Update app.py

app.py

@@ -1,9 +1,14 @@
+from fastapi import FastAPI, Request, Response
 import numpy as np
 from tensorflow import keras
 from tensorflow.keras import layers
 
 from huggingface_hub import push_to_hub_keras
 
+KEY = os.environ.get("WEBHOOK_SECRET")
+
+app = FastAPI()
+
 def to_numpy(examples):
     examples["pixel_values"] = [np.array(image) for image in examples["image"]]
     return examples
@@ -31,7 +36,7 @@ def preprocess():
 
     return x_train, y_train, x_test, y_test
 
-def training():
+def train():
     x_train, y_train, x_test, y_test = preprocess()
 
     model = keras.Sequential(
@@ -84,3 +89,22 @@ def find_samples_to_label():
     )
     unlabeled_data.push_to_hub("active-learning/unlabeled_samples")
 
+@app.get("/")
+def read_root():
+    data = """
+    <h2 style="text-align:center">Active Learning Trainer</h2>
+    <p style="text-align:center">This is a demo app showing how to webhooks to do Active Learning.</p>
+    """
+    return Response(content=data, media_type="text/html")
+
+@app.post("/webhook")
+async def webhook(request):
+    if request.method == "POST":
+        if request.headers.get("X-Webhook-Secret") != KEY:
+            return Response("Invalid secret", status_code=401)
+        data = await request.json()
+        print("Webhook received!")
+        train() 
+        find_samples_to_label()
+        return "Webhook received!" if result else result
+