Feat/use uv instead of poetry

.github/ISSUE_TEMPLATE/feat-request.md

@@ -10,4 +10,4 @@ assignees: callmesora
 
 ## Motivation
 
-## Solutions
+## Solutions

.github/ISSUE_TEMPLATE/fix-request.md

@@ -12,4 +12,4 @@ assignees: callmesora
 
 ## Steps to Reproduce
 
-## Additional Context
+## Additional Context

.github/PULL_REQUEST_TEMPLATE.md

@@ -6,4 +6,4 @@
 
 # Impacts
 
-# Notes
+# Notes

.github/actions/setup/action.yml

@@ -3,9 +3,9 @@ description: Setup for project workflows
 runs:
   using: composite
   steps:
-    - run: pipx install invoke poetry
+    - run: pipx install invoke uv
       shell: bash
     - uses: actions/setup-python@v5
       with:
         python-version: 3.12
-        cache: poetry
+        cache: uv

.github/workflows/check.yml

@@ -12,10 +12,9 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - uses: ./.github/actions/setup
-      - run: poetry install --with checks
-      - run: poetry run invoke checks.format
-      - run: poetry run invoke checks.code
-      - run: poetry run invoke checks.type
-      - run: poetry run invoke checks.security
+      - run: uv sync --group checks
+      - run: uv run invoke checks.format
+      - run: uv run invoke checks.code
+      - run: uv run invoke checks.type
+      - run: uv run invoke checks.security
       # TODO: Add tests once figuring out how to mock mlflow and qdrant
-

.github/workflows/publish.yml

@@ -15,8 +15,8 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - uses: ./.github/actions/setup
-      - run: poetry install --with docs
-      - run: poetry run invoke docs
+      - run: uv sync --group docs
+      - run: uv run invoke docs
       - uses: JamesIves/github-pages-deploy-action@v4
         with:
           folder: docs/
@@ -28,8 +28,8 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - uses: ./.github/actions/setup
-      - run: poetry install --with dev
-      - run: poetry run invoke packages
+      - run: uv sync --group dev
+      - run: uv run invoke packages
       - uses: docker/login-action@v3
         with:
           registry: ghcr.io

.pre-commit-config.yaml

@@ -16,10 +16,11 @@ repos:
       - id: end-of-file-fixer
       - id: mixed-line-ending
       - id: trailing-whitespace
-  - repo: https://github.com/python-poetry/poetry
-    rev: 1.8.3
+  - repo: https://github.com/astral-sh/uv-pre-commit
+    # uv version.
+    rev: 0.5.8
     hooks:
-      - id: poetry-check
+      - id: uv-lock
   - repo: https://github.com/astral-sh/ruff-pre-commit
     rev: v0.5.0
     hooks:
@@ -30,4 +31,4 @@ repos:
     hooks:
       - id: commitizen
       - id: commitizen-branch
-        stages: [push]
+        stages: [pre-push]

CODE_OF_CONDUCT.md

@@ -125,4 +125,4 @@ enforcement ladder](https://github.com/mozilla/diversity).
 
 For answers to common questions about this code of conduct, see the FAQ at
 https://www.contributor-covenant.org/faq. Translations are available at
-https://www.contributor-covenant.org/translations.
+https://www.contributor-covenant.org/translations.

LICENCE.txt

@@ -4,4 +4,4 @@ Permission is hereby granted, free of charge, to any person obtaining a copy of
 
 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.
+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

@@ -23,58 +23,30 @@ This package is a variation / fork of these resources but specicially tailored f
 
