Update app.py

app.py

@@ -3,8 +3,11 @@ import requests
 import io
 import random
 import os
+import time
 from PIL import Image
 from deep_translator import GoogleTranslator
+import json
+
 
 API_TOKEN = os.getenv("HF_READ_TOKEN")
 headers = {"Authorization": f"Bearer {API_TOKEN}"}
@@ -23,19 +26,27 @@ article_text = """
 </div>
 """
 
-def query(lora_id, prompt, steps=28, cfg_scale=3.5, randomize_seed=True, seed=-1, width=1024, height=1024, output_format="PNG"):
-    if not prompt:
-        return None, None, None
+def query(lora_id, prompt, steps=28, cfg_scale=3.5, randomize_seed=True, seed=-1, width=1024, height=1024):
+    if prompt == "" or prompt == None:
+        return None
 
-    if not lora_id.strip():
-        lora_id = "black-forest-labs/FLUX.1-dev"
+    if lora_id.strip() == "" or lora_id == None:
+        lora_id = "black-forest-labs/FLUX.1-dev" 
 
     key = random.randint(0, 999)
-    API_URL = "https://api-inference.huggingface.co/models/" + lora_id.strip()
+
+    API_URL = "https://api-inference.huggingface.co/models/"+ lora_id.strip()
+    
+    API_TOKEN = random.choice([os.getenv("HF_READ_TOKEN")])
+    headers = {"Authorization": f"Bearer {API_TOKEN}"}
     
+     #prompt = GoogleTranslator(source='my', target='en').translate(prompt)
+    # print(f'\033[1mGeneration {key} translation:\033[0m {prompt}')
+
     prompt = f"{prompt} | ultra detail, ultra elaboration, ultra quality, perfect."
+   #  print(f'\033[1mGeneration {key}:\033[0m {prompt}')
 
-    # Generate a random seed if needed
+    # If seed is -1, generate a random seed and use it
     if randomize_seed:
         seed = random.randint(1, 4294967296)
     
@@ -45,12 +56,11 @@ def query(lora_id, prompt, steps=28, cfg_scale=3.5, randomize_seed=True, seed=-1
         "cfg_scale": cfg_scale,
         "seed": seed,
         "parameters": {
-            "width": width,
-            "height": height
+            "width": width,  # Pass the width to the API
+            "height": height  # Pass the height to the API
         }
     }
 
-    # Send the request and get the image data
     response = requests.post(API_URL, headers=headers, json=payload, timeout=timeout)
     if response.status_code != 200:
         print(f"Error: Failed to get image. Response status: {response.status_code}")
@@ -60,20 +70,13 @@ def query(lora_id, prompt, steps=28, cfg_scale=3.5, randomize_seed=True, seed=-1
         raise gr.Error(f"{response.status_code}")
     
     try:
-        # Load and convert the image to the specified format (JPEG or PNG)
         image_bytes = response.content
         image = Image.open(io.BytesIO(image_bytes))
         print(f'\033[1mGeneration {key} completed!\033[0m ({prompt})')
-
-        img_byte_arr = io.BytesIO()
-        image.save(img_byte_arr, format=output_format)
-        img_byte_arr.seek(0)
-
-        # Prepare for Gradio's download
-        return image, seed, img_byte_arr
+        return image, seed, seed
     except Exception as e:
         print(f"Error when trying to open the image: {e}")
-        return None, None, None
+        return None
 
 
 examples = [
@@ -109,28 +112,23 @@ with gr.Blocks(theme='Nymbo/Nymbo_Theme', css=css) as app:
                         with gr.Row():
                             steps = gr.Slider(label="Sampling steps", value=28, minimum=1, maximum=100, step=1)
                             cfg = gr.Slider(label="CFG Scale", value=3.5, minimum=1, maximum=20, step=0.5)
-                        output_format = gr.Dropdown(label="Output Format", choices=["JPEG", "PNG"], value="PNG")
+                        # method = gr.Radio(label="Sampling method", value="DPM++ 2M Karras", choices=["DPM++ 2M Karras", "DPM++ SDE Karras", "Euler", "Euler a", "Heun", "DDIM"])
 
         with gr.Row():
             text_button = gr.Button("Run", variant='primary', elem_id="gen-button")
         with gr.Row():
             image_output = gr.Image(type="pil", label="Image Output", elem_id="gallery")
         with gr.Row():
-            seed_output = gr.Textbox(label="Seed Used", show_copy_button=True, elem_id="seed-output")
-        with gr.Row():
-            download_button = gr.File(label="Download Image", elem_id="download-button")
+            seed_output = gr.Textbox(label="Seed Used", show_copy_button = True, elem_id="seed-output")
 
         gr.Markdown(article_text)
         
         gr.Examples(
-            examples=examples,
-            inputs=[text_prompt],
+            examples = examples,
+            inputs = [text_prompt],
         )
 
-        def download_image(image_data):
-            return image_data
-
-        text_button.click(query, inputs=[custom_lora, text_prompt, steps, cfg, randomize_seed, seed, width, height, output_format], outputs=[image_output, seed_output, download_button])
-        download_button.change(download_image, inputs=[download_button], outputs=download_button)
+        
+        text_button.click(query, inputs=[custom_lora, text_prompt, steps, cfg, randomize_seed, seed, width, height], outputs=[image_output,seed_output, seed])
 
 app.launch(show_api=False, share=True)