Update app.py

app.py

@@ -1,19 +1,18 @@
 from fastapi import FastAPI
-from fastapi.middleware.cors import CORSMiddleware  # 新增 CORS 支持
-import gradio as gr
+from fastapi.middleware.cors import CORSMiddleware
 from transformers import AutoTokenizer, AutoModelForSequenceClassification
 import torch
 import os
 
-# === FastAPI 初始化 ===
+# === FastAPI 配置 ===
 app = FastAPI()
 
-# 添加 CORS 中间件（关键步骤）
+# 解决 CSP 限制的关键配置
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["*"],  # 允许所有来源
-    allow_methods=["*"],  # 允许所有 HTTP 方法
-    allow_headers=["*"],  # 允许所有请求头
+    allow_origins=["*"],
+    allow_methods=["*"],
+    allow_headers=["*"],
 )
 
 # === 模型加载 ===
@@ -23,30 +22,15 @@ tokenizer = AutoTokenizer.from_pretrained("mrm8488/codebert-base-finetuned-detec
 
 # === HTTP API 接口 ===
 @app.post("/detect")
-async def api_detect(code: str):
-    """HTTP API 接口"""
+async def detect(code: str):
     try:
         inputs = tokenizer(code[:2000], return_tensors="pt", truncation=True, max_length=512)
         with torch.no_grad():
             outputs = model(**inputs)
         label_id = outputs.logits.argmax().item()
         return {
-            "label": int(label_id),  # 强制返回 0/1 数字
+            "label": int(label_id),  # 严格返回 0/1
             "score": outputs.logits.softmax(dim=-1)[0][label_id].item()
         }
     except Exception as e:
-        return {"error": str(e)}
-
-# === Gradio 界面（可选）===
-def gradio_predict(code: str):
-    result = api_detect(code)
-    return f"Prediction: {result['label']} (Confidence: {result['score']:.2f})"
-
-gr_interface = gr.Interface(
-    fn=gradio_predict,
-    inputs=gr.Textbox(lines=10, placeholder="Paste code here..."),
-    outputs="text",
-    title="Code Security Detector"
-)
-
-app = gr.mount_gradio_app(app, gr_interface, path="/")
+        return {"error": str(e)}