-
python3-jupyterlab-dash-0.1.0a3-1.lbn36.noarch
jupyterlab-dash
A JupyterLab extension for rendering Plotly Dash apps as a separate window in JupyterLab :tada:
Note:: This extension does not currently support Windows or Python 2
Prerequisites
JupyterLab 1.0.0
Dash
Installation
The jupyterlab-dash library requires both a Python package and a JupyterLab
extension.
First, install the Python package using either pip...
$ pip install "jupyterlab>=1.0" jupyterlab-dash==0.1.0a3
or conda (but not both!).
$ conda install -c plotly -c defaults -c conda-forge "jupyterlab>=1.0" jupyterlab-dash=0.1.0a3
Then, install the JupyterLab extension. v6.17.1 of node works, and node 8.x.x or 10+ should also work.
$ jupyter labextension install jupyterlab-dash@0.1.0-alpha.3
Development Installation
If you'd like to install jupyterlab-dash for development
$ git clone https:/github.com/plotly/jupyterlab-dash
$ cd jupyterlab-dash
$ pip install -e .
$ npm install # or yarn
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-jupyterlab-heroku-0.2.1-1.lbn36.noarch
jupyterlab-heroku[![npm]( [![pypi]( extension to manage and deploy
applications to Heroku.The extension enables 1-click deployments of [voila](
dashboards.![screencast]( Requirements Create an Heroku account_If you already
have an Heroku account, you can skip to the next section_.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-jupyterlab-irods-3.0.5-1.lbn36.noarch
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-jupyterlab-server-2.27.2-1.lbn36.noarch
jupyterlab server
Motivation
JupyterLab Server sits between JupyterLab and Jupyter Server, and provides a
set of REST API handlers and utilities that are used by JupyterLab. It is a separate project in order to
accommodate creating JupyterLab-like applications from a more limited scope.
Install
pip install jupyterlab_server
To include optional openapi dependencies, use:
pip install jupyterlab_server[openapi]
To include optional pytest_plugin dependencies, use:
pip install jupyterlab_server[test]
Usage
See the full documentation for API docs and REST endpoint descriptions.
Extending the Application
Subclass the LabServerApp and provide additional traits and handlers as appropriate for your application.
Contribution
Please see CONTRIBUTING.md for details.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-jupyterlab-vpython-3.1.6-1.lbn36.noarch
jupyterlab_vpython
A VPython extension for JupyterLab
Requirements
JupyterLab >= 4.0.0
Install
To install the extension, execute:
pip install jupyterlab_vpython
Uninstall
To remove the extension, execute:
pip uninstall jupyterlab_vpython
Contributing
Development install
Note: You will need NodeJS to build the extension package.
The jlpm command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
yarn or npm in lieu of jlpm below.
pip install -e "."
jupyter labextension develop . --overwrite
jlpm build
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-langchain-0.3.26-1.lbn36.noarch
🦜️🔗 LangChain
Building applications with LLMs through composability
🤔 What is this?
Large language models (LLMs) are emerging as a transformative technology, enabling developers to build applications that they previously could not. However, using these LLMs in isolation is often insufficient for creating a truly powerful app - the real power comes when you can combine them with other sources of computation or knowledge.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-langserve-0.0.27-1.lbn36.noarch
🦜️🏓 LangServe
🚩 We will be releasing a hosted version of LangServe for one-click deployments of LangChain applications. Sign up here to get on the waitlist.
Overview
LangServe helps developers deploy LangChain runnables and chains as a REST API.
This library is integrated with FastAPI and uses pydantic for data validation.
In addition, it provides a client that can be used to call into runnables deployed on a server.
A javascript client is available in LangChainJS.
Features
Input and Output schemas automatically inferred from your LangChain object, and enforced on every API call, with rich error messages
API docs page with JSONSchema and Swagger (insert example link)
Efficient /invoke, /batch and /stream endpoints with support for many concurrent requests on a single server
/stream_log endpoint for streaming all (or some) intermediate steps from your chain/agent
Playground page at /playground with streaming output and intermediate steps
Built-in (optional) tracing to LangSmith, ju
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-langsmith-0.4.5-1.lbn36.noarch
LangSmith Client SDK
This package contains the Python client for interacting with the LangSmith platform.
LangSmith helps you and your team develop and evaluate language models and intelligent
agents. It is compatible with any LLM Application and provides seamless integration with
LangChain, a widely recognized open-source framework that simplifies the process for
developers to create powerful language model applications.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
python3-langtable-0.0.58-1.fc36.noarch
This package contains a Python module to query the data
from langtable-data.
Located in
LBN
/
…
/
Data Science
/
BastionLinux 36
-
mozjs78-78.15.0-3.fc36.x86_64
SpiderMonkey is the code-name for Mozilla Firefox's C++ implementation of
JavaScript. It is intended to be embedded in other applications
that provide host environments for JavaScript.
Located in
LBN
/
…
/
Core Linux
/
BastionLinux 36
