Create main.py

main.py

@@ -0,0 +1,38 @@
+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from gradio_client import Client
+
+# Init FastAPI app
+app = FastAPI()
+
+# Initialize the Gradio Client
+client = Client("Efficient-Large-Model/SanaSprint")
+
+# Request body schema
+class GenerationRequest(BaseModel):
+    prompt: str
+    model_size: str = "1.6B"
+    seed: int = 0
+    randomize_seed: bool = True
+    width: int = 1024
+    height: int = 1024
+    guidance_scale: float = 4.5
+    num_inference_steps: int = 2
+
+@app.post("/generate")
+async def generate_image(request: GenerationRequest):
+    try:
+        result = client.predict(
+            prompt=request.prompt,
+            model_size=request.model_size,
+            seed=request.seed,
+            randomize_seed=request.randomize_seed,
+            width=request.width,
+            height=request.height,
+            guidance_scale=request.guidance_scale,
+            num_inference_steps=request.num_inference_steps,
+            api_name="/infer"
+        )
+        return {"result": result}
+    except Exception as e:
+        raise HTTPException(status_code=500, detail=str(e))