Update app.py
Browse files
app.py
CHANGED
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@@ -1,6 +1,7 @@
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import gradio as gr
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import time
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import torch
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModelForCausalLM, pipeline
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# ── Device ────────────────────────────────────────────────────────────────────
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@@ -48,9 +49,23 @@ Final Answer: <answer>
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Be deliberate. Show your full working. Each step should be one clear thought."""
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# ── Step Probe inference ──────────────────────────────────────────────────────
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def
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-
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current = steps_so_far[-1] if steps_so_far else ""
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input_text = (
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f"[PROBLEM] {problem.strip()} "
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f"[STEPS SO FAR] {context} "
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@@ -70,6 +85,7 @@ def probe_step(problem: str, steps_so_far: list) -> tuple:
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return label, conf
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# ── Core pipeline ─────────────────────────────────────────────────────────────
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def run_twt(problem: str):
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if not problem.strip():
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yield ("", "<div class='msg warn'>⚠️ Enter a problem to analyze.</div>", "<div class='msg empty'>Waiting...</div>")
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@@ -77,7 +93,6 @@ def run_twt(problem: str):
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cot_html = ""
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# Build prompt
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messages = [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": problem.strip()}
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@@ -95,15 +110,17 @@ def run_twt(problem: str):
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lines = full_response.strip().split("\n")
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parsed_steps = [l.strip() for l in lines if l.strip()]
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displayed_steps
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first_fail_seen
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for i, step in enumerate(parsed_steps):
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displayed_steps.append(step)
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is_final = step.lower().startswith("final answer")
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if not is_final:
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label, conf = probe_step(problem, displayed_steps)
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else:
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label, conf = "FINAL", 1.0
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@@ -124,18 +141,20 @@ def run_twt(problem: str):
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</div>"""
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cot_html += step_card
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yield (full_response, cot_html, build_trace(problem, displayed_steps, first_fail_seen))
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time.sleep(0.1)
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yield (full_response, cot_html, build_trace(problem, displayed_steps, first_fail_seen, done=True))
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def build_trace(problem, displayed, first_fail, done=False):
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faults, rows = 0, ""
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for i, s in enumerate(displayed):
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is_final = s.lower().startswith("final answer")
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if not is_final:
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lbl, conf = probe_step(problem, displayed[:i+1])
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if lbl == "FAIL": faults += 1
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dot = f"<span class='dot dot-{'ok' if lbl == 'OK' else 'fail'}'></span>"
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rows += f"<div class='trace-row'>{dot} Step {i+1} <span class='trace-conf'>— {int(conf*100)}%</span></div>"
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@@ -160,34 +179,32 @@ CSS = """
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*, *::before, *::after { box-sizing: border-box; }
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body, .gradio-container, .gradio-container * {
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font-family: 'Inter', -apple-system, sans-serif !important;
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color: #1e293b !important;
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}
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.gradio-container {
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background-color: #f4f6f8 !important;
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max-width: 1280px !important;
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padding-top: 1rem !important;
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}
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/* Header */
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.twt-header {
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text-align: center;
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padding: 0 1rem 1rem;
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margin-bottom: 1.5rem;
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border-bottom: 1px solid #cbd5e1;
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}
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.twt-title {
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font-size: 2rem;
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font-weight: 800;
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letter-spacing: -0.03em;
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font-family: 'JetBrains Mono', monospace !important;
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margin-bottom: 0.25rem;
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color: #0f172a !important;
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}
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.twt-title span {
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color: #0033a0 !important; /* Morgan Stanley signature blue */
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}
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.twt-sub {
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font-size: 0.85rem;
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color: #475569 !important;
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font-weight: 500;
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letter-spacing: 0.02em;
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@@ -195,12 +212,12 @@ body, .gradio-container, .gradio-container * {
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/* Labels */
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.input-label, .panel-label {
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font-size: 0.7rem;
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font-weight: 700;
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color: #334155 !important;
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text-transform: uppercase;
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letter-spacing: 0.08em;
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margin-bottom: 0.5rem;
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display: block;
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}
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.panel-label {
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@@ -212,11 +229,11 @@ body, .gradio-container, .gradio-container * {
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textarea {
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background: #ffffff !important;
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border: 1px solid #94a3b8 !important;
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border-radius: 6px !important;
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color: #0f172a !important;
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font-size: 0.85rem !important;
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line-height: 1.5 !important;
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padding: 0.75rem !important;
