Merge branch 'develop' into feature/db_schema_setup

.github/workflows/ci.yml

@@ -16,16 +16,15 @@ jobs:
     steps:
       - uses: actions/setup-python@v5
         with:
-          python-version: "3.11"
+          python-version: "3.11.9"
 
       - uses: actions/checkout@v4
 
-      - name: Install dependencies
-        run: |
-          pip install .
-          pip install -r requirements.txt
-          pip install pytest
-
-      - name: Run tests
-        run: pytest
-
+      - name: Install Poetry 
+        run: pip install poetry 
+      
+      - name: Install dependencies with Poetry 
+        run: poetry install --no-interaction --no-root 
+        
+      - name: Run tests 
+        run: poetry run pytest

.gitignore

@@ -4,7 +4,7 @@ venv/
 .venv/
 .pytest_cache/
 .coverage
-App/model
-App/model/modele_final_xgb.joblib
+App/modl/
 *.joblib
 *.json
+App/model/modele_final_xgb.joblib

App/main.py

@@ -8,6 +8,10 @@ app = FastAPI(
     version="0.1.0"
 )
 
+@app.get("/") 
+def root(): 
+    return {"status": "API OK"}
+
 @app.post("/predict")
 def predict(data: EmployeeFeatures):
     """

App/predict.py

@@ -3,10 +3,9 @@ import pandas as pd
 from App.schemas import EmployeeFeatures
 import json
 from pathlib import Path
+from huggingface_hub import hf_hub_download
 
-# Chemin des fichiers
-chemin_model = Path("App/model/modele_final_xgb.joblib")
-chemin_mapping = Path("App/model/mapping_classes.json")
+MODEL_REPO = "Diaure/xgb_model"
 
 # Variables chargées
 model = None
@@ -14,17 +13,21 @@ classes_mapping = None
 Features = list(EmployeeFeatures.model_fields.keys())
 
 
+
 # Chargement des fichiers: fonction pour charger le modèle, le mapping afin de permettre à l'API de démarrer m^me si les éléments ne sont pas présents
 def files_load():
     global model, classes_mapping
+
     if model is None:
-        if not chemin_model.exists():
-            raise RuntimeError("Eléments du modèle introuvable.")
+        chemin_model = Path(hf_hub_download(repo_id=MODEL_REPO, filename="modele_final_xgb.joblib"))
+        # if not chemin_model.exists():
+        #     raise RuntimeError("Eléments du modèle introuvable.")
         model =joblib.load(chemin_model)
 
     if classes_mapping is None:
-        if not chemin_mapping.exists():
-            raise RuntimeError("Mapping des classes introuvable.")
+        chemin_mapping = Path(hf_hub_download(repo_id=MODEL_REPO, filename="mapping_classes.json"))
+        # if not chemin_mapping.exists():
+        #     raise RuntimeError("Mapping des classes introuvable.")
         with open(chemin_mapping) as f:
             classes_mapping = json.load(f)
 

Dockerfile

@@ -0,0 +1,13 @@
+# force rebuild
+FROM python:3.11
+
+WORKDIR /code
+
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 7860
+
+CMD ["uvicorn", "App.main:app", "--host", "0.0.0.0", "--port", "7860"]

README.md

@@ -1,3 +1,13 @@
+---
+title: Futurisys ML API
+emoji: 🚀
+colorFrom: blue
+colorTo: green
+sdk: docker
+pinned: false
+---
+
+
 # Futurisys – Déploiement d’un modèle de Machine Learning via API
 
 ## Contexte

pyproject.toml

@@ -21,11 +21,17 @@ dependencies = [
     "catboost ==1.2.7",
     "numba ==0.59.1",
     "llvmlite ==0.42.0",
-    "ipykernel>=6.25,<7.0"
+    "ipykernel>=6.25,<7.0",
+    "huggingface-hub ==1.3.1",
+    "fastapi ==0.115.0",
+    "uvicorn ==0.30.1"
 ]
 
-
 [build-system]
 requires = ["poetry-core>=2.0.0,<3.0.0"]
 build-backend = "poetry.core.masonry.api"
 
+[tool.poetry.group.dev.dependencies]
+pytest = "9.0.2"
+
+

requirements.txt

@@ -6,4 +6,10 @@ Pygments==2.19.2
 pytest==9.0.2
 fastapi==0.115.0 
 uvicorn==0.30.1 
-httpx==0.27.0
+httpx==0.27.0
+huggingface-hub==1.3.1
+joblib==1.4.2
+pandas==2.2.2
+scikit-learn==1.4.2
+xgboost ==2.0.3
+huggingface-hub ==1.3.1