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arnavmishra4
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NeuroBio_Agent

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File size: 68,533 Bytes

# ── Patch 3: fix Gradio 4.44.0 + Starlette API mismatch ──
import starlette.templating as _st

_orig_TemplateResponse = _st.Jinja2Templates.TemplateResponse

def _safe_TemplateResponse(self, *args, **kwargs):
    # If the arguments are shifted, re-align them:
    if len(args) >= 2 and isinstance(args[0], str) and isinstance(args[1], dict):
        name_str = args[0]
        context_dict = args[1]
        request_obj = context_dict.get("request")
        args = (request_obj, name_str, context_dict) + args[2:]
    return _orig_TemplateResponse(self, *args, **kwargs)

_st.Jinja2Templates.TemplateResponse = _safe_TemplateResponse


# ── Patch 1: restore HfFolder for gradio 4.44.0 ──
import unittest.mock as _mock
import sys as _sys

_hf_hub = __import__("huggingface_hub")
if not hasattr(_hf_hub, "HfFolder"):
    class _FakeHfFolder:
        @staticmethod
        def get_token(): return None
        @staticmethod  
        def save_token(token): pass
        @staticmethod
        def delete_token(): pass
    _hf_hub.HfFolder = _FakeHfFolder
    _sys.modules["huggingface_hub"].HfFolder = _FakeHfFolder


# ── Patch 2: fix gradio_client schema bug ──
import gradio_client.utils as _gcu

_orig = _gcu._json_schema_to_python_type
def _safe(schema, defs=None):
    if not isinstance(schema, dict):
        return "Any"
    return _orig(schema, defs)
_gcu._json_schema_to_python_type = _safe


# ── Imports ──
import json
import time
import threading
import datetime
import gradio as gr
from langchain_core.messages import HumanMessage, AIMessage, ToolMessage

# ─────────────────────────────────────────────────────────────────────
# CSS — 600+ lines of premium dark-theme styling
# ─────────────────────────────────────────────────────────────────────
# ─────────────────────────────────────────────────────────────────────
# CSS — 600+ lines of premium dark-theme styling (Safari Compatible)
# ─────────────────────────────────────────────────────────────────────
CUSTOM_CSS = """
/* ── Google Fonts ── */
@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500&family=Sora:wght@300;400;600;700&display=swap');

/* ── Global Reset ── */
*, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }

:root {
  --bg-void:        #04050a;
  --bg-deep:        #080c14;
  --bg-surface:     #0d1220;
  --bg-raised:      #111827;
  --bg-glass:       rgba(13,18,32,0.72);
  --bg-card:        rgba(17,24,39,0.85);

  --border-subtle:  rgba(99,120,190,0.12);
  --border-glow:    rgba(99,179,237,0.28);
  --border-active:  rgba(99,179,237,0.6);

  --blue-400:       #60a5fa;
  --blue-500:       #3b82f6;
  --blue-600:       #2563eb;
  --blue-glow:      rgba(59,130,246,0.35);

  --cyan-400:       #22d3ee;
  --cyan-glow:      rgba(34,211,238,0.25);

  --green-400:      #4ade80;
  --green-500:      #22c55e;
  --green-glow:     rgba(74,222,128,0.25);

  --orange-400:     #fb923c;
  --orange-glow:    rgba(251,146,60,0.25);

  --red-400:        #f87171;
  --red-glow:       rgba(248,113,113,0.25);

  --purple-400:     #c084fc;
  --purple-glow:    rgba(192,132,252,0.2);

  --text-primary:   #f0f4ff;
  --text-secondary: #94a3b8;
  --text-muted:     #4b5563;
  --text-accent:    #93c5fd;

  --font-display:   'Sora', sans-serif;
  --font-body:      'Inter', sans-serif;
  --font-mono:      'JetBrains Mono', monospace;

  --radius-sm:      6px;
  --radius-md:      10px;
  --radius-lg:      16px;
  --radius-xl:      22px;

  --shadow-card:    0 4px 24px rgba(0,0,0,0.45), 0 1px 4px rgba(0,0,0,0.3);
  --shadow-glow-blue: 0 0 20px rgba(59,130,246,0.3), 0 0 60px rgba(59,130,246,0.1);
  --shadow-glow-green: 0 0 20px rgba(74,222,128,0.25), 0 0 50px rgba(74,222,128,0.08);
  --shadow-glow-orange: 0 0 20px rgba(251,146,60,0.25);

