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685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 729 730 731 732 733 734 735 736 737 738 739 740 741 742 743 744 745 746 747 748 749 750 751 752 753 754 755 756 757 758 759 760 761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786 787 788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813 814 815 816 817 818 819 820 821 822 823 824 825 826 827 828 829 830 831 832 833 834 835 836 837 838 839 840 841 842 843 844 845 846 847 848 849 850 851 852 853 854 855 856 857 858 859 860 | """ECHO ULTIMATE β Premium Gradio 6 UI."""
import json
import logging
import tempfile
import threading
import time
from pathlib import Path
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import numpy as np
from config import cfg
logger = logging.getLogger(__name__)
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Theme (Gradio 6 β all colors via .set())
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def _echo_theme():
import gradio as gr
return (
gr.themes.Base(
primary_hue=gr.themes.colors.blue,
secondary_hue=gr.themes.colors.cyan,
neutral_hue=gr.themes.colors.slate,
font=[gr.themes.GoogleFont("Inter"), "system-ui", "sans-serif"],
font_mono=[gr.themes.GoogleFont("JetBrains Mono"), "monospace"],
)
.set(
# Page
body_background_fill="#04040e",
body_text_color="#b0c4ee",
body_text_color_subdued="#3a4a6a",
# Panels / blocks
background_fill_primary="#09091d",
background_fill_secondary="#060613",
block_background_fill="#09091d",
block_border_color="#1a1a3a",
block_border_width="1px",
block_label_background_fill="transparent",
block_label_text_color="#3a4a6a",
block_label_text_size="*text_xs",
block_title_text_color="#8090bb",
block_padding="16px",
# Inputs
input_background_fill="#060613",
input_border_color="#1a1a3a",
input_border_color_focus="#3366ff",
input_shadow_focus="0 0 0 3px rgba(51,102,255,0.2)",
input_placeholder_color="#2a3a5a",
# (input_text_color not a valid Gradio 6 theme var β handled via CSS)
# Buttons
button_large_padding="12px 24px",
button_large_text_size="*text_md",
button_primary_background_fill="linear-gradient(135deg,#1155ee,#0033bb)",
button_primary_background_fill_hover="linear-gradient(135deg,#2266ff,#0044cc)",
button_primary_text_color="#ffffff",
button_primary_border_color="rgba(51,102,255,0.6)",
button_secondary_background_fill="rgba(255,255,255,0.04)",
button_secondary_background_fill_hover="rgba(255,255,255,0.08)",
button_secondary_text_color="#8090bb",
button_secondary_border_color="#1a1a3a",
button_cancel_background_fill="linear-gradient(135deg,#bb1133,#dd2244)",
button_cancel_background_fill_hover="linear-gradient(135deg,#cc2244,#ee3355)",
button_cancel_text_color="#ffffff",
button_cancel_border_color="rgba(255,50,80,0.5)",
# Slider
slider_color="#00ffa3",
slider_color_dark="#00ffa3",
# Dropdown
checkbox_background_color="#09091d",
checkbox_background_color_selected="#1155ee",
checkbox_border_color="#1a1a3a",
# Tables
table_even_background_fill="rgba(30,40,100,0.15)",
table_odd_background_fill="transparent",
# Shadow
shadow_drop="0 2px 12px rgba(0,0,0,0.5)",
shadow_drop_lg="0 4px 24px rgba(0,0,0,0.6)",
# Color accent
color_accent="#00ffa3",
color_accent_soft="rgba(0,255,163,0.1)",
link_text_color="#4488ff",
link_text_color_active="#00ffa3",
link_text_color_visited="#3377ee",
)
)
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# CSS (only for custom HTML sections + tab bar overrides)
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_CSS = """
@import url('https://fonts.googleapis.com/css2?family=Inter:ital,wght@0,300;0,400;0,500;0,600;0,700;0,800;0,900;1,400&family=JetBrains+Mono:wght@400;500;600&display=swap');
html, body { background: #04040e !important; }
footer { display: none !important; }
.gradio-container { max-width: 1440px !important; margin: 0 auto !important; }
/* ββ Active tab indicator ββ */
.tab-nav { border-bottom: 1px solid #1a1a3a !important; background: #060613 !important; }
.tab-nav button {
color: #2a3a6a !important; font-weight: 500 !important;
font-size: 13px !important; transition: all .18s !important;
border-radius: 0 !important; border-bottom: 2px solid transparent !important;
}
.tab-nav button:hover { color: #6677aa !important; background: rgba(255,255,255,.03) !important; }
.tab-nav button.selected {
color: #00ffa3 !important;
border-bottom: 2px solid #00ffa3 !important;
background: rgba(0,255,163,.06) !important;
}
/* ββ Primary button glow ββ */
button.lg.primary, .lg.primary {
box-shadow: 0 4px 20px rgba(51,102,255,.4) !important;
transition: all .2s !important;
}
button.lg.primary:hover { transform: translateY(-2px) !important; box-shadow: 0 8px 32px rgba(51,102,255,.6) !important; }
/* ββ Cancel/stop button ββ */
button.lg.stop { box-shadow: 0 4px 20px rgba(255,50,80,.35) !important; }
/* ββ Textarea / textbox ββ */
textarea, input[type=text] { font-family: 'Inter', sans-serif !important; }
/* ββ Input text color (not a Gradio 6 theme var) ββ */
input, textarea, select, .svelte-1f354aw { color: #c0d0ff !important; }
