import torch.nn as nn

# ================================
# 🧠 MODEL CLASSES
# ================================

class BrainTumorModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.model = nn.Sequential(
            nn.Conv2d(3, 16, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(16, 32, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Flatten(),
            nn.Linear(32 * 56 * 56, 128),
            nn.ReLU(),
            nn.Linear(128, 4)
        )

    def forward(self, x):
        return self.model(x)

class GliomaStageModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.model = nn.Sequential(
            nn.Conv2d(3, 16, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Conv2d(16, 32, 3, padding=1),
            nn.ReLU(),
            nn.MaxPool2d(2),
            nn.Flatten(),
            nn.Linear(32 * 56 * 56, 128),
            nn.ReLU(),
            nn.Linear(128, 4)
        )

    def forward(self, x):
        return self.model(x)

def get_precautions_from_gemini(tumor_type: str) -> str:
    db = {
        "meningioma": "Avoid radiation exposure and get regular check‑ups.",
        "pituitary":   "Monitor hormonal levels and follow medication strictly.",
        "notumor":     "Stay healthy and get annual MRI scans if symptoms appear."
    }
    return db.get(tumor_type.lower(), "No specific precautions found.")