal
Kedro - Kedro is a toolbox for production-ready data science. It uses software engineering best practices to help you create data engineering and data science pipelines that are reproducible, maintainable, and modular.