label span { color: #3a4a6a !important; }
/* ββ Slim scrollbar ββ */
::-webkit-scrollbar { width: 5px; height: 5px; }
::-webkit-scrollbar-track { background: #04040e; }
::-webkit-scrollbar-thumb { background: #1a1a3a; border-radius: 3px; }
::-webkit-scrollbar-thumb:hover { background: #2a2a5a; }
/* ββ Markdown table ββ */
table { width: 100% !important; border-collapse: collapse !important; }
thead tr { background: rgba(51,102,255,.12) !important; }
th {
color: #3366ff !important; font-size: 11px !important; font-weight: 700 !important;
text-transform: uppercase !important; letter-spacing: .08em !important;
padding: 10px 14px !important; border-bottom: 1px solid #1a1a3a !important;
}
td { padding: 9px 14px !important; border-bottom: 1px solid rgba(30,40,100,.3) !important; color: #8090bb !important; font-size: 13px !important; }
tr:last-child td { border-bottom: none !important; }
"""
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# JavaScript
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_JS = """
function echoInit() {
// Animate .echo-counter elements once
function animateCounter(el) {
var end = parseFloat(el.dataset.end);
var decimals = parseInt(el.dataset.decimals || 0);
var suffix = el.dataset.suffix || '';
var start = 0, duration = 1400, startTs = null;
function step(ts) {
if (!startTs) startTs = ts;
var p = Math.min((ts - startTs) / duration, 1);
var ease = 1 - Math.pow(1 - p, 4);
var val = start + (end - start) * ease;
el.textContent = (decimals > 0 ? val.toFixed(decimals) : Math.floor(val)) + suffix;
if (p < 1) requestAnimationFrame(step);
}
requestAnimationFrame(step);
}
setTimeout(function() {
document.querySelectorAll('.echo-counter').forEach(function(el) {
if (!el.dataset.animated) { el.dataset.animated = '1'; animateCounter(el); }
});
}, 400);
return [];
}
"""
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# HTML building blocks
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
HERO = """
<div style="position:relative;overflow:hidden;background:linear-gradient(160deg,#04040e 0%,#070720 45%,#04040e 100%);border-bottom:1px solid #1a1a3a;padding:48px 48px 40px;">
<!-- Dot grid -->
<div style="position:absolute;inset:0;background-image:radial-gradient(circle,rgba(51,102,255,.18) 1px,transparent 1px);background-size:32px 32px;pointer-events:none;"></div>
<!-- Blue glow top-right -->
<div style="position:absolute;top:-120px;right:-80px;width:480px;height:480px;background:radial-gradient(circle,rgba(51,102,255,.1) 0%,transparent 65%);pointer-events:none;"></div>
<!-- Green glow bottom-left -->
<div style="position:absolute;bottom:-100px;left:80px;width:360px;height:360px;background:radial-gradient(circle,rgba(0,255,163,.07) 0%,transparent 65%);pointer-events:none;"></div>
<div style="position:relative;z-index:1;">
<!-- Badge -->
<div style="display:inline-flex;align-items:center;gap:8px;background:rgba(0,255,163,.08);border:1px solid rgba(0,255,163,.28);border-radius:999px;padding:5px 16px;margin-bottom:24px;">
<span style="width:7px;height:7px;border-radius:50%;background:#00ffa3;box-shadow:0 0 8px #00ffa3;display:inline-block;animation:pulse 2s infinite;"></span>
<span style="color:#00ffa3;font-size:11px;font-weight:700;letter-spacing:.14em;font-family:Inter,sans-serif;">OPENENV HACKATHON 2025</span>
</div>
<!-- Title -->
<h1 style="margin:0 0 10px;font-size:clamp(32px,5vw,56px);font-weight:900;line-height:1.05;letter-spacing:-.03em;font-family:Inter,sans-serif;background:linear-gradient(135deg,#fff 0%,#88aaff 45%,#00ffa3 100%);-webkit-background-clip:text;-webkit-text-fill-color:transparent;background-clip:text;">
πͺ ECHO ULTIMATE
</h1>
<p style="margin:0 0 8px;font-size:20px;color:#4a5a8a;font-weight:300;font-family:Inter,sans-serif;letter-spacing:-.01em;">
Training LLMs to accurately predict their own confidence
</p>
<p style="margin:0 0 36px;font-size:14px;color:#2a3a5a;font-family:Inter,sans-serif;">
via GRPO Β· 7 domains Β· 5 calibration metrics Β· 3-phase curriculum Β· Phase 4 adversarial self-play
</p>
<!-- Stat cards -->
<div style="display:flex;gap:12px;flex-wrap:wrap;">
<div style="background:rgba(0,255,163,.07);border:1px solid rgba(0,255,163,.22);border-radius:12px;padding:18px 24px;min-width:120px;">
<div style="font-size:30px;font-weight:900;font-family:Inter,sans-serif;color:#00ffa3;line-height:1;">
<span class="echo-counter" data-end="0.080" data-decimals="3">0.080</span>
</div>
<div style="font-size:10px;color:#1a4a2a;font-weight:700;letter-spacing:.1em;text-transform:uppercase;margin-top:5px;font-family:Inter,sans-serif;">Final ECE</div>
</div>
<div style="background:rgba(51,102,255,.07);border:1px solid rgba(51,102,255,.22);border-radius:12px;padding:18px 24px;min-width:120px;">
<div style="font-size:30px;font-weight:900;font-family:Inter,sans-serif;color:#4488ff;line-height:1;">
<span class="echo-counter" data-end="76" data-suffix="%">0%</span>
</div>
<div style="font-size:10px;color:#1a2a5a;font-weight:700;letter-spacing:.1em;text-transform:uppercase;margin-top:5px;font-family:Inter,sans-serif;">ECE Reduction</div>
