portfolio backend to render

main.py

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+from fastapi import FastAPI
+from pydantic import BaseModel
+from fastapi.middleware.cors import CORSMiddleware
+from diffusers import DiffusionPipeline
+import torch
+import uuid
+from PIL import Image
+import os
+from fastapi.staticfiles import StaticFiles
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["http://localhost:5173"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+# Remote Hugging Face model IDs
+hf_model_ids = {
+    "model1": "Pacicap/FineTuned_claude_StableDiffussion_2_1",
+    "model2": "Pacicap/FineTuned_gpt4o_StableDiffussion_2_1"
+}
+
+loaded_models = {}
+
+class PromptInput(BaseModel):
+    prompt: str
+    model: str  # should be "model1" or "model2"
+
+@app.post("/generate")
+def generate(data: PromptInput):
+    model_key = data.model
+
+    if model_key not in hf_model_ids:
+        return {"error": "Invalid model selected"}
+
+    model_id = hf_model_ids[model_key]
+
+    if model_key not in loaded_models:
+        device = "cuda" if torch.cuda.is_available() else "cpu"
+        pipe = DiffusionPipeline.from_pretrained(model_id).to(device)
+        loaded_models[model_key] = pipe
+    else:
+        pipe = loaded_models[model_key]
+
+    image = pipe(data.prompt).images[0]
+
+    os.makedirs("generated", exist_ok=True)
+    filename = f"{uuid.uuid4().hex}.png"
+    filepath = os.path.join("generated", filename)
+    image.save(filepath)
+
+    return {"url": f"http://localhost:8000/generated/{filename}"}
+
+# Serve images
+app.mount("/generated", StaticFiles(directory="generated"), name="generated")

render.ymal

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+services:
+  - type: web
+    name: fastapi-backend
+    env: python
+    buildCommand: ""
+    startCommand: uvicorn main:app --host 0.0.0.0 --port 10000
+    plan: free
+    autoDeploy: true