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python3-notebook-7.2.0-1.lbn36.noarch
The Jupyter Notebook is a web application that allows you to create and
share documents that contain live code, equations, visualizations, and
explanatory text. The Notebook has support for multiple programming
languages, sharing, and interactive widgets.
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python3-notebook-shim-0.2.3-1.lbn36.noarch
Notebook Shim
This project provides a way for JupyterLab and other frontends to switch to Jupyter Server for their Python Web application backend.
Basic Usage
Install from PyPI:
pip install notebook_shim
This will automatically enable the extension in Jupyter Server.
Usage
This project also includes an API for shimming traits that moved from NotebookApp in to ServerApp in Jupyter Server. This can be used by applications that subclassed NotebookApp to leverage the Python server backend of Jupyter Notebooks. Such extensions should now switch to ExtensionApp API in Jupyter Server and add NotebookConfigShimMixin in their inheritance list to properly handle moved traits.
For example, an application class that previously looked like:
from notebook.notebookapp import NotebookApp
class MyApplication(NotebookApp):
should switch to look something like:
from jupyter_server.extension.application import ExtensionApp
from notebook_shim.shim import NotebookConfigShimMixin
class MyApplication(Note
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python3-numpy-2.2.4-1.lbn36.x86_64
NumPy is a general-purpose array-processing package designed to
efficiently manipulate large multi-dimensional arrays of arbitrary
records without sacrificing too much speed for small multi-dimensional
arrays. NumPy is built on the Numeric code base and adds features
introduced by numarray as well as an extended C-API and the ability to
create arrays of arbitrary type.
There are also basic facilities for discrete fourier transform,
basic linear algebra and random number generation. Also included in
this package is a version of f2py that works properly with NumPy.
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python3-numpy-f2py-2.2.4-1.lbn36.x86_64
This package includes a version of f2py that works properly with NumPy.
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python3-ollama-0.4.7-1.lbn36.noarch
Ollama Python Library
The Ollama Python library provides the easiest way to integrate Python 3.8+ projects with Ollama.
Prerequisites
Ollama should be installed and running
Pull a model to use with the library: ollama pull <model> e.g. ollama pull llama3.2
See Ollama.com for more information on the models available.
Usage
from ollama import chat
from ollama import ChatResponse
response: ChatResponse = chat(model='llama3.2', messages=[
{
'role': 'user',
'content': 'Why is the sky blue?',
},
])
print(response['message']['content'])
print(response.message.content)
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python3-openai+realtime-1.77.0-1.lbn36.noarch
This is a metapackage bringing in realtime extras requires for python3-openai.
It makes sure the dependencies are installed.
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python3-openai+voice_helpers-1.77.0-1.lbn36.noarch
This is a metapackage bringing in voice_helpers extras requires for
python3-openai.
It makes sure the dependencies are installed.
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python3-openai-datalib-1.6.1-1.lbn36.noarch
Data libraries like numpy and pandas are not installed by default due to their
size. They’re needed for some functionality of this library, but generally not
for talking to the API.
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python3-openai-embeddings-1.6.1-1.lbn36.noarch
Install dependencies for embedding utilities.
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python3-openai-wandb-1.6.1-1.lbn36.noarch
Install support for Weights and Biases
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