Update app.py

app.py

@@ -1,13 +1,14 @@
+#Save ZeroGPU limited resources, switch to InferenceAPI
 import os
 import gradio as gr
 import numpy as np
 import random
 from huggingface_hub import AsyncInferenceClient
 from translatepy import Translator
+import requests
+import re
 import asyncio
 from PIL import Image
-import io
-import base64
 
 translator = Translator()
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
@@ -35,26 +36,25 @@ def enable_lora(lora_add):
         return lora_add
 
 async def generate_image(
-    prompt: str,
-    model: str,
-    lora_word: str,
-    width: int = 768,
-    height: int = 1024,
-    scales: float = 3.5,
-    steps: int = 24,
-    seed: int = -1,
-):
+    prompt:str,
+    model:str,
+    lora_word:str,
+    width:int=768,
+    height:int=1024,
+    scales:float=3.5,
+    steps:int=24,
+    seed:int=-1):
+
     if seed == -1:
         seed = random.randint(0, MAX_SEED)
     seed = int(seed)
-    print(f'prompt: {prompt}')
-
+    print(f'prompt:{prompt}')
+    
     text = str(translator.translate(prompt, 'English')) + "," + lora_word
 
     client = AsyncInferenceClient()
     try:
-        # Generate image using the Inference API
-        image_bytes = await client.text_to_image(
+        image = await client.text_to_image(
             prompt=text,
             height=height,
             width=width,
@@ -62,58 +62,44 @@ async def generate_image(
             num_inference_steps=steps,
             model=model,
         )
-        return image_bytes, seed
     except Exception as e:
         raise gr.Error(f"Error in {e}")
+    
+    return image, seed
 
 async def gen(
-    prompt: str,
-    lora_add: str = "",
-    lora_word: str = "",
-    width: int = 768,
-    height: int = 1024,
-    scales: float = 3.5,
-    steps: int = 24,
-    seed: int = -1,
-    progress=gr.Progress(track_tqdm=True),
+    prompt:str,
+    lora_add:str="",
+    lora_word:str="",
+    width:int=768,
+    height:int=1024,
+    scales:float=3.5,
+    steps:int=24,
+    seed:int=-1,
+    progress=gr.Progress(track_tqdm=True)
 ):
     model = enable_lora(lora_add)
     print(model)
-    image, seed = await generate_image(prompt, model, lora_word, width, height, scales, steps, seed)
+    image, seed = await generate_image(prompt,model,lora_word,width,height,scales,steps,seed)
     return image, seed
-
-def export_image(image_bytes, format: str = "png"):
-    """Convert image to PNG or Base64."""
-    img = Image.open(io.BytesIO(image_bytes))
-    if format == "png":
-        png_buffer = io.BytesIO()
-        img.save(png_buffer, format="PNG")
-        png_buffer.seek(0)
-        return png_buffer
-    elif format == "base64":
-        buffered = io.BytesIO()
-        img.save(buffered, format="PNG")
-        img_base64 = base64.b64encode(buffered.getvalue()).decode("utf-8")
-        return f"data:image/png;base64,{img_base64}"
-    else:
-        raise ValueError("Unsupported format. Use 'png' or 'base64'.")
-
+     
 examples = [
-    ["wanita cantik sedang duduk di pinggir kolam renang memakai bikini warna pink", "burhansyam/davina", "wanita"],
-    ["a seal holding a beach ball in a pool", "bingbangboom/flux_dreamscape", "in the style of BSstyle004"],
-    ["a tourist in London, illustration in the style of VCTRNDRWNG, Victorian-era drawing", "dvyio/flux-lora-victorian-drawing", "illustration in the style of VCTRNDRWNG"],
-    ["an African American and a Caucasian man petting a cat at a busy electronic store. Flickr photo from 2012. Three people working in the background", "kudzueye/boreal-flux-dev-v2", "photo"],
-    ["mgwr/cine, woman silhouette, morning light, sun rays, indoor scene, soft focus, golden hour, stretching pose, peaceful mood, cozy atmosphere, window light, shadows and highlights, backlit figure, minimalistic interior, warm tones, contemplative moment, calm energy, serene environment, yoga-inspired, elegant posture, natural light beams, artistic composition", "mgwr/Cine-Aesthetic", "atmospheric lighting and a dreamy, surreal vibe"]
+    ["wanita cantik sepertinya seorang barista, sedang membuat kopi hanya memakai celemek, tanpa baju dan bra. Tatapannya menggoda dan menggairahkan", "burhansyam/davina", "wanita"],    ["photograph, background of Earth from space, red car on the Moon watching Earth","martintomov/retrofuturism-flux","retrofuturism"],
+    ["a living room interior","fofr/flux-80s-cyberpunk","80s cyberpunk"],
+    ["a tourist in London, illustration in the style of VCTRNDRWNG, Victorian-era drawing","dvyio/flux-lora-victorian-drawing","illustration in the style of VCTRNDRWNG"],
+    ["an African American and a caucasian man petting a cat at a busy electronic store. flikr photo from 2012. three people working in the background","kudzueye/boreal-flux-dev-v2","photo"],
+    ["mgwr/cine, woman silhouette, morning light, sun rays, indoor scene, soft focus, golden hour, stretching pose, peaceful mood, cozy atmosphere, window light, shadows and highlights, backlit figure, minimalistic interior, warm tones, contemplative moment, calm energy, serene environment, yoga-inspired, elegant posture, natural light beams, artistic composition","mgwr/Cine-Aesthetic","atmospheric lighting and a dreamy, surreal vibe"]
 ]
 