 # Table of Contents
 
-- [LLMOps Python Package](#mlops-python-package)
+- [LLMOps Python Pacakge](#llmops-python-pacakge)
 - [Table of Contents](#table-of-contents)
+- [Architecture](#architecture)
+  - [RAG Evaluation](#rag-evaluation)
+  - [Model Registry](#model-registry)
+  - [Guardrails](#guardrails)
+  - [Endpoint Deployment](#endpoint-deployment)
+  - [Model Monitoring](#model-monitoring)
+  - [LLMOps Design Pattern](#llmops-design-pattern)
 - [Install](#install)
   - [Prerequisites](#prerequisites)
+  - [Credentials for LLM](#credentials-for-llm)
   - [Installation](#installation)
   - [Next Steps](#next-steps)
 - [Usage](#usage)
   - [Configuration](#configuration)
   - [Execution](#execution)
+  - [Pipelines](#pipelines)
+    - [Generate Rag Dataset](#generate-rag-dataset)
+    - [Feature Engineering](#feature-engineering)
+    - [Deployment](#deployment)
+    - [Monitoring](#monitoring)
   - [Automation](#automation)
-  - [Workflows](#workflows)
 - [Tools](#tools)
-  - [Automation](#automation-1)
-    - [Commits: Commitizen](#commits-commitizen)
-    - [Git Hooks: Pre-Commit](#git-hooks-pre-commit)
-    - [Tasks: PyInvoke](#tasks-pyinvoke)
-  - [CI/CD](#cicd)
-    - [Runner: GitHub Actions](#runner-github-actions)
-  - [CLI](#cli)
-    - [Parser: Argparse](#parser-argparse)
-    - [Logging: Loguru](#logging-loguru)
-  - [Code](#code)
-    - [Coverage: Coverage](#coverage-coverage)
-    - [Editor: VS Code](#editor-vs-code)
-    - [Formatting: Ruff](#formatting-ruff)
-    - [Quality: Ruff](#quality-ruff)
-    - [Security: Bandit](#security-bandit)
-    - [Testing: Pytest](#testing-pytest)
-    - [Typing: Mypy](#typing-mypy)
-    - [Versioning: Git](#versioning-git)
-  - [Configs](#configs)
-    - [Format: YAML](#format-yaml)
-    - [Parser: OmegaConf](#parser-omegaconf)
-    - [Reader: Cloudpathlib](#reader-cloudpathlib)
-    - [Validator: Pydantic](#validator-pydantic)
-  - [Model](#model)
-    - [Format: Mlflow Model](#format-mlflow-model)
-    - [Registry: Mlflow Registry](#registry-mlflow-registry)
-    - [Tracking: Mlflow Tracking](#tracking-mlflow-tracking)
-  - [Package](#package)
-    - [Evolution: Changelog](#evolution-changelog)
-    - [Format: Wheel](#format-wheel)
-    - [Manager: Poetry](#manager-poetry)
-    - [Runtime: Docker](#runtime-docker)
-  - [Programming](#programming)
-    - [Language: Python](#language-python)
-    - [Version: Pyenv](#version-pyenv)
-  - [Observability](#observability)
-    - [Monitoring : Mlflow Evaluate](#monitoring--mlflow-evaluate)
-    - [Infrastructure: Mlflow System Metrics](#infrastructure-mlflow-system-metrics)
-  - [Model Serving](#endpoint)
-    - [Serving Endpoint: Litserve](#serving-endpoint)
 - [Tips](#tips)
   - [Design Patterns](#design-patterns)
     - [Directed-Acyclic Graph](#directed-acyclic-graph)
@@ -96,6 +68,7 @@ This package is a variation / fork of these resources but specicially tailored f
   - [VS Code](#vs-code)
     - [Code Workspace](#code-workspace)
     - [GitHub Copilot](#github-copilot)
+    - [VSCode VIM](#vscode-vim)
 - [Resources](#resources)
   - [Python](#python)
   - [AI/ML/MLOps](#aimlmlops)
@@ -154,17 +127,16 @@ This section details the requirements, actions, and next steps to kickstart your
 
 ## Prerequisites
 
-- [Python>=3.10](https://www.python.org/downloads/): to benefit from [the latest features and performance improvements](https://docs.python.org/3/whatsnew/3.12.html)
-- [Poetry>=1.8.2](https://python-poetry.org/): to initialize the project [virtual environment](https://docs.python.org/3/library/venv.html) and its dependencies
+- [UV>=0.5.11](https://docs.astral.sh/uv/): to initialize the project [virtual environment](https://docs.python.org/3/library/venv.html) and its dependencies
 
-Use the package manager [Poetry](https://python-poetry.org/):
+Use the package manager [UV](https://docs.astral.sh/uv/):
 
 ## Credentials for LLM
 
 To access Bedrock, OpenAI, or any other LLM provider, you need to set up your  credentials. These credentials will allow the package to authenticate and interact with the respective services.
 In this code template we used Bedrock but feel free to change it to your needs.
 
