Update main.py

main.py

@@ -1,4 +1,55 @@
+from fastapi import FastAPI, File, UploadFile
+from fastapi import FastAPI, File, UploadFile, Form, Request
+from fastapi.responses import HTMLResponse, FileResponse
+from fastapi.staticfiles import StaticFiles
+from fastapi.templating import Jinja2Templates
+from fastapi import FastAPI, File, UploadFile, HTTPException
+from fastapi.responses import JSONResponse
+from fastapi.responses import StreamingResponse
+from gradio_client import Client
 import os
+import io
+app = FastAPI()
 
+hf_token = os.environ.get('HF_TOKEN')
+client = Client("https://ashrafb-image-face-upscale-restoration-gfpgan.hf.space/", hf_token=hf_token)
 
-exec(os.environ.get('API'))
+import tempfile
+
+
+
+import base64
+
+@app.post("/upload/")
+async def upload_file(file: UploadFile = File(...), version: str = Form(...), scale: int = Form(...)):
+    with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+        temp_file.write(await file.read())
+        temp_file_path = temp_file.name
+
+    try:
+        result = client.predict(temp_file_path, api_name="/predict")
+        
+        # Check if the result is valid
+        if result and len(result) == 2:
+            # Convert the image data to base64 string
+            with open(result[0], "rb") as image_file:
+                image_data = base64.b64encode(image_file.read()).decode("utf-8")
+
+            return {
+                "sketch_image_base64": f"data:image/png;base64,{image_data}",
+                "result_file": result[1]
+            }
+        else:
+            return {"error": "Invalid result from the prediction API."}
+    except Exception as e:
+        return {"error": str(e)}
+    finally:
+        if os.path.exists(temp_file_path):
+            os.unlink(temp_file_path)
+
+
+app.mount("/", StaticFiles(directory="static", html=True), name="static")
+
+@app.get("/")
+def index() -> FileResponse:
+    return FileResponse(path="/app/static/index.html", media_type="text/html")