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README.md

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| Information | Links |
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| :-------------------- | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| **Package** | [![PyPI Latest Release](https://img.shields.io/pypi/v/vuegen.svg)][vuegen-pypi] [![Conda Latest Release](https://img.shields.io/conda/v/bioconda/vuegen.svg)][vuegen-conda] [![Supported versions](https://img.shields.io/pypi/pyversions/vuegen.svg)][vuegen-pypi] [![Docker Repository on Quay](https://quay.io/repository/dtu_biosustain_dsp/vuegen/status "Docker Repository on Quay")][vuegen-docker-quay] [![License](https://img.shields.io/github/license/Multiomics-Analytics-Group/vuegen)][vuegen-license] |
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| **Documentation** | [![View - Documentation](https://img.shields.io/badge/view-Documentation-blue?style=flat)][vuegen-docs] [![made-with-sphinx-doc](https://img.shields.io/badge/Made%20with-Sphinx-1f425f.svg)](https://www.sphinx-doc.org/) ![Docs](https://readthedocs.org/projects/vuegen/badge/?style=flat) |
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| **Documentation** | [![View - Documentation](https://img.shields.io/badge/view-Documentation-blue?style=flat)][vuegen-docs] [![made-with-sphinx-doc](https://img.shields.io/badge/Made%20with-Sphinx-1f425f.svg)](https://www.sphinx-doc.org/) ![Docs](https://readthedocs.org/projects/vuegen/badge/?style=flat) |
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| **Build** | [![CI](https://github.com/Multiomics-Analytics-Group/vuegen/actions/workflows/cdci.yml/badge.svg)][ci-gh-action] [![Docs](https://github.com/Multiomics-Analytics-Group/vuegen/actions/workflows/docs.yml/badge.svg)][ci-docs] |
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| **Examples** | [![HTML5](https://img.shields.io/badge/html5-%23E34F26.svg?style=for-the-badge&logo=html5&logoColor=white)][emp-html-demo] [![Streamlit](https://img.shields.io/badge/Streamlit-%23FE4B4B.svg?style=for-the-badge&logo=streamlit&logoColor=white)][emp-st-demo] |
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| **Discuss on GitHub** | [![GitHub issues](https://img.shields.io/github/issues/Multiomics-Analytics-Group/vuegen)][issues] [![GitHub pull requests](https://img.shields.io/github/issues-pr/Multiomics-Analytics-Group/vuegen)][pulls] |
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### Folder structure
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Your input directory should follow a **nested folder structure**, where first-level folders are treated as **sections** and second-level folders as **subsections**, containing the components (plots, tables, networks, Markdown text, and HTML files). If the component files are in the first-level folders, an `overview` subsection will be created automatically.
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Your input directory should follow a **nested folder structure**, where first-level folders are treated as **sections** and second-level folders as **subsections**, containing the components (plots, tables, networks, Markdown text, and HTML files). If the component files are in the first-level folders, an `overview` subsection will be created automatically.
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Here is an example layout:
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You will need to unzip the file and run `vuegen_gui` in the unpacked main folder.
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Most dependencies are included into the bundle using [PyInstaller][pyinstaller].
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Streamlit works out of the box as a purely Python based package. For the rest of report types you
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Streamlit works out of the box as a purely Python based package. For the rest of report types you
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will have to have a **Python 3.12** installation with the `jupyter` package installed, as `quarto` needs to start
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a kernel for execution. This is also true if you install `quarto` globally on your machine.
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> [!TIP]
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> It is advisable to create a virtual environment to manage depenendencies and avoid conflicts with existing packages. You can use the virtual environment manager of your choice, such as `poetry`, `conda`, or `pipenv`. We recommend using [miniforge][conda-download] to install Python and the `conda` package manager.
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We assume you have installed the `miniforge` distribution for your machine (MacOS with arm64/ apple silicon
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or x86_64/ intel or Windows x86_64). Also, download the
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We assume you have installed the `miniforge` distribution for your machine (MacOS with arm64/ apple silicon
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or x86_64/ intel or Windows x86_64). Also, download the
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[latest `vuegen_gui` bundle](https://github.com/Multiomics-Analytics-Group/vuegen/releases/latest)
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from the releases page according to your operating system.
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You can create a new conda environment with Python 3.12 and the `jupyter` and `vuegen` package:
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```bash
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conda create -n vuegen_gui -c conda-forge python=3.12 jupyter vuegen
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conda create -n vuegen_gui -c conda-forge -c bioconda python=3.12 jupyter vuegen
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```
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> [!WARNING]
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> If you have errors with the `vuegen` package, you can install it separately using pip, as explained in the installation section.
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>
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> ```
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> conda create -n vuegen_gui -c conda-forge -c bioconda python=3.12 jupyter
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> conda activate vuegen_gui
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> pip install vuegen
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> ```
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Then, activate the environment:
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```bash
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conda activate vuegen_gui
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```
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> [!WARNING]
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> If you have errors with the `vuegen` package, you can install it separately using pip, as explained in the installation section.
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Now, you can list all conda environments to find the location of the `vuegen_gui` environment:
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```bash
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### 3. ChatBot Component
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This case study highlights VueGen’s capability to embed a chatbot component into a report subsection,
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enabling interactive conversations inside the report. This component is streamlit-specific and is not
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This case study highlights VueGen’s capability to embed a chatbot component into a report subsection,
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enabling interactive conversations inside the report. This component is streamlit-specific and is not
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available for other report types.
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Two API modes are supported:
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- **Ollama-style streaming chat completion**
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Once a Streamlit report is generated, it can be deployed as a web application to make it accessible online. There are multiple ways to achieve this:
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### Streamlit Community Cloud
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### Streamlit Community Cloud
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Deploy your report easily using [Streamlit Cloud][st-cloud], as demonstrated in the [EMP VueGen Demo][emp-st-demo]. The process involves moving the necessary scripts, data, and a requirements.txt file into a GitHub repository. Then, the app can be deployed via the Streamlit Cloud interface. The deployment example is available in the `streamlit-report-example` branch.
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gui/app.py

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kwargs["max_depth"] = int(max_depth.get())
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print("kwargs:")
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pprint(kwargs)
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global config_app
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if python_dir_entry.get():
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if python_dir_entry.get() != config_app["python_dir_entry"]:
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config_app["python_dir_entry"] = python_dir_entry.get()

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