  --transition-fast:   0.15s ease;
  --transition-smooth: 0.3s cubic-bezier(0.4,0,0.2,1);
  --transition-spring: 0.5s cubic-bezier(0.34,1.56,0.64,1);
}

/* ── App Shell ── */
.gradio-container {
  background: var(--bg-void) !important;
  font-family: var(--font-body) !important;
  min-height: 100vh !important;
  max-width: 100% !important;
  padding: 0 !important;
}

/* hide gradio chrome */
footer { display: none !important; }
.gr-form { background: transparent !important; border: none !important; }
.gr-box { background: transparent !important; border: none !important; }

/* ── Ambient Background ── */
#nb-root {
  background:
    radial-gradient(ellipse 80% 50% at 20% 10%, rgba(37,99,235,0.08) 0%, transparent 60%),
    radial-gradient(ellipse 60% 40% at 80% 80%, rgba(124,58,237,0.06) 0%, transparent 55%),
    radial-gradient(ellipse 40% 30% at 60% 30%, rgba(6,182,212,0.04) 0%, transparent 50%),
    var(--bg-void);
  padding: 0;
  -webkit-font-smoothing: antialiased; /* Safari font smoothing */
}

/* ─────────────────── HEADER ─────────────────── */
#nb-header {
  padding: 40px 48px 32px;
  border-bottom: 1px solid var(--border-subtle);
  display: flex;
  align-items: center;
  justify-content: space-between;
  gap: 32px;
  position: relative;
  overflow: hidden;
}

#nb-header::before {
  content: '';
  position: absolute;
  inset: 0;
  background: linear-gradient(135deg, rgba(37,99,235,0.06) 0%, transparent 60%);
  pointer-events: none;
}

.nb-logo-group { display: flex; flex-direction: column; gap: 6px; }

.nb-wordmark {
  font-family: var(--font-display) !important;
  font-size: 26px !important;
  font-weight: 700 !important;
  letter-spacing: -0.03em !important;
  color: var(--text-primary) !important;
  background: linear-gradient(135deg, #f0f4ff 0%, #93c5fd 50%, #60a5fa 100%);
  -webkit-background-clip: text !important;
  -webkit-text-fill-color: transparent !important;
  background-clip: text !important;
  display: inline-block; /* Essential for Safari background-clip */
  line-height: 1.2 !important;
  margin: 0 !important;
  padding: 0 !important;
}

.nb-tagline {
  font-family: var(--font-mono) !important;
  font-size: 11px !important;
  font-weight: 400 !important;
  color: var(--blue-400) !important;
  letter-spacing: 0.12em !important;
  text-transform: uppercase !important;
  opacity: 0.8;
  margin: 0 !important;
  padding: 0 !important;
}

.nb-header-right {
  display: flex;
  align-items: center;
  gap: 24px;
}

.nb-status-chip {
  display: flex;
  align-items: center;
  gap: 8px;
  padding: 6px 14px;
  border-radius: 99px;
  border: 1px solid var(--border-subtle);
  background: var(--bg-card);
  font-family: var(--font-mono);
  font-size: 11px;
  color: var(--text-secondary);
  letter-spacing: 0.06em;
}

.nb-status-dot {
  width: 7px;
  height: 7px;
  border-radius: 50%;
  background: var(--green-400);
  box-shadow: 0 0 6px var(--green-glow);
  animation: nb-pulse-dot 2s ease-in-out infinite;
}

@keyframes nb-pulse-dot {
  0%, 100% { opacity: 1; transform: scale(1); }
  50% { opacity: 0.6; transform: scale(0.85); }
}

/* ─────────────────── UPLOAD ROW ─────────────────── */
#nb-upload-row {
  padding: 24px 48px;
  display: flex;
  align-items: center;
  gap: 20px;
  border-bottom: 1px solid var(--border-subtle);
  background: rgba(13,18,32,0.4);
}

#nb-upload-row .gr-file-upload,
#nb-upload-row input[type="file"] {
  display: none !important;
}

