README files

examples/docker/ocr-solara/README.md

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+# OCR app
+
+A Solara app to extract text from images.

examples/docker/personality-quiz-rag-solara/README.md

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+# Personality Quiz
+
+A RAG application to deduce user's Myers-Briggs personality type from answers to quiz questions.
+
 ## How to run this application locally
 
 ### 1. Install dependencies

examples/docker/shiny-express/README.md

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+# Restaurant tipping dashboard
+
+A restaurant tipping dashboard designed to offer valuable insights into tipping behaviors like average tip, tips percentage over the week, etc. 

examples/docker/shiny/README.md

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 # Model monitoring application
 
-This app is built on Shiny and allows you to visualize model training accuracy scores in realtime in 2 steps:
+A Shiny app to visualize model training accuracy scores in realtime.
+
+## Steps
 
 * Train multiple models with different parameters locally, and store the accuracy scores to a remote database at the end of every epoch.
 * The visualisation application dynamically detects changes in the remote database and generates a plot as the training progresses.

examples/docker/solara/README.md

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 # Keyword Extraction Solara App
 
-This Solara app is designed for performing keyword extraction from text documents. Currently, it supports the packages `PyTextRank` and `Yake` for extracting the most relevant keywords from the input text. 
+A Solara app designed for performing keyword extraction from text documents. 
+
+Currently, it supports the packages `PyTextRank` and `Yake` for extracting the most relevant keywords from the input text. 
 The extracted keywords can be useful for content analysis, search engine optimization (SEO), and other natural language processing tasks.
 
 ## Getting Started

examples/docker/streamlit/README.md

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+# A basic app
+
+A basic Streamlit app.

examples/docker/video-rag/README.md

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 ## RAG from video
 
+A RAG application that takes video content as input and answers questions about it.
+
 This is a full stack project that uses a video as input, populates an ElasticSearch instance with vectors through an indexing pipeline, and initializes a retriver pipeline with a Solara app.
 
 A complete walk through of this application can be found [here](https://ploomber.io/blog/rag-video-app/)

examples/docker/voila/README.md

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-# Custom Voila app
+# Scotch data visualisation
+
+A dashboard for visualising different properties of the type of scotch selected by the user.
 
 `app.ipynb` was taken from the [`voila-gridstack`](https://github.com/voila-dashboards/voila-gridstack/blob/main/examples/scotch_dashboard.ipynb) repository.

examples/panel/chat-with-github/README.md

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 # Chat with Github
 
-This Panel app enables users to chat with their GitHub repositories using the llama_index [GithubRepositoryReader](https://docs.llamaindex.ai/en/stable/examples/data_connectors/GithubRepositoryReaderDemo.html).
+A Panel app that enables users to chat with their GitHub repositories using the llama_index [GithubRepositoryReader](https://docs.llamaindex.ai/en/stable/examples/data_connectors/GithubRepositoryReaderDemo.html).
 
 To run the app you need to set a couple of [environment variables](https://docs.cloud.ploomber.io/en/latest/user-guide/env-vars.html):
 

examples/panel/chat-with-pdf/README.md

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 # Chat with a PDF
 
-This Panel app was [originally developed](https://github.com/holoviz-topics/panel-chat-examples/blob/main/docs/examples/langchain/langchain_pdf_assistant.py) by [Andrew Huang](https://github.com/ahuang11),
+A Panel app that allows users to chat with a PDF document.
+
+This app was [originally developed](https://github.com/holoviz-topics/panel-chat-examples/blob/main/docs/examples/langchain/langchain_pdf_assistant.py) by [Andrew Huang](https://github.com/ahuang11),
 and [Marc Skov Madsen](https://github.com/MarcSkovMadsen).
 
