refactor: chnage in UI component

app.py

@@ -1,91 +1,142 @@
+import base64
 import os
 
 import gradio as gr
 import requests
 
 
-def generate(images, model_choice):
-    outputs = []
+def generate(
+    images,
+    prompt,
+    size,
+):
+    api_key = os.getenv("BYTEPLUS_API_KEY")
+    base_url = os.getenv("BYTEPLUS_URL").rstrip("/")
+    response_format = "b64_json"
+    watermark = False
+
+    images_iput = []
 
     for img in images:
-        img_path = img.name if hasattr(img, "name") else img  # handle temp file
+        try:
+            with open(img.name, "rb") as f:
+                image_bytes = f.read()
+                encoded = base64.b64encode(image_bytes).decode("utf-8")
+                images_iput.append(encoded)
+        except Exception as e:
+            print(f"⚠️ Failed to process image {img.name}: {e}")
+
+    try:
+        model_name = "seedream-4-0-250828"
+        request_data = {
+            "model": model_name,
+            "prompt": prompt,
+            "response_format": response_format,
+            "sequential_image_generation": "disabled",
+            "size": size,
+            "watermark": watermark,
+        }
+    except Exception as e:
+        print(f"⚠️ Failed to process everything: {e}")
+        # if model_choice == "Flux Kontext Pro":
+        #     response = requests.post(
+        #         "https://api.fluxkontext.pro/v1/generate",
+        #         headers={"Authorization": f"Bearer {os.getenv('FLUX_API_KEY')}"},
+        #         files={"image": open(img_path, "rb")},
+        #     )
+        #     result = response.json().get("result_url")
+
+        # elif model_choice == "Wan 2.5":
+        #     response = requests.post(
+        #         "https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation",
+        #         headers={
+        #             "Authorization": f"Bearer {os.getenv('WAN_API_KEY')}",
+        #             "Content-Type": "application/json",
+        #         },
+        #         json={"model": "wan2.5-t2v-preview", "input": {"image": img_path}},
+        #     )
+        #     result = response.json().get("output", {}).get("url")
+
+        # elif model_choice == "Qwen 3":
+        #     response = requests.post(
+        #         "https://qwen-api.aliyun.com/v1/image/generate",
+        #         headers={"Authorization": f"Bearer {os.getenv('QWEN_API_KEY')}"},
+        #         files={"image": open(img_path, "rb")},
+        #     )
+        #     result = response.json().get("data", {}).get("image_url")
+
+        # elif model_choice == "Nano Banana":
+        #     response = requests.post(
+        #         "https://api.nanobanana.io/v1/image-gen",
+        #         headers={"Authorization": f"Bearer {os.getenv('NANO_API_KEY')}"},
+        #         files={"image": open(img_path, "rb")},
+        #     )
+        #     result = response.json().get("url")
+
+        # elif model_choice == "GPT":
+        #     response = requests.post(
+        #         "https://api.openai.com/v1/images/edits",
+        #         headers={"Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"},
+        #         files={"image": open(img_path, "rb")},
+        #     )
+        #     result = response.json().get("data", [{}])[0].get("url")
+
+        # else:
+        #     result = None
+
+        # outputs.append(result)
+
+    return
 
-        if model_choice == "Flux Kontext Pro":
-            response = requests.post(
-                "https://api.fluxkontext.pro/v1/generate",
-                headers={"Authorization": f"Bearer {os.getenv('FLUX_API_KEY')}"},
-                files={"image": open(img_path, "rb")},
-            )
-            result = response.json().get("result_url")
-
-        elif model_choice == "Wan 2.5":
-            response = requests.post(
-                "https://dashscope.aliyuncs.com/api/v1/services/aigc/image-generation",
-                headers={
-                    "Authorization": f"Bearer {os.getenv('WAN_API_KEY')}",
-                    "Content-Type": "application/json",
-                },
-                json={"model": "wan2.5-t2v-preview", "input": {"image": img_path}},
-            )
-            result = response.json().get("output", {}).get("url")
 
-        elif model_choice == "Qwen 3":
-            response = requests.post(
-                "https://qwen-api.aliyun.com/v1/image/generate",
-                headers={"Authorization": f"Bearer {os.getenv('QWEN_API_KEY')}"},
-                files={"image": open(img_path, "rb")},
-            )
-            result = response.json().get("data", {}).get("image_url")
+with gr.Blocks(theme=gr.themes.Glass()) as demo:
+    gr.Markdown("## 🔥 Multi-API Image-to-Image Generator")
 
-        elif model_choice == "Nano Banana":
-            response = requests.post(
-                "https://api.nanobanana.io/v1/image-gen",
-                headers={"Authorization": f"Bearer {os.getenv('NANO_API_KEY')}"},
-                files={"image": open(img_path, "rb")},
+    with gr.Row(equal_height=True):
+        # Left Column — inputs
+        with gr.Column(scale=1):
+            image_input = gr.File(
+                file_count="multiple", label="Upload your reference images (optional)"
             )
-            result = response.json().get("url")
 
-        elif model_choice == "GPT":
-            response = requests.post(
-                "https://api.openai.com/v1/images/edits",
-                headers={"Authorization": f"Bearer {os.getenv('OPENAI_API_KEY')}"},
-                files={"image": open(img_path, "rb")},
+            prompt_input = gr.Textbox(
+                label="Prompt",
+                placeholder="Describe how you want to modify or generate the image...",
+                lines=2,
             )
-            result = response.json().get("data", [{}])[0].get("url")
-
-        else:
-            result = None
 
-        outputs.append(result)
-
-    return outputs
-
-
-with gr.Blocks(theme=gr.themes.Glass()) as demo:
-    gr.Markdown("## 🔥 Multi-API Image-to-Image Generator")
+            variation_choice = gr.Dropdown(
+                choices=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10],
+                label="Model / Variation",
+                value=1,
+            )
 
-    with gr.Row(equal_height=True):
-        # Left Column
-        with gr.Column(scale=1):
-            image_input = gr.File(file_count="multiple", label="Upload your images")
-            model_choice = gr.Dropdown(
-                [
-                    "Flux Kontext Pro",
-                    "Flux Kontext MAX",
-                    "Wan 2.5",
-                    "Qwen 3",
-                    "Nano Banana",
-                    "GPT",
+            size_choice = gr.Dropdown(
+                choices=[
+                    "2048x2048",
+                    "1728x2304",
+                    "2304x1728",
+                    "2560x1440",
+                    "1440x2560",
+                    "1664x2496",
+                    "2496x1664",
+                    "3024x1296",
                 ],
-                value="Flux Kontext Pro",
-                label="Select Model",
+                label="Output Size",
+                value="2048x2048",
             )
 
-        # Right Column
+            btn = gr.Button("🚀 Generate", variant="primary", size="lg")
+
+        # Right Column — outputs
         with gr.Column(scale=1):
             gallery = gr.Gallery(label="Generated Results", columns=2, height=400)
-            btn = gr.Button("Generate", variant="primary", size="lg")
 
-    btn.click(generate, [image_input, model_choice], gallery)
+    # Connect button click to function
+    btn.click(
+        fn=generate,
+        inputs=[image_input, prompt_input, variation_choice, size_choice],
+        outputs=gallery,
+    )
 
 demo.launch()