Update app.py

app.py

@@ -1,7 +1,8 @@
 import gradio as gr
 from transformers import pipeline
+import fastapi
+from gradio import fastapi as gr_api
 
-# Load the model (this runs only once!)
 generator = pipeline("text2text-generation", model="LahiruProjects/recipe-generator-flan-t5")
 
 def generate_recipe(name, ingredients, calories, time):
@@ -10,18 +11,19 @@ def generate_recipe(name, ingredients, calories, time):
     result = generator(prompt)
     return result[0]["generated_text"]
 
-# Gradio interface
-iface = gr.Interface(
-    fn=generate_recipe,
-    inputs=[
-        gr.Textbox(label="Recipe Name"),
-        gr.Textbox(label="Ingredients (comma-separated)"),
-        gr.Number(label="Max Calories", value=400),
-        gr.Number(label="Max Cooking Time (minutes)", value=30)
-    ],
-    outputs="text",
-    title="🍳 Recipe Generator (FLAN-T5)",
-    description="Generate a step-by-step recipe based on ingredients, calorie limit, and time"
-)
+# Using gr.Blocks() for a custom interface
+with gr.Blocks() as demo:
+    with gr.Row():
+        name = gr.Textbox(label="Recipe Name")
+        ingredients = gr.Textbox(label="Ingredients (comma-separated)")
+        calories = gr.Number(label="Max Calories", value=400)
+        time = gr.Number(label="Max Cooking Time (minutes)", value=30)
+    output = gr.Textbox()
+    demo.add(name, ingredients, calories, time, output)
+
+# Set up FastAPI app to expose the REST API
+app = fastapi.FastAPI()
+app = gr_api.FastAPI(app, demo)
+
+gr_api.add_api_route(app, "/api/predict", demo, methods=["POST"])
 
-iface.launch()