Ajout de la documentation et de la configuration Backstage.io

catalog-info.yaml

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+apiVersion: backstage.io/v1alpha1
+kind: Component
+metadata:
+  name: wine-quality-predictor
+  description: A machine learning service for predicting wine quality based on chemical properties
+  annotations:
+    github.com/project-slug: wine-quality-predictor
+    backstage.io/techdocs-ref: dir:./docs
+  tags:
+    - fastapi
+    - python
+    - machine-learning
+    - wine
+spec:
+  type: service
+  lifecycle: experimental
+  owner: data-science-team
+  system: ml-services

docs/index.md

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+# Wine Quality Predictor
+
+## Overview
+
+This is a machine learning service that predicts wine quality based on chemical properties. The service uses a pre-trained machine learning model and provides an API endpoint for predictions.
+
+## Features
+
+- Wine quality prediction based on chemical properties
+- RESTful API for programmatic access
+- Detailed input validation
+- Comprehensive documentation
+
+## Architecture
+
+The service is built using:
+- FastAPI for the web framework
+- Scikit-learn for the machine learning model
+- Pandas and NumPy for data handling
+- Pydantic for input validation
+
+## Documentation
+
+- [API Reference](api-reference.md)
+- [Model Information](model-info.md)
+- [Getting Started](getting-started.md)

mkdocs.yml

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+site_name: 'Wine Quality Predictor'
+nav:
+  - Home: index.md
+  - API Reference: api-reference.md
+  - Model Information: model-info.md
+  - Getting Started: getting-started.md
+plugins:
+  - techdocs-core
+markdown_extensions:
+  - admonition
+  - pymdownx.highlight
+  - pymdownx.superfences