gllm-datastore-binary 0.5.59

A library containing data store components for Gen AI applications.

GLLM Datastore

Description

A library for managing data storage and retrieval operations in Generative AI applications.

---

Installation

Prerequisites

Mandatory:

1. Python 3.11+ — Install here

2. pip — Install here

3. uv — Install here

4. gcloud CLI (for authentication) — Install here, then log in using:

   gcloud auth login
   

---

Install from Artifact Registry

This 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-datastore

---

Local Development Setup

Prerequisites

1. Python 3.11+ — Install here

2. pip — Install here

3. uv — Install here

4. gcloud CLI — Install here, then log in using:

   gcloud auth login
   

5. Git — Install here

6. Access to the GDP Labs SDK GitHub repository

---

1. Clone Repository

git clone [e-mail]:GDP-ADMIN/gl-sdk.git
cd gl-sdk/libs/gllm-datastore

---

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.