-Example for AWS 
+Example for AWS
 
  **Environment Variables**:
     ```bash
@@ -174,7 +146,7 @@ Example for AWS
     ```
 
 
-  - You can easily replace `ChatBedrock` with `ChatOllama` or any other provider. 
+  - You can easily replace `ChatBedrock` with `ChatOllama` or any other provider.
 
 
 ## Installation
@@ -186,10 +158,10 @@ $ git clone -
 # with https
 $ git clone -
 ```
-2. [Run the project installation with poetry](https://python-poetry.org/docs/)
+2. [Run the project installation with UV](https://docs.astral.sh/uv/)
 ```bash
 $ cd llmops-python-package/
-$ poetry install
+$ uv sync --all-groups
 ```
 3. Adapt the code base to your desire
 
@@ -225,17 +197,17 @@ job:
 This config file instructs the program to start a `DeploymentJob` with respective parameters
 You can find all the parameters of your program in the `src/[package]/pipelines/*.py` files.
 
-You can also print the full schema supported by this package using `poetry run llmops --schema`.
+You can also print the full schema supported by this package using `uv run llmops --schema`.
 
 ## Execution
 
-The project code can be executed with poetry during your development, this is the order recommended:
+The project code can be executed with UV during your development, this is the order recommended:
 
 ```bash
-$ poetry run llmops-project confs/generate_rag_dataset.yaml # Run once to generate rag dataset
-$ poetry run llmops-project confs/feature_eng.yaml # Creates Vector DB and Injests documents
-$ poetry run llmops-project confs/deployment.yaml # Deploys model on model registry
-$ poetry run llmops-project confs/monitoring.yaml # Monitors Model Inferences "every week"
+$ uv run llmops-project confs/generate_rag_dataset.yaml # Run once to generate rag dataset
+$ uv run llmops-project confs/feature_eng.yaml # Creates Vector DB and Injests documents
+$ uv run llmops-project confs/deployment.yaml # Deploys model on model registry
+$ uv run llmops-project confs/monitoring.yaml # Monitors Model Inferences "every week"
 ```
 
 To deploy the serving endpoint you can use the following automation:
@@ -252,13 +224,13 @@ This project is organized under a manager pattern, each manager is responsible f
 ### Generate Rag Dataset
 This pipeline generates a rag QA dataset under `/data/datasets/``
 
-### Feature Engineering 
+### Feature Engineering
 This pipeline creates a Vector Database instance collection and ingests documents onto it in the form of vectors.
 ![Vector Database](static/vector_db.png)
 
-### Deployment 
+### Deployment
 This pipeline:
--  registers a model using Mlflow 
+-  registers a model using Mlflow
 -  promote the model to `champion`alias
 -  validates model input /output and singatures
 -  sets tag "passed_tests" on mlflow registry to True/False depending if model passed tests
@@ -283,8 +255,8 @@ These metrics are also saved with a display in case you want to load it in a das
 In production, you can build, ship, and run the project as a Python package:
 
