first push test scripts automatic slide from shared DB #49

.github/workflows/slides_reveal.yml

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+name: Generate Slides
+
+on: [push, workflow_dispatch]
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+
+    steps:
+    - name: Checkout main repository
+      uses: actions/checkout@v3
+
+    - name: Checkout submodules
+      run: git submodule update --init --recursive
+
+    - name: Set up Python
+      uses: actions/setup-python@v2
+      with:
+        python-version: 3.11
+
+    - name: Install Python dependencies
+      run: |
+        pip install pandas
+        pip install jinja2
+
+    - name: Generate slides using Python
+      run: python generate_slides.py
+
+    - name: Install Pandoc
+      run: sudo apt-get install pandoc
+
+    - name: Convert Markdown to HTML using reveal.js
+      run: |
+        pandoc slides.md -t revealjs -s -o slides.html -V revealjs-url=./reveal.js -V theme=black
+
+    - name: Commit changes
+      run: |
+        git config --local user.email "[email protected]"
+        git config --local user.name "GitHub Action"
+        git add .
+        git commit -m "Generate slides"
+        git push
+      env:
+        github_token: ${{ secrets.GITHUB_TOKEN }}

slides/generate_slides.py

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+'''
+this script reads in the output_ram.csv file
+and populates a markdown template writing to slides.md
+which can be used to generate slides using reveal.js
+'''
+import pandas as pd
+import os
+from jinja2 import Environment, FileSystemLoader
+
+# Set up Jinja2 environment and load the templates
+env = Environment(loader=FileSystemLoader('.'))
+slide_project = env.get_template('slide_templates/template_project_horizontal.md')
+slide_bullets = env.get_template('slide_templates/template_bullets_vertical.md')
+slide_bullets2 = env.get_template('slide_templates/template_iframe_background.md')
+slide_image = env.get_template('slide_templates/template_image.md')
+slide_url = env.get_template('slide_templates/template_url_vertical.md')
+
+# Read the title slide from title_template.md
+with open('slide_templates/template_title.md', 'r') as title_file:
+    markdown = title_file.read()
+
+# Read data from CSV to pandas
+df = pd.read_csv('output_ram.csv')
+#group by project
+df = df.groupby('Project')
+
+# Add a slide for each project
+for project in df['Project'].unique():
+    # add project slide with description
+    description = df.get_group(project[0])['Project description'].values[0]
+    # make sure description is not nan
+    if description != description:
+        description = ''
+    slide_content = slide_project.render(Project=project[0], Project_content=description)
+    markdown += slide_content
+
+    # check if value in Output type is RAM assessment:
+    if 'RAM assessment' in df.get_group(project[0])['Output type'].values:
+        # add slide template with image and use column "Output Media" as image_path
+        image_path = df.get_group(project[0])['Output Media'].values[0]
+        slide_content = slide_image.render(image_path=image_path)
+        markdown += slide_content
+
+    # add vertical slides with output bullets
+    bullets = df.get_group(project[0])['Output description']
+    #check if series contains NA
+    if not bullets.isnull().values.any():
+        slide_content = slide_bullets.render(Bullets=bullets.tolist())
+        markdown += slide_content
+
+    # add vertical slides with url
+    url = df.get_group(project[0])['Landing page']
+    if url.values[0] != '':
+        slide_content = slide_url.render(URL=url.values[0])
+        markdown += slide_content
+
+    # add combined slide
+    if (not bullets.isnull().values.any()) & (url.values[0] != ''):
+        slide_content = slide_bullets2.render(bullet=bullets.tolist()[0], URL=url.values[0])
+        markdown += slide_content
+
+# Write the entire slide deck to a markdown file
+with open('slides.md', 'w') as md_file:
+    md_file.write(markdown)
+
+print("Generated slides.md")

