Create generation.py

feat: add generation.py

generation.py

@@ -0,0 +1,51 @@
+import os
+import random
+from datetime import datetime
+from typing import Optional
+
+from huggingface_hub import InferenceClient
+
+# Directorio donde se guardan las imágenes generadas
+OUTPUT_DIR = "generated_images"
+os.makedirs(OUTPUT_DIR, exist_ok=True)
+
+# Cliente de inferencia (igual que en Sofia Rivera)
+client = InferenceClient()
+
+def generate_image_from_prompt(
+    prompt: str,
+    negative_prompt: str = "",
+    model_name: str = "black-forest-labs/FLUX.1-dev",
+    seed: Optional[int] = None,
+) -> tuple[Optional[str], str]:
+    """
+    Genera una imagen usando Hugging Face InferenceClient.text_to_image
+    y la guarda en OUTPUT_DIR.
+
+    Devuelve (image_path, status_message).
+    Si hay error, image_path = None y status_message contiene el error.
+    """
+    try:
+        if seed is None:
+            seed = random.randint(0, 2_147_483_647)
+
+        image = client.text_to_image(
+            prompt=prompt,
+            negative_prompt=negative_prompt,
+            model=model_name,
+            guidance_scale=7.5,
+            num_inference_steps=50,
+        )
+
+        timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        filename = f"sofia_{timestamp}_{seed}.png"
+        file_path = os.path.join(OUTPUT_DIR, filename)
+
+        image.save(file_path)
+
+        status = f"✅ Imagen generada y guardada: {filename}\nModelo: {model_name}\nSeed: {seed}"
+        return file_path, status
+
+    except Exception as e:
+        error_msg = f"❌ Error al generar imagen: {str(e)}"
+        return None, error_msg