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Average Ratings 0 Ratings
Description
Apache Ossie serves as an open specification and conversion toolkit designed for the seamless exchange of semantic metadata among analytics, business intelligence, and AI systems. Utilizing a YAML-based format, it articulates semantic models, datasets, fields, metrics, dimensions, relationships, and SQL expressions in a manner that is easily transferable. This enables data and analytics engineers to create, translate, and repurpose these definitions across interconnected platforms, thus ensuring a unified business context for reporting and AI-driven analysis. As a collaborative initiative, the project operates under the Apache License 2.0, and the availability of conversions is contingent upon the specific implementation by each platform. Additionally, this initiative fosters collaboration and innovation within the open-source community, encouraging contributions that enhance the toolkit's capabilities.
Description
Phoenix serves as a comprehensive open-source observability toolkit tailored for experimentation, evaluation, and troubleshooting purposes. It empowers AI engineers and data scientists to swiftly visualize their datasets, assess performance metrics, identify problems, and export relevant data for enhancements. Developed by Arize AI, the creators of a leading AI observability platform, alongside a dedicated group of core contributors, Phoenix is compatible with OpenTelemetry and OpenInference instrumentation standards. The primary package is known as arize-phoenix, and several auxiliary packages cater to specialized applications. Furthermore, our semantic layer enhances LLM telemetry within OpenTelemetry, facilitating the automatic instrumentation of widely-used packages. This versatile library supports tracing for AI applications, allowing for both manual instrumentation and seamless integrations with tools like LlamaIndex, Langchain, and OpenAI. By employing LLM tracing, Phoenix meticulously logs the routes taken by requests as they navigate through various stages or components of an LLM application, thus providing a clearer understanding of system performance and potential bottlenecks. Ultimately, Phoenix aims to streamline the development process, enabling users to maximize the efficiency and reliability of their AI solutions.
API Access
Has API
No
API Access
Has API
Yes
Screenshots View All
No images available
Integrations
Databricks
Yes
Amazon Bedrock
No
CoLab
No
CrewAI
No
Holistics
Yes
JavaScript
No
JupyterLab
No
Ministral 3B
No
Ministral 8B
No
Mistral Large
No
Integrations
Databricks
Yes
Amazon Bedrock
Yes
CoLab
Yes
CrewAI
Yes
Holistics
No
JavaScript
Yes
JupyterLab
Yes
Ministral 3B
Yes
Ministral 8B
Yes
Mistral Large
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
Yes
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
Yes
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
Apache Software Foundation
Founded
1999
Country
United States
Website
ossie.apache.org
Vendor Details
Company Name
Arize AI
Country
United States
Website
docs.arize.com/phoenix
Product Features
Product Features
Alternatives
No Alternatives