slides/output_ram.csv

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+Project,Project description,Output type,Output description,Landing page,Output Media,Other Link,RAM,Active RAM engagement?,Date,Notes,Turing Programme / GC,Contact
+AB Street,"An open source urban modelling platform that invites users to add different street interventions to view the impact on traffic in the surrounding neighbourhood and city at large. A/B street can help residents and planners have a shared canvas for discussing potential street-level changes, such as planting street trees or installing a model filter to encourage cycling and walking.",Stakeholder engagement,We worked with local councils to use the tool in public consultation and co-creation session.,https://a-b-street.github.io/docs/software/ltn/index.html,https://www.turing.ac.uk/blog/street-smart-putting-neighbourhood-design-hands-bristol-residents,,,Y,,,,
+AI Standards Hub,,Stakeholder engagement,We facilitated external stakeholder workshops with organisations like Department for Transport,https://aistandardshub.org/,,,SL,Y,,,,
+clim-recal,"The aim of clim-recal is to provide non-climate scientists with an extensive guide to the application, disadvantages/advantages and use of bias adjustment methods, provide researchers with a collated set of resources for how to technically apply the methods, with a framework for open additions, and create accessible information on methods for non quantitative researchers and lay-audience stakeholders",, ,,,,"JD, SA",Y,,,,
+Colouring Cities,,, ,https://colouringcities.org/,,https://github.com/orgs/colouring-cities/repositories,,Y,,,,
+Data Safe Haven,"The Turing Data Safe Haven is an open-source framework for creating secure environments to analyse sensitive data. It provides a set of scripts and templates that will allow you to deploy, administer and use your own secure environment.",,,,,,HS,Y,,,,
+DfT Short Straits,"DfT Short Straits is a collaboration between TRIC, DCE, and UA with Department for Transport for creating a Digital Twin of the Short Straits around Port of Dover, including road, port, and maritime systems in the area",,We co-created resources for stakeholder engagement,,https://miro.com/app/board/uXjVMAOaBQA=/,,,Y,,,,
+London Data Week,"London Data Week is a free, public festival of events across the city, run by different organisations with different communities, to bring Londoners into the conversations about data and AI",,"with Turing and LOTI we convened the London data community, in partnership with organisations like Open Data Institute, Royal Statistical Society, GLA, Better Images of AI, and the Francis Crick Institute",https://www.londondataweek.org/,,,JD,N,,,,
+Scivision,,,,https://sci.vision/,,https://github.com/alan-turing-institute/scivision,AC,Y,,,,
+The Turing Way Practitioner’s Hub,,,,,,,CR,Y,,,,
+PitchFest at AI UK,,,We contribute to Institute-wide flagship events,,,,,N,,,,
+Other,,Conference Talks / Workshops,We organize collaborationwWorkshops: Pathways to Sustainability for Research Projects and Outputs,,https://miro.com/app/board/uXjVMQDvxC0=/,,"HS, CR, ALS",N,,,,
+Other,,Scoping,We have been assessing RAM potential across Turing projects ,,,,,,,,,
+The Trustworthy and Ethical Assurance platform,"The platform brings together elements of Ethics and Assurance methodology like SAFED principles and argument patterns in a usable and accessible manner, and helps project teams to provide trustworthy and justifiable assurance about the processes they undertook when designing, developing, and deploying their technology or system.",RAM assessment,,https://alan-turing-institute.github.io/AssurancePlatform/,https://user-images.githubusercontent.com/5104098/262439184-1c18c514-02c2-434e-abc1-dfcdff3769ba.png, ,"SA, KW",Y,28-9,https://hackmd.io/qbm6EGeNTmqL_t2HoYBJDA?both,,

slides/slide_templates/template_bullets_vertical.md

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+<section>{% for bullet in Bullets %}
+- {{ bullet }}
+{% endfor %}</section>

slides/slide_templates/template_iframe_background.md

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+<section data-background-iframe="{{URL}}" style="background-color: rgba(0,0,0,0.5);">
+        {{ bullet }}
+</section>

slides/slide_templates/template_image.md

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+<section>
+    <h2>RAM assessment</h2>
+    <img src="{{image_path}}">
+</section>

slides/slide_templates/template_project_horizontal.md

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+
+---
+
+## {{Project}}
+<section>{{Project_content}}</section>

slides/slide_templates/template_title.md

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+
+# Ram outputs NEW
+
+<div class="footer">Slides by <a href="https://www.turing.ac.uk/research/research-programmes/tools-practices-and-systems/research-application-management">RAM Team</a></div>
+

slides/slide_templates/template_url_vertical.md

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+<section><iframe src="{{URL}}" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section>