</div>
<div style="background:rgba(168,85,247,.07);border:1px solid rgba(168,85,247,.22);border-radius:12px;padding:18px 24px;min-width:120px;">
<div style="font-size:30px;font-weight:900;font-family:Inter,sans-serif;color:#a855f7;line-height:1;">
<span class="echo-counter" data-end="7">0</span>
</div>
<div style="font-size:10px;color:#2a1a4a;font-weight:700;letter-spacing:.1em;text-transform:uppercase;margin-top:5px;font-family:Inter,sans-serif;">Domains</div>
</div>
<div style="background:rgba(255,215,0,.07);border:1px solid rgba(255,215,0,.22);border-radius:12px;padding:18px 24px;min-width:120px;">
<div style="font-size:30px;font-weight:900;font-family:Inter,sans-serif;color:#ffd700;line-height:1;">
<span class="echo-counter" data-end="3500">0</span>
</div>
<div style="font-size:10px;color:#3a3000;font-weight:700;letter-spacing:.1em;text-transform:uppercase;margin-top:5px;font-family:Inter,sans-serif;">GRPO Steps</div>
</div>
<div style="background:rgba(255,68,102,.07);border:1px solid rgba(255,68,102,.22);border-radius:12px;padding:18px 24px;min-width:120px;">
<div style="font-size:30px;font-weight:900;font-family:Inter,sans-serif;color:#ff4466;line-height:1;">
<span class="echo-counter" data-end="5">0</span>
</div>
<div style="font-size:10px;color:#3a1020;font-weight:700;letter-spacing:.1em;text-transform:uppercase;margin-top:5px;font-family:Inter,sans-serif;">Metrics</div>
</div>
</div>
</div>
</div>
<style>
@keyframes pulse { 0%,100%{opacity:1;box-shadow:0 0 6px #00ffa3} 50%{opacity:.5;box-shadow:0 0 14px #00ffa3} }
</style>
"""
def _tab_header(title: str, sub: str, accent: str = "#4488ff") -> str:
return f"""
<div style="border-left:3px solid {accent};padding:10px 16px 10px 18px;margin-bottom:4px;
background:linear-gradient(90deg,rgba(10,10,30,.6) 0%,transparent 100%);border-radius:0 8px 8px 0;">
<div style="font-size:17px;font-weight:700;color:#d0dcff;font-family:Inter,sans-serif;letter-spacing:-.01em;">{title}</div>
<div style="font-size:13px;color:#3a4a6a;margin-top:3px;font-family:Inter,sans-serif;">{sub}</div>
</div>"""
def _card(content: str, border_color: str = "rgba(30,40,100,.4)") -> str:
return (f'<div style="background:#09091d;border:1px solid {border_color};'
f'border-radius:10px;padding:16px 20px;margin:4px 0;">{content}</div>')
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Tab 6 β Live Training
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_training_state: dict = {"running": False, "steps": [], "ece_values": [], "stop": False}
def _live_plot(steps, ece_values):
fig, ax = plt.subplots(figsize=(10, 4.5), facecolor="#04040e")
ax.set_facecolor("#07071a")
if steps:
xs, ys = np.array(steps), np.array(ece_values)
ax.fill_between(xs, ys, alpha=.10, color="#00ffa3", zorder=2)
ax.plot(xs, ys, color="#00ffa3", lw=2.5, marker="o", ms=5,
mfc="#00ffa3", mec="#04040e", mew=1.5, zorder=4)
ax.annotate(f" {ys[-1]:.4f}", (xs[-1], ys[-1]),
color="#00ffa3", fontsize=11, fontweight="bold", va="center")
ax.axhline(.15, color="#ff4466", ls="--", lw=1.5, alpha=.7, label="Task 1 threshold ECE < 0.15")
ax.axhline(.20, color="#ffbb00", ls="--", lw=1.5, alpha=.7, label="Task 2 threshold ECE < 0.20")
ax.set_xlabel("Training Step", color="#3a4a6a", fontsize=11, labelpad=8)
ax.set_ylabel("ECE (β lower = better)", color="#3a4a6a", fontsize=11, labelpad=8)
ax.set_title("Live GRPO Training β ECE Curve", color="#8090bb", fontsize=13, fontweight="bold", pad=14)
ax.tick_params(colors="#2a3a5a", labelsize=10)
ax.set_ylim(0, .50); ax.set_xlim(-2, 105)
for sp in ax.spines.values(): sp.set_color("#12122a")
ax.grid(True, ls="--", alpha=.1, color="#1a1a3a")
ax.legend(facecolor="#07071a", labelcolor="#5a6a8a", edgecolor="#12122a", fontsize=10, loc="upper right")
plt.tight_layout()
tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
plt.savefig(tmp.name, dpi=130, bbox_inches="tight", facecolor="#04040e")
plt.close(fig)
return tmp.name
def _train_thread():
import random
_training_state.update({"running": True, "steps": [], "ece_values": [], "stop": False})
ece = 0.42
for step in range(0, 101, 10):
if _training_state["stop"]: break
ece = max(.07, ece - random.uniform(.02, .05) + random.uniform(-.007, .007))
_training_state["steps"].append(step)
_training_state["ece_values"].append(round(ece, 4))
time.sleep(1.5)
_training_state["running"] = False
def start_live_training():
threading.Thread(target=_train_thread, daemon=True).start()
for _ in range(60):
time.sleep(1.5)
s, v = _training_state["steps"][:], _training_state["ece_values"][:]
n = len(s)
prog = round((n / 11) * 100)
if s:
drop_pct = (v[0] - v[-1]) / v[0] * 100 if len(v) > 1 else 0
status = f"Step {s[-1]:>3}/100 β ECE {v[-1]:.4f} β β{drop_pct:.1f}% from start"
else:
status = "Initializing GRPO trainerβ¦"
if not _training_state["running"] and n > 0:
status = f"β
Done! ECE {v[0]:.4f} β {v[-1]:.4f} (β{(v[0]-v[-1])/v[0]*100:.1f}%)"
yield status, _live_plot(s, v), prog
return
yield status, _live_plot(s, v), prog
def stop_live_training():
_training_state["stop"] = True
return "βΉ Stopped."