 # Gradio Interface
+
 with gr.Blocks(css=CSS, js=JS, theme="ocean") as demo:
-    gr.HTML("<h1><center>Flux Lab Light</center></h1>")
+    gr.HTML("<h1><center>Flux Mantab!</center></h1>")
     gr.HTML("<p><center>Powered By HF Inference API</center></p>")
     with gr.Row():
         with gr.Column(scale=4):
             with gr.Row():
-                img = gr.Image(type="filepath", label='Flux Generated Image', height=600)
+                img = gr.Image(type="filepath", label='flux Generated Image', height=600)
             with gr.Row():
                 prompt = gr.Textbox(label='Enter Your Prompt (Multi-Languages)', placeholder="Enter prompt...", scale=6)
                 sendBtn = gr.Button(scale=1, variant='primary')
@@ -167,15 +153,9 @@ with gr.Blocks(css=CSS, js=JS, theme="ocean") as demo:
                     value="",
                 )
 
-    with gr.Row():
-        export_png_btn = gr.Button("Export as PNG")
-        export_base64_btn = gr.Button("Export as Base64")
-
-    export_output = gr.Textbox(label="Exported Image", visible=False)
-
     gr.Examples(
         examples=examples,
-        inputs=[prompt, lora_add, lora_word],
+        inputs=[prompt,lora_add,lora_word],
         outputs=[img, seed],
         fn=gen,
         cache_examples="lazy",
@@ -192,26 +172,14 @@ with gr.Blocks(css=CSS, js=JS, theme="ocean") as demo:
             prompt,
             lora_add,
             lora_word,
-            width,
-            height,
-            scales,
-            steps,
-            seed,
+            width, 
+            height, 
+            scales, 
+            steps, 
+            seed
         ],
         outputs=[img, seed]
     )
-
-    export_png_btn.click(
-        export_image,
-        inputs=[img, gr.State("png")],
-        outputs=export_output,
-    )
-
-    export_base64_btn.click(
-        export_image,
-        inputs=[img, gr.State("base64")],
-        outputs=export_output,
-    )
-
+    
 if __name__ == "__main__":
     demo.queue(api_open=False).launch(show_api=False, share=False)