migrate to uv

Author: fmind

.github/FUNDING.yml

@@ -1,4 +1,4 @@
 # These are supported funding model platforms
 
-# github: ["MLOps-Courses"]
+github: ["MLOps-Courses"]
 custom: ["https://donate.stripe.com/4gw8xT9oVbCc98s7ss"]

.github/workflows/assign.yml

@@ -0,0 +1,19 @@
+name: Auto Assign
+on:
+  issues:
+    types: [opened]
+  pull_request:
+    types: [opened]
+jobs:
+  run:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+      pull-requests: write
+    steps:
+    - name: 'Auto-assign issue'
+      uses: pozil/auto-assign-issue@v1
+      with:
+          repo-token: ${{ secrets.GITHUB_TOKEN }}
+          assignees: fmind
+          numOfAssignee: 1

.github/workflows/publish.yml

@@ -12,12 +12,14 @@ jobs:
   pages:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v4
-      - run: pipx install invoke poetry
-        shell: bash
-      - uses: actions/setup-python@v5
-        with:
-          python-version: 3.12
-          cache: poetry
-      - run: poetry install
-      - run: poetry run invoke deploy
+    - name: Checkout
+      uses: actions/checkout@v4
+    - name: Install uv
+      uses: astral-sh/setup-uv@v4
+      with:
+        enable-cache: true
+    - name: Setup Python
+      uses: actions/setup-python@v5
+      with:
+        python-version-file: .python-version
+    - run: uv run invoke deploy

README.md

@@ -8,14 +8,15 @@ Whether you are a beginner eager to explore or an experienced professional seeki
 
 **Related Resources:**
 - **[MLOps Python Package (Example)](https://github.com/fmind/mlops-python-package)**: Kickstart your MLOps initiative with a flexible, robust, and productive Python package.
+- **[LLMOps Coding Package (Example)](https://github.com/callmesora/llmops-python-package/)**: Example with best practices and tools to support your LLMOps projects.
 - **[Cookiecutter MLOps Package (Template)](https://github.com/fmind/cookiecutter-mlops-package)**: Start building and deploying Python packages and Docker images for MLOps tasks.
 
 ## Key Features
 
 - **Hands-on Python Coding**: Learn to code with Python in a way that's directly applicable to real-world AI projects.
 - **Project-Driven Learning**: Each chapter includes practical project instructions to help you apply what you've learned.
 - **MLOps Techniques**: Gain insights into effective MLOps coding strategies that streamline the development and deployment of AI/ML models.
-- **Open Source Tools**: Familiarize yourself with industry-standard tools like [poetry](https://python-poetry.org/), [pytest](https://docs.pytest.org/en/latest/), [pyenv](https://github.com/pyenv/pyenv), [ruff](https://docs.astral.sh/ruff/), [mlflow](https://mlflow.org/), [bandit](https://bandit.readthedocs.io/en/latest/), [pre-commit](https://pre-commit.com/), [GitHub](https://github.com/), and [VS Code](https://code.visualstudio.com/).
+- **Open Source Tools**: Familiarize yourself with industry-standard tools like [uv](https://docs.astral.sh/uv/), [pytest](https://docs.pytest.org/en/latest/), [pyenv](https://github.com/pyenv/pyenv), [ruff](https://docs.astral.sh/ruff/), [mlflow](https://mlflow.org/), [bandit](https://bandit.readthedocs.io/en/latest/), [pre-commit](https://pre-commit.com/), [GitHub](https://github.com/), and [VS Code](https://code.visualstudio.com/).
 - **Mentoring sessions**: Boost your learning experience with personalized feedback and expert insights from the course authors.
   - Book [a one-on-one mentoring session](https://calendar.app.google/9KfEBkpCHQKwarLF8) to receive tailored guidance and support on the course.
   - Contact the [course creators](mailto:[email protected]) to request a personalized quote for group and organization training.
@@ -37,7 +38,7 @@ Whether you are a beginner eager to explore or an experienced professional seeki
 To start contributing , you will need to set up your development environment:
 
 1. Clone the repository.
-2. Install dependencies using [Poetry](https://python-poetry.org/):
+2. Install dependencies using [uv](https://docs.astral.sh/uv/):
 
 ```bash
 invoke install
@@ -49,7 +50,7 @@ invoke install
 invoke serve
 ```
 
-You can then access the course at this URL from your computer: http://localhost:8000/mlops-coding-course/
+You can then access the course at this URL from your computer: http://localhost:8000/
 
 ## Contributions
 

mkdocs.yml

@@ -14,8 +14,8 @@ repo_url: https://github.com/MLOPS-Courses/mlops-coding-course
 copyright: Copyright © MLOps Courses
 
 # Configs
-use_directory_urls: false
 strict: true
+use_directory_urls: false
 
 # Theme
 theme:

mlops-coding-course.code-workspace

@@ -6,5 +6,5 @@
 	],
 	"settings": {
 		"python.defaultInterpreterPath": ".venv/bin/python"
-	},
+	}
 }