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Merge pull request #114 from open-source-labs/readme
Fix: Update readme file and refactored test files to pass CI test
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README.md

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[![License: MIT](https://img.shields.io/badge/License-MIT-blue.svg)](/LICENSE)
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![Release](https://img.shields.io/badge/Release-v1.0.1-426B20)
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![Build](https://img.shields.io/badge/Build-Passing-brightgreen.svg)
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![Coverage](https://img.shields.io/badge/Coverage-87%25-c7ea46.svg)
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![Coverage](https://img.shields.io/badge/Coverage-89%25-c7ea46.svg)
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[![Contributions](https://img.shields.io/badge/Contributions-Welcome-brightgreen.svg)](/CONTRIBUTING.md)
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<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.
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**Note:** <i>MLflow.js</i> is a community-maintained project and is **not** affiliated with or endorsed by Databricks or the official MLflow maintainers.
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<br>
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## Features
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pip install mlflow
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```
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**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`.
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For MacOS users, we recommend creating and activating a Python virtual environment to avoid common installation issues and keep dependencies isolated:
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```bash
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python3 -m venv mlflow-venv
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source mlflow-venv/bin/activate
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pip install mlflow
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```
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Remember to activate your virtual environment (`source mlflow-venv/bin/activate`) each time you open a new terminal before running MLflow commands.
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### Start the MLflow Tracking Server
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To start the MLflow tracking server locally, use the following command:
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After activating the virtual environment, start the MLflow tracking server locally, use the following command:
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```bash
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mlflow ui --port 5001
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## Contributing
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We welcome contributions to <i>MLflow.js</i>! Please see our [Contributing Guide](/CONTRIBUTING.md) for more details on how to get started.
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We welcome contributions to <i>MLflow.js</i>! Please note that this library is maintained by independent community contributors, not the MLflow core team or Databricks. See our [Contributing Guide](/CONTRIBUTING.md) for more details on how to get started.
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<br>
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mlflow/lib/tracking/ExperimentClient.js

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mlflow/lib/tracking/ExperimentClient.js.map

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mlflow/lib/workflows/ExperimentManager.js

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mlflow/lib/workflows/ExperimentManager.js.map

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mlflow/src/tracking/RunClient.ts

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);
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}
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return data;
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return {
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metrics: data.metrics || [],
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next_page_token: data.next_page_token,
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};
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}
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/**

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