slides/slides.md

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+
+# Ram outputs NEW
+
+<div class="footer">Slides by <a href="https://www.turing.ac.uk/research/research-programmes/tools-practices-and-systems/research-application-management">RAM Team</a></div>
+
+
+---
+
+## AB Street
+<section>An open source urban modelling platform that invites users to add different street interventions to view the impact on traffic in the surrounding neighbourhood and city at large. A/B street can help residents and planners have a shared canvas for discussing potential street-level changes, such as planting street trees or installing a model filter to encourage cycling and walking.</section><section>
+- We worked with local councils to use the tool in public consultation and co-creation session.
+</section><section><iframe src="https://a-b-street.github.io/docs/software/ltn/index.html" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="https://a-b-street.github.io/docs/software/ltn/index.html" style="background-color: rgba(0,0,0,0.5);">
+        We worked with local councils to use the tool in public consultation and co-creation session.
+</section>
+---
+
+## AI Standards Hub
+<section></section><section>
+- We facilitated external stakeholder workshops with organisations like Department for Transport
+</section><section><iframe src="https://aistandardshub.org/" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="https://aistandardshub.org/" style="background-color: rgba(0,0,0,0.5);">
+        We facilitated external stakeholder workshops with organisations like Department for Transport
+</section>
+---
+
+## Colouring Cities
+<section></section><section>
+-  
+</section><section><iframe src="https://colouringcities.org/" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="https://colouringcities.org/" style="background-color: rgba(0,0,0,0.5);">
+         
+</section>
+---
+
+## Data Safe Haven
+<section>The Turing Data Safe Haven is an open-source framework for creating secure environments to analyse sensitive data. It provides a set of scripts and templates that will allow you to deploy, administer and use your own secure environment.</section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section>
+---
+
+## DfT Short Straits
+<section>DfT Short Straits is a collaboration between TRIC, DCE, and UA with Department for Transport for creating a Digital Twin of the Short Straits around Port of Dover, including road, port, and maritime systems in the area</section><section>
+- We co-created resources for stakeholder engagement
+</section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="nan" style="background-color: rgba(0,0,0,0.5);">
+        We co-created resources for stakeholder engagement
+</section>
+---
+
+## London Data Week
+<section>London Data Week is a free, public festival of events across the city, run by different organisations with different communities, to bring Londoners into the conversations about data and AI</section><section>
+- with Turing and LOTI we convened the London data community, in partnership with organisations like Open Data Institute, Royal Statistical Society, GLA, Better Images of AI, and the Francis Crick Institute
+</section><section><iframe src="https://www.londondataweek.org/" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="https://www.londondataweek.org/" style="background-color: rgba(0,0,0,0.5);">
+        with Turing and LOTI we convened the London data community, in partnership with organisations like Open Data Institute, Royal Statistical Society, GLA, Better Images of AI, and the Francis Crick Institute
+</section>
+---
+
+## Other
+<section></section><section>
+- We organize collaborationwWorkshops: Pathways to Sustainability for Research Projects and Outputs
+
+- We have been assessing RAM potential across Turing projects 
+</section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="nan" style="background-color: rgba(0,0,0,0.5);">
+        We organize collaborationwWorkshops: Pathways to Sustainability for Research Projects and Outputs
+</section>
+---
+
+## PitchFest at AI UK
+<section></section><section>
+- We contribute to Institute-wide flagship events
+</section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="nan" style="background-color: rgba(0,0,0,0.5);">
+        We contribute to Institute-wide flagship events
+</section>
+---
+
+## Scivision
+<section></section><section><iframe src="https://sci.vision/" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section>
+---
+
+## The Trustworthy and Ethical Assurance platform
+<section>The platform brings together elements of Ethics and Assurance methodology like SAFED principles and argument patterns in a usable and accessible manner, and helps project teams to provide trustworthy and justifiable assurance about the processes they undertook when designing, developing, and deploying their technology or system.</section><section>
+    <h2>RAM assessment</h2>
+    <img src="https://user-images.githubusercontent.com/5104098/262439184-1c18c514-02c2-434e-abc1-dfcdff3769ba.png">
+</section><section><iframe src="https://alan-turing-institute.github.io/AssurancePlatform/" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section>
+---
+
+## The Turing Way Practitioner’s Hub
+<section></section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section>
+---
+
+## clim-recal
+<section>The aim of clim-recal is to provide non-climate scientists with an extensive guide to the application, disadvantages/advantages and use of bias adjustment methods, provide researchers with a collated set of resources for how to technically apply the methods, with a framework for open additions, and create accessible information on methods for non quantitative researchers and lay-audience stakeholders</section><section>
+-  
+</section><section><iframe src="nan" style="width: 100%; height: 200%; float: right; border: none;"></iframe></section><section data-background-iframe="nan" style="background-color: rgba(0,0,0,0.5);">
+         
+</section>