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box-shadow: inset 0 1px 2px rgba(15, 23, 42, 0.05) !important;
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transition: all 0.2s ease !important;
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}
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@@ -229,13 +246,13 @@ textarea::placeholder { color: #94a3b8 !important; }
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/* Primary Button */
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button.primary {
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background: #0033a0 !important;
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color: #ffffff !important;
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font-weight: 600 !important;
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border: none !important;
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border-radius: 6px !important;
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padding: 0.6rem 1.25rem !important;
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font-size: 0.85rem !important;
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box-shadow: 0 2px 4px -1px rgba(0, 51, 160, 0.2) !important;
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transition: all 0.15s ease-in-out !important;
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cursor: pointer !important;
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@@ -255,14 +272,14 @@ button.primary:active {
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.step-card {
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display: flex;
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align-items: flex-start;
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gap: 0.75rem;
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padding: 0.75rem 1rem;
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margin-bottom: 0.5rem;
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background: #ffffff;
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border: 1px solid #cbd5e1;
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border-radius: 6px;
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line-height: 1.5;
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animation: fadeUp 0.2s ease-out both;
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box-shadow: 0 1px 2px rgba(15, 23, 42, 0.03);
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transition: all 0.15s ease;
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}
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border-color: #fca5a5;
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background: #fff1f2;
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}
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.step-card.step-fault:hover {
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border-color: #f87171;
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}
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@keyframes fadeUp {
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from { opacity: 0; transform: translateY(6px); }
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to { opacity: 1; transform: translateY(0); }
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}
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.step-icon { font-size: 1rem; margin-top: 1px; }
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.step-text { flex: 1; color: #1e293b !important; font-size: 0.85rem; }
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/* Status Badges */
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.badge {
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flex-shrink: 0;
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font-size: 0.6rem;
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font-weight: 700;
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font-family: 'JetBrains Mono', monospace !important;
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letter-spacing: 0.02em;
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padding: 0.15rem 0.4rem;
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border-radius: 4px;
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margin-top: 2px;
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text-transform: uppercase;
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.trace-row {
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display: flex;
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align-items: center;
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gap: 0.5rem;
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font-size: 0.75rem;
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color: #334155 !important;
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font-family: 'JetBrains Mono', monospace !important;
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padding: 0.35rem 0;
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border-bottom: 1px solid #e2e8f0;
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}
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.trace-conf { color: #64748b !important; }
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.dot { width: 6px; height: 6px; border-radius: 50%; flex-shrink: 0; }
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.dot-ok { background: #10b981; box-shadow: 0 0 0 2px #d1fae5; }
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.dot-fail { background: #e11d48; box-shadow: 0 0 0 2px #ffe4e6; }
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.dot-final { background: #0033a0; box-shadow: 0 0 0 2px #dbeafe; }
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/* Progress Bar */
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.trace-summary {
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margin-top: 1rem;
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padding-top: 0.75rem;
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border-top: 1px solid #cbd5e1;
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}
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.trace-label {
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font-size: 0.65rem;
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font-weight: 700;
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color: #475569 !important;
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text-transform: uppercase;
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letter-spacing: 0.05em;
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margin-bottom: 0.4rem;
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}
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.trace-bar-bg {
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background: #cbd5e1;
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border-radius: 999px;
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height: 4px;
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overflow: hidden;
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}
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.trace-bar {
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@@ -358,7 +373,7 @@ button.primary:active {
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color: #64748b !important;
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font-size: 0.8rem;
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font-family: 'JetBrains Mono', monospace !important;
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padding: 1.5rem 1rem;
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text-align: center;
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background: #ffffff;
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border: 1px dashed #94a3b8;
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"""
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EXAMPLES = [
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"
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"A
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"
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"
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]
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with gr.Blocks(css=CSS, title="ThinkWhileThinking") as demo:
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run_btn.click(fn=run_twt, inputs=[problem_input], outputs=[raw_output, cot_output, trace_output])
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problem_input.submit(fn=run_twt, inputs=[problem_input], outputs=[raw_output, cot_output, trace_output])
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demo.launch()
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import gradio as gr
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import time
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import torch
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import spaces
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModelForCausalLM, pipeline
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# ── Device ────────────────────────────────────────────────────────────────────
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Be deliberate. Show your full working. Each step should be one clear thought."""
