Update app.py

app.py

@@ -7,9 +7,6 @@ import os
 import random
 import numpy as np
 import yaml
-import requests
-
-HUGGINGFACE_API = os.environ.get("HF_TOKEN")
 
 try:
     with open("config.yaml", "r") as file:
@@ -27,28 +24,20 @@ DATA_PATH.mkdir(exist_ok=True)
 def authenticate_user(username, password):
     return username == credentials["username"] and password == credentials["password"]
 
-async def gen(prompts, width, height, model_name, num_variants, prompt_checkbox):
-    headers = {"Authorization": f"Bearer {HUGGINGFACE_API}"}
-    
-    for prompt in prompts: 
-        payload = {
-            "inputs": prompt,  
-            "parameters": {
-                "width": width,
-                "height": height,
-                "num_inference_steps": 50,
-                "guidance_scale": 7.5
-            }
-        }
-
-        url = f"https://api-inference.huggingface.co/models/{model_name}"
-        response = requests.post(url, headers=headers, json=payload)
-
-        if response.status_code != 200:
-            raise Exception(f"Error: {response.status_code}, {response.text}")
-        
-        return response.json()
-    
+async def gen(prompts, width, height, model_name, num_variants=1, use_enhanced=True):
+    images = []
+    try:
+        for idx, prompt in enumerate(prompts):
+            seed = random.randint(0, MAX_SEED)
+            image, seed = await generate_image(prompt, width, height, seed, model_name)
+            image_path = save_image(image, f"generated_image_{seed}.jpg", prompt)
+            if image_path:
+                st.success(f"Imagen {idx + 1} generada")
+                images.append(str(image_path))
+    except Exception as e:
+        st.error(f"Error al generar imágenes: {e}")
+    return images
+
 def list_saved_images():
     return sorted(DATA_PATH.glob("*.jpg"), key=os.path.getmtime, reverse=True)
 
@@ -154,11 +143,9 @@ async def main():
 
     st.title("Flux + Multiple Images")
     prompt = st.sidebar.text_area("Descripción de la imagen", height=150, max_chars=500)
-    style_option = st.sidebar.selectbox("Selecciona un estilo", ["realistic", "photorealistic", "illustration", "cartoon", "comic", "imaginative", "abstract"])
-    prompt_with_style = f"{prompt}, {style_option} style"
     format_option = st.sidebar.selectbox("Formato", ["9:16", "16:9", "1:1"]) 
     prompt_checkbox = st.sidebar.checkbox("Prompt Enhancer")
-    model_option = st.sidebar.selectbox("Modelo", ["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-dev", "XLabs-AI/flux-RealismLora"])
+    model_option = st.sidebar.selectbox("Modelo", ["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-dev", "enhanceaiteam/Flux-Uncensored-V2", "enhanceaiteam/Flux-Uncensored"])
     width, height = (360, 640) if format_option == "9:16" else (640, 360) if format_option == "16:9" else (640, 640)
 
     if prompt_checkbox:
@@ -166,18 +153,16 @@ async def main():
     else:
         num_variants = 1
 
-    model_name = model_option
-
     if prompt_checkbox:
         with st.spinner("Generando prompts mejorados..."):
-            prompts = await generate_variations(prompt_with_style, num_variants, True)
+            prompts = await generate_variations(prompt, num_variants, True)
     else:
-        prompts = [prompt_with_style]  
+        prompts = [prompt] 
 
     if st.sidebar.button("Generar Imágenes"):
         with st.spinner("Generando imágenes..."):
             try:
-                results = await gen(prompts, width, height, model_name, num_variants, prompt_checkbox)
+                results = await gen(prompts, width, height, model_option, num_variants, prompt_checkbox)
                 st.session_state['generated_image_paths'] = results
                 for result in results:
                     st.image(result, caption="Imagen Generada")