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Average Ratings 0 Ratings

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ease
features
design
support

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Write a Review

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.

Description

Laminar is a comprehensive open-source platform designed to facilitate the creation of top-tier LLM products. The quality of your LLM application is heavily dependent on the data you manage. With Laminar, you can efficiently gather, analyze, and leverage this data. By tracing your LLM application, you gain insight into each execution phase while simultaneously gathering critical information. This data can be utilized to enhance evaluations through the use of dynamic few-shot examples and for the purpose of fine-tuning your models. Tracing occurs seamlessly in the background via gRPC, ensuring minimal impact on performance. Currently, both text and image models can be traced, with audio model tracing expected to be available soon. You have the option to implement LLM-as-a-judge or Python script evaluators that operate on each data span received. These evaluators provide labeling for spans, offering a more scalable solution than relying solely on human labeling, which is particularly beneficial for smaller teams. Laminar empowers users to go beyond the constraints of a single prompt, allowing for the creation and hosting of intricate chains that may include various agents or self-reflective LLM pipelines, thus enhancing overall functionality and versatility. This capability opens up new avenues for experimentation and innovation in LLM development.

API Access

Has API Yes 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

APIFuzzer Yes 
Amazon Bedrock Yes 
Arize AI Yes 
CoLab Yes 
Codestral Mamba Yes 
CrewAI Yes 
GitHub Yes 
Haystack Yes 
LangChain Yes 
LlamaIndex Yes 
Mathstral Yes 
Mistral AI Yes 
Mistral NeMo Yes 
Mixtral 8x22B Yes 
Mixtral 8x7B Yes 
OpenAI Yes 
OpenTelemetry Yes 
Python Yes 
Slack Yes 
Vercel Yes 

Integrations

APIFuzzer No 
Amazon Bedrock No 
Arize AI No 
CoLab No 
Codestral Mamba No 
CrewAI No 
GitHub No 
Haystack No 
LangChain No 
LlamaIndex No 
Mathstral No 
Mistral AI No 
Mistral NeMo No 
Mixtral 8x22B No 
Mixtral 8x7B No 
OpenAI No 
OpenTelemetry No 
Python No 
Slack No 
Vercel No 

Pricing Details

Free
Free Trial No 
Free Version Yes 

Pricing Details

$25 per month
Free Trial No 
Free Version Yes 

Deployment

Web-Based Yes 
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) Yes 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
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) Yes 
In Person No 

Vendor Details

Company Name

Arize AI

Country

United States

Website

docs.arize.com/phoenix

Vendor Details

Company Name

Laminar

Country

United States

Website

www.lmnr.ai/

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