Skip to main content

A library containing components related to model inferences in Gen AI applications.

Project description

GLLM Inference

Description

A library containing components related to model inferences in Gen AI applications.

Installation

Prerequisites

1. Installation from Artifact Registry

Choose one of the following methods to install the package:

Using pip

pip install gllm-inference-binary

Using Poetry

poetry add gllm-inference-binary

2. Development Installation (Git)

For development purposes, you can install directly from the Git repository:

poetry add "git+ssh://git@github.com/GDP-ADMIN/gen-ai-internal.git#subdirectory=libs/gllm-inference"

Available extras:

  • anthropic: Install Anthropic models dependencies
  • google-genai: Install Google Generative AI models dependencies
  • google-vertexai: Install Google Vertex AI models dependencies
  • huggingface: Install HuggingFace models dependencies
  • openai: Install OpenAI models dependencies
  • twelvelabs: Install TwelveLabs models dependencies

Managing Dependencies

  1. Go to root folder of gllm-inference module, e.g. cd libs/gllm-inference.
  2. Run poetry shell to create a virtual environment.
  3. Run poetry lock to create a lock file if you haven't done it yet.
  4. Run poetry install to install the gllm-inference requirements for the first time.
  5. Run poetry update if you update any dependency module version at pyproject.toml.

Contributing

Please refer to this Python Style Guide to get information about code style, documentation standard, and SCA that you need to use when contributing to this project

  1. Activate pre-commit hooks using pre-commit install
  2. Run poetry shell to create a virtual environment.
  3. Run poetry lock to create a lock file if you haven't done it yet.
  4. Run poetry install to install the gllm-inference requirements for the first time.
  5. Run which python to get the path to be referenced at Visual Studio Code interpreter path (Ctrl+Shift+P or Cmd+Shift+P)
  6. Try running the unit test to see if it's working:
poetry run pytest -s tests/unit_tests/

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 Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

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

gllm_inference_binary-0.2.44-cp312-cp312-manylinux_2_31_x86_64.whl (1.2 MB view details)

Uploaded CPython 3.12manylinux: glibc 2.31+ x86-64

gllm_inference_binary-0.2.44-cp311-cp311-manylinux_2_31_x86_64.whl (1.1 MB view details)

Uploaded CPython 3.11manylinux: glibc 2.31+ x86-64

File details

Details for the file gllm_inference_binary-0.2.44-cp312-cp312-manylinux_2_31_x86_64.whl.

File metadata

File hashes

Hashes for gllm_inference_binary-0.2.44-cp312-cp312-manylinux_2_31_x86_64.whl
Algorithm Hash digest
SHA256 f788d98d19ad84ec91636f3a4bda1d0fb39f3b60863e4ffab7dc55bef1fd485a
MD5 b810781d6e225d174a39d3e8a1c1b4e0
BLAKE2b-256 f7607ca04caf832ff8bcaa57967f050017801b9100fbbcbb17165d8d9bd5d365

See more details on using hashes here.

File details

Details for the file gllm_inference_binary-0.2.44-cp311-cp311-manylinux_2_31_x86_64.whl.

File metadata

File hashes

Hashes for gllm_inference_binary-0.2.44-cp311-cp311-manylinux_2_31_x86_64.whl
Algorithm Hash digest
SHA256 81b2b95a47ecd6b3d5de5b1bb1b6ba175b95efc55afe321c9b998cb1d008d0fb
MD5 e08c77af09c6b94153e1960f0e482aa3
BLAKE2b-256 92f663228b70af5b9cfc1d7957870b59f270b58ce80faa7c3e33f7c4a31472c8

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