Add web UI with forms

app/main.py

@@ -1,7 +1,9 @@
 from fastapi import FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
 from fastapi.responses import JSONResponse
-from app.routers import health, predict, train
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+from app.routers import health, predict, train, ui
 from mlpipeline.exception import MLPipelineException
 import uvicorn
 
@@ -11,6 +13,9 @@ app = FastAPI(
     version="1.0.0"
 )
 
+app.mount("/static", StaticFiles(directory="app/static"), name="static")
+templates = Jinja2Templates(directory="app/templates")
+
 app.add_middleware(
     CORSMiddleware,
     allow_origins=["*"],
@@ -22,6 +27,7 @@ app.add_middleware(
 app.include_router(health.router)
 app.include_router(predict.router)
 app.include_router(train.router)
+app.include_router(ui.router)
 
 
 @app.exception_handler(MLPipelineException)
@@ -33,16 +39,8 @@ async def mlpipeline_exception_handler(request: Request, exc: MLPipelineExceptio
 
 
 @app.get("/")
-async def root():
-    return {
-        "message": "AutoML MLOps API",
-        "version": "1.0.0",
-        "endpoints": {
-            "health": "/health",
-            "predict": "/predict",
-            "train": "/train"
-        }
-    }
+async def root(request: Request):
+    return templates.TemplateResponse("index.html", {"request": request})
 
 
 if __name__ == "__main__":

app/routers/ui.py

@@ -0,0 +1,15 @@
+from fastapi import APIRouter, Request
+from fastapi.templating import Jinja2Templates
+
+router = APIRouter(prefix="/ui", tags=["ui"])
+templates = Jinja2Templates(directory="app/templates")
+
+
+@router.get("/predict")
+async def predict_page(request: Request):
+    return templates.TemplateResponse("predict.html", {"request": request})
+
+
+@router.get("/health")
+async def health_page(request: Request):
+    return templates.TemplateResponse("health.html", {"request": request})

app/static/style.css

@@ -0,0 +1,134 @@
+* {
+    margin: 0;
+    padding: 0;
+    box-sizing: border-box;
+}
+
+body {
+    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
+    background: #f5f7fa;
+    color: #333;
+}
+
+nav {
+    background: #2c3e50;
+    color: white;
+    padding: 1rem 2rem;
+    display: flex;
+    align-items: center;
+    gap: 2rem;
+    box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+}
+
+nav h1 {
+    font-size: 1.5rem;
+    margin-right: auto;
+}
+
+nav a {
+    color: white;
+    text-decoration: none;
+    padding: 0.5rem 1rem;
+    border-radius: 4px;
+    transition: background 0.3s;
+}
+
+nav a:hover {
+    background: #34495e;
+}
+
+.container {
+    max-width: 1200px;
+    margin: 2rem auto;
+    padding: 0 2rem;
+}
+
+.card {
+    background: white;
+    border-radius: 8px;
+    padding: 2rem;
+    margin-bottom: 2rem;
+    box-shadow: 0 2px 8px rgba(0,0,0,0.1);
+}
+
+.card h3 {
+    margin-bottom: 1rem;
+    color: #2c3e50;
+}
+
+.form-row {
+    display: grid;
+    grid-template-columns: 1fr 1fr;
+    gap: 1rem;
+    margin-bottom: 1rem;
+}
+
+.form-group {
+    display: flex;
+    flex-direction: column;
+}
+
+.form-group label {
+    font-weight: 600;
+    margin-bottom: 0.5rem;
+    color: #555;
+}
+
+.form-group input {
+    padding: 0.75rem;
+    border: 1px solid #ddd;
+    border-radius: 4px;
+    font-size: 1rem;
+}
+
+.form-group input:focus {
+    outline: none;
+    border-color: #3498db;
+}
+
+.btn {
+    background: #3498db;
+    color: white;
+    padding: 0.75rem 1.5rem;
+    border: none;
+    border-radius: 4px;
+    font-size: 1rem;
+    cursor: pointer;
+    text-decoration: none;
+    display: inline-block;
+    transition: background 0.3s;
+}
+
+.btn:hover {
+    background: #2980b9;
+}
+
+.actions {
+    display: flex;
+    gap: 1rem;
+    margin-top: 1rem;
+}
+
+h2 {
+    margin-bottom: 1.5rem;
+    color: #2c3e50;
+}
+
+p {
+    line-height: 1.6;
+    margin-bottom: 0.5rem;
+}
+
+@media (max-width: 768px) {
+    .form-row {
+        grid-template-columns: 1fr;
+    }
+    
+    .actions {
+        flex-direction: column;
+    }
+    
+    nav {
+        flex-wrap: wrap;
+    }
+}

