Added API endpoint to access ML models

api/main.py

@@ -0,0 +1,29 @@
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from models.linear_regression import LinearRegressionModel
+from models.logistic_regression import LogisticRegressionModel
+
+app = FastAPI(title="ML Simulator API", version="1.0")
+
+# Example input format
+class ModelInput(BaseModel):
+    model_name: str
+    features: list[float]
+
+@app.post("/predict")
+def predict(data: ModelInput):
+    model_name = data.model_name.lower()
+    features = data.features
+
+    if model_name == "linear_regression":
+        model = LinearRegressionModel()
+    elif model_name == "logistic_regression":
+        model = LogisticRegressionModel()
+    else:
+        raise HTTPException(status_code=400, detail="Model not found")
+
+    try:
+        prediction = model.predict(features)
+        return {"model": model_name, "prediction": prediction}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))

models/linear_regression.py

@@ -0,0 +1,11 @@
+import numpy as np
+
+class LinearRegressionModel:
+    def __init__(self):
+        # Placeholder coefficients
+        self.coefficients = [1.5, -0.7, 0.3]
+        self.bias = 2.0
+
+    def predict(self, features):
+        x = np.array(features)
+        return float(np.dot(self.coefficients, x) + self.bias)