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# ── Step Probe inference ──────────────────────────────────────────────────────
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def is_notation_step(step: str) -> bool:
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"""Detect pure LaTeX/notation steps — restatements, not new reasoning."""
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s = step.strip()
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return (
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s.startswith("\\[") or s.startswith("$$") or
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s.startswith("\\(") or
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(s.startswith("\\") and len(s.split()) < 8)
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)
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def probe_step(problem: str, steps_so_far: list, prev_result: tuple = None) -> tuple:
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current = steps_so_far[-1] if steps_so_far else ""
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# Notation-only steps inherit previous score — they restate, not reason
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if is_notation_step(current):
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return prev_result if prev_result is not None else ("OK", 0.9)
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context = " ".join(steps_so_far[:-1]) if len(steps_so_far) > 1 else ""
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input_text = (
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f"[PROBLEM] {problem.strip()} "
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f"[STEPS SO FAR] {context} "
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return label, conf
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# ── Core pipeline ─────────────────────────────────────────────────────────────
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@spaces.GPU
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def run_twt(problem: str):
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if not problem.strip():
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yield ("", "<div class='msg warn'>⚠️ Enter a problem to analyze.</div>", "<div class='msg empty'>Waiting...</div>")
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cot_html = ""
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messages = [
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{"role": "system", "content": SYSTEM_PROMPT},
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{"role": "user", "content": problem.strip()}
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lines = full_response.strip().split("\n")
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parsed_steps = [l.strip() for l in lines if l.strip()]
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displayed_steps = []
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first_fail_seen = False
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prev_probe_result = None
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for i, step in enumerate(parsed_steps):
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displayed_steps.append(step)
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is_final = step.lower().startswith("final answer")
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if not is_final:
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label, conf = probe_step(problem, displayed_steps, prev_probe_result)
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prev_probe_result = (label, conf)
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else:
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label, conf = "FINAL", 1.0
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</div>"""
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cot_html += step_card
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yield (full_response, cot_html, build_trace(problem, displayed_steps, first_fail_seen, prev_probe_result))
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time.sleep(0.1)
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yield (full_response, cot_html, build_trace(problem, displayed_steps, first_fail_seen, prev_probe_result, done=True))
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def build_trace(problem, displayed, first_fail, prev_result=None, done=False):
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faults, rows = 0, ""
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last_result = None
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for i, s in enumerate(displayed):
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is_final = s.lower().startswith("final answer")
