Create app.py

app.py

@@ -0,0 +1,149 @@
+import gradio as gr
+from collections import deque, Counter
+
+# =====================
+# STATE
+# =====================
+history = deque(maxlen=400)
+last10 = [None] * 10
+selected_index = {"idx": None}
+
+# =====================
+# HELPERS
+# =====================
+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)
+
+# =====================
+# ENGINE
+# =====================
+def predict():
+    if len(history) < 15:
+        return "WAIT", 0.50, "Not enough data"
+
+    data = list(history)
+    w5, w8, w13 = data[-5:], data[-8:], data[-13:]
+
+    b5 = bias_ratio(w5)
+    b13 = bias_ratio(w13)
+    avg_bias = (b5 + bias_ratio(w8) + b13) / 3
+    run = run_length(data)
+
+    pred = "BIG" if avg_bias >= 0.5 else "SMALL"
+
+    conf = 0.55
+    conf += 0.08 if run <= 2 else 0.03 if run == 3 else -0.15
+    conf += 0.05 if abs(b5 - b13) < 0.15 else -0.05
+    conf = max(0.35, min(conf, 0.75))
+
+    status = "GO" if conf >= 0.60 else "WARN"
+    return pred, round(conf, 2), status
+
+# =====================
+# RENDER
+# =====================
+def render():
+    boxes = ["" if x is None else str(x) for x in last10]
+    pred, conf, status = predict()
+    out = f"""Prediction : {pred}
+Confidence : {conf}
+Status     : {status}"""
+    return boxes + [out]
+
+# =====================
+# INPUT
+# =====================
+def add_number(n):
+    # fill selected box if exists
+    if selected_index["idx"] is not None:
+        idx = selected_index["idx"]
+        last10[idx] = n
+        history.append(bs(n))
+        selected_index["idx"] = None
+    else:
+        # shift left
+        last10.pop(0)
+        last10.append(n)
+        history.append(bs(n))
+    return render()
+
+def select_box(idx):
+    selected_index["idx"] = idx
+    return render()
+
+def backspace():
+    idx = selected_index["idx"]
+    if idx is not None and last10[idx] is not None:
+        last10[idx] = None
+        if history:
+            history.pop()
+    return render()
+
+def reset_all():
+    history.clear()
+    for i in range(10):
+        last10[i] = None
+    selected_index["idx"] = None
+    return render()
+
+# =====================
+# UI
+# =====================
+with gr.Blocks(theme=gr.themes.Soft()) as demo:
+    gr.Markdown("## 🧠 Big / Small Prediction Engine")
+
+    # last 10 boxes
+    with gr.Row():
+        boxes = []
+        for i in range(10):
+            b = gr.Button("", size="sm")
+            b.click(select_box,
+                    inputs=gr.Number(value=i, visible=False),
+                    outputs=[])
+            boxes.append(b)
+
+    with gr.Row():
+        out_box = gr.Textbox(label="Engine Output", lines=4)
+        back_btn = gr.Button("⌫ BACKSPACE", size="sm")
+        back_btn.click(backspace, outputs=boxes + [out_box])
+
+    gr.Markdown("### Quick Input")
+    with gr.Row():
+        for i in range(5):
+            gr.Button(str(i), size="sm").click(
+                add_number,
+                inputs=gr.Number(value=i, visible=False),
+                outputs=boxes + [out_box],
+            )
+    with gr.Row():
+        for i in range(5, 10):
+            gr.Button(str(i), size="sm").click(
+                add_number,
+                inputs=gr.Number(value=i, visible=False),
+                outputs=boxes + [out_box],
+            )
+
+    gr.Markdown("---")
+    gr.Button("RESET ALL DATA", variant="stop").click(
+        reset_all,
+        outputs=boxes + [out_box]
+    )
+
+demo.launch()