Authentication with Firebase

.github/workflows/deploy.yml

@@ -19,21 +19,23 @@ jobs:
         with:
           node-version: 18
           cache: npm
-          cache-dependency-path: sb-docs/package-lock.json
+          cache-dependency-path: package-lock.json
 
       - name: Install dependencies
-        run: |
-            cd sb-docs
-            npm ci
+        run: npm ci
+
       - name: Build website
-        run: |
-            cd sb-docs
-            npm run build
+        env:
+          FIREBASE_API_KEY: ${{ secrets.FIREBASE_API_KEY }}
+          FIREBASE_AUTH_DOMAIN: ${{ secrets.FIREBASE_AUTH_DOMAIN }}
+          FIREBASE_PROJECT_ID: ${{ secrets.FIREBASE_PROJECT_ID }}
+          FIREBASE_STORAGE_BUCKET: ${{ secrets.FIREBASE_STORAGE_BUCKET }}
+        run: npm run build
 
       - name: Upload Build Artifact
         uses: actions/upload-pages-artifact@v3
         with:
-          path: sb-docs/build
+          path: build
 
   deploy:
     name: Deploy to GitHub Pages
@@ -55,4 +57,4 @@ jobs:
         id: deployment
         uses: actions/deploy-pages@v4
         with:
-            path: sb-docs/build
+          path: build

.github/workflows/pre-deploy.yml

@@ -19,13 +19,15 @@ jobs:
         with:
           node-version: 18
           cache: npm
-          cache-dependency-path: sb-docs/package-lock.json
+          cache-dependency-path: package-lock.json
 
       - name: Install dependencies
-        run: |
-            cd sb-docs
-            npm ci
+        run: npm ci
+
       - name: Test build website
-        run: |
-            cd sb-docs
-            npm run build
+        env:
+          FIREBASE_API_KEY: ${{ secrets.FIREBASE_API_KEY }}
+          FIREBASE_AUTH_DOMAIN: ${{ secrets.FIREBASE_AUTH_DOMAIN }}
+          FIREBASE_PROJECT_ID: ${{ secrets.FIREBASE_PROJECT_ID }}
+          FIREBASE_STORAGE_BUCKET: ${{ secrets.FIREBASE_STORAGE_BUCKET }}
+        run: npm run build

.gitignore

@@ -1 +1,19 @@
 .idea/
+.history
+node_modules/
+.docusaurus/
+.cache-loader
+
+# Misc
+.DS_Store
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+.env
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+tmp

sb-docs/docs/02-onboarding/README.md → docs/02-onboarding.md

@@ -1,33 +1,40 @@
-# Software Team On-boarding
+# Onboarding
 
 ## 1. Meet the team :busts_in_silhouette:
-* A full list of the `Sunbird team` members is available on the Sunbird website [`about page`](https://sunbird.ai/about/#SBteam).
+
+- A full list of the `Sunbird team` members is available on the Sunbird website [`about page`](https://sunbird.ai/about/#SBteam).
 
 ## 2. Meetings :calendar:
-* Meetings are generally held every Monday, Wendesday and Friday, as detailed below: 
-    * The Monday meeting is a `Technical sync`, a meeting for the tech team to discuss tech-related issues (e.g blockers).
-    * The Wednesday meeting is a `Reading group meeting` for the tech team and it is meant for research-related discussions (reading papers, writing research proposals etc).
-    * The Friday meeting is a `Sunbird sync`, a company-wide meeting including non-tech departments like Operations and Finance. It is used to present progress on ongoing work.
-* Specific `Software Team` meetings are held once a week (details are added to each team member's Google calendar).
+
+- Meetings are generally held every Monday, Wendesday and Friday, as detailed below:
+  - The Monday meeting is a `Technical sync`, a meeting for the tech team to discuss tech-related issues (e.g blockers).
+  - The Wednesday meeting is a `Reading group meeting` for the tech team and it is meant for research-related discussions (reading papers, writing research proposals etc).
+  - The Friday meeting is a `Sunbird sync`, a company-wide meeting including non-tech departments like Operations and Finance. It is used to present progress on ongoing work.
+- Specific `Software Team` meetings are held once a week (details are added to each team member's Google calendar).
 