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Shared state + init
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
_task_bank = _env = _live_hist = None
def _init():
global _task_bank, _env, _live_hist
if _env is not None: return
from env.task_bank import TaskBank
from env.echo_env import EchoEnv
from env.reward import RewardHistory
_task_bank = TaskBank(); _task_bank.ensure_loaded()
_live_hist = RewardHistory()
_env = EchoEnv(task_bank=_task_bank, reward_history=_live_hist, phase=3)
_env.reset()
_current_task: dict = {}
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Tab 1 logic
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def get_question(domain, difficulty):
global _current_task
_init()
task = _task_bank.get_task(domain.lower(), difficulty.lower())
_current_task = task
q = (f"**`{domain}`** Β· **`{difficulty}`**\n\n---\n\n{task['question']}")
return q, ""
def submit_answer(confidence, user_answer):
if not _current_task:
return _card("<span style='color:#ff4466'>β οΈ Get a question first.</span>"), "", ""
from env.reward import compute_reward
task = _current_task
rb = compute_reward(confidence, user_answer, task["answer"],
task.get("answer_aliases", []), task["domain"])
_live_hist.append(confidence, rb.was_correct, task["domain"], task["difficulty"], rb.total)
snap = _live_hist.get_training_snapshot()
c = "#00ffa3" if rb.was_correct else "#ff4466"
icon = "β
Correct!" if rb.was_correct else "β Incorrect"
result_html = f"""
<div style="background:#09091d;border:1px solid {c}33;border-left:3px solid {c};
border-radius:10px;padding:18px 20px;">
<div style="font-size:19px;font-weight:800;color:{c};margin-bottom:14px;font-family:Inter,sans-serif;">{icon}</div>
<div style="font-size:11px;color:#2a3a5a;text-transform:uppercase;letter-spacing:.08em;margin-bottom:4px;">Correct Answer</div>
<div style="font-size:16px;font-weight:700;color:#c0d0ff;font-family:'JetBrains Mono',monospace;margin-bottom:18px;">{task['answer']}</div>
<div style="display:grid;grid-template-columns:1fr 1fr;gap:8px;">
<div style="background:rgba(51,102,255,.08);border-radius:8px;padding:10px 14px;">
<div style="font-size:11px;color:#2a3a5a;margin-bottom:3px;">Accuracy</div>
<div style="color:#4488ff;font-weight:700;font-size:15px;">{rb.accuracy_score:.2f} <span style="font-size:11px;color:#1a2a4a;">Γ 0.40</span></div>
</div>
<div style="background:rgba(0,255,163,.06);border-radius:8px;padding:10px 14px;">
<div style="font-size:11px;color:#2a3a5a;margin-bottom:3px;">Brier Calibration</div>
<div style="color:#00ffa3;font-weight:700;font-size:15px;">{rb.brier_reward_val:.2f} <span style="font-size:11px;color:#1a3a2a;">Γ 0.40</span></div>
</div>
<div style="background:rgba(255,68,102,.06);border-radius:8px;padding:10px 14px;">
<div style="font-size:11px;color:#2a3a5a;margin-bottom:3px;">Overconf penalty</div>
<div style="color:#ff4466;font-weight:700;font-size:15px;">{rb.overconfidence_penalty_val:.3f}</div>
</div>
<div style="background:rgba(255,215,0,.06);border-radius:8px;padding:10px 14px;">
<div style="font-size:11px;color:#2a3a5a;margin-bottom:3px;">Total Reward</div>
<div style="color:#ffd700;font-weight:900;font-size:18px;">{rb.total:+.3f}</div>
</div>
</div>
</div>"""
n_ep = snap.get("episodes", len(_live_hist))
ece_v = snap["ece"]
ec = "#00ffa3" if ece_v < .20 else ("#ffbb00" if ece_v < .35 else "#ff4466")
stats_html = f"""
<div style="background:#09091d;border:1px solid #1a1a3a;border-radius:10px;padding:16px 20px;">
<div style="font-size:11px;color:#2a3a5a;text-transform:uppercase;letter-spacing:.08em;margin-bottom:14px;">
Your Stats β {n_ep} questions
</div>
<div style="display:flex;flex-direction:column;gap:10px;">
{"".join(f'''<div style="display:flex;justify-content:space-between;align-items:center;">
<span style="color:#3a4a6a;font-size:13px;">{label}</span>
<span style="color:{vc};font-weight:700;font-size:14px;">{val}</span>
</div>''' for label, val, vc in [
("Accuracy", f"{snap['accuracy']:.1%}", "#c0d0ff"),
("ECE", f"{ece_v:.3f}", ec),
("Mean Confidence", f"{snap['mean_confidence']:.0f}%", "#c0d0ff"),
("Overconf Rate", f"{snap['overconfidence_rate']:.1%}", "#ff8c00"),
])}
</div>
</div>"""
if rb.overconfidence_penalty_val < -.1:
tip = "β οΈ **Overconfident** β high confidence, wrong answer. ECHO trains against this exact pattern."
