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import gradio as gr |
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from collections import deque, Counter |
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history = deque(maxlen=200) |
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last10 = deque(maxlen=10) |
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def bs(n): |
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return "S" if n <= 4 else "B" |
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def run_length(data): |
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if len(data) < 2: |
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return 1 |
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r = 1 |
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for i in range(len(data)-1, 0, -1): |
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if data[i] == data[i-1]: |
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r += 1 |
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else: |
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break |
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return r |
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def bias_ratio(data): |
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if not data: |
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return 0.5 |
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c = Counter(data) |
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return c["B"] / len(data) |
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def predict(): |
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if len(history) < 15: |
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return "WAIT", 0.50, "Not enough data" |
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data = list(history) |
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w5 = data[-5:] |
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w8 = data[-8:] |
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w13 = data[-13:] |
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b5 = bias_ratio(w5) |
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b8 = bias_ratio(w8) |
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b13 = bias_ratio(w13) |
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avg_bias = (b5 + b8 + b13) / 3 |
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run = run_length(data) |
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pred = "BIG" if avg_bias >= 0.5 else "SMALL" |
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conf = 0.55 |
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if run <= 2: |
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conf += 0.08 |
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elif run == 3: |
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conf += 0.03 |
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else: |
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conf -= 0.15 |
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if abs(b5 - b13) < 0.15: |
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conf += 0.05 |
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else: |
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conf -= 0.05 |
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conf = max(0.35, min(conf, 0.75)) |
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status = "GO" if conf >= 0.60 else "WARN" |
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return pred, round(conf, 2), status |
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def add_number(n): |
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n = int(n) |
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history.append(bs(n)) |
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last10.append(str(n)) |
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pred, conf, status = predict() |
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hist_view = " ".join(last10) |
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out = f""" |
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Prediction : {pred} |
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Confidence : {conf} |
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Status : {status} |
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""" |
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return hist_view, out |
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with gr.Blocks(theme=gr.themes.Soft()) as demo: |
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gr.Markdown("## 🧠 Big / Small Engine (Rule + Short Memory)") |
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hist_box = gr.Textbox(label="Last 10 Inputs", interactive=False) |
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out_box = gr.Textbox(label="Engine Output", lines=5) |
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with gr.Row(): |
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for i in range(10): |
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btn = gr.Button(str(i)) |
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btn.click( |
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fn=add_number, |
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inputs=gr.Number(value=i, visible=False), |
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outputs=[hist_box, out_box] |
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) |
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demo.launch() |
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