app/templates/health.html

@@ -0,0 +1,68 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Status - AutoML MLOps</title>
+    <link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+    <nav>
+        <h1>AutoML MLOps Pipeline</h1>
+        <a href="/">Home</a>
+        <a href="/ui/predict">Predict</a>
+        <a href="/ui/health">Status</a>
+        <a href="/docs">API Docs</a>
+    </nav>
+    
+    <div class="container">
+        <h2>System Status</h2>
+        
+        <div class="card">
+            <h3>Health Check</h3>
+            <div id="healthStatus">Loading...</div>
+        </div>
+        
+        <div class="card">
+            <h3>Model Management</h3>
+            <button onclick="reloadModel()" class="btn">Reload Model</button>
+            <div id="reloadStatus"></div>
+        </div>
+    </div>
+    
+    <script>
+        async function checkHealth() {
+            try {
+                const response = await fetch('/health/');
+                const data = await response.json();
+                
+                const color = data.status === 'healthy' ? '#27ae60' : '#e74c3c';
+                document.getElementById('healthStatus').innerHTML = `
+                    <p><strong>Status:</strong> <span style="color: ${color}">${data.status.toUpperCase()}</span></p>
+                    <p><strong>Model Loaded:</strong> ${data.model_loaded ? 'Yes' : 'No'}</p>
+                    <p><strong>Message:</strong> ${data.message}</p>
+                `;
+            } catch (error) {
+                document.getElementById('healthStatus').innerHTML = `<p style="color: #e74c3c;">Error checking health</p>`;
+            }
+        }
+        
+        async function reloadModel() {
+            try {
+                const response = await fetch('/train/reload', {method: 'POST'});
+                const data = await response.json();
+                
+                document.getElementById('reloadStatus').innerHTML = `
+                    <p style="color: #27ae60; margin-top: 10px;">${data.message}</p>
+                `;
+                setTimeout(checkHealth, 1000);
+            } catch (error) {
+                document.getElementById('reloadStatus').innerHTML = `
+                    <p style="color: #e74c3c; margin-top: 10px;">Error reloading model</p>
+                `;
+            }
+        }
+        
+        checkHealth();
+        setInterval(checkHealth, 5000);
+    </script>
+</body>
+</html>

app/templates/index.html

@@ -0,0 +1,37 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>AutoML MLOps</title>
+    <link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+    <nav>
+        <h1>AutoML MLOps Pipeline</h1>
+        <a href="/">Home</a>
+        <a href="/ui/predict">Predict</a>
+        <a href="/ui/health">Status</a>
+        <a href="/docs">API Docs</a>
+    </nav>
+    
+    <div class="container">
+        <h2>Heart Disease Prediction System</h2>
+        <p>Welcome to the AutoML-powered heart disease prediction system.</p>
+        
+        <div class="card">
+            <h3>Quick Actions</h3>
+            <div class="actions">
+                <a href="/ui/predict" class="btn">Make Prediction</a>
+                <a href="/ui/health" class="btn">Check Status</a>
+                <a href="/docs" class="btn">View API</a>
+            </div>
+        </div>
+        
+        <div class="card">
+            <h3>System Information</h3>
+            <p><strong>Model:</strong> AutoGluon WeightedEnsemble</p>
+            <p><strong>Accuracy:</strong> 88.74%</p>
+            <p><strong>Features:</strong> 14 input features</p>
+        </div>
+    </div>
+</body>
+</html>

