Added app file

app.py

@@ -0,0 +1,27 @@
+import gradio as gr
+import requests
+import json
+import os
+
+API_URL = "https://api-inference.huggingface.co/models/davidaf3/ReverseNutrition_TFIngPort"
+headers = {"Authorization": f"Bearer {os.environ['API_TOKEN']}"}
+
+def predict(image_file):
+    with open(image_file, "rb") as f:
+      data = f.read()
+    response = requests.request("POST", API_URL, headers=headers, data=data)
+    predictions = json.loads(response.content.decode("utf-8"))
+    return [[element["label"], element["score"]] for element in predictions if element["score"] > 0]
+
+app = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(type="filepath"), 
+    outputs=gr.Dataframe(headers=["ingredient", "amount per 100g (in g)"]), 
+    allow_flagging="never",
+    description=
+      "Upload food images and get an estimation about their ingredients and the ingredient proportions.\
+      The model used is [ReverseNutrition_TFIngPort](https://huggingface.co/davidaf3/ReverseNutrition_TFIngPort).\
+      If the output table shows an error, wait until the model is loaded."
+  )
+
+app.launch()