feat: add ML service scaffolding with Python FastAPI, Docker, and MLflow setup

services/ml/pyproject.toml

@@ -0,0 +1,28 @@
+[project]
+name = "candle-ml"
+version = "0.1.0"
+description = "ML service for candlestick pattern recognition"
+requires-python = ">=3.11"
+dependencies = [
+    "fastapi>=0.109.0",
+    "uvicorn[standard]>=0.27.0",
+    "scikit-learn>=1.4.0",
+    "xgboost>=2.0.3",
+    "pandas>=2.2.0",
+    "numpy>=1.26.0",
+    "joblib>=1.3.2",
+    "mlflow>=2.10.0",
+    "pyyaml>=6.0.1",
+    "TA-Lib>=0.4.28",
+    "dvc>=3.40.0",
+    "sqlalchemy>=2.0.25",
+    "psycopg2-binary>=2.9.9",
+    "pydantic>=2.5.0",
+    "pydantic-settings>=2.1.0",
+    "matplotlib>=3.8.2",
+    "seaborn>=0.13.1",
+]
+
+[build-system]
+requires = ["setuptools>=61.0"]
+build-backend = "setuptools.build_meta"