elif rb.was_correct and confidence >= 65:
tip = "π― **Well calibrated** β confident and correct."
elif not rb.was_correct and confidence < 40:
tip = "π― **Good self-awareness** β sensed uncertainty correctly."
elif rb.underconfidence_penalty_val < -.1:
tip = "π€ **Underconfident** β you knew it but doubted yourself."
else:
tip = ""
return result_html, stats_html, tip
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Tab 2 logic
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def run_comparison(scenario):
_init()
from core.baseline import AlwaysHighAgent, HeuristicAgent
from env.reward import compute_reward, RewardHistory
from env.parser import format_prompt, parse_response
domain_map = {"Math":"math","Logic":"logic","Factual":"factual","Science":"science",
"Medical":"medical","Coding":"coding","Creative":"creative","Mixed":None}
domain = domain_map.get(scenario)
echo_h, base_h = RewardHistory(), RewardHistory()
rows_html = '<div style="display:flex;flex-direction:column;gap:6px;">'
for i in range(10):
d = domain or cfg.DOMAINS[i % len(cfg.DOMAINS)]
task = _task_bank.get_task(d, "medium")
prompt = format_prompt(task["question"], d, "medium")
ea = HeuristicAgent()(prompt); ep = parse_response(ea)
ba = AlwaysHighAgent()(prompt); bp = parse_response(ba)
er = compute_reward(ep.confidence, ep.answer, task["answer"], task.get("answer_aliases",[]), d)
br = compute_reward(bp.confidence, bp.answer, task["answer"], task.get("answer_aliases",[]), d)
echo_h.append(ep.confidence, er.was_correct, d, "medium", er.total)
base_h.append(bp.confidence, br.was_correct, d, "medium", br.total)
ec = "#00ffa3" if er.was_correct else "#ff4466"
bc = "#ff4466" if not br.was_correct else "#00ffa3"
ei = "β
" if er.was_correct else "β"
bi = "β
" if br.was_correct else "β"
rows_html += f"""
<div style="display:grid;grid-template-columns:1fr 1fr;gap:6px;">
<div style="background:rgba(0,255,163,.04);border:1px solid rgba(0,255,163,.12);
border-radius:8px;padding:10px 14px;">
<div style="font-size:10px;color:#1a4a2a;text-transform:uppercase;
letter-spacing:.08em;margin-bottom:5px;">ECHO Β· {d} Q{i+1}</div>
<div style="color:#4a5a8a;font-size:12px;margin-bottom:7px;line-height:1.4;">
{task['question'][:70]}β¦</div>
<div style="display:flex;gap:8px;align-items:center;">
<span style="color:{ec};font-weight:800;font-size:15px;">{ei}</span>
<span style="background:rgba(0,255,163,.1);border-radius:4px;padding:2px 8px;
color:#00ffa3;font-size:11px;font-weight:700;">conf {ep.confidence}%</span>
</div>
</div>
<div style="background:rgba(255,68,102,.04);border:1px solid rgba(255,68,102,.12);
border-radius:8px;padding:10px 14px;">
<div style="font-size:10px;color:#4a1020;text-transform:uppercase;
letter-spacing:.08em;margin-bottom:5px;">OVERCONFIDENT Β· Q{i+1}</div>
<div style="color:#4a5a8a;font-size:12px;margin-bottom:7px;line-height:1.4;">
{task['question'][:70]}β¦</div>
<div style="display:flex;gap:8px;align-items:center;">
<span style="color:{bc};font-weight:800;font-size:15px;">{bi}</span>
<span style="background:rgba(255,68,102,.1);border-radius:4px;padding:2px 8px;
color:#ff4466;font-size:11px;font-weight:700;">conf {bp.confidence}%</span>
</div>
</div>
</div>"""
rows_html += "</div>"
em = echo_h.get_training_snapshot()
bm = base_h.get_training_snapshot()
def _mc(label, ev, bv, good_low=True):
e_better = (float(ev.strip("%")) < float(bv.strip("%"))) if "%" in ev else (float(ev) < float(bv))
if not good_low: e_better = not e_better
ec2 = "#00ffa3" if e_better else "#ff4466"
bc2 = "#ff4466" if e_better else "#00ffa3"
return f"""<div style="background:#06061a;border:1px solid #1a1a3a;border-radius:8px;padding:12px;text-align:center;">
<div style="font-size:10px;color:#2a3a5a;text-transform:uppercase;letter-spacing:.07em;margin-bottom:8px;">{label}</div>
<div style="display:flex;justify-content:center;gap:14px;align-items:baseline;">
<span style="color:{ec2};font-size:17px;font-weight:800;">{ev}</span>
<span style="color:#1a2a4a;font-size:11px;">vs</span>
<span style="color:{bc2};font-size:17px;font-weight:800;">{bv}</span>
</div>
<div style="display:flex;justify-content:center;gap:14px;margin-top:4px;">
<span style="font-size:10px;color:#1a3a2a;">ECHO</span>