 [Click here](https://docs.cloud.ploomber.io/en/latest/apps/panel.html) to see deployment instructions.

examples/panel/data-viz/README.md

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+# Penguin Crossfilter
+
+A Panel app that uses the box-select and lasso-select tools to select a subset of penguins and reveal more information about the selected subgroup through the power of cross-filtering.

examples/panel/rag-news/README.md

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 # News summarizer
 
+A RAG application for summarizing the latest news.
+
 To download today's news and compute the embeddings you first need to set the OpenAI key:
 
 ```bash

examples/shiny-r/shiny-r-data-visualization/README.md

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+# Data visualization
+
+An app for visualising the Penguins dataset.

examples/shiny/basic-app/README.md

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 # Model monitoring application
 
-This app is built on Shiny and allows you to visualize model training accuracy scores in realtime in 2 steps:
+A Shiny app to visualize model training accuracy scores in realtime.
+
+## Steps
 
 * Train multiple models with different parameters locally, and store the accuracy scores to a remote database at the end of every epoch.
 * The visualisation application dynamically detects changes in the remote database and generates a plot as the training progresses.

examples/shiny/express-tip-calculator/README.md

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+# Restaurant tipping dashboard
+
+A restaurant tipping dashboard designed to offer valuable insights into tipping behaviors like average tip, tips percentage over the week, etc.

examples/solara/arxiv-chat/README.md

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+# Arxiv Chat
+
+A chat assistant that can help find academic papers using Arxiv and also allows users to chat with an uploaded article.

examples/solara/gpt-4-tokenizer/README.md

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+# GPT4 Tokenizer
+
+A Solara app that shows how to use a language model tokenizer to encode and decode and how to search for a token.

examples/solara/keyword-extraction/README.md

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 # Keyword Extraction Solara App
 
-This Solara app is designed for performing keyword extraction from text documents. Currently, it supports the packages `PyTextRank` and `Yake` for extracting the most relevant keywords from the input text. 
+This Solara app is designed for performing keyword extraction from text documents. 
+
+Currently, it supports the packages `PyTextRank` and `Yake` for extracting the most relevant keywords from the input text. 
 The extracted keywords can be useful for content analysis, search engine optimization (SEO), and other natural language processing tasks.
 
 ## Getting Started

examples/solara/ocr/README.md

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+# OCR app
+
+A Solara app to extract text from images.

examples/solara/personality-quiz-rag/README.md

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+# Personality Quiz
+
+A RAG application to deduce user's Myers-Briggs personality type from answers to quiz questions.
+
 ## How to run this application locally
 
 ### 1. Install dependencies

examples/solara/video-rag/README.md

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 ## RAG from video
 
+A RAG application that takes video content as input and answers questions about it.
+
 This is a full stack project that uses a video as input, populates an ElasticSearch instance with vectors through an indexing pipeline, and initializes a retriver pipeline with a Solara app.
 
 A complete walk through of this application can be found [here](https://ploomber.io/blog/rag-video-app/)

examples/streamlit/basic-app/README.md

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+# A basic app
+
+A basic Streamlit app.

examples/streamlit/data-viz/README.md

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+# Data visualisation
+
+An interactive app that explores a public Uber dataset for pickups and drop-offs in New York City. 

examples/voila/animated-viz/README.md

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+# Data visualisation
+
+An interactive app that allows users to explore population by continent or countries.

examples/voila/basic-app/README.md

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-# Custom Voila app
+# Scotch data visualisation app
+
+A dashboard for visualising different properties of the type of scotch selected by the user.
 
 `app.ipynb` was taken from the [`voila-gridstack`](https://github.com/voila-dashboards/voila-gridstack/blob/main/examples/scotch_dashboard.ipynb) repository.

examples/voila/chat-with-csv/README.md

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+# Chat with a CSV
+
+Chat with a CSV file using natural language.

examples/voila/env-variable/README.md

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+# Environment variable
+
+A simple app for demonstrating how to access environment variables in Ploomber Cloud.

examples/voila/image-mask-generator/README.md

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+# Mask generator
+
+This tool allows you to create mask images, required by inpainting models such as Stable Diffusion Inpainting.

examples/voila/jupysql/README.md

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+# Analytical application
+
+An application that uses the Penguins dataset to demonstrate model prediction values given an input.

examples/voila/ml/README.md

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+# Machine Learning
+
+An application that uses the Penguins dataset to demonstrate model prediction values given an input.

examples/voila/mosaic/README.md

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+# Mosaic visualisation app
+
+This application uses Mosaic to display plots that are interactive and linked together through cross-filtering.

examples/voila/object-removal/README.md

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+# Object Removal app
+
+This app allows you to remove objects from images.