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A library for orchestrating the processing of document. Typically in a Gen AI applications (but not limited to just Gen AI).

Project description

GLLM Docproc

dummy commit

Description

A library for orchestrating the processing of document. Typically in a Gen AI applications (but not limited to just Gen AI).


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.

  1. Export token
export GCLOUD_ACCESS_TOKEN="$(gcloud auth print-access-token)"
  1. Configure the index in your pyproject.tom;
[[tool.uv.index]]
name = "gen-ai-internal"
url = "https://oauth2accesstoken:${GCLOUD_ACCESS_TOKEN}@glsdk.gdplabs.id/gen-ai-internal/simple/"
  1. Add the dependency
uv add gllm-docproc

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

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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