suite

.env copy

@@ -1 +1 @@
-MODEL_REGISTRY = "local"
+MODEL_REGISTRY = "local"

.github/workflows/ci.yml

@@ -0,0 +1,31 @@
+name: CI
+
+on:
+  push:
+    branches:
+      - 0-Starter-productionizing-ml
+      - main
+      - master
+  pull_request:
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: code checkout
+        uses: actions/checkout@v4
+
+      - name: isntall Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install poetry
+        run: pip install poetry
+
+      - name: Install dependencies
+        run: poetry install
+
+      - name: launch Makefile
+        run: make lint-all

.gitignore

@@ -2,6 +2,7 @@
 .venv/
 .python-version
 .ipynb_checkpoints/
+__pycache__/
 
 # Data
 data/
@@ -13,4 +14,9 @@ models/
 
 # Env
 .env
-.envrc
+.envrc
+
+# MLflow
+mlartifacts/
+mlruns/
+mlflow.db

.mlflow.pid

@@ -0,0 +1 @@
+78638

Makefile

@@ -0,0 +1,30 @@
+.PHONY: lint lint-fix format lint-all
+
+lint:
+	@echo "checking lint with ruff"
+	poetry run ruff check .
+
+lint-fix:
+	@echo "auto fix lint with ruff"
+	poetry run ruff check . --fix
+
+format:
+	@echo "checking format" 
+	poetry run ruff format .
+
+lint-all: lint-fix lint format
+
+.PHONY: start-mlflow stop-mlflow
+MLFLOW_PORT=5000
+MLFLOW_PID_FILE=.mlflow.pid
+
+start-mlflow:
+	mlflow ui --backend-store-uri sqlite:///models/mlflow.db -port $(MLFLOW_PORT) & echo $$! > $(MLFLOW_PID_FILE)
+
+stop-mlflow:
+	@if [ -f $(MLFLOW_PID_FILE) ]; then \
+		kill `cat $(MLFLOW_PID_FILE)` && rm $(MLFLOW_PID_FILE); \
+		echo "MLflow server stopped"; \
+	else \
+		echo "No MLflow server running"; \
+	fi

api/data_model.py

@@ -0,0 +1,18 @@
+from pydantic import BaseModel
+
+class Diamond(BaseModel):
+    carat: float
+    cut: str
+    color: str
+    clarity: str
+    depth: float
+    table: float
+    x: float
+    y: float
+    z: float
+
+class DiamondResponse(Diamond):
+    price: float
+
+class Diamonds(BaseModel):
+    diamonds: list[Diamond]

api/rest.py

@@ -0,0 +1,23 @@
+import pandas as pd
+from fastapi import FastAPI
+from src.diamonds.registry import load_model
+from .data_model import Diamond, DiamondResponse
+
+app = FastAPI(
+    title="Diamond API",
+    description="api to get diamond price",
+    version="0.1.0"
+)
+
+model = load_model("model", "local")
+
+@app.get("/")
+def read_root():
+    return {"Hello": "World"}
+
+@app.post("/price")
+def predict_price(diamond: Diamond):
+    diamond_df = pd.Dataframe([diamond.model_dump()])
+    prediction = model.predict(diamond_df)
+    diamond_reponse = DiamondResponse(**diamond.model_dump(), price=prediction[0])
+    return diamond_reponse

comments.txt

@@ -0,0 +1,2 @@
+hello, this is yufo
+great jcc