/* Upload button (gr.File renders as a button) */
#nb-upload-btn button {
  -webkit-appearance: none !important; /* Safari Reset */
  appearance: none !important;
  background: var(--bg-card) !important;
  border: 1px dashed rgba(99,120,190,0.3) !important;
  color: var(--text-secondary) !important;
  font-family: var(--font-body) !important;
  font-size: 13px !important;
  border-radius: var(--radius-md) !important;
  padding: 10px 20px !important;
  cursor: pointer !important;
  transition: all var(--transition-smooth) !important;
  width: 100% !important;
}

#nb-upload-btn button:hover {
  border-color: var(--border-glow) !important;
  color: var(--text-primary) !important;
  background: rgba(59,130,246,0.08) !important;
}

/* Begin Investigation button */
#nb-begin-btn button {
  -webkit-appearance: none !important; /* Safari Reset */
  appearance: none !important;
  background: linear-gradient(135deg, #1d4ed8 0%, #2563eb 50%, #3b82f6 100%) !important;
  border: 1px solid rgba(99,179,237,0.4) !important;
  color: #fff !important;
  font-family: var(--font-display) !important;
  font-size: 14px !important;
  font-weight: 600 !important;
  border-radius: var(--radius-md) !important;
  padding: 11px 28px !important;
  cursor: pointer !important;
  transition: all var(--transition-smooth) !important;
  box-shadow: 0 4px 20px rgba(37,99,235,0.35), 0 0 0 0 rgba(59,130,246,0) !important;
  letter-spacing: 0.01em !important;
}

#nb-begin-btn button:hover {
  transform: translateY(-1px) !important;
  box-shadow: 0 6px 28px rgba(37,99,235,0.5), 0 0 40px rgba(59,130,246,0.2) !important;
  background: linear-gradient(135deg, #1e40af 0%, #2563eb 50%, #60a5fa 100%) !important;
}

#nb-begin-btn button:active {
  transform: translateY(0) !important;
}

.nb-patient-badge {
  display: flex;
  align-items: center;
  gap: 10px;
  padding: 8px 16px;
  border-radius: var(--radius-md);
  border: 1px solid var(--border-subtle);
  background: var(--bg-card);
  font-family: var(--font-mono);
  font-size: 12px;
  color: var(--text-secondary);
}

.nb-patient-badge .nb-badge-dot {
  width: 6px; height: 6px;
  border-radius: 50%;
  background: var(--cyan-400);
  box-shadow: 0 0 8px var(--cyan-glow);
}

/* ─────────────────── MAIN LAYOUT ─────────────────── */
#nb-main {
  display: grid;
  grid-template-columns: 220px 1fr 340px;
  gap: 0;
  height: calc(100vh - 180px);
  overflow: hidden;
}

#nb-main > * {
  border-right: 1px solid var(--border-subtle);
  overflow-y: auto;
  overflow-x: hidden;
  min-width: 0; /* Crucial Safari fix for CSS grid blowout */
  min-height: 0; /* Crucial Safari fix */
}

#nb-main > *:last-child { border-right: none; }

/* ── Scrollbar ── */
::-webkit-scrollbar { width: 4px; }
::-webkit-scrollbar-track { background: transparent; }
::-webkit-scrollbar-thumb { background: rgba(99,120,190,0.25); border-radius: 99px; }
::-webkit-scrollbar-thumb:hover { background: rgba(99,120,190,0.45); }

/* ─────────────────── LEFT PANEL — TIMELINE ─────────────────── */
#nb-left {
  padding: 24px 0;
  background: rgba(8,12,20,0.6);
}

.nb-panel-title {
  font-family: var(--font-mono) !important;
  font-size: 10px !important;
  font-weight: 500 !important;
  color: var(--text-muted) !important;
  letter-spacing: 0.16em !important;
  text-transform: uppercase !important;
  padding: 0 20px 16px !important;
  margin: 0 !important;
  border-bottom: 1px solid var(--border-subtle) !important;
  margin-bottom: 8px !important;
}

/* Loop counter */
.nb-loop-counter {
  margin: 12px 16px;
  padding: 12px 14px;
  border-radius: var(--radius-md);
  background: rgba(37,99,235,0.08);
  border: 1px solid rgba(59,130,246,0.15);
}

.nb-loop-label {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  letter-spacing: 0.1em;
  text-transform: uppercase;
  margin-bottom: 4px;
}