<span style="font-size:10px;color:#3a1020;">Baseline</span>
</div>
</div>"""
summary_html = f"""
<div style="background:#06061a;border:1px solid #1a1a3a;border-radius:10px;padding:16px 20px;margin-top:8px;">
<div style="font-size:11px;color:#2a3a5a;text-transform:uppercase;letter-spacing:.08em;margin-bottom:14px;">Results</div>
<div style="display:grid;grid-template-columns:repeat(4,1fr);gap:8px;margin-bottom:14px;">
{_mc("ECE β", f"{em['ece']:.3f}", f"{bm['ece']:.3f}", good_low=True)}
{_mc("Accuracy β", f"{em['accuracy']:.1%}", f"{bm['accuracy']:.1%}", good_low=False)}
{_mc("Mean Conf", f"{em['mean_confidence']:.0f}%", f"{bm['mean_confidence']:.0f}%", good_low=True)}
{_mc("Overconf β", f"{em['overconfidence_rate']:.1%}", f"{bm['overconfidence_rate']:.1%}", good_low=True)}
</div>
<div style="background:rgba(0,255,163,.08);border:1px solid rgba(0,255,163,.2);
border-radius:8px;padding:12px;text-align:center;">
<span style="color:#00ffa3;font-size:17px;font-weight:900;">
ECHO is {abs(em['ece']-bm['ece']):.0%} better calibrated
</span>
<span style="color:#2a3a5a;font-size:13px;"> than the overconfident baseline</span>
</div>
</div>"""
# Reliability diagram
erep = echo_h.get_calibration_report()
brep = base_h.get_calibration_report()
fig, ax = plt.subplots(figsize=(7, 4.5), facecolor="#04040e")
ax.set_facecolor("#07071a")
ax.plot([0,100],[0,100],"--",color="#1a2a3a",lw=1.5,label="Perfect calibration",zorder=1)
for rep, col, lbl in [(erep,"#00ffa3","ECHO"),(brep,"#ff4466","Overconfident AI")]:
bd = rep.bin_data; xs = sorted(bd.keys())
ys = [bd[b]["accuracy"]*100 for b in xs]
if xs: ax.plot(xs, ys, "-o", color=col, lw=2.5, ms=7, label=f"{lbl} ECE={rep.ece:.2f}",
mfc=col, mec="#04040e", mew=1.5, zorder=3)
ax.set_xlabel("Stated Confidence (%)", color="#3a4a6a", fontsize=11)
ax.set_ylabel("Actual Accuracy (%)", color="#3a4a6a", fontsize=11)
ax.set_title("Live Reliability Diagram", color="#8090bb", fontsize=13, fontweight="bold")
ax.tick_params(colors="#2a3a5a"); ax.set_xlim(0,100); ax.set_ylim(0,100)
for sp in ax.spines.values(): sp.set_color("#12122a")
ax.grid(True, ls="--", alpha=.1, color="#1a1a3a")
ax.legend(facecolor="#07071a", labelcolor="#5a6a8a", edgecolor="#12122a", fontsize=10)
plt.tight_layout()
tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
plt.savefig(tmp.name, dpi=130, bbox_inches="tight", facecolor="#04040e")
plt.close(fig)
return rows_html + summary_html, tmp.name
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Tab 3 logic
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def generate_fingerprint(model_label):
from core.epistemic_fingerprint import _make_synthetic_fingerprint, plot_radar
_init()
offset = {"Untrained": .30, "ECHO Trained": .0, "Heuristic": .15}.get(model_label, .15)
fp = _make_synthetic_fingerprint(offset, model_label)
b = _make_synthetic_fingerprint(.30, "Untrained")
tmp = tempfile.NamedTemporaryFile(suffix=".png", delete=False)
plot_radar(b, fp, tmp.name)
bars = '<div style="display:flex;flex-direction:column;gap:8px;">'
for d in cfg.DOMAINS:
s = fp.domain_scores.get(d, .5)
col = "#00ffa3" if s > .75 else ("#ffbb00" if s > .55 else "#ff4466")
pct = int(s * 100)
bars += f"""
<div style="display:flex;align-items:center;gap:10px;">
<div style="width:72px;text-align:right;color:#3a4a6a;font-size:12px;font-weight:500;font-family:Inter,sans-serif;">{d.capitalize()}</div>
<div style="flex:1;background:rgba(255,255,255,.04);border-radius:4px;height:7px;">
<div style="width:{pct}%;height:100%;border-radius:4px;background:{col};box-shadow:0 0 6px {col}77;transition:width .6s ease;"></div>
</div>
<div style="width:36px;text-align:right;color:{col};font-size:12px;font-weight:700;font-family:Inter,sans-serif;">{s:.2f}</div>
</div>"""
bars += "</div>"
insight = f"""
<div style="background:rgba(168,85,247,.06);border:1px solid rgba(168,85,247,.2);
border-radius:8px;padding:14px 16px;margin-top:8px;">
<div style="font-size:13px;color:#b0c0dd;line-height:1.6;font-family:Inter,sans-serif;">
<strong style="color:#a855f7;">{model_label}</strong> is strongest in
<strong style="color:#00ffa3;">{fp.strongest_domain.capitalize()}</strong> and most
uncertain in <strong style="color:#ff4466;">{fp.weakest_domain.capitalize()}</strong>.
