Skip to main content

Afnio Python library and Tellurio Studio CLI tool

Project description

Afnio: Making AI System Optimization Easy for Everyone

Afnio is a framework for automatic prompt and hyperparameter optimization, particularly designed for complex AI systems where Language Models (LMs) are employed multiple times in workflows, such as in LM pipelines and agent-driven architectures. Effortlessly build and optimize AI systems for classification, information retrieval, question-answering, etc.

  • Accelerated AI System Development: Ship complex AI systems faster thanks to high-level UX and easy-to-debug runtime.
  • State-of-the-Art Performance: Leverage built-in optimizers to automatically refine prompts and tune model parameters for any LM task, ensuring optimal performance.
  • LM Agnostic: Decouple prompts and parameters from application logic, reducing LM model selection to a single hyperparameter in Afnio’s optimizers. Seamlessly switch between models without any additional rework.
  • Minimal and Flexible: Pure Python with no API calls or dependencies, ensuring seamless integration with any tools or libraries.
  • Progressive Disclosure of Complexity: Leverage diverse UX workflows, from high-level abstractions to fine-grained control, designed to suit various user profiles. Start simple and customize as needed, without ever feeling like you’re falling off a complexity cliff.
  • Define-by-Run Scheme: Your compound AI system is dynamically defined at runtime through forward computation, allowing for seamless handling of complex control flows like conditionals and loops, common in agent-based AI applications. With no need for precompilation, Afnio adapts on the fly to your evolving system.

Contributing Guidelines

:computer: Would love to contribute? Please follows our contribution guidelines.

Project details


Download files

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

Source Distribution

afnio-0.2.3.tar.gz (136.0 kB view details)

Uploaded Source

Built Distribution

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

afnio-0.2.3-py3-none-any.whl (172.9 kB view details)

Uploaded Python 3

File details

Details for the file afnio-0.2.3.tar.gz.

File metadata

  • Download URL: afnio-0.2.3.tar.gz
  • Upload date:
  • Size: 136.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for afnio-0.2.3.tar.gz
Algorithm Hash digest
SHA256 55b65aaffa5905d73b1089d6d2a9e006cb03a597de873ca295fd663989b244ae
MD5 091cbf68c5ce4e0bd6c5a6e9550e35c7
BLAKE2b-256 18f2dc7839543ab321810baeb8dd76b5be1fc2584f331cebde7c084c6a3d7a37

See more details on using hashes here.

File details

Details for the file afnio-0.2.3-py3-none-any.whl.

File metadata

  • Download URL: afnio-0.2.3-py3-none-any.whl
  • Upload date:
  • Size: 172.9 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.9.23

File hashes

Hashes for afnio-0.2.3-py3-none-any.whl
Algorithm Hash digest
SHA256 da32777f211e7bb83313e798832707c468809be31a69f996f7da7edc7a69d6b4
MD5 bd80193a99ac192ebc50c303ace7efd1
BLAKE2b-256 c85a0d451367ab651bf00728d4929657453f3296a49abdf9066c334e5f6eef4b

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