Skip to main content

Full stack ML Observability with AryaXAI

Project description

AryaXAI: ML Observability for mission-critical ‘AI’

AryaXAI is a full-stack ML Observability platform that integrates with your MLOPs platform to Explain, Monitor, Audit and Improve your ML models.

AryaXAI has multiple components to address the complex observability required for mission-critical ‘AI’.

  1. ML Explainability: AryaXAI offers diverse explainability options like- Bactrace(Specialized for deep learning models), SHAPE, Decision View, Observations (New way to correlate expert functioning vs model functioning) and Similar Cases (reference as explanations).
  2. ML Monitoring: Monitor your models for drifts, performance & bias. The tool offers diverse options for drift (data/model) like - PSI, KL Divergence, Chi-square test,
  3. Synthetic ‘AI’: Deploy advanced synthetic ‘AI’ techniques like GPT-2 & GANs on your tabular data to generate high-quality synthetic datasets. Test the quality and privacy of these data sets using our Anonymity tests, column tests etc.
  4. ML Risk policies: Define advanced risk policies on your models.
  5. AutoML: AryaXAI also provides fully low-code and no-code options to build ML models on your data. For advanced users, it also provides more options to fine-tune it.

AryaXAI also acts as a common workflow and provides insights acceptable by all stakeholders - Data Science, IT, Risk, Operations and compliance teams, making the rollout and maintenance of AI/ML models seamless and clutter-free.

Quickstart:

Get started with AryaXAI with a few easy steps:

  1. Sign up and log in to your new AryaXAI account.
  2. After logging in, generate an Access Token for your user account.
  3. Set the environment variable XAI_ACCESS_TOKEN with the generated value.

Once you've completed these steps, you're all set! Now, you can easily log in and start using the AryaXAI SDK:

  1. Log in by importing the "xai" object instance from the "arya_xai" package.
  2. Call the "login" method. This method automatically takes the access token value from the "XAI_ACCESS_TOKEN" environment variable and stores the JWT in the object instance. This means that all your future SDK operations will be authorized automatically, making it simple and hassle-free!
from aryaxai import xai as aryaxai

## login() function authenticates user using token that can be generated in app.aryaxai.com/sdk


aryaxai.login()


Enter your Arya XAI Access Token: ··········
Authenticated successfully.

Cookbook:

In this section, you can review the examples of implementation of AryaXAI-SDK.

  1. Full features overview of AryaXAI
  2. Using AryaXAI in Loan Underwriting (Coming Soon)

Contribution guidelines:

At AryaXAI, we're passionate about open source and value community contributions! Explore our contribution guide for insights into the development workflow and AryaXAI library internals. For bug reports or feature requests, head to GitHub Issues or reach out to us at support@aryaxai.com.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

aryaxai-0.0.156.tar.gz (81.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

aryaxai-0.0.156-py3-none-any.whl (89.8 kB view details)

Uploaded Python 3

File details

Details for the file aryaxai-0.0.156.tar.gz.

File metadata

  • Download URL: aryaxai-0.0.156.tar.gz
  • Upload date:
  • Size: 81.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for aryaxai-0.0.156.tar.gz
Algorithm Hash digest
SHA256 a0614fda60b0c40dbf03b99b75e3486215cff04cd2a966a7134dcb5a52d6eccb
MD5 b36b90a954b5159de4ec08f6c25d3c5c
BLAKE2b-256 36b9020be32394b841f7c2d90bd11fb107ead2605786caf3d9f1ef8769ef0eda

See more details on using hashes here.

File details

Details for the file aryaxai-0.0.156-py3-none-any.whl.

File metadata

  • Download URL: aryaxai-0.0.156-py3-none-any.whl
  • Upload date:
  • Size: 89.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.12.3

File hashes

Hashes for aryaxai-0.0.156-py3-none-any.whl
Algorithm Hash digest
SHA256 2b768efd47682346080c1ecdcfb343fe7c4a2aedb7f5aa80b41f8526ab42a538
MD5 84da88dae88525ca55e10bb17afa8746
BLAKE2b-256 6c28df69ee1904bb7bf9b8292af82091a344fb31d963e6d0ff1e39abf2833bd0

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page