Create app.py

app.py

@@ -0,0 +1,40 @@
+from fastapi import FastAPI, File, UploadFile
+from fastapi.middleware.cors import CORSMiddleware
+from transformers import AutoImageProcessor, AutoModel
+from PIL import Image
+import torch
+import io
+
+app = FastAPI()
+
+# CORS (para pruebas locales o producción cruzada)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],  # Cambia esto en producción
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Carga del modelo y procesador
+processor = AutoImageProcessor.from_pretrained("facebook/dinov2-base")
+model = AutoModel.from_pretrained("facebook/dinov2-base")
+model.eval()
+
+@app.post("/embedding")
+async def get_embedding(file: UploadFile = File(...)):
+    try:
+        image_bytes = await file.read()
+        image = Image.open(io.BytesIO(image_bytes)).convert("RGB")
+
+        inputs = processor(images=image, return_tensors="pt")
+        with torch.no_grad():
+            outputs = model(**inputs)
+
+        # Promedio de los embeddings de todos los tokens (sin CLS)
+        embedding = outputs.last_hidden_state.mean(dim=1).squeeze().tolist()
+
+        return {"embedding": embedding}
+
+    except Exception as e:
+        return {"error": str(e)}