GLLM Pipeline

Description

A library containing components related to Gen AI applications pipeline orchestration, including routers, steps, and utility functions for building and managing AI application workflows.

Installation

Prerequisites

Mandatory:

Python 3.11+ — Install here
pip — Install here
uv — Install here

Extras (required only for Artifact Registry installations):

gcloud CLI (for authentication) — Install here, then log in using:
```
gcloud auth login
```

Option 1: Install from Artifact Registry

This option requires authentication via the gcloud CLI.

uv pip install \
  --extra-index-url "https://oauth2accesstoken:$(gcloud auth print-access-token)@glsdk.gdplabs.id/gen-ai-internal/simple/" \
  gllm-pipeline

Option 2: Install from PyPI

This option requires no authentication. However, it installs the binary wheel version of the package, which is fully usable but does not include source code.

uv pip install gllm-pipeline-binary

Local Development Setup

Prerequisites

Python 3.11+ — Install here
pip — Install here
uv — Install here
gcloud CLI — Install here, then log in using:
```
gcloud auth login
```
Git — Install here
Access to the GDP Labs SDK GitHub repository

1. Clone Repository

git clone git@github.com:GDP-ADMIN/gl-sdk.git
cd gl-sdk/libs/gllm-pipeline

2. Setup Authentication

Set the following environment variables to authenticate with internal package indexes:

export UV_INDEX_GEN_AI_INTERNAL_USERNAME=oauth2accesstoken
export UV_INDEX_GEN_AI_INTERNAL_PASSWORD="$(gcloud auth print-access-token)"
export UV_INDEX_GEN_AI_USERNAME=oauth2accesstoken
export UV_INDEX_GEN_AI_PASSWORD="$(gcloud auth print-access-token)"

3. Quick Setup

Run:

make setup

4. Activate Virtual Environment

source .venv/bin/activate

Local Development Utilities

The following Makefile commands are available for quick operations:

Install uv

make install-uv

Install Pre-Commit

make install-pre-commit

Install Dependencies

make install

Update Dependencies

make update

Run Tests

make test

Contributing

Please refer to the Python Style Guide for information about code style, documentation standards, and SCA requirements.

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