Prompt flow

Prompt flow

Microsoft
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About

MLflow is an open source platform to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry. MLflow currently offers four components. Record and query experiments: code, data, config, and results. Package data science code in a format to reproduce runs on any platform. Deploy machine learning models in diverse serving environments. Store, annotate, discover, and manage models in a central repository. The MLflow Tracking component is an API and UI for logging parameters, code versions, metrics, and output files when running your machine learning code and for later visualizing the results. MLflow Tracking lets you log and query experiments using Python, REST, R API, and Java API APIs. An MLflow Project is a format for packaging data science code in a reusable and reproducible way, based primarily on conventions. In addition, the Projects component includes an API and command-line tools for running projects.

About

Prompt Flow is a suite of development tools designed to streamline the end-to-end development cycle of LLM-based AI applications, from ideation, prototyping, testing, and evaluation to production deployment and monitoring. It makes prompt engineering much easier and enables you to build LLM apps with production quality. With Prompt Flow, you can create flows that link LLMs, prompts, Python code, and other tools together in an executable workflow. It allows for debugging and iteration of flows, especially tracing interactions with LLMs with ease. You can evaluate your flows, calculate quality and performance metrics with larger datasets, and integrate the testing and evaluation into your CI/CD system to ensure quality. Deployment of flows to the serving platform of your choice or integration into your app’s code base is made easy. Additionally, collaboration with your team is facilitated by leveraging the cloud version of Prompt Flow in Azure AI.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies looking for an open source platform solution for the machine learning lifecycle

Audience

AI application developers searching for a tool to streamline the development and deployment of LLM-based applications

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

MLflow
Founded: 2018
United States
mlflow.org

Company Information

Microsoft
Founded: 1975
United States
microsoft.github.io/promptflow/

Alternatives

Union Cloud

Union Cloud

Union.ai

Alternatives

Vertex AI

Vertex AI

Google
Vellum AI

Vellum AI

Vellum

Categories

Categories

Integrations

Azure Data Science Virtual Machines
Azure Machine Learning
Comet LLM
Cranium
Databricks Data Intelligence Platform
Determined AI
HoneyHive
Kubernetes
LiteLLM
Ludwig
Microsoft Azure
Modulos AI Governance Platform
Ragas
Superwise
TensorFlow
TrueFoundry
Vectice
ZenML
neptune.ai

Integrations

Azure Data Science Virtual Machines
Azure Machine Learning
Comet LLM
Cranium
Databricks Data Intelligence Platform
Determined AI
HoneyHive
Kubernetes
LiteLLM
Ludwig
Microsoft Azure
Modulos AI Governance Platform
Ragas
Superwise
TensorFlow
TrueFoundry
Vectice
ZenML
neptune.ai
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