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if not is_final:
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lbl, conf = probe_step(problem, displayed[:i+1], last_result)
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last_result = (lbl, conf)
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if lbl == "FAIL": faults += 1
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dot = f"<span class='dot dot-{'ok' if lbl == 'OK' else 'fail'}'></span>"
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rows += f"<div class='trace-row'>{dot} Step {i+1} <span class='trace-conf'>— {int(conf*100)}%</span></div>"
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*, *::before, *::after { box-sizing: border-box; }
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body, .gradio-container, .gradio-container * {
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font-family: 'Inter', -apple-system, sans-serif !important;
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color: #1e293b !important;
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}
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.gradio-container {
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background-color: #f4f6f8 !important;
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max-width: 1280px !important;
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padding-top: 1rem !important;
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}
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/* Header */
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.twt-header {
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text-align: center;
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padding: 0 1rem 1rem;
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margin-bottom: 1.5rem;
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border-bottom: 1px solid #cbd5e1;
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}
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.twt-title {
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font-size: 2rem;
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font-weight: 800;
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letter-spacing: -0.03em;
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font-family: 'JetBrains Mono', monospace !important;
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margin-bottom: 0.25rem;
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color: #0f172a !important;
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}
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.twt-title span { color: #0033a0 !important; }
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.twt-sub {
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font-size: 0.85rem;
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color: #475569 !important;
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font-weight: 500;
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letter-spacing: 0.02em;
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/* Labels */
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.input-label, .panel-label {
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font-size: 0.7rem;
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font-weight: 700;
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color: #334155 !important;
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text-transform: uppercase;
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letter-spacing: 0.08em;
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margin-bottom: 0.5rem;
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display: block;
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}
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.panel-label {
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textarea {
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background: #ffffff !important;
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border: 1px solid #94a3b8 !important;
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border-radius: 6px !important;
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color: #0f172a !important;
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font-size: 0.85rem !important;
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line-height: 1.5 !important;
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padding: 0.75rem !important;
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box-shadow: inset 0 1px 2px rgba(15, 23, 42, 0.05) !important;
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transition: all 0.2s ease !important;
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}
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/* Primary Button */