app/templates/predict.html

@@ -0,0 +1,147 @@
+<!DOCTYPE html>
+<html>
+<head>
+    <title>Predict - AutoML MLOps</title>
+    <link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+    <nav>
+        <h1>AutoML MLOps Pipeline</h1>
+        <a href="/">Home</a>
+        <a href="/ui/predict">Predict</a>
+        <a href="/ui/health">Status</a>
+        <a href="/docs">API Docs</a>
+    </nav>
+    
+    <div class="container">
+        <h2>Heart Disease Prediction</h2>
+        
+        <form id="predictionForm" class="card">
+            <div class="form-row">
+                <div class="form-group">
+                    <label>ID:</label>
+                    <input type="number" name="id" value="1" required>
+                </div>
+                <div class="form-group">
+                    <label>Age:</label>
+                    <input type="number" name="Age" value="50" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>Sex (0=F, 1=M):</label>
+                    <input type="number" name="Sex" min="0" max="1" value="1" required>
+                </div>
+                <div class="form-group">
+                    <label>Chest Pain Type (1-4):</label>
+                    <input type="number" name="Chest pain type" min="1" max="4" value="2" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>BP (mmHg):</label>
+                    <input type="number" name="BP" value="120" required>
+                </div>
+                <div class="form-group">
+                    <label>Cholesterol (mg/dl):</label>
+                    <input type="number" name="Cholesterol" value="200" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>FBS over 120 (0/1):</label>
+                    <input type="number" name="FBS over 120" min="0" max="1" value="0" required>
+                </div>
+                <div class="form-group">
+                    <label>EKG Results (0-2):</label>
+                    <input type="number" name="EKG results" min="0" max="2" value="0" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>Max HR:</label>
+                    <input type="number" name="Max HR" value="150" required>
+                </div>
+                <div class="form-group">
+                    <label>Exercise Angina (0/1):</label>
+                    <input type="number" name="Exercise angina" min="0" max="1" value="0" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>ST Depression:</label>
+                    <input type="number" name="ST depression" step="0.1" value="1.0" required>
+                </div>
+                <div class="form-group">
+                    <label>Slope of ST (1-3):</label>
+                    <input type="number" name="Slope of ST" min="1" max="3" value="1" required>
+                </div>
+            </div>
+            
+            <div class="form-row">
+                <div class="form-group">
+                    <label>Vessels Fluro (0-3):</label>
+                    <input type="number" name="Number of vessels fluro" min="0" max="3" value="0" required>
+                </div>
+                <div class="form-group">
+                    <label>Thallium (3/6/7):</label>
+                    <input type="number" name="Thallium" value="3" required>
+                </div>
+            </div>
+            
+            <button type="submit" class="btn">Predict</button>
+        </form>
+        
+        <div id="result" class="card" style="display:none">
+            <h3>Prediction Result</h3>
+            <div id="resultContent"></div>
+        </div>
+    </div>
+    
+    <script>
+        document.getElementById('predictionForm').addEventListener('submit', async (e) => {
+            e.preventDefault();
+            const formData = new FormData(e.target);
+            const data = {};
+            formData.forEach((value, key) => {
+                data[key] = key.includes('depression') ? parseFloat(value) : parseInt(value);
+            });
+            
+            try {
+                const response = await fetch('/predict/', {
+                    method: 'POST',
+                    headers: {'Content-Type': 'application/json'},
+                    body: JSON.stringify(data)
+                });
+                const result = await response.json();
+                
+                const resultDiv = document.getElementById('result');
+                const resultContent = document.getElementById('resultContent');
+                
+                if (response.ok) {
+                    const prediction = result.prediction === 1 ? 'POSITIVE' : 'NEGATIVE';
+                    const color = result.prediction === 1 ? '#e74c3c' : '#27ae60';
+                    const prob = result.probability ? `${(result.probability[result.prediction] * 100).toFixed(2)}%` : 'N/A';
+                    
+                    resultContent.innerHTML = `
+                        <p style="font-size: 24px; color: ${color}; font-weight: bold;">${prediction}</p>
+                        <p><strong>Confidence:</strong> ${prob}</p>
+                        <p><strong>Probabilities:</strong> [Negative: ${(result.probability[0] * 100).toFixed(2)}%, Positive: ${(result.probability[1] * 100).toFixed(2)}%]</p>
+                    `;
+                } else {
+                    resultContent.innerHTML = `<p style="color: #e74c3c;">Error: ${result.detail}</p>`;
+                }
+                
+                resultDiv.style.display = 'block';
+            } catch (error) {
+                alert('Error: ' + error.message);
+            }
+        });
+    </script>
+</body>
+</html>