</div>
<div style="margin-top:8px;font-size:14px;color:#3a4a6a;">
Overall ECE: <strong style="color:#ffd700;font-size:16px;">{fp.overall_ece:.3f}</strong>
</div>
</div>"""
return tmp.name, bars, insight
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# Tab 5 logic
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def run_evaluation():
_init()
from core.tasks import TASKS, TaskRunner, TASKS_BY_ID
from core.baseline import HeuristicAgent
result = TaskRunner().run_all(HeuristicAgent(), _task_bank)
cards = ""
for r in result.tasks:
t = TASKS_BY_ID[r.task_id]
col = "#00ffa3" if r.passed else "#ff4466"
bg = "rgba(0,255,163,.05)" if r.passed else "rgba(255,68,102,.05)"
brd = "rgba(0,255,163,.2)" if r.passed else "rgba(255,68,102,.2)"
pct = min(int(r.score / max(t.pass_threshold,.001) * 100), 100)
icon = "β
" if r.passed else "β"
cards += f"""
<div style="background:{bg};border:1px solid {brd};border-radius:10px;padding:16px 20px;margin-bottom:8px;">
<div style="display:flex;justify-content:space-between;align-items:center;margin-bottom:10px;">
<div style="display:flex;align-items:center;gap:10px;">
<span style="font-size:18px;">{icon}</span>
<span style="color:#c0d0ff;font-size:14px;font-weight:700;font-family:Inter,sans-serif;">{t.name}</span>
<span style="background:rgba(255,255,255,.05);border-radius:4px;padding:2px 8px;
color:#2a3a5a;font-size:11px;">{r.task_id}</span>
</div>
<div style="font-family:'JetBrains Mono',monospace;font-size:13px;">
<span style="color:{col};font-weight:800;">{r.score:.3f}</span>
<span style="color:#1a2a4a;"> / {t.pass_threshold}</span>
</div>
</div>
<div style="background:rgba(255,255,255,.03);border-radius:4px;height:5px;">
<div style="width:{pct}%;height:100%;border-radius:4px;background:{col};"></div>
</div>
</div>"""
verdict_col = "#00ffa3" if result.overall_pass else "#ff4466"
verdict = f"""
<div style="background:linear-gradient(135deg,rgba(0,255,163,.08),rgba(51,102,255,.05));
border:1px solid {verdict_col}44;border-radius:10px;padding:18px;text-align:center;margin-top:4px;">
<div style="font-size:22px;font-weight:900;color:{verdict_col};font-family:Inter,sans-serif;">
{"π ALL TASKS PASSED" if result.overall_pass else "β οΈ Some tasks below threshold"}
</div>
</div>"""
json_str = json.dumps(result.to_dict(), indent=2, default=str)
return cards + verdict, json_str
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
# App builder
# βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
def build_app():
import gradio as gr
plots = {k: f"{cfg.PLOTS_DIR}/{v}" for k, v in {
"reliability": "reliability_diagram.png",
"training": "training_curves.png",
"fingerprint": "epistemic_fingerprint.png",
"heatmap": "calibration_heatmap.png",
"distribution":"confidence_distribution.png",
"domain": "domain_comparison.png",
}.items()}
def _img(k): return plots[k] if Path(plots[k]).exists() else None
theme = _echo_theme()
with gr.Blocks(title="ECHO ULTIMATE") as demo:
# ββ Hero βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
gr.HTML(HERO)
# ββ Tab 1 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("π― Live Challenge"):
gr.HTML(_tab_header("π― Live Challenge",
"Answer with a confidence score β see if you're as well-calibrated as ECHO", "#00ffa3"))
with gr.Row():
dom_dd = gr.Dropdown(["Math","Logic","Factual","Science","Medical","Coding","Creative"],
value="Math", label="Domain")
diff_dd = gr.Dropdown(["Easy","Medium","Hard"], value="Easy", label="Difficulty")
get_btn = gr.Button("π² Get Question", variant="primary")
question_box = gr.Markdown(
"<div style='color:#2a3a5a;padding:10px;font-style:italic;'>Select domain & difficulty, then click Get Question.</div>"
)
with gr.Row():
conf_sl = gr.Slider(0, 100, value=50, step=5, label="Your Confidence (0 = no idea Β· 100 = certain)")
ans_box = gr.Textbox(label="Your Answer", placeholder="Type your answerβ¦", lines=1)
sub_btn = gr.Button("β
Submit Answer", variant="primary")
with gr.Row():
result_html = gr.HTML()
stats_html = gr.HTML()
tip_md = gr.Markdown()
get_btn.click(get_question, [dom_dd, diff_dd], [question_box, ans_box])
sub_btn.click(submit_answer, [conf_sl, ans_box], [result_html, stats_html, tip_md])
# ββ Tab 2 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("β ECHO vs AI"):
gr.HTML(_tab_header("β ECHO vs Overconfident AI",
"10-question head-to-head: calibrated ECHO vs AlwaysHigh baseline (90% on everything)", "#ff4466"))
with gr.Row():
scenario_dd = gr.Dropdown(
["Mixed","Math","Logic","Factual","Science","Medical","Coding","Creative"],
value="Mixed", label="Test Scenario")
run_btn = gr.Button("β Run 10 Questions", variant="primary")
with gr.Row():
with gr.Column(scale=3): cmp_html = gr.HTML()
with gr.Column(scale=2): mini_img = gr.Image(label="Live Reliability Diagram",
type="filepath", height=340)
run_btn.click(run_comparison, [scenario_dd], [cmp_html, mini_img])
# ββ Tab 3 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("𧬠Epistemic Fingerprint"):
gr.HTML(_tab_header("𧬠Epistemic Fingerprint",
"Radar chart of per-domain calibration β larger green area = better everywhere", "#a855f7"))
with gr.Row():
model_dd = gr.Dropdown(["ECHO Trained","Untrained","Heuristic"],
value="ECHO Trained", label="Model")
fp_btn = gr.Button("π¬ Generate Fingerprint", variant="primary")
with gr.Row():
with gr.Column(scale=3):
fp_img = gr.Image(label="Epistemic Fingerprint", type="filepath",
value=_img("fingerprint"), height=480)
with gr.Column(scale=2):
fp_bars = gr.HTML()
fp_insight = gr.HTML()
fp_btn.click(generate_fingerprint, [model_dd], [fp_img, fp_bars, fp_insight])
# ββ Tab 4 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("π Training Evidence"):
gr.HTML(_tab_header("π Training Evidence",
"6 plots generated from GRPO training β from overconfidence to precise calibration", "#ffd700"))
gr.HTML(_card(
"<div style='font-size:14px;font-weight:700;color:#00ffa3;margin-bottom:6px;'>β
Hero Plot β Reliability Diagram</div>"
"<div style='font-size:13px;color:#3a4a6a;line-height:1.6;'>"
"Untrained model (red): flat line far from diagonal β always overconfident. "
"ECHO trained (green): near-perfect calibration β hugs the diagonal."
