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python3-litellm-1.69.0-1.lbn36.noarch
🚅 LiteLLM Call all LLM APIs using the OpenAI format [Bedrock, Huggingface, VertexAI, TogetherAI, Azure, OpenAI, Groq etc.] LiteLLM manages: Translate inputs to provider's completion, embedding, and image_generation endpoints Consistent output, text responses will always be available at ['choices'][0]['message']['content'] Retry/fallback logic across multiple deployments (e.g. Azure/OpenAI) - Router Set Budgets & Rate limits per project, api key, model LiteLLM Proxy Server (LLM Gateway)
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python3-litellm+proxy-1.69.0-1.lbn36.noarch
This is a metapackage bringing in proxy extras requires for python3-litellm. It makes sure the dependencies are installed.
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python3-mistralai-1.7.0-1.lbn36.noarch
Mistral Python Client Mistral AI API: Our Chat Completion and Embeddings APIs specification.
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python3-mistralclient-4.5.0-1.lbn36.noarch
Python client for Mistral REST API. Includes python library for Mistral API and Command Line Interface (CLI) library.
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python3-nbconvert-7.16.4-1.lbn36.noarch
nbconvert Jupyter Notebook Conversion The nbconvert tool, jupyter nbconvert, converts notebooks to various other formats via Jinja templates. The nbconvert tool allows you to convert an .ipynb notebook file into various static formats including: HTML LaTeX PDF Reveal JS Markdown (md) ReStructured Text (rst) executable script Usage From the command line, use nbconvert to convert a Jupyter notebook (input) to a a different format (output). The basic command structure is: $ jupyter nbconvert --to <output format> <input notebook> where <output format> is the desired output format and <input notebook> is the filename of the Jupyter notebook. Example: Convert a notebook to HTML Convert Jupyter notebook file, mynotebook.ipynb, to HTML using: $ jupyter nbconvert --to html mynotebook.ipynb This command creates an HTML output file named mynotebook.html. Dev Install Check if pandoc is installed (pandoc --version); if needed, install: sudo apt-get install pandoc Or brew install pandoc I
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python3-nbformat-5.9.2-1.lbn36.noarch
This package contains the base implementation of the Jupyter Notebook format, and Python APIs for working with notebooks.
Located in LBN / … / Data Science / BastionLinux 36
python3-nbsphinx-0.8.7-2.fc36.noarch
nbsphinx is a Sphinx extension that provides a source parser for *.ipynb files. Custom Sphinx directives are used to show Jupyter Notebook code cells (and of course their results) in both HTML and LaTeX output. Unevaluated notebooks, i.e. notebooks without stored output cells, will be automatically executed during the Sphinx build process.
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python3-needle-0.5.0-2.lbn36.noarch
Needle is a tool for testing your CSS and visuals with Selenium and nose. It checks that visuals (CSS/fonts/images/SVG/etc.) render correctly by taking screenshots of portions of a website and comparing them against known good screenshots. It also provides tools for testing calculated CSS values and the position of HTML elements.
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python3-needle-python-0.4.0-1.lbn36.noarch
Needle Python Library This Python library provides convenient acccess to Needle API. There are various methods and data types which, we believe will help you explore Needle API quickly. There may be some functionality available in REST API earlier than this Python library. In any case, we recommend to take look the the complete documentation. Thank you for flying with us. 🚀 Installation This library requires Python >3.8 and pip to use. You don't need the sources unless you want to modify it. Install with: pip install needle-python Usage ⚡️ To get started, generate an API key for your account in developer settings menu at Needle. Note that your key will be valid until you revoke it. Set the following env variable before you run your code: export NEEDLE_API_KEY=<your-api-key> NeedleClient reads the API key from the environment by default. If you like to override this behaviour you can pass it in as a parameter. Retrieve context from Needle from needle.v1 import NeedleClient from need
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python3-networkx-3.4.2-1.lbn36.noarch
NetworkX is a Python 3 package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.
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