semvec/pypi-packages huggingface dataset:
queky 0.1.2.2
Si Un Problema Puede Solucionarse, Entonces No Vale La Pena Preocuparse Por El.
License: MIT

# queky

### Instalestion
`pip install queky`

### Usage:
1. Get your gemini api key from [here](https://aistudio.google.com/app/apikey).
2. Open terminal and run the command `pip install queky`
3. Type `qk` and press enter to activate the tool.
4. Paste the gemini api key (only asked for the first time).
5. Now copy your questions and paste them in the terminal window by just pressing the enter key.
7. You should receive your answers.
groqflow 4.3.1
GroqFlow toolchain library
License: MIT
Requires Python: <3.11,>=3.8

# GroqFlow 🚀

GroqFlow™ is the easiest way to get started with Groq's technology. GroqFlow provides an automated workflow for compiling Machine Learning, Artifical Intelligence, and High-Performance Computing workloads into Groq programs and executing those programs on the Groq Language Processing Unit™ (LPU).

---

## System Requirements

To begin, we recommend that your system meets the following software and hardware requirements:

- Ubuntu 22.04 or Rocky 8.4 Linux distribution.
- 32GB RAM (or more) to build models.
- 8 LPUs (especially for larger models) to run models.
- GroqWare Suite™ version >=0.9.2.1 installation*:
  - Groq Developer Tools Package (groq-devtools) for building and compiling models.
  - Groq Runtime Package (groq-runtime) for running compiled models on Groq hardware.

*For information on how to install GroqWare Suite on your system, create an account on our [portal](https://support.groq.com/) and view the [GroqWare Quick Start Guide](https://support.groq.com/#/downloads/view/groqware-qsg) for installation instructions.

---

## Navigating GroqFlow

* [Documentation](docs/): All GroqFlow documentation, including the installation guide, user guide, known issues, and versioning.

* [Examples](examples/): Includes various GroqFlow examples.

* [GroqFlow](groqflow/): The source code for the `groqflow` package.

* [Proof Points](proof_points/): Machine learning proof points using GroqFlow.

* [README.md](readme.md): This README.

---

## Contributors

GroqFlow development is primarily conducted within Groq's internal repo and is periodically synced to GitHub. This approach means that developer contributions are not immediately obvious in the commit log.

This project follows the [all-contributors](https://allcontributors.org) specification.
Contributions of any kind are welcome!
reportlab-qrcode 0.1.6
Allows to create QR codes for use with the ReportLab PDF library.
License: MIT
Requires Python: >=3.6
Keywords: qrcode reportlab pdf

reportlab-qrcode
================

reportlab-qrcode implements a QR code flowable for the ReportLab PDF library
using the [qrcode package](https://pypi.org/project/qrcode/).


Installation
------------

reportlab-qrcode can be installed via pip:

    pip install reportlab-qrcode


Usage
-----

Simply use the *QRCodeImage* class with your data. All non-recognized keyword
arguments will be passed to the *qrcode.QRCode* class from the qrcode package.

    from reportlab.lib.units import mm
    from reportlab.pdfgen.canvas import Canvas
    from reportlab_qrcode import QRCodeImage

    doc = Canvas('simple.pdf')
    qr = QRCodeImage('Some data here', size=30 * mm)
    qr.drawOn(doc, 0, 0)
    doc.showPage()
    doc.save()

For further examples, including setting fill and back colors, QR code size,
error correction level, as well as using the QR code as ReportLab Flowable
object, see the [examples directory](https://github.com/hprid/reportlab-qrcode/tree/master/examples).


Maintenance note
----------------

This package is considered completed. So please do not wonder if you see no
further commits. Despite the lack of new commits, this package is still
maintained, i. e., I plan to keep this package compatible with the newest
Python, qrcode and ReportLab version. If you find a bug, please open an issue
in the issue tracker.


License
-------

reportlab-qrcode is licensed under the MIT license. See LICENSE file for
details.