.nb-loop-value {
  font-family: var(--font-display);
  font-size: 18px;
  font-weight: 700;
  color: var(--blue-400);
  line-height: 1;
}

.nb-loop-sub {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-secondary);
  margin-top: 4px;
}

/* ── Timeline nodes ── */
.nb-timeline {
  padding: 16px 0;
  position: relative;
}

.nb-timeline-node {
  display: flex;
  align-items: center;
  gap: 12px;
  padding: 10px 20px;
  cursor: default;
  position: relative;
  transition: background var(--transition-fast);
}

.nb-timeline-node:hover { background: rgba(59,130,246,0.04); }

.nb-node-line {
  position: absolute;
  left: 30px;
  top: 50%;
  width: 2px;
  height: calc(100% + 0px);
  background: var(--border-subtle);
  transform: translateX(-50%);
  z-index: 0;
}

.nb-node-dot {
  width: 22px;
  height: 22px;
  border-radius: 50%;
  border: 2px solid currentColor;
  background: var(--bg-deep);
  display: flex;
  align-items: center;
  justify-content: center;
  flex-shrink: 0;
  position: relative;
  z-index: 1;
  transition: all var(--transition-smooth);
  font-size: 9px;
}

.nb-node-label {
  font-family: var(--font-mono);
  font-size: 10px;
  letter-spacing: 0.06em;
  text-transform: uppercase;
  color: var(--text-muted);
  transition: color var(--transition-smooth);
  font-weight: 500;
}

/* Node states */
.nb-timeline-node[data-state="future"] .nb-node-dot {
  color: var(--text-muted);
  border-color: var(--text-muted);
  opacity: 0.4;
}

.nb-timeline-node[data-state="active"] .nb-node-dot {
  color: var(--blue-400);
  border-color: var(--blue-400);
  background: rgba(59,130,246,0.12);
  box-shadow: 0 0 14px var(--blue-glow), 0 0 0 4px rgba(59,130,246,0.12);
  animation: nb-glow-pulse 1.5s ease-in-out infinite;
}

.nb-timeline-node[data-state="active"] .nb-node-label { color: var(--blue-400); }

.nb-timeline-node[data-state="complete"] .nb-node-dot {
  color: var(--green-400);
  border-color: var(--green-400);
  background: rgba(74,222,128,0.1);
  box-shadow: 0 0 10px var(--green-glow);
}

.nb-timeline-node[data-state="complete"] .nb-node-label { color: var(--green-400); }

.nb-timeline-node[data-state="contradiction"] .nb-node-dot {
  color: var(--orange-400);
  border-color: var(--orange-400);
  background: rgba(251,146,60,0.1);
  box-shadow: 0 0 10px var(--orange-glow);
}

.nb-timeline-node[data-state="contradiction"] .nb-node-label { color: var(--orange-400); }

.nb-timeline-node[data-state="error"] .nb-node-dot {
  color: var(--red-400);
  border-color: var(--red-400);
  background: rgba(248,113,113,0.1);
}

@keyframes nb-glow-pulse {
  0%, 100% { box-shadow: 0 0 14px var(--blue-glow), 0 0 0 4px rgba(59,130,246,0.12); }
  50% { box-shadow: 0 0 22px rgba(59,130,246,0.6), 0 0 0 8px rgba(59,130,246,0.06); }
}

/* ── Event feed ── */
.nb-event-feed {
  margin: 16px 0 0;
  padding-top: 16px;
  border-top: 1px solid var(--border-subtle);
}

.nb-event-feed-title {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  letter-spacing: 0.14em;
  text-transform: uppercase;
  padding: 0 20px 12px;
}

.nb-event-item {
  display: flex;
  align-items: flex-start;
  gap: 10px;
  padding: 7px 20px;
  animation: nb-slide-in 0.4s cubic-bezier(0.4,0,0.2,1);
}

.nb-event-time {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  flex-shrink: 0;
  margin-top: 1px;
}

.nb-event-text {
  font-family: var(--font-body);
  font-size: 11px;
  color: var(--text-secondary);
  line-height: 1.4;
}

@keyframes nb-slide-in {
  from { opacity: 0; transform: translateX(-10px); }
  to   { opacity: 1; transform: translateX(0); }
}

