Update app.py

app.py

@@ -8,35 +8,24 @@ import os
 import random
 import numpy as np
 import yaml
-import traceback
-import asyncio
 
-TEMP_PATH = Path("./temp")
-TEMP_PATH.mkdir(parents=True, exist_ok=True)
-st.set_page_config(layout="wide")
-llm_client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1", token=os.getenv("HF_TOKEN_UPSCALER"))
+try:
+    with open("config.yaml", "r") as file:
+        credentials = yaml.safe_load(file)
+except Exception as e:
+    st.error(f"Error al cargar el archivo de configuración: {e}")
+    credentials = {"username": "", "password": ""}
 
-def login_form():
-    st.title("Iniciar Sesión")
-    username = st.text_input("Usuario")
-    password = st.text_input("Contraseña", type="password")
-    
-    if st.button("Iniciar Sesión"):
-        if username == "admin" and password == "flux3x":
-            st.session_state['authenticated'] = True
-            st.success("Autenticación exitosa.")
-        else:
-            st.error("Credenciales incorrectas.")
+MAX_SEED = np.iinfo(np.int32).max
+client = InferenceClient()
+DATA_PATH = Path("./data")
+DATA_PATH.mkdir(exist_ok=True)
+PREDEFINED_SEED = random.randint(0, MAX_SEED)
+HF_TOKEN_UPSCALER = os.environ.get("HF_TOKEN_UPSCALER")
 
 if not HF_TOKEN_UPSCALER:
     st.warning("HF_TOKEN_UPSCALER no está configurado. Algunas funcionalidades pueden no funcionar.")
 
-def handle_file(file_path):
-    if isinstance(file_path, (str, Path)):
-        with open(file_path, 'rb') as f:
-            return f.read()
-    return file_path
-
 def get_upscale_finegrain(prompt, img_path, upscale_factor):
     try:
         upscale_client = InferenceClient("fal/AuraSR-v2", hf_token=HF_TOKEN_UPSCALER)
@@ -136,53 +125,10 @@ def save_prompt(prompt):
         f.write(prompt + "\n")
         st.success("Prompt guardado.")
 
-async def improve_prompt(prompt):
-    if not prompt.strip() or not llm_client:
-        return prompt
-    
-    try:
-        with st.spinner('Generando y mejorando prompts...'):
-            instructions = [
-                "With this words, create a photorealistic description for a detailed txt2img prompt in English in 200 characters maximum",
-                "With this idea, write a creative, realistic, and detailed text-to-image prompt in English in 200 characters maximum",
-                "With this text, generate a descriptive and True to life txt2img prompt in English in 200 characters maximum",
-                "With my idea, describe a photorealistic scene with detailed illumination for a txt2img prompt in English in 200 characters maximum",
-                "With this concept, give a realistic, elegant txt2img prompt in English, emphasizing photorealism in 200 characters maximum",
-                "With this perspective, conform a visually dynamic and hyperrealistic txt2img prompt in English in 200 characters maximum",
-                "With this inspiration, realize a cinematic txt2img prompt in English with hyperrealistic elements in 200 characters maximum",
-                "With my idea, make a lifelike and txt2img prompt in English, focusing on photorealistic depth in 200 characters maximum"
-            ]
-            result = llm_client(
-                f"{prompt}: {random.choice(instructions)}",
-                max_new_tokens=256,
-                temperature=0.7,
-                top_p=0.95,
-                repetition_penalty=1.1,
-                do_sample=True
-            )
-            generated_text = result[0]['generated_text'] if isinstance(result, list) else str(result)
-            return generated_text[:200].strip() or prompt
-    except Exception as e:
-        st.error(f"Error al mejorar prompt: {str(e)}\n{traceback.format_exc()}")
-        return prompt
-
-async def generate_variations(prompt, num_variants, use_enhanced):
+def generate_variations(prompt, num_variants, use_enhanced):
     prompts = set()
-    if not use_enhanced:
-        return [prompt] * num_variants
-    
-    try:
-        while len(prompts) < num_variants:
-            enhanced_prompt = await improve_prompt(prompt)
-            prompts.add(enhanced_prompt)
-            if len(prompts) == 1 and num_variants > 1:
-                prompts.add(prompt)
-        if len(prompts) < num_variants:
-            prompts.update([prompt] * (num_variants - len(prompts)))
-    except Exception as e:
-        st.error(f"Error generando variaciones: {e}")
-        return [prompt] * num_variants
-        
+    while len(prompts) < num_variants:
+        prompts.add(prompt)
     return list(prompts)
 
 def get_prompt_for_image(image_name):
@@ -231,6 +177,7 @@ def upload_image_to_gallery():
             st.sidebar.success(f"Imagen subida: {image_path}")
 
 def main():
+    st.set_page_config(layout="wide")
 
     if 'authenticated' not in st.session_state or not st.session_state['authenticated']:
         login_form()
@@ -242,22 +189,12 @@ def main():
     format_option = st.sidebar.selectbox("Formato", ["9:16", "16:9", "1:1"])
     model_option = st.sidebar.selectbox("Modelo", ["black-forest-labs/FLUX.1-schnell", "black-forest-labs/FLUX.1-dev"])
     upscale_checkbox = st.sidebar.checkbox("Escalar imagen")
-    prompt_enhance = st.sidebar.checkbox("Mejorar Prompt", True)
-    num_variants = st.sidebar.slider("Número de imágenes", 1, 8, 1)
     width, height = (720, 1280) if format_option == "9:16" else (1280, 720) if format_option == "16:9" else (1280, 1280)
-    
-    if prompt_enhance:
-        prompts = asyncio.run(generate_variations(prompt, num_variants, use_enhanced=True))
-    else:
-        prompts = [prompt] * num_variants
+    num_variants = 1
 
     if st.sidebar.button("Generar Imagen"):
-        try:
-            images = gen(prompts, width, height, model_option, num_variants=num_variants)
-            if not images:
-                st.error("No se pudieron generar imágenes")
-        except Exception as e:
-            st.error(f"Error durante la generación: {e}")
+        prompts = [prompt]
+        images = gen(prompts, width, height, model_option, num_variants)
 
     if generated_image_path and upscale_checkbox:
         upscale_factor = st.sidebar.slider("Factor de Escalado", 1, 4, 2)
@@ -269,4 +206,4 @@ def main():
     display_gallery()
 
 if __name__ == "__main__":
-    main()
+    main()