Merge dev to main

.github/workflows/mlflow-js.yaml

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+name: mlflow
+on:
+  pull_request:
+    branches:
+      - main
+
+jobs:
+  build-and-test:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Use Node.js
+        uses: actions/setup-node@v4
+        with:
+          node-version: '22.7'
+
+      - name: Install dependencies
+        working-directory: ./mlflow
+        run: npm ci
+
+      - name: Eslint
+        working-directory: ./mlflow
+        run: npm run lint
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Run MLflow server
+        run: |
+          docker run -d -p 5002:5002 --name mlflow-container ghcr.io/mlflow/mlflow:latest mlflow server --host 0.0.0.0 --port 5002
+          sleep 30
+
+      - name: Run tests
+        working-directory: ./mlflow
+        run: npm run test
+
+      - name: Stop MLflow server
+        run: docker stop mlflow-container
+
+      - name: Build
+        working-directory: ./mlflow
+        run: npm run build

CONTRIBUTING.md

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+# Contribution Guidelines
+
+We are always open to accepting any potential contributions. Here is how you can contribute:
+
+1. Fork the repository
+2. Clone your forked repository
+
+```bash
+git clone https://github.com/your-username/repository-name.git
+```
+
+3. Create your feature branch
+
+```bash
+git checkout -b feature/AmazingFeature
+```
+
+4. Install dependencies for both mlflow and mlflow-site directories
+
+```bash
+cd /mlflow && npm install
+cd ../mlflow-site && npm install
+```
+
+5. Start the MLflow Tracking Server
+
+```bash
+cd ../mlflow && npm run docker
+```
+
+This will launch the MLflow UI on your local machine at `http://localhost:5001`.
+
+6. Make your changes
+
+7. Run ESLint to check code style
+
+```bash
+npm run lint
+```
+
+8. Run tests to ensure your changes don't break existing functionality
+
+   (Make sure you have mlflow UI server running on port 5002. We set 5002 as our default port for testing.)
+
+```bash
+cd /mlflow && npm run dockerTest # Run this in a separate terminal
+npm run test
+```
+
+This will launch the MLflow UI on your local machine at `http://localhost:5002`, and run the Jest tests.
+
+9. Add and commit your changes
+
+If the tests all pass:
+
+```bash
+git add .
+git commit -m 'Add AmazingFeature'
+```
+
+10. Push to the branch
+
+```bash
+git push origin feature/AmazingFeature
+```
+
+11. Open a Pull Request
+
+**Note:** Please ensure your code adheres to our style guidelines and includes appropriate documentation for any new features.

LICENSE

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+MIT License
+
+Copyright (c) 2024 Open Source Labs Beta
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1 +1,178 @@
+<div style="text-align: center">
+<img src="/mlflow-site/public/assets/mlflow-js-logo-whitebg.png" width=600px;"/></div>
 
