Skip to main content

Software Development Kit to interact with Globant Enterprise AI.

Project description

PyGEAI - SDK for Globant Enterprise AI

PyGEAI is a Software Development Kit (SDK) for interacting with Globant Enterprise AI. It comprises libraries, tools, code samples, and documentation to simplify your experience with the platform.

Repository

Find the PyGEAI source code and documentation in the following GitHub repository:

GitHub repository

Compatibility

This package is compatible with the Globant Enterprise AI release from June 2025.

Configuration

Before using the SDK, you need to define GEAI_API_KEY ($SAIA_APITOKEN) and GEAI_API_BASE_URL ($BASE_URL). You can achieve this in three ways:

  • Environment variables: Set GEAI_API_KEY and GEAI_API_BASE_URL as environment variables in your operating system.
  • Credentials file: Create a file named credentials in the .geai directory within your user home directory ($USER_HOME/.geai/credentials) and define GEAI_API_KEY and GEAI_API_BASE_URL within this file.
  • Client instantiation: Specify the api_key and base_url parameters directly when creating an instance of a client class.

Note: If you plan to use the Evaluation Module, you must also define GEAI_API_EVAL_URL

Modules

The SDK consists of several modules, all accessible through a meta-package:

  • pygeai: This meta-package encapsulates all components of the SDK.
  • pygeai-cli: This package provides a command-line tool for interacting with the SDK.
  • pygeai-chat: This package offers facilities to chat with assistants/agents created in Globant Enterprise AI.
  • pygeai-dbg: This package includes a debugger to troubleshoot potential SDK issues and gain detailed insights into its operations.
  • pygeai-core: This package handles interactions with the fundamental components of Globant Enterprise AI, including users, groups, permissions, API keys, organizations, and Projects.
  • pygeai-admin: This package enables interactions with the Globant Enterprise AI instance.
  • pygeai-lab: This package facilitates interactions with AI LAB.
  • pygeai-evaluation: This package provides functionality from the evaluation module.
  • pygeai-gam: This package allows interaction with [GAM] (https://wiki.genexus.com/commwiki/wiki?24746,Table+of+contents%3AGeneXus+Access+Manager+%28GAM%29,).
  • pygeai-assistant: This package handles interactions with various Assistants, including Data Analyst Assistants, RAG Assistants, Chat with Data Assistants, Chat with API Assistants, and Chat Assistants.
  • pygeai-organization: This package facilitates interactions with Organizations in Globant Enterprise AI.
  • pygeai-flows: This package enables interactions with Flows [in development].

Usage

Install PyGEAI

Use pip to install the package from PyPI:

(venv) ~$ pip install pygeai

To install pre-release versions, you can run:

(venv) ~$ pip install --pre pygeai

Verify installation

To check the installed PyGEAI version, run:

(venv) ~$ geai v

View help

To access the general help menu:

(venv) ~$ geai h

To view help for a specific command:

(venv) ~$ geai <command> h

Debugger

The pygeai-dbg package provides a command-line debugger (geai-dbg) for troubleshooting and inspecting the geai CLI. It pauses execution at breakpoints, allowing you to inspect variables, execute Python code, and control program flow interactively.

To debug a geai command, replace geai with geai-dbg. For example:

(venv) ~$ geai-dbg ail lrs

This pauses at the main function in pygeai.cli.geai, displaying an interactive prompt (geai-dbg). You can then use commands like continue (resume), run (run without pauses), quit (exit), or help (list commands).

Man Pages Documentation

The package includes Unix manual pages (man pages) for detailed command-line documentation.

To install man pages locally:

geai-install-man

To install man pages system-wide:

sudo geai-install-man --system

To access the man pages:

man geai

Setting up Man Pages Access

If you're using a virtual environment, you'll need to configure your system to find the man pages. Add the following to your shell configuration file (.bashrc, .zshrc, etc.):

# For macOS
if [ -n "$VIRTUAL_ENV" ]; then
    export MANPATH="$VIRTUAL_ENV/share/man:$MANPATH"
fi

# For Linux
if [ -n "$VIRTUAL_ENV" ]; then
    export MANPATH="$VIRTUAL_ENV/man:$MANPATH"
fi

After adding this configuration:

  1. Reload your shell configuration: source ~/.bashrc or source ~/.zshrc
  2. The man pages will be available when your virtual environment is active

Bugs and suggestions

To report any bug, request features or make any suggestions, the following email is available:

geai-sdk@globant.com

Authors

Copyright 2025, Globant. All rights reserved

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

pygeai-0.2.7b37.tar.gz (495.1 kB view details)

Uploaded Source

Built Distribution

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

pygeai-0.2.7b37-py3-none-any.whl (662.3 kB view details)

Uploaded Python 3

File details

Details for the file pygeai-0.2.7b37.tar.gz.

File metadata

  • Download URL: pygeai-0.2.7b37.tar.gz
  • Upload date:
  • Size: 495.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for pygeai-0.2.7b37.tar.gz
Algorithm Hash digest
SHA256 5517e41cfcf59c7b956dc374097e9beb2d71e101cf3cec38e2796b37d3d1db6d
MD5 7a7bac8eaad6083905551e3f1922cd41
BLAKE2b-256 ae07e368ec6bd4d6f60020f4b2af70a2620fe932e50e7241b8957af98178e1e5

See more details on using hashes here.

File details

Details for the file pygeai-0.2.7b37-py3-none-any.whl.

File metadata

  • Download URL: pygeai-0.2.7b37-py3-none-any.whl
  • Upload date:
  • Size: 662.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.3

File hashes

Hashes for pygeai-0.2.7b37-py3-none-any.whl
Algorithm Hash digest
SHA256 dbea3bea7d2b1c846ba42ae0d235975ec175d2f6a5eaaa699438923f5535fe51
MD5 db0e72492c8242591f3f5ced855890fa
BLAKE2b-256 a8644feca22afbcdee40c4c9ac3334f98a2914a7590aecfcb8fd2fceb590a5ac

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page