requirements.txt

@@ -2,6 +2,7 @@ fastapi
 uvicorn[standard]
 pydantic
 pydantic-settings
+jinja2
 
 pandas
 numpy

test_api.py

@@ -1,85 +0,0 @@
-import requests
-import json
-
-BASE_URL = "http://localhost:8000"
-
-
-def test_health():
-    response = requests.get(f"{BASE_URL}/health/")
-    print(f"Health Check: {response.json()}")
-
-
-def test_predict():
-    data = {
-        "id": 1,
-        "Age": 50,
-        "Sex": 1,
-        "Chest pain type": 2,
-        "BP": 120,
-        "Cholesterol": 200,
-        "FBS over 120": 0,
-        "EKG results": 0,
-        "Max HR": 150,
-        "Exercise angina": 0,
-        "ST depression": 1.0,
-        "Slope of ST": 1,
-        "Number of vessels fluro": 0,
-        "Thallium": 3
-    }
-    response = requests.post(f"{BASE_URL}/predict/", json=data)
-    print(f"Prediction: {response.json()}")
-
-
-def test_batch_predict():
-    data = {
-        "data": [
-            {
-                "id": 1,
-                "Age": 50,
-                "Sex": 1,
-                "Chest pain type": 2,
-                "BP": 120,
-                "Cholesterol": 200,
-                "FBS over 120": 0,
-                "EKG results": 0,
-                "Max HR": 150,
-                "Exercise angina": 0,
-                "ST depression": 1.0,
-                "Slope of ST": 1,
-                "Number of vessels fluro": 0,
-                "Thallium": 3
-            },
-            {
-                "id": 2,
-                "Age": 60,
-                "Sex": 0,
-                "Chest pain type": 1,
-                "BP": 130,
-                "Cholesterol": 220,
-                "FBS over 120": 1,
-                "EKG results": 1,
-                "Max HR": 140,
-                "Exercise angina": 1,
-                "ST depression": 2.0,
-                "Slope of ST": 2,
-                "Number of vessels fluro": 1,
-                "Thallium": 6
-            }
-        ]
-    }
-    response = requests.post(f"{BASE_URL}/predict/batch", json=data)
-    print(f"Batch Prediction: {response.json()}")
-
-
-if __name__ == "__main__":
-    print("Testing API Endpoints...")
-    print("-" * 50)
-    
-    try:
-        test_health()
-        print("-" * 50)
-        test_predict()
-        print("-" * 50)
-        test_batch_predict()
-    except Exception as e:
-        print(f"Error: {e}")

test_train_endpoints.py

@@ -1,28 +0,0 @@
-import requests
-
-BASE_URL = "http://localhost:8000"
-
-
-def test_reload():
-    print("Testing model reload...")
-    response = requests.post(f"{BASE_URL}/train/reload")
-    print(f"Response: {response.json()}\n")
-
-
-def test_health_after_load():
-    print("Testing health after model load...")
-    response = requests.get(f"{BASE_URL}/health/")
-    print(f"Response: {response.json()}\n")
-
-
-def test_ready():
-    print("Testing readiness endpoint...")
-    response = requests.get(f"{BASE_URL}/health/ready")
-    print(f"Response: {response.json()}\n")
-
-
-if __name__ == "__main__":
-    test_reload()
-    test_health_after_load()
-    test_ready()
-    print("All endpoint tests completed!")