 ## 3. Projects and OKRs :chart_with_upwards_trend:
+
 **Projects:**<br/>
 For a detailed list of projects and their related repositories, refer to the [`Projects and repos`](https://github.com/SunbirdAI/sunbird-docs/tree/main/03-projects-and-repos#projects-and-repositories) section.<br/>
 
 **OKRs (Objectives and Key Results):**<br/>
 Sunbird uses OKRs to plan, manage and track projects. Our OKRs are discussed and documented at the beginning of each quarter.
 
 ## 4. Task tracking :outbox_tray:
+
 Tasks are created from the OKRs mentioned above and the software-related ones are tracked using [`GitHub projects`](https://github.com/orgs/SunbirdAI/projects).
 
 ## 5. Tech stack & tools :computer:
+
 Sunbird coding projects include Machine Learning (ML) models, backend, frontend and DevOps/MLOps. The main programming languages used are `Python` for ML and backend and `Javascript` for frontend. <br/>
 For a more detailed breakdown of the languages and tech stack (including libraries, frameworks and tools/platforms), please refer to the [`Development Process`](https://github.com/SunbirdAI/sunbird-docs/tree/main/04-development-process) section.
- 
+
 ## 6. Deployment processes :wrench:
+
 Please refer to the [`Release and Deployment`](https://github.com/SunbirdAI/sunbird-docs/tree/main/05-release-and-deployment#release-and-deployment) section.
 
 ## 7. Other onboarding activities :mailbox:
-* 1-on-1s for new engineers with the rest of the team to build rapport and share company culture
-* Setting goals and expectations for each team member's role and what success looks like in the role
-* Buddy system, in which each new engineer is assigned a buddy/buddies to help them onboard onto the team
+
+- 1-on-1s for new engineers with the rest of the team to build rapport and share company culture
+- Setting goals and expectations for each team member's role and what success looks like in the role
+- Buddy system, in which each new engineer is assigned a buddy/buddies to help them onboard onto the team

