Déploiement automatique depuis GitLab CI

5_Notebooks/mlartifacts/1/models/m-c06ca7184d99459a87df34d662e183c5/artifacts/model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:ee985276707b479db2f000d76455b7c48c0a72704218f7b373ae576eeeee50dd
+size 28419612

Dockerfile

@@ -18,7 +18,7 @@ RUN pip install --no-cache-dir --upgrade pip && \
 COPY --chown=user main.py .
 COPY --chown=user config.py .
 COPY --chown=user 2_Data_transformed/crop_yield_2_train_set_simplified.csv ./2_Data_transformed/
-COPY --chown=user 5_Notebooks/mlruns/2/models/m-7d0b2bca11e140be907efb132e749af8/artifacts/model.pkl ./5_Notebooks/mlruns/2/models/m-7d0b2bca11e140be907efb132e749af8/artifacts/
+COPY --chown=user 5_Notebooks/mlartifacts/1/models/m-c06ca7184d99459a87df34d662e183c5/artifacts/model.pkl ./5_Notebooks/mlartifacts/1/models/m-c06ca7184d99459a87df34d662e183c5/artifacts/
 COPY --chown=user 8_Tests/test_functional.py ./8_Tests/
 
 # ============================================

config.py

@@ -11,7 +11,7 @@ ALL_COLUMNS = FEATURE_COLUMNS + [TARGET_COLUMN]
 YEAR_THRESHOLD = 2009
 
 # Chemin relatif vers le modèle MLflow (pipeline sklearn complet avec préprocesseur)
-MODEL_REL_PATH = "5_Notebooks/mlruns/2/models/m-7d0b2bca11e140be907efb132e749af8/artifacts"
+MODEL_REL_PATH = "5_Notebooks/mlartifacts/1/models/m-c06ca7184d99459a87df34d662e183c5/artifacts"
 
 # ========================================================================
 # Paramètres pour les services (Frontend et Backend)