#SHIVA AI
Shiva AI is an OpenAI-powered Python module created to help developers easily integrate artificial intelligence into their Python projects. AI2PY provides a comprehensive set of tools for creating AI-generated text, images, and image variations. An OpenAI API Key is required.
The module contains functions to create text, create text commands, create images, and create image variations. The init function initializes the class with an api_key. The create_text function takes in data and a word count and uses the OpenAI API to generate text based on the data. The create_text_command function takes in a command, data, and a word count and uses the OpenAI API to generate text based on the command and data. The create_image function takes in prompt text and an image size and uses the OpenAI API to generate an image based on the prompt text. The create_image_variation function takes in data and an image size and uses the OpenAI API to generate an image variation based on the data. The options class contains two functions: display_imagesizes and image_resize. The display_imagesizes function prints out the required image sizes for the OpenAI API. The image_resize function takes in an image and a size and resizes the image to the specified size.
In addition, Shiva AI also provides a set of pre-trained models that can be used for various tasks such as natural language processing, computer vision, and more. These models can be used to quickly build AI applications without having to train your own models from scratch.
If you have any questions, feel free to ask them in the GitHub Discussion tab. If you need help with a project or want to show off a project made with Shiva AI, you can also do so in the Discussion tab. If you find a bug, please report it in the GitHub Issues tab and provide the complete error message and a minimal example code that reproduces the error. If you have ideas for improvements or requests for new functions, you can also report these in the GitHub Issues tab, but please check for previous requests to prevent duplicates.
Metadata
Release files for shiva-ai 0.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | Provenance | |
|---|---|---|---|---|
| shiva-ai-0.0.1.tar.gz | 3.1 kB | Without provenance | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| shiva_ai-0.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 6.3 kB
Release files / shiva-ai-0.0.1.tar.gz
| Download URL | shiva-ai-0.0.1.tar.gz |
|---|---|
| Size | 3.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
fb187f1a106883bb1738abb3f020012d8da6a4a915ca4162a32dae722c41351b
|
|
BLAKE2b-256 checksum How to use checksums |
50811c95defb92bc2deedda84c9ff8bca7132457abb62f02efd8986e6f73c97e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
|
Release files / shiva_ai-0.0.1-py3-none-any.whl
| Download URL | shiva_ai-0.0.1-py3-none-any.whl |
|---|---|
| Size | 3.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
783113bd9f80cd34ee8985b3c4fff2d5cdf30f094f847f24dd5e363ad9a252d8
|
|
BLAKE2b-256 checksum How to use checksums |
59bf741625c6826ee73beebc5b3ade7180e675573f4f5a179e42ba7be5f2095e
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/4.0.2 CPython/3.11.3
|
Security for shiva-ai 0.0.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.