SivaMallikarjun commited on
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Create app.py

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  1. app.py +73 -0
app.py ADDED
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+ import torch
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+ import torch.nn as nn
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+ import torch.optim as optim
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+ import gradio as gr
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+ import numpy as np
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+
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+ # =========================
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+ # AI Model Definition (CNN for Brain-Eye Sync)
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+ # =========================
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+ class BrainEyeCNN(nn.Module):
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+ def __init__(self):
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+ super(BrainEyeCNN, self).__init__()
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+ self.conv1 = nn.Conv1d(in_channels=1, out_channels=8, kernel_size=3, stride=1, padding=1)
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+ self.relu = nn.ReLU()
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+ self.fc1 = nn.Linear(8 * 5, 5) # Fully connected layer
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+
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+ def forward(self, x):
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+ x = x.unsqueeze(1) # Add channel dimension
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+ x = self.relu(self.conv1(x))
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+ x = x.view(x.size(0), -1) # Flatten
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+ x = self.fc1(x)
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+ return x
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+
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+ # Initialize Model
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+ model = BrainEyeCNN()
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+
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+ # =========================
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+ # Pre-trained Simulated Weights
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+ # =========================
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+ # Normally, you'd train & save, but here we load fixed weights for Hugging Face
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+ with torch.no_grad():
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+ model.fc1.weight.fill_(0.5)
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+ model.fc1.bias.fill_(0.1)
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+
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+ # =========================
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+ # Quantum-Inspired Prediction
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+ # =========================
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+ def quantum_predict(data):
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+ """
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+ Quantum-Inspired Prediction: Uses parallel thought processing
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+ """
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+ q_data = torch.tensor([data], dtype=torch.float32)
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+ ai_output = model(q_data)
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+ prediction = torch.argmax(ai_output, dim=1).item()
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+
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+ # Quantum Parallelism Simulation
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+ quantum_states = ["Relaxed", "Focused", "Anxiety", "Meditative", "Decision-Making"]
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+ return quantum_states[prediction]
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+
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+ # =========================
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+ # Gradio UI for Hugging Face
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+ # =========================
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+ def predict_live(breathing, heartbeat, eye_focus, memory, cognition):
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+ input_data = [float(breathing), float(heartbeat), float(eye_focus), float(memory), float(cognition)]
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+ prediction = quantum_predict(input_data)
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+ return f"Predicted Mental State: {prediction}"
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+
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+ # Deploy on Hugging Face
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+ interface = gr.Interface(
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+ fn=predict_live,
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+ inputs=[
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+ gr.Textbox(label="Breathing Rate (0-1)"),
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+ gr.Textbox(label="Heart Rate (bpm)"),
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+ gr.Textbox(label="Eye Focus Level (0-1)"),
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+ gr.Textbox(label="Memory Recall Strength (0-1)"),
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+ gr.Textbox(label="Cognitive Load (0-1)")
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+ ],
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+ outputs="text"
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+ )
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+
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+ # Run the Gradio app
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+ if __name__ == "__main__":
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+ interface.launch()