docs/03-projects-and-repositories.md

@@ -0,0 +1,74 @@
+# Projects and Repositories
+
+This page provides an organized way to find all of Sunbird AI's repositories for different projects.
+For a description of the projects (including details about the project aims and execution), please refer to the [Projects](https://sunbird.ai/projects/) page on the [Sunbird AI website](https://sunbird.ai/).
+
+## African Language Technology
+
+#### 1. Language translation
+
+- [Translation portal (front end) - ReactJS](https://github.com/SunbirdAI/translation-portal-react)
+- [Exploratory analysis, data preparation & training](https://github.com/SunbirdAI/parallel-text-EDA)
+- [SALT Dataset](https://github.com/SunbirdAI/salt)
+- [Sunbird AI SALT Inference server](https://github.com/SunbirdAI/sunbirdai-model-inferences)
+- [Sunbird AI API](https://github.com/SunbirdAI/sunbird-ai-api)
+- Datasets related to the use of [HuggingFace](https://huggingface.co/):
+  - [Sunbird HuggingFace datasets](https://github.com/SunbirdAI/datasets)
+  - [Test datasets](https://github.com/SunbirdAI/toy-hf-datasets)
+- [Named Entity Recognition exploratory code](https://github.com/SunbirdAI/sunbird-ner)
+
+#### 2. Speech-to-text
+
+- [Data collection tool](https://github.com/SunbirdAI/speech-data-collection-twilio-whatsapp)
+- [Model training](https://github.com/SunbirdAI/sunbird-speech)
+
+#### 3. Text-to-speech
+
+- [Data collection tool](https://github.com/SunbirdAI/sunbird-prompt-reader)
+- [Model training](https://github.com/SunbirdAI/sunbird-speech)
+
+#### 4. COVID 19 analysis & Text classification
+
+- [COVID 19 Twitter data analysis](https://github.com/SunbirdAI/covid19-uganda-twitter-data-analysis)
+- [COVID-19 Facebook data analysis](https://github.com/SunbirdAI/covid19-uganda-facebook-data-analysis)
+- [Social media data dashboard (Streamlit)](https://github.com/SunbirdAI/social-media-data-dashboard)
+- [SunBERT text classification model](https://github.com/SunbirdAI/SunBERT)
+- [Text classification code](https://github.com/SunbirdAI/text-classification)
+- [Radio advert analysis for COVID 19](https://github.com/SunbirdAI/radio-data-analysis)
+- [Youtube text data collection](https://github.com/SunbirdAI/youtube-data-collection)
+- [Web scraper for Ugandan news](https://github.com/SunbirdAI/ug-news-data-collection)
+
+## Environmental Sensing (Noise Pollution Sensing)
+
+#### 1. Noise Sensors Monitoring
+
+- [Noise sensors monitoring (backend) - Django app](https://github.com/SunbirdAI/noise-sensors-monitoring)
+- [Noise portal (front end) - ReactJS](https://github.com/SunbirdAI/noise-portal)
+- [AWS IoT backend - Django app](https://github.com/SunbirdAI/aws-iot-noise-monitoring)
+
+#### 2. Hardware (sensors)
+
+- [Updated firmware with AWS communication](https://github.com/SunbirdAI/sb-generation2-stm32-firmware)
+- [Generation 2 firmware](https://github.com/SunbirdAI/sbgen2firmware-clean)
+- [Generation 1 firmware](https://github.com/SunbirdAI/sb-generation1-firmware)
+- [Device audio upload 4G](https://github.com/SunbirdAI/audio-file-upload-4G)
+- [Device audio upload 2G](https://github.com/SunbirdAI/audio-file-upload-2G)
+- [TinyML experiment on Arduino](https://github.com/SunbirdAI/sb-tiny-ml-arduino-nano-33-ble)
+
+#### 3. Noise data collection on mobile phones
+
+- [Map of noise phone-collected data](https://github.com/SunbirdAI/noise-data-mapping)
+- [Data pipeline for phone-collected data](https://github.com/SunbirdAI/odk-noise-data-pipeline) and [related exploratory code](https://github.com/SunbirdAI/odk-api-calls)
+
+## Rural electrification planning
+
+#### 1. Mini-grid site identification
+
+- [Mini-grid site identification portal](https://github.com/SunbirdAI/mini-grid-site-identification)
+- [Rural electrification project](https://github.com/SunbirdAI/lamwo-electrification)
+- [Rural electrification project (front end)](https://github.com/SunbirdAI/lamwo-electrification-project)
+
+## SEMA project
+
+- [Device management/monitoring](https://github.com/SunbirdAI/sunbird-sema)
+- [Device sound capture](https://github.com/SunbirdAI/sbgeneration1audiofeedback)

sb-docs/docs/04-development-process/README.md → docs/04-development-process.md

@@ -1,13 +1,17 @@
 # Development Process
 
 ## High level (planning phase) :bookmark_tabs:
+
 ### 1. OKR planning
+
 OKR planning is done at the beginning of every quarter and enables us to scope out what we want to achieve for a given quarter. We lay out the projects to be worked on, then we break down the work into features and tasks to be carried out by different teams.
 
 ### 2. System design document
-Ideally, each major project (maybe even feature) should have a system design document. This helps us plan for the project and understand what kind of work needs to be done. 
+
+Ideally, each major project (maybe even feature) should have a system design document. This helps us plan for the project and understand what kind of work needs to be done.
 
 This document should contain:
+
 - Introduction of what the project is about.
 - Requirements (functional and non-functional).
 - Propose solution / Architecture
@@ -18,30 +22,39 @@ This document should contain:
 Check out [this article](https://www.freecodecamp.org/news/how-to-write-a-good-software-design-document-66fcf019569c/) for a detailed explanation of what goes into each section.<br/><br/>
 
 ## Low level (development phase) :computer:
+
 ### 1. Task tracking
-Once the system design document is done, the requirements should be clear enough to allow us to break down the work into tasks. Software tasks are tracked using [`GitHub projects`](https://github.com/orgs/SunbirdAI/projects).
+
+Once the system design document is done, the requirements should be clear enough to allow us to break down the work into tasks. Software tasks are tracked using [GitHub projects](https://github.com/orgs/SunbirdAI/projects).
+
 ### 2. Development tools
+
 Software projects fall into four main categories: `Machine Learning (ML) models`, `backend`, `frontend` and `DevOps/MLOps`.<br/>
 