+<br>
+
+## About
+
+[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](/LICENSE)
+![Release](https://img.shields.io/badge/Release-v1.0.1-426B20)
+![Build](https://img.shields.io/badge/Build-Passing-brightgreen.svg)
+![Coverage](https://img.shields.io/badge/Coverage-87%25-c7ea46.svg)
+[![Contributions](https://img.shields.io/badge/Contributions-Welcome-brightgreen.svg)](/CONTRIBUTING.md)
+
+<i>MLflow.js</i> is an open-source JavaScript library that helps developers track machine learning experiments and manage models with MLflow, providing functionalities for machine learning lifecycle in JavaScript/TypeScript environments.
+
+<br>
+
+## Features
+
+<i>MLflow.js</i> covers all REST API endpoints under MLflow's Tracking Server and Model Registry. Moreover, high-level abstractions have been developed to facilitate developers' common ML workflows. It provides some key advantages:
+
+- Native JavaScript Integration: Seamlessly integrate MLflow capabilities within JavaScript codebases
+- Type Safety: Built with TypeScript for enhanced developer experience and code reliability
+- Modular Architecture: Designed with object-oriented structure that mirrors MLflow's concepts while being extensible and maintainable
+- Client-side ML Compatibility: Complements popular JavaScript libraries like TensorFlow.js, enabling ML deployment directly in the browser or client side
+
+<br>
+
+## Built with
+
+[![TypeScript](https://img.shields.io/badge/TypeScript-0077B5?style=for-the-badge&logo=typescript&logoColor=white)](https://www.typescriptlang.org/)
+[![JavaScript](https://img.shields.io/badge/JavaScript-000435?style=for-the-badge&logo=javascript&logoColor=00fff)](https://www.javascript.com/)
+[![React](https://img.shields.io/badge/React-36454F?style=for-the-badge&logo=React&logoColor=00fff)](https://react.dev/)
+[![Next.js](https://img.shields.io/badge/Next.js-24292e?style=for-the-badge&logo=next.js&logoColor=00fff)](https://nextjs.org/)
+[![TailwindCSS](https://img.shields.io/badge/Tailwind_CSS-008080?style=for-the-badge&logo=tailwindcss&logoColor=bfffff)](https://tailwindcss.com/)
+[![ESLINT](https://img.shields.io/badge/ESLINT-4B32C3?style=for-the-badge&logo=eslint&logoColor=bfffff)](https://eslint.org/)
+[![Node.js](https://img.shields.io/badge/Node.js-339933?style=for-the-badge&logo=node.js&logoColor=ffffff)](https://nodejs.org/en/)
+[![Jest](https://img.shields.io/badge/Jest-800020?style=for-the-badge&logo=jest&logoColor=00fff)](https://jestjs.io/)
+[![GitHub Actions](https://img.shields.io/badge/GitHub_Actions-30363d?style=for-the-badge&logo=github&logoColor=00fff)](https://github.com/features/actions)
+[![Docker](https://img.shields.io/badge/Docker-lightblue?style=for-the-badge&logo=Docker&logoColor=00fff)](https://www.docker.com/)
+[![NPM](https://img.shields.io/badge/NPM-CC3534?style=for-the-badge&logo=npm&logoColor=00fff)](https://www.npmjs.com/)
+[![Vercel](https://img.shields.io/badge/Vercel-966FD6?style=for-the-badge&logo=Vercel&logoColor=00fff)](https://vercel.com/)
+
+<br>
+
+## Prerequisites
+
+### Set Up MLflow
+
+Ensure MLflow is installed on your system:
+
+```bash
+pip install mlflow
+```
+
+**Note:** MLflow is compatible with MacOS. If you encounter issues with the default system Python, consider installing Python 3 via the Homebrew package manger using `brew install python`. In this case, installing MLflow is now `pip3 install mlflow`.
+
+### Start the MLflow Tracking Server
+
+To start the MLflow tracking server locally, use the following command:
+
+```bash
+mlflow ui --port 5001
+```
+
+This will launch the MLflow UI on your local machine at `http://localhost:5001`.
+
+### Alternative Docker approach to the MLflow Tracking Server
+
+Install [Docker Desktop](https://www.docker.com/).
+
+To start the MLflow tracking server locally, use the following commands:
+
+```bash
+docker pull ghcr.io/mlflow/mlflow
+docker run -p 5001:5001 ghcr.io/mlflow/mlflow:latest mlflow server --host 0.0.0.0 --port 5001
+```
+
+This will launch the MLflow UI on your local machine at `http://localhost:5001`.
+
+### Development Setup
+
+For development environment setup instructions, please refer to our [Contributing Guide](/CONTRIBUTING.md).
+
+<br>
+
+## Quickstart
+
+### Install <i>mlflow.js</i> Library
+
+To use the <i>mlflow.js</i> library, navigate to your project directory and install it via npm:
+
+```bash
+npm install mlflow-js
+```
+
+### Usage Example
+
+Here is an example of how to use the <i>mlflow.js</i> library to create an experiment:
+
+```JavaScript
+import Mlflow from 'mlflow-js';
+
+// Initialize the MLflow client
+const mlflow = new Mlflow(process.env.MLFLOW_TRACKING_URI);
+
+// Create a new experiment
+async function createExperiment(){
+	await mlflow.createExperiment('My Experiment');
+	console.log('Experiment created successfully');
+}
+
+createExperiment();
+
+```
+
+<br>
+
+## Resources
+
+- [Example Repository](https://github.com/oslabs-beta/mlflow-js/tree/dev/mlflow/examples) - Practical examples demonstrating <i>MLflow.js</i>'s functionality
+- [Quick Tutorials](https://www.mlflow-js.org/) - Video walkthrough of the example code with MLflow UI