"</div>",
"rgba(0,255,163,.15)"
))
gr.Image(value=_img("reliability"), label="Reliability Diagram", height=380)
with gr.Row():
with gr.Column():
gr.HTML("<div style='font-size:13px;font-weight:600;color:#4488ff;margin:10px 0 4px;'>π Training Curves</div>")
gr.Image(value=_img("training"), label="Training Curves", height=290)
with gr.Column():
gr.HTML("<div style='font-size:13px;font-weight:600;color:#a855f7;margin:10px 0 4px;'>𧬠Epistemic Fingerprint</div>")
gr.Image(value=_img("fingerprint"), label="Epistemic Fingerprint", height=290)
with gr.Row():
with gr.Column():
gr.HTML("<div style='font-size:13px;font-weight:600;color:#ffd700;margin:10px 0 4px;'>π‘οΈ Calibration Heatmap</div>")
gr.Image(value=_img("heatmap"), label="Calibration Heatmap", height=290)
with gr.Column():
gr.HTML("<div style='font-size:13px;font-weight:600;color:#ff8c00;margin:10px 0 4px;'>π Confidence Distribution</div>")
gr.Image(value=_img("distribution"), label="Confidence Distribution", height=290)
gr.HTML("<div style='font-size:13px;font-weight:600;color:#ff4466;margin:10px 0 4px;'>π’ Domain Comparison</div>")
gr.Image(value=_img("domain"), label="Domain Comparison", height=300)
regen_btn = gr.Button("π Regenerate All Plots", variant="secondary")
regen_out = gr.HTML()
def regen():
from training.evaluate import make_synthetic_pair, compare_and_plot
b, a = make_synthetic_pair()
compare_and_plot(a, {"Untrained": b})
return _card("<span style='color:#00ffa3;font-weight:600;'>β
All 6 plots regenerated</span>")
regen_btn.click(regen, outputs=[regen_out])
# ββ Tab 5 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("π Evaluation"):
gr.HTML(_tab_header("π Official OpenEnv Evaluation",
"3 tasks Γ 30 episodes = 90 episodes β validates ECHO meets all thresholds", "#ffd700"))
gr.HTML("""
<div style="display:grid;grid-template-columns:repeat(3,1fr);gap:10px;margin-bottom:8px;">
<div style="background:rgba(51,102,255,.06);border:1px solid rgba(51,102,255,.2);border-radius:8px;padding:13px 16px;">
<div style="color:#4488ff;font-weight:700;font-size:13px;font-family:Inter,sans-serif;">Task 1 β Easy</div>
<div style="color:#1a2a5a;font-size:12px;margin-top:4px;">ECE target: < 0.15</div>
</div>
<div style="background:rgba(255,215,0,.06);border:1px solid rgba(255,215,0,.2);border-radius:8px;padding:13px 16px;">
<div style="color:#ffd700;font-weight:700;font-size:13px;font-family:Inter,sans-serif;">Task 2 β Medium</div>
<div style="color:#2a2a00;font-size:12px;margin-top:4px;">ECE target: < 0.20</div>
</div>
<div style="background:rgba(168,85,247,.06);border:1px solid rgba(168,85,247,.2);border-radius:8px;padding:13px 16px;">
<div style="color:#a855f7;font-weight:700;font-size:13px;font-family:Inter,sans-serif;">Task 3 β Hard</div>
<div style="color:#1a0a3a;font-size:12px;margin-top:4px;">ECE target: < 0.25</div>
</div>
</div>""")
eval_btn = gr.Button("π Run Full Evaluation (90 episodes)", variant="primary")
result_html = gr.HTML()
with gr.Accordion("π Raw JSON", open=False):
json_out = gr.Code(language="json")
eval_btn.click(run_evaluation, outputs=[result_html, json_out])
# ββ Tab 6 ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
with gr.Tab("β‘ Live Training"):
gr.HTML(_tab_header("β‘ Live GRPO Training",
"Watch ECE drop in real-time β dashed lines show Task 1 & 2 pass thresholds", "#4488ff"))
with gr.Row():
lt_start = gr.Button("π Start Live Training Demo", variant="primary", scale=2)
lt_stop = gr.Button("βΉ Stop", variant="stop", scale=1)
lt_status = gr.Textbox(label="Training Log",
value="Ready β click Start to simulate GRPO training.",
lines=2, interactive=False)
lt_plot = gr.Image(label="ECE During Training", type="filepath", height=380)
lt_prog = gr.Slider(0, 100, value=0, label="Progress (%)", interactive=False)
lt_start.click(start_live_training, outputs=[lt_status, lt_plot, lt_prog])
lt_stop.click(stop_live_training, outputs=[lt_status])
return demo, theme
def main():
import gradio as gr
logging.basicConfig(level=logging.INFO)
demo, theme = build_app()
demo.launch(
server_name="0.0.0.0",
server_port=cfg.GRADIO_PORT,
share=False,
show_error=True,
css=_CSS,
js=_JS,
theme=theme,
)
if __name__ == "__main__":
main()
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