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