Add application file

Dockerfile

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+FROM python:3.10-slim
+
+WORKDIR /app
+
+COPY requirements.txt ./
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY . .
+
+EXPOSE 8000
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "8000"]

app.py

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+from fastapi import FastAPI, UploadFile, File
+from fastapi.middleware.cors import CORSMiddleware
+from PIL import Image
+import io
+import base64
+import requests
+import os
+from dotenv import load_dotenv
+import multipart
+
+load_dotenv()  # 🔒 Load .env variables
+
+app = FastAPI()
+
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+HF_API_URL = "https://api-inference.huggingface.co/models/OttoYu/TreeClassification"
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+
+@app.post("/predict")
+async def predict(file: UploadFile = File(...)):
+    image_data = await file.read()
+    base64_image = base64.b64encode(image_data).decode("utf-8")
+
+    headers = {
+        "Authorization": f"Bearer {HF_API_TOKEN}",
+        "Content-Type": "application/json"
+    }
+
+    response = requests.post(
+        HF_API_URL,
+        headers=headers,
+        json={"inputs": f"data:image/jpeg;base64,{base64_image}"}
+    )
+
+    if response.status_code != 200:
+        return {"error": "Failed to get prediction from Hugging Face API", "details": response.text}
+
+    result = response.json()
+    try:
+        label = result[0]["label"]
+    except Exception:
+        label = "ไม่สามารถจำแนกได้"
+
+    return {"label": label}

requirements.txt

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+fastapi
+uvicorn
+transformers
+torch
+pillow
+python-dotenv
+python-multipart