Skip to main content

ai_environment

Configurator for a Python AI environment for SupportVectors AI training labs

  1. git clone the repo to a folder of your choice

  2. For a new uv project that you want to create, follow the below steps:

     uv init <my_project> --python=3.12
     cd <my_project>
     cp <my_path>/ai_environment/ensure_config.sh ./
     cp <my_path>/ai_environment/docs.tgz ./
     chmod +x ./ensure_config.sh
     ./ensure_config.sh ## Enter the appropriate path, project, description, url when prompted during the run of ensure_config.sh
    
  3. Your project setup for <my_project> is now complete.

  4. Note that these steps are needed only when you create a completely new UV based python project using the best practices recommended by SupportVectors. If you are downloading an existing code repo uploaded by the SupportVectors team, you would just have to download the code repo and follow the steps as given in the project guide within the repo.

Metadata

Release files for golden-retrievers 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for golden-retrievers 0.1.0
File Size Uploaded
golden_retrievers-0.1.0.tar.gz 2.4 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for golden-retrievers 0.1.0
File Interpreter ABI Platform
golden_retrievers-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 4.2 kB

Release files / golden_retrievers-0.1.0.tar.gz

Download URL golden_retrievers-0.1.0.tar.gz
Size 2.4 kB
Tags Source
SHA-256 checksum
How to use checksums
116d78a879b67e5fc645c4a2926f7aa73ddea8debf8b85fe679ed32eca6972d7
BLAKE2b-256 checksum
How to use checksums
842271dbc387b4de1b1badd40041950c86e82bace62995814afd20c9ae4a4c69
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.7.10

Release files / golden_retrievers-0.1.0-py3-none-any.whl

Download URL golden_retrievers-0.1.0-py3-none-any.whl
Size 1.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
4047a4757783dd2f5a8a55feec8be717b31750c5ad748b5d8f92abb4196311ba
BLAKE2b-256 checksum
How to use checksums
0d55d2159f59ecb54e62e679b52e31928f94a1243637569ecc67e3a190f8d03e
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via uv/0.7.10

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page