 **Tech Stacks**:
-  * ML models: `Python` (pandas, numpy, pytorch etc), Jupyter Notebooks and Google Colabs
-  * Backend: `Python` (Django, FastAPI)
-  * Frontend: `Javascript` (ReactJS)
-  * DevOps/MLOps: `Python` (pandas), AWS (S3, Lambda, API Gateway, IoT, Sagemaker), GCP, Twilio, HuggingFace
+
+- ML models: `Python` (pandas, numpy, pytorch etc), Jupyter Notebooks and Google Colabs
+- Backend: `Python` (Django, FastAPI)
+- Frontend: `Javascript` (ReactJS)
+- DevOps/MLOps: `Python` (pandas), AWS (S3, Lambda, API Gateway, IoT, Sagemaker), GCP, Twilio, HuggingFace
 
 **Tools/Platforms**:<br/>
 We use a number of software platforms/tools that all new software team members will be onboarded onto, including `Google Workspace` (email, calendar, chat, drive), `GitHub`, `AWS`, `GCP`, `Heroku`, and others (`HuggingFace`, `Weights & Biases`, `Heroku`, `Twilio` etc).
 
 ### 3. Coding, collaboration and review
-We use [`GitHub`](https://github.com/SunbirdAI) to store and track our coding work.<br/><br/>
+
+We use [GitHub](https://github.com/SunbirdAI) to store and track our coding work.<br/><br/>
 Our repositories follow a simple repository convention laid out in this [document](https://docs.google.com/document/d/1a4QsLAKhew-5YyAtDO3dTyMsAM3yTDSkgSAPfg_-bFM/edit?usp=sharing), while the code itself follows general well-known coding conventions ([PEP Style Guide](https://peps.python.org/pep-0008/) for Python code and [Mozilla Developer Guidelines](https://developer.mozilla.org/en-US/docs/MDN/Writing_guidelines/Writing_style_guide/Code_style_guide/JavaScript) for Javascript).<br/><br/>
 When working with other team members on the same repository, start by pulling the latest changes from the repository (assuming you have cloned the repository already. Create a new branch from the default branch (usually `main`). After doing your task, create a pull request and link it to the related `GitHub projects task` in order to automate the task tracking process.<br/><br/>
 When done, you can assign a reviewer to your pull request to review it and possibly give feedback/comments.
 
 ### 4. Documentation
+
 Documentation is done in two ways:
-  * Detailed, specific technical documentation in the `README` file of the specific project repository
-  * General documentation in this ([`Sunbird docs`](https://github.com/SunbirdAI/sunbird-docs)) repository
+
+- Detailed, specific technical documentation in the `README` file of the specific project repository
+- General documentation in this [Sunbird docs](https://github.com/SunbirdAI/sunbird-docs) repository
 
 ### 5. Deployment
-Please refer to the [`Release and Deployment`](https://github.com/SunbirdAI/sunbird-docs/tree/main/05-release-and-deployment#release-and-deployment) section.
+
+Please refer to the [Release and Deployment](https://github.com/SunbirdAI/sunbird-docs/tree/main/05-release-and-deployment#release-and-deployment) section.

sb-docs/docs/05-release-and-deployment/README.md → docs/05-release-and-deployment.md

@@ -1,6 +1,9 @@
 # Release and Deployment
+
 ## API Deployment
+
 For deploying and releasing the api in production, see the deployment process [here](https://github.com/SunbirdAI/sunbird-ai-api/blob/main/api-deployment-docs.md)
 
 ## Model Inference Deployment
+
 The model inference deployment process can be found [here](https://github.com/SunbirdAI/sunbirdai-model-inferences/tree/main/deploy-docs)

docs/06-design-docs/_category_.json

@@ -0,0 +1,8 @@
+{
+    "label": "Sunbird Design Documents",
+    "link": {
+      "type": "generated-index",
+      "description": "Contains design documentations for all projects"
+    }
+  }
+