Thu Apr 10 12:45:00 CST 2025 inscode

main.py

-import torch
-import logging
-from datetime import datetime
-
-# 初始化配置和标识
-genes = {'minsize': 3072, 'target_mod': 'site', 'cnt': 0, 'memory': []}
-mark = f"#####MyPython####_{datetime.now().strftime('%Y%m%d%H%M')}"
-
-# 配置日志
-logging.basicConfig(filename=f'{mark}.log', level=logging.INFO)
-
-class SiteModel(torch.nn.Module):
-    def __init__(self):
-        super().__init__()
-        self.fc = torch.nn.Linear(3072, 10)  # 假设输入维度 3072
-
-    def forward(self, x):
-        return self.fc(x)
-
-def train(genes, mark):
-    model = SiteModel()
-    optimizer = torch.optim.Adam(model.parameters())
-    criterion = torch.nn.CrossEntropyLoss()
-
-    # 模拟数据（实际需替换为 DataLoader）
-    inputs = torch.randn(10, 3072)  # 10 个样本
-    labels = torch.randint(0, 10, (10,))
-
-    for epoch in range(5):
-        optimizer.zero_grad()
-        outputs = model(inputs)
-        loss = criterion(outputs, labels)
-        loss.backward()
-        optimizer.step()
-
-        # 更新状态
-        genes['cnt'] += 1
-        genes['memory'].append(loss.item())
-        logging.info(f"Epoch {epoch}, Loss: {loss.item():.4f}")
-
-    # 保存模型和配置
-    torch.save({
-        'model_state': model.state_dict(),
-        'genes': genes
-    }, f"{mark}_checkpoint.pth")
-
-if __name__ == "__main__":
-    train(genes, mark)
-    print(f"Training completed! Check {mark}_*.log and {mark}_*.pth")
+from flask import Flask, request, jsonify
+import requests
+
+app = Flask(__name__)
+
+CSDN_API_URL = "https://g.csdnimg.cn/??lib/jquery/1.12.4/jquery.min.js"
+CSDN_API_KEY = "sk-pdcbucazcpktrpywbhoafyjvybwiogrrworwsuvbfryxv"
+
+@app.route('/ai', methods=['POST'])
+def ai_generate():
+    user_input = request.json.get('prompt')
+    if not user_input:
+        return jsonify({"error": "缺少输入"}), 400
+
+    # 调用 CSDN 的 AI 模型
+    try:
+        response = requests.post(
+            CSDN_API_URL,
+            headers={
+                "Content-Type": "application/json",
+                "Authorization": f"Bearer {sk-pdcbucazcpktrpywbhoafyjvybwiogrrworwsuvbfryxv}"
+            },
+            json={"prompt": user_input}
+        )
+        response.raise_for_status()
+        result = response.json().get("result", "无法生成内容")
+        return jsonify({"result": result})
+    except Exception as e:
+        return jsonify({"error": str(e)}), 500
+
+if __name__ == '__main__':
+    app.run(debug=True)
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