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button.primary {
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background: #0033a0 !important;
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color: #ffffff !important;
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font-weight: 600 !important;
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border: none !important;
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border-radius: 6px !important;
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padding: 0.6rem 1.25rem !important;
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font-size: 0.85rem !important;
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box-shadow: 0 2px 4px -1px rgba(0, 51, 160, 0.2) !important;
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transition: all 0.15s ease-in-out !important;
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cursor: pointer !important;
|
|
|
|
| 272 |
.step-card {
|
| 273 |
display: flex;
|
| 274 |
align-items: flex-start;
|
| 275 |
+
gap: 0.75rem;
|
| 276 |
+
padding: 0.75rem 1rem;
|
| 277 |
+
margin-bottom: 0.5rem;
|
| 278 |
background: #ffffff;
|
| 279 |
border: 1px solid #cbd5e1;
|
| 280 |
+
border-radius: 6px;
|
| 281 |
line-height: 1.5;
|
| 282 |
+
animation: fadeUp 0.2s ease-out both;
|
| 283 |
box-shadow: 0 1px 2px rgba(15, 23, 42, 0.03);
|
| 284 |
transition: all 0.15s ease;
|
| 285 |
}
|
|
|
|
| 291 |
border-color: #fca5a5;
|
| 292 |
background: #fff1f2;
|
| 293 |
}
|
| 294 |
+
.step-card.step-fault:hover { border-color: #f87171; }
|
|
|
|
|
|
|
| 295 |
@keyframes fadeUp {
|
| 296 |
from { opacity: 0; transform: translateY(6px); }
|
| 297 |
to { opacity: 1; transform: translateY(0); }
|
| 298 |
}
|
| 299 |
+
.step-icon { font-size: 1rem; margin-top: 1px; }
|
| 300 |
.step-text { flex: 1; color: #1e293b !important; font-size: 0.85rem; }
|
| 301 |
|
| 302 |
/* Status Badges */
|
| 303 |
.badge {
|
| 304 |
flex-shrink: 0;
|
| 305 |
+
font-size: 0.6rem;
|
| 306 |
font-weight: 700;
|
| 307 |
font-family: 'JetBrains Mono', monospace !important;
|
| 308 |
letter-spacing: 0.02em;
|
| 309 |
+
padding: 0.15rem 0.4rem;
|
| 310 |
border-radius: 4px;
|
| 311 |
margin-top: 2px;
|
| 312 |
text-transform: uppercase;
|
|
|
|
| 319 |
.trace-row {
|
| 320 |
display: flex;
|
| 321 |
align-items: center;
|
| 322 |
+
gap: 0.5rem;
|
| 323 |
+
font-size: 0.75rem;
|
| 324 |
color: #334155 !important;
|
| 325 |
font-family: 'JetBrains Mono', monospace !important;
|
| 326 |
+
padding: 0.35rem 0;
|
| 327 |
border-bottom: 1px solid #e2e8f0;
|
| 328 |
}
|
| 329 |
.trace-conf { color: #64748b !important; }
|
| 330 |
+
.dot { width: 6px; height: 6px; border-radius: 50%; flex-shrink: 0; }
|
| 331 |
.dot-ok { background: #10b981; box-shadow: 0 0 0 2px #d1fae5; }
|
| 332 |
.dot-fail { background: #e11d48; box-shadow: 0 0 0 2px #ffe4e6; }
|
| 333 |
.dot-final { background: #0033a0; box-shadow: 0 0 0 2px #dbeafe; }
|
| 334 |
|
| 335 |
/* Progress Bar */
|
| 336 |
.trace-summary {
|
| 337 |
+
margin-top: 1rem;
|
| 338 |
padding-top: 0.75rem;
|
| 339 |
border-top: 1px solid #cbd5e1;
|
| 340 |
}
|
| 341 |
.trace-label {
|
| 342 |
+
font-size: 0.65rem;
|
| 343 |
font-weight: 700;
|
| 344 |
color: #475569 !important;
|
| 345 |
text-transform: uppercase;
|
| 346 |
letter-spacing: 0.05em;
|
| 347 |
+
margin-bottom: 0.4rem;
|
| 348 |
}
|
| 349 |
.trace-bar-bg {
|
| 350 |
background: #cbd5e1;
|
| 351 |
border-radius: 999px;
|
| 352 |
+
height: 4px;
|
| 353 |
overflow: hidden;
|
| 354 |
}
|
| 355 |
.trace-bar {
|
|
|
|
| 373 |
color: #64748b !important;
|
| 374 |
font-size: 0.8rem;
|
| 375 |
font-family: 'JetBrains Mono', monospace !important;
|
| 376 |
+
padding: 1.5rem 1rem;
|
| 377 |
text-align: center;
|
| 378 |
background: #ffffff;
|
| 379 |
border: 1px dashed #94a3b8;
|
|
|
|
| 390 |
"""
|
| 391 |
|
| 392 |
EXAMPLES = [
|
| 393 |
+
"Janet has 3 times as many apples as John. John has 8 apples. How many apples does Janet have?",
|
| 394 |
+
"A store had 50 chocolates. They sold 18 in the morning and 14 in the afternoon. How many chocolates are left?",
|
| 395 |
+
"Tom reads 12 pages every day. How many pages will he read in 3 weeks?",
|
| 396 |
+
"A train travels 60 miles per hour. How far will it travel in 2 hours and 30 minutes?",
|
| 397 |
+
"Lucy earns $15 per hour. She worked 6 hours on Monday and 4 hours on Tuesday. How much did she earn in total?",
|
| 398 |
]
|
| 399 |
|
| 400 |
with gr.Blocks(css=CSS, title="ThinkWhileThinking") as demo:
|
|
|
|
| 417 |
run_btn.click(fn=run_twt, inputs=[problem_input], outputs=[raw_output, cot_output, trace_output])
|
| 418 |
problem_input.submit(fn=run_twt, inputs=[problem_input], outputs=[raw_output, cot_output, trace_output])
|
| 419 |
|
| 420 |
+
demo.launch()
|