Update app.py

app.py

@@ -16,14 +16,13 @@ llm_client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 def enable_lora(lora_add, basemodel):
     return basemodel if not lora_add else lora_add
 
-async def generate_image(prompt, model, lora_word, width, height, scales, steps, seed):
+async def generate_image(combined_prompt, model, width, height, scales, steps, seed):
     try:
         if seed == -1:
             seed = random.randint(0, MAX_SEED)
         seed = int(seed)
-        text = prompt + "," + lora_word
         image = await client.text_to_image(
-            prompt=text, height=height, width=width, guidance_scale=scales,
+            prompt=combined_prompt, height=height, width=width, guidance_scale=scales,
             num_inference_steps=steps, model=model
         )
         return image, seed
@@ -40,7 +39,7 @@ def get_upscale_finegrain(prompt, img_path, upscale_factor):
             tile_height=144, denoise_strength=0.35, num_inference_steps=18,
             solver="DDIM", api_name="/process"
         )
-        return result[1]
+        return result[1] if isinstance(result, list) and len(result) > 1 else None
     except Exception as e:
         return None
 
@@ -48,7 +47,12 @@ async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_fac
     model = enable_lora(lora_model, basemodel) if process_lora else basemodel
     improved_prompt = await improve_prompt(prompt)
     combined_prompt = f"{prompt} {improved_prompt}"
-    image, seed = await generate_image(combined_prompt, model, "", width, height, scales, steps, seed)
+    
+    if seed == -1:
+        seed = random.randint(0, MAX_SEED)
+    seed = int(seed)
+    
+    image, seed = await generate_image(combined_prompt, model, width, height, scales, steps, seed)
 
     if isinstance(image, str) and image.startswith("Error"):
         return [image, None]
@@ -58,7 +62,7 @@ async def gen(prompt, basemodel, width, height, scales, steps, seed, upscale_fac
 
     if process_upscale:
         upscale_image_path = get_upscale_finegrain(combined_prompt, image_path, upscale_factor)
-        if upscale_image_path is not None:
+        if upscale_image_path:
             upscale_image = Image.open(upscale_image_path)
             upscale_image.save("upscale_image.jpg", format="JPEG")
             return [image_path, "upscale_image.jpg"]
@@ -91,7 +95,7 @@ with gr.Blocks(css=css, theme="Nymbo/Nymbo_Theme") as demo:
                 prompt = gr.Textbox(label="Descripción de imágen")
                 basemodel_choice = gr.Dropdown(
                     label="Modelo", 
-                    choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV", "enhanceaiteam/Flux-uncensored"],
+                    choices=["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-DEV"],
                     value="black-forest-labs/FLUX.1-schnell"
                 )
                 lora_model_choice = gr.Dropdown(