Update myapp.py

myapp.py

@@ -2,8 +2,8 @@ from flask import Flask, request, jsonify, send_file
 from flask_cors import CORS
 import os
 from huggingface_hub import InferenceClient
-from io import BytesIO  # For converting image to bytes
-from PIL import Image  # Import Pillow for image processing
+from io import BytesIO
+from PIL import Image  # Importing Pillow for image processing
 
 # Initialize the Flask app
 myapp = Flask(__name__)
@@ -13,14 +13,10 @@ CORS(myapp)  # Enable CORS for all routes
 HF_TOKEN = os.environ.get("HF_TOKEN")  # Ensure to set your Hugging Face token in the environment
 client = InferenceClient(token=HF_TOKEN)
 
-@myapp.route('/')
-def home():
-    return "Welcome to the Image Background Remover!"
-
-# Function to generate an image from a prompt
-def generate_image(prompt, seed=1, model="prompthero/openjourney-v4"):
+# Function to generate an image from a prompt using the specified model
+def generate_image(prompt, seed=1, model="prompthero/openjourney-v4"):  # Default model if none provided
     try:
-        # Generate the image using Hugging Face's inference API with the given model
+        # Generate the image using Hugging Face's inference API
         result_image = client.text_to_image(prompt=prompt, seed=seed, model=model)
         return result_image
     except Exception as e:
@@ -31,27 +27,32 @@ def generate_image(prompt, seed=1, model="prompthero/openjourney-v4"):
 @myapp.route('/generate_image', methods=['POST'])
 def generate_api():
     data = request.get_json()
-    
+
     # Extract required fields from the request
     prompt = data.get('prompt', '')
     seed = data.get('seed', 1)
-    model_name = data.get('model', 'prompthero/openjourney-v4')  # Default model
+    model_name = data.get('model', 'prompthero/openjourney-v4')  # Use the provided model name or a default one
 
     if not prompt:
         return jsonify({"error": "Prompt is required"}), 400
 
     try:
-        # Call the generate_image function with the custom model name
+        # Call the generate_image function with the dynamically provided model name
         image = generate_image(prompt, seed, model_name)
-        
+
         if image:
-            # Save the image to a BytesIO object to send as response
+            # Save the image to a BytesIO object
             image_bytes = BytesIO()
             image.save(image_bytes, format='PNG')
             image_bytes.seek(0)  # Go to the start of the byte stream
 
-            # Send the generated image as a response with a download option
-            return send_file(image_bytes, mimetype='image/png', as_attachment=True, download_name='generated_image.png')
+            # Send the generated image as an attachment
+            return send_file(
+                image_bytes, 
+                mimetype='image/png', 
+                as_attachment=True,  # Send the file as an attachment
+                download_name='generated_image.png'  # The file name for download
+            )
         else:
             return jsonify({"error": "Failed to generate image"}), 500
     except Exception as e: