Spaces:
Sleeping
Sleeping
File size: 1,558 Bytes
c691d87 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 |
from fastapi import FastAPI
from pydantic import BaseModel
import requests
import os
app = FastAPI(title="ICD-10 Remote Inference")
# 🔑 ضع توكنك من إعدادات Hugging Face (Read access)
HF_TOKEN = os.getenv("HF_TOKEN", "YOUR_HF_API_TOKEN")
# قائمة الموديلات المراد تجربتها
MODELS = [
"AkshatSurolia/ICD-10-Code-Prediction",
"rjac/biobert-ICD10-L3-mimic",
"dataphysician/ModernBERT-icd10-classifier"
]
HEADERS = {"Authorization": f"Bearer {HF_TOKEN}"}
class TextInput(BaseModel):
text: str
@app.get("/")
def home():
return {"status": "running", "models_to_try": MODELS}
def query_model(model_name: str, text: str):
url = f"https://api-inference.huggingface.co/models/{model_name}"
payload = {"inputs": text}
response = requests.post(url, headers=HEADERS, json=payload, timeout=30)
if response.status_code == 200:
return response.json()
else:
raise RuntimeError(f"{model_name} failed: {response.status_code}")
@app.post("/predict")
def predict_icd10(input: TextInput):
for model_name in MODELS:
try:
print(f"🔹 Trying remote model: {model_name}")
result = query_model(model_name, input.text)
return {
"model_used": model_name,
"input": input.text,
"raw_response": result
}
except Exception as e:
print(f"⚠️ {model_name} failed: {e}")
continue
return {"error": "❌ All remote models failed to respond"}
|