+- [Read our Medium Article](link) - Overview on why we built <i>MLflow.js</i> and how it enhances ML workflows in JavaScript environments
+
+<br>
+
+## Documentation
+
+Official documentation for <i>MLflow.js</i> can be found <a href="https://www.mlflow-js.org/documentation">here</a>.
+
+### High-Level Workflows
+
+**Experiment Manager**
+
+- runExistingExperiment - Full workflow of creating, naming, and starting a run under an existing experiment, logging metrics, params, tags, and the model, and finishing the run
+- runNewExperiment - Full workflow of creating, naming, and starting a run under a new experiment, logging metrics, params, tags, and the model, and finishing the run
+- experimentSummary - Returns an array of all the passed-in experiment's runs, sorted according to the passed-in metric
+
+**Run Manager**
+
+- cleanupRuns - Deletes runs that do not meet certain criteria and return an object of deleted runs and details
+- copyRun - Copies a run from one experiment to another (without artifacts and models)
+
+**Model Manager**
+
+- createRegisteredModelWithVersion - Creates a new registered model and the first version of that model
+- updateRegisteredModelDescriptionAndTag - Updates a registered model's description and tags
+- updateAllLatestModelVersion - Updates the latest version of the specified registered model's description, adds a new alias, and tag key/value for the latest version
+- setLatestModelVersionTag - Adds a new tag key/value for the latest version of the specified registered model
+- setLatestModelVersionAlias - Adds an alias for the latest version of the specified registered model
+- updateLatestModelVersion - Updates the description of the latest version of a registered model
+- updateAllModelVersion - Updates the specified version of the specified registered model's description and adds a new alias and tag key/value for that specified version
+- deleteLatestModelVersion - Deletes the latest version of the specified registered model
+- createModelFromRunWithBestMetric - Creates a new model with the specified model name from the run with the best specified metric
+
+<br>
+
+## Contributing
+
+We welcome contributions to <i>MLflow.js</i>! Please see our [Contributing Guide](/CONTRIBUTING.md) for more details on how to get started.
+
+<br>
+
+## License
+
+[MIT License](/LICENSE)
+
+<br>
+
+## Meet The Team
+
+| Name           | GitHub                                                                                                                    | LinkedIn                                                                                                                                                 |
+| -------------- | ------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| Yiqun Zheng    | [![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github)](https://github.com/yiqunzheng)    | [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/yiqunzheng/)   |
+| Kyler Chiago   | [![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github)](https://github.com/Kyler-Chiago)  | [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/kyler-chiago/) |
+| Austin Fraser  | [![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github)](https://github.com/austinbfraser) | [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](http://www.linkedin.com/in/austin-fraser)  |
+| Stephany Ho    | [![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github)](https://github.com/seneyu)        | [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/stephanyho/)   |
+| Winston Ludlam | [![GitHub](https://img.shields.io/badge/GitHub-181717?style=for-the-badge&logo=github)](https://github.com/winjolu/)      | [![LinkedIn](https://img.shields.io/badge/LinkedIn-0077B5?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/wjludlam/)     |

mlflow-site/.eslintrc.json

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+{
+  "extends": ["next/core-web-vitals", "next/typescript"]
+}

mlflow-site/.gitignore

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+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+.yarn/install-state.gz
+
+# testing
+/coverage
+
+# next.js
+/.next/
+/out/
+
+# production
+/build
+
+# misc
+.DS_Store
+../.DS_Store
+*.pem
+
+# debug
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+# local env files
+.env*.local
+
+# vercel
+.vercel
+
+# typescript
+*.tsbuildinfo
+next-env.d.ts

mlflow-site/README.md

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+## Getting Started
+
+First, run the development server:
+
+```bash
+npm run dev
+# or
+yarn dev
+# or
+pnpm dev
+# or
+bun dev
+```
+
+Open [http://localhost:3000](http://localhost:3000) with your browser to see the result.

mlflow-site/next.config.mjs

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+/** @type {import('next').NextConfig} */
+const nextConfig = {
+    images: {
+        remotePatterns: [
+            {
+                protocol: 'https',
+                hostname: 'i.giphy.com'
+            },
+        ],
+    },
+};
+
+export default nextConfig;