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Update generation.py
Browse files- generation.py +12 -18
generation.py
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@@ -2,50 +2,44 @@ import os
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import random
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from datetime import datetime
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from typing import Optional
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from huggingface_hub import InferenceClient
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# Directorio donde se guardan las imágenes generadas
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OUTPUT_DIR = "generated_images"
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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# Cliente de inferencia
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client = InferenceClient()
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def generate_image_from_prompt(
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prompt: str,
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negative_prompt: str = "",
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model_name: str = "black-forest-labs/FLUX.1-
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seed: Optional[int] = None,
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) -> tuple[Optional[str], str]:
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"""
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Genera una imagen usando Hugging Face InferenceClient.text_to_image
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y la guarda en OUTPUT_DIR.
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Devuelve (image_path, status_message).
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Si hay error, image_path = None y status_message contiene el error.
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"""
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try:
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if seed is None:
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seed = random.randint(0, 2_147_483_647)
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image = client.text_to_image(
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prompt=prompt,
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negative_prompt=negative_prompt,
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model=model_name,
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num_inference_steps=
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"sofia_{timestamp}_{seed}.png"
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file_path = os.path.join(OUTPUT_DIR, filename)
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image.save(file_path)
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status = f"✅
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return file_path, status
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except Exception as e:
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error_msg = f"❌ Error al generar imagen: {str(e)}"
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return None, error_msg
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import random
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from datetime import datetime
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from typing import Optional
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from huggingface_hub import InferenceClient
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# Directorio donde se guardan las imágenes generadas
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OUTPUT_DIR = "generated_images"
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os.makedirs(OUTPUT_DIR, exist_ok=True)
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# Cliente de inferencia
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# Si tienes un Token de HF en tus Secrets, lo detectará automáticamente
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client = InferenceClient()
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def generate_image_from_prompt(
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prompt: str,
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negative_prompt: str = "",
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model_name: str = "black-forest-labs/FLUX.1-schnell", # CAMBIADO A VERSIÓN GRATUITA
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seed: Optional[int] = None,
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) -> tuple[Optional[str], str]:
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try:
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if seed is None:
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seed = random.randint(0, 2_147_483_647)
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# Parámetros optimizados para el modelo gratuito FLUX Schnell
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image = client.text_to_image(
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prompt=prompt,
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model=model_name,
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seed=seed,
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num_inference_steps=4, # Schnell solo necesita 4 pasos (es muy rápido)
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# guidance_scale se omite en Schnell para evitar errores de API gratuita
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)
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
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filename = f"sofia_{timestamp}_{seed}.png"
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file_path = os.path.join(OUTPUT_DIR, filename)
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image.save(file_path)
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status = f"✅ ¡Sofía está lista!\nModelo: {model_name}\nSeed: {seed}"
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return file_path, status
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except Exception as e:
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error_msg = f"❌ Error al generar imagen: {str(e)}"
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return None, error_msg
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