AI Engineering Platform

PyPI code checks unit tests docs codecov GitHub License

Infrastructure and tooling for AI Engineering bootcamps, providing secure, isolated development environments and automated participant onboarding.

Overview

This platform consists of the following components:

  1. Coder Deployment - Containerized development environments supported by Coder
  2. Participant Onboarding System - Secure, automated participant onboarding

1. Coder Deployment for GCP

The coder folder contains all resources needed to deploy a Coder instance on Google Cloud Platform (GCP), along with reusable workspace templates and Docker images for the workspace environment.

Structure

  • deploy/ - Terraform scripts and startup automation for provisioning the Coder server on a GCP VM
  • docker/ - Dockerfiles and guides for building custom images used by Coder workspace templates
  • templates/ - Coder workspace templates for reproducible, containerized development environments on GCP

Usage

  1. Provision Coder on GCP - Follow the steps in coder/deploy/README.md
  2. Build and Push Docker Images - See coder/docker/README.md
  3. Push Workspace Templates - See coder/templates/README.md

2. Participant Onboarding System

Automated API key distribution for bootcamp participants using GCP Secret Manager and workload identity.

  • Secrets never written to disk — exported into the shell via eval "$(onboard ...)"
  • Workspace VMs authenticate directly to Secret Manager via workload identity (no Firebase, no token service)
  • Per-participant JSON secrets named {bootcamp-name}-env-{github-handle}
  • Firestore tracks participant records and onboarded status

Architecture

Admin Phase
  1. Setup participants/teams in Firestore
  2. Generate API keys (Gemini, Langfuse, etc.)
  3. onboard admin setup-secrets  →  creates per-participant Secret Manager secrets
  4. Grant workspace SA roles/secretmanager.secretAccessor
  5. Add users to GitHub org

Participant Phase
  1. eval "$(onboard --bootcamp-name <name>)"  in Coder workspace
  2. Fetches env vars from Secret Manager via workload identity
  3. Runs integration tests (env vars injected, nothing written to disk)
  4. Marks participant as onboarded in Firestore

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Latest release

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for vector-institute from gravatar.com vector-institute

Credits

Author: Vector AI Engineering

License expression

Apache-2.0
View SPDX License List

Requires

Python >=3.12

Report project as malware

Download files

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

Source Distribution

aieng_platform_onboard-0.7.4.tar.gz (38.4 kB view details)

Uploaded Source

Built Distribution

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

aieng_platform_onboard-0.7.4-py3-none-any.whl (48.5 kB view details)

Uploaded Python 3

File details

Details for the file aieng_platform_onboard-0.7.4.tar.gz.

File metadata

  • Download URL: aieng_platform_onboard-0.7.4.tar.gz
  • Upload date:
  • Size: 38.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/7.0.0 CPython/3.13.14

File hashes

Hashes for aieng_platform_onboard-0.7.4.tar.gz
Algorithm Hash digest
SHA256 0ed298144e6968573654ae317d4f77613c014169d0ee9115e867a8a7be767834
MD5 3dd9f2716b81c08752fc24713f1516a3
BLAKE2b-256 54949e27ccc9d8f801013c777455dc04261601e52b44ba7ee0765fa8f3253c7d

See more details on using hashes here.

Provenance

The following attestation bundles were made for aieng_platform_onboard-0.7.4.tar.gz:

Publisher: publish.yml on VectorInstitute/aieng-platform

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file aieng_platform_onboard-0.7.4-py3-none-any.whl.

File metadata

File hashes

Hashes for aieng_platform_onboard-0.7.4-py3-none-any.whl
Algorithm Hash digest
SHA256 6adaed0616dc1e684a9ef82f380736c51577a5686fc000263ef9625ab49a5177
MD5 2b1eff41aaab00dd00e29645fa9b5a45
BLAKE2b-256 60a1e25cd68a482cd08a112af218f3906820e03e3c074bf454bf4d11032b8154

See more details on using hashes here.

Provenance

The following attestation bundles were made for aieng_platform_onboard-0.7.4-py3-none-any.whl:

Publisher: publish.yml on VectorInstitute/aieng-platform

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Release history Release notifications | RSS feed

This release

0.7.4 This release

2 files

0.7.3

2 files

0.7.2

2 files

0.7.1

2 files

0.7.0

2 files

0.6.5

2 files

0.6.4

2 files

0.6.3

2 files

0.6.2

2 files

0.6.1

2 files

0.6.0

2 files

0.5.4

2 files

0.5.3

2 files

0.5.2

2 files

0.5.1

2 files

0.5.0

2 files

0.4.0

2 files

0.3.6

2 files

0.3.5

2 files

0.3.4

2 files

0.3.3

2 files

0.3.2

2 files

0.3.1

2 files

0.3.0

2 files

0.2.0

2 files

0.1.0

2 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