 ```bash
-poetry build
-poetry publish # optional
+uv build
+uv publish # optional
 python -m pip install [package]
 [package] confs/deployment.yaml
 ```
@@ -326,7 +298,7 @@ $ inv --list
 - **checks.code** - Check the codes with ruff.
 - **checks.coverage** - Check the coverage with coverage.
 - **checks.format** - Check the formats with ruff.
-- **checks.poetry** - Check poetry config files.
+- **checks.uv** - Check uv config files.
 - **checks.security** - Check the security with bandit.
 - **checks.test** - Check the tests with pytest.
 - **checks.type** - Check the types with mypy.
@@ -340,7 +312,7 @@ $ inv --list
 - **cleans.mlruns** - Clean the mlruns folder.
 - **cleans.mypy** - Clean the mypy tool.
 - **cleans.outputs** - Clean the outputs folder.
-- **cleans.poetry** - Clean poetry lock file.
+- **cleans.uv** - Clean uv lock file.
 - **cleans.pytest** - Clean the pytest tool.
 - **cleans.projects** - Run all projects tasks.
 - **cleans.python** - Clean python caches and bytecodes.
@@ -365,7 +337,7 @@ $ inv --list
 - **formats.imports** - Format python imports with ruff.
 - **formats.sources** - Format python sources with ruff.
 - **installs.all (installs)** - Run all install tasks.
-- **installs.poetry** - Install poetry packages.
+- **installs.uv** - Install uv packages.
 - **installs.pre-commit** - Install pre-commit hooks on git.
 - **mlflow.all (mlflow)** - Run all mlflow tasks.
 - **mlflow.doctor** - Run mlflow doctor to diagnose issues.
@@ -467,10 +439,10 @@ Using Python package for your AI/ML project has the following benefits:
 - Install Python package as a library (e.g., like pandas)
 - Expose script entry points to run a CLI or a GUI
 
-To build a Python package with Poetry, you simply have to type in a terminal:
+To build a Python package with UV, you simply have to type in a terminal:
 ```bash
-# for all poetry project
-poetry build
+# for all uv project
+uv build
 # for this project only
 inv packages
 ```
@@ -524,7 +496,7 @@ Semantic Versioning (SemVer) provides a simple schema to communicate code change
 - *Minor* (Y): minor release with new features (i.e., provide new capabilities)
 - *Patch* (Z): patch release to fix bugs (i.e., correct wrong behavior)
 
-Poetry and this package leverage Semantic Versioning to let developers control the speed of adoption for new releases.
+UV and this package leverage Semantic Versioning to let developers control the speed of adoption for new releases.
 
 ## [Testing Tricks](https://en.wikipedia.org/wiki/Software_testing)
 
@@ -596,8 +568,3 @@ This section provides resources for building packages for Python and AI/ML/MLOps
 
 - https://github.com/josephmisiti/awesome-machine-learning
 - https://github.com/visenger/awesome-mlops
-
-
-
-
-

confs/deployment.yaml

@@ -5,10 +5,10 @@ job:
   registry_model_name: "rag-chatbot-with-guardrails"
   llm_confs: "/confs/rag_chain_config.yaml"
   llm_model_code_path: "/src/llmops_project/models/chatbot_with_guardrails.py"
-  vector_store_path: "https://34beb054-2278-47fe-9731-cd7ed574320f.eu-west-2-0.aws.cloud.qdrant.io:6333" #"http://localhost:6333"
+  vector_store_path: "http://localhost:6333" 
   qa_dataset_path: "/data/datasets/rag_dataset.csv"
   alias: "champion"
 
   metric_tresholds:
     flesch_kincaid_grade_level_mean: 5.1 # bigger than
-    ari_grade_level_mean: 4.1 # bigger than
+    ari_grade_level_mean: 4.1 # bigger than

confs/feature_eng.yaml

@@ -1,6 +1,6 @@
 job:
   KIND: FeatureEngineeringJob
-  embedding_model: "amazon.titan-embed-text-v1" 
-  vector_store_path: "http://localhost:6333" 
+  embedding_model: "amazon.titan-embed-text-v1"
+  vector_store_path: "http://localhost:6333"
   document_path: "/data/documents/"
-  collection_name: "hr-documents"
+  collection_name: "hr-documents"

confs/generate_rag_dataset.yaml

@@ -4,4 +4,3 @@ job:
   qa_dataset_path_csv: "data/datasets/rag_dataset.csv" # will save a QA dataset in csv and json
   qa_dataset_path_json: "data/datasets/rag_dataset.json" # will save a QA dataset in csv and json
   llm_model: "anthropic.claude-3-haiku-20240307-v1:0" # model_id to generate the QA dataset
-

confs/monitoring.yaml

@@ -5,4 +5,3 @@ job:
 
   trace_experiment_name: "rag_chatbot_experiment"
   monitoring_experiment_name: "monitoring"
-

confs/rag_chain_config.yaml

@@ -8,7 +8,7 @@ guardrail_config:
       - leadership
       - management
       - productivity
-      
+
     invalid:
       - software programming
       - religion
@@ -29,7 +29,7 @@ output_example:
   sources:
     - "example_source_1.pdf"
     - "example_source_2.pdf"
-  
+
 llm_config:
   llm_model: anthropic.claude-3-haiku-20240307-v1:0
   llm_parameters: