Merge pull request #108 from oslabs-beta/kyler/finalDocker

feat: Modified README.md and CONTRIBUTING.md

Author: yiqunzheng

CONTRIBUTING.md

@@ -9,26 +9,27 @@ We are always open to accepting any potential contributions. Here is how you can
 git clone https://github.com/your-username/repository-name.git
 ```
 
-3. Install dependencies for both mlflow and mlflow-site directories
+3. Create your feature branch
 
 ```bash
-cd mlflow && npm install
-cd ../mlflow-site && npm install
+git checkout -b feature/AmazingFeature
 ```
 
-4. Create your feature branch
+4. Install dependencies for both mlflow and mlflow-site directories
 
 ```bash
-git checkout -b feature/AmazingFeature
+cd /mlflow && npm install
+cd ../mlflow-site && npm install
 ```
 
-5. Run MLflow Tracking Server container with Docker
+5. Start the MLflow Tracking Server
 
 ```bash
-cd mlflow
-npm run docker
+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
@@ -42,13 +43,18 @@ npm run lint
    (Make sure you have mlflow UI server running on port 5002. We set 5002 as our default port for testing.)
 
 ```bash
-mlflow ui --port 5002 # Run this in a separate terminal
+cd /mlflow && npm run dockerTest # Run this in a separate terminal
 npm run test
 ```
 
-9. Commit your changes
+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'
 ```
 

README.md

@@ -60,10 +60,23 @@ pip install mlflow
 To start the MLflow tracking server locally, use the following command:
 
 ```bash
-mlflow ui --port 5000
+mlflow ui --port 5001
 ```
 
-This will launch the MLflow UI on your local machine at `http://localhost:5000`.
+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
 

mlflow/Dockerfile

@@ -7,9 +7,6 @@ RUN apt-get update && apt-get install -y \
     curl \
     git \
     && rm -rf /var/lib/apt/lists/*
-# RUN apt-get update 
-# RUN apt-get install -y gcc
-# RUN apt-get install -y curl
 # Copy package files
 # Uses package-lock.json for exact versions
 COPY package*.json ./

mlflow/docker-compose-test.yml

@@ -0,0 +1,27 @@
+# docker-compose.yml
+name: mlflowtest
+services:
+  # MLflow server for testing
+  mlflowtest:
+    # The latest mlflow docker image
+    image: ghcr.io/mlflow/mlflow
+    ports:
+      - "5002:5002"
+    command: mlflow server --host 0.0.0.0 --port 5002
+    healthcheck:
+      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:5002/health')"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+  # Development environment to ensure consistency across contributors
+  devtest:
+    build: 
+      context: .
+      dockerfile: Dockerfile
+    volumes:
+      - .:/mlflow  # Mount code for live development
+      - /mlflow/node_modules  # Keep node_modules in container
+    command: /bin/sh -c "while sleep 1000; do :; done"  # Keep container running
+    depends_on:
+      mlflowtest:
+        condition: service_healthy

mlflow/lib/tracking/ExperimentClient.d.ts

@@ -51,15 +51,15 @@ declare class ExperimentClient {
      * Mark an experiment for deletion.
      *
      * @param {string} experiment_id ID of the associated experiment.  (required)
-     * @returns {void}
+     * @returns {Promise<void>}
      * @throws {ApiError} If the API request fails
      */
     deleteExperiment(experiment_id: string): Promise<void>;
     /**
      * Restore an experiment marked for deletion.
      *
      * @param {string} experiment_id ID of the associated experiment.  (required)
-     * @returns {void}
+     * @returns {Promise<void>}
      * @throws {ApiError} If the API request fails
      */
     restoreExperiment(experiment_id: string): Promise<void>;
@@ -68,7 +68,7 @@ declare class ExperimentClient {
      *
      * @param {string} experiment_id ID of the associated experiment. (required)
      * @param {string} new_name The experiment’s name is changed to the new name. The new name must be unique. (required)
-     * @returns {void}
+     * @returns {Promise<void>}
      * @throws {ApiError} If the API request fails
      */
     updateExperiment(experiment_id: string, new_name: string): Promise<void>;
@@ -78,7 +78,7 @@ declare class ExperimentClient {
      * @param {string} experiment_id ID of the experiment under which to log the tag. (required)
      * @param {string} key Name of the tag.  (required)
      * @param {string} value String value of the tag being logged.  (required)
-     * @returns {void}
+     * @returns {Promise<void>}
      * @throws {ApiError} If the API request fails
      */
     setExperimentTag(experiment_id: string, key: string, value: string): Promise<void>;

mlflow/lib/tracking/ExperimentClient.js

@@ -1,3 +1,4 @@
+import { MetricHistoryResponse } from '../utils/interface.js';
 declare class RunClient {
     private baseUrl;
     constructor(trackingUri: string);
@@ -172,7 +173,7 @@ declare class RunClient {
      * @returns {Promise<MetricHistory>} A promise that resolves with the values for the specified metric.
      * @throws {ApiError} If the API request fails.
      */
-    getMetricHistory(run_id: string, metric_key: string, page_token?: string, max_results?: number): Promise<object>;
+    getMetricHistory(run_id: string, metric_key: string, page_token?: string, max_results?: number): Promise<MetricHistoryResponse>;
     /**
      * Search for runs that satisfy expressions. Search expressions can use Metric and Param keys.
      *
@@ -197,7 +198,7 @@ declare class RunClient {
      * @returns {Promise<SearchedRuns>} A promise that resovles with the runs that match the search criteria.
      * @throws {ApiError} If the API request fails.
      */
-    searchRuns(experiment_ids: Array<string>, filter: string, run_view_type?: 'ACTIVE_ONLY' | 'DELETED_ONLY' | 'ALL', max_results?: number, order_by?: Array<string>, page_token?: string): Promise<object>;
+    searchRuns(experiment_ids: Array<string>, filter?: string, run_view_type?: 'ACTIVE_ONLY' | 'DELETED_ONLY' | 'ALL', max_results?: number, order_by?: Array<string>, page_token?: string): Promise<object>;
     /**
      * List artifacts for a run. Takes an optional artifact_path prefix which if specified, the response contains only
      * artifacts with the specified prefix.