Working on it

routers/training.py

@@ -9,6 +9,8 @@ import torch
 import requests
 from PIL import Image
 from io import BytesIO
+from pydantic import BaseModel
+import base64
 
 from diffusers import StableDiffusionImg2ImgPipeline
 
@@ -19,6 +21,33 @@ pipe = pipe.to("cuda")
 
 router = APIRouter()
 
+class ActionBody(BaseModel):
+    url: str
+    prompt: str
+    strength: float
+    guidance_scale: float
+
+@router.post("/perform-action")
+async def hifunction(actionBody: ActionBody):
+    
+    response = requests.get(actionBody.url)
+    init_image = Image.open(BytesIO(response.content)).convert("RGB")
+    init_image = init_image.resize((768, 512))
+    images = pipe(prompt=actionBody.prompt, image=init_image, strength=actionBody.strength, guidance_scale=actionBody.guidance_scale).images
+    print(images)
+    print(images[0])
+
+    buffered = BytesIO()
+    images[0].save(buffered, format="JPEG")
+    img_str = base64.b64encode(buffered.getvalue())
+
+    # images[0].save("fantasy_landscape.png")
+
+    return {
+        "image": img_str
+    }
+
+
 @router.get("/hi")
 async def hifunction():