/* ─────────────────── CENTER PANEL ─────────────────── */
#nb-center {
  padding: 24px 32px;
  display: flex;
  flex-direction: column;
  gap: 0;
  background: transparent;
}

/* Reasoning messages */
.nb-msg-block {
  display: flex;
  gap: 14px;
  padding: 20px 0;
  border-bottom: 1px solid var(--border-subtle);
  animation: nb-fade-up 0.5s cubic-bezier(0.4,0,0.2,1);
}

.nb-msg-block:last-child { border-bottom: none; }

@keyframes nb-fade-up {
  from { opacity: 0; transform: translateY(16px); }
  to   { opacity: 1; transform: translateY(0); }
}

.nb-msg-avatar {
  width: 36px;
  height: 36px;
  border-radius: var(--radius-md);
  display: flex;
  align-items: center;
  justify-content: center;
  font-size: 16px;
  flex-shrink: 0;
  margin-top: 2px;
}

.nb-msg-avatar.observe   { background: rgba(99,179,237,0.12); border: 1px solid rgba(99,179,237,0.25); }
.nb-msg-avatar.hypothesis{ background: rgba(168,85,247,0.12); border: 1px solid rgba(168,85,247,0.25); }
.nb-msg-avatar.search    { background: rgba(34,211,238,0.1);  border: 1px solid rgba(34,211,238,0.2);  }
.nb-msg-avatar.interpret { background: rgba(74,222,128,0.1);  border: 1px solid rgba(74,222,128,0.2);  }
.nb-msg-avatar.revise    { background: rgba(251,146,60,0.1);  border: 1px solid rgba(251,146,60,0.2);  }
.nb-msg-avatar.converge  { background: rgba(59,130,246,0.12); border: 1px solid rgba(59,130,246,0.3);  }
.nb-msg-avatar.final     { background: rgba(74,222,128,0.12); border: 1px solid rgba(74,222,128,0.3);  }

.nb-msg-content { flex: 1; min-width: 0; }

.nb-msg-header {
  display: flex;
  align-items: center;
  gap: 10px;
  margin-bottom: 10px;
}

.nb-msg-role {
  font-family: var(--font-mono);
  font-size: 11px;
  font-weight: 500;
  letter-spacing: 0.08em;
  text-transform: uppercase;
}

.nb-msg-role.observe    { color: var(--cyan-400); }
.nb-msg-role.hypothesis { color: var(--purple-400); }
.nb-msg-role.search     { color: var(--cyan-400); }
.nb-msg-role.interpret  { color: var(--green-400); }
.nb-msg-role.revise     { color: var(--orange-400); }
.nb-msg-role.converge   { color: var(--blue-400); }
.nb-msg-role.final      { color: var(--green-400); }

.nb-msg-timestamp {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  margin-left: auto;
}

.nb-msg-body {
  font-family: var(--font-body);
  font-size: 14px;
  line-height: 1.7;
  color: var(--text-secondary);
}

/* Data grids inside messages */
.nb-data-grid {
  display: grid;
  grid-template-columns: repeat(auto-fit, minmax(140px, 1fr));
  gap: 10px;
  margin: 14px 0;
}

.nb-data-cell {
  padding: 12px 14px;
  border-radius: var(--radius-md);
  background: rgba(13,18,32,0.8);
  border: 1px solid var(--border-subtle);
}

.nb-data-cell-label {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  letter-spacing: 0.08em;
  text-transform: uppercase;
  margin-bottom: 5px;
}

.nb-data-cell-value {
  font-family: var(--font-mono);
  font-size: 15px;
  font-weight: 600;
  color: var(--text-primary);
}

.nb-data-cell-value.positive { color: var(--orange-400); }
.nb-data-cell-value.neutral  { color: var(--cyan-400); }

/* Confidence bar */
.nb-confidence-row {
  display: flex;
  align-items: center;
  gap: 12px;
  margin: 12px 0;
}

.nb-confidence-label {
  font-family: var(--font-mono);
  font-size: 11px;
  color: var(--text-muted);
  min-width: 80px;
  text-transform: uppercase;
  letter-spacing: 0.07em;
}

.nb-confidence-bar {
  flex: 1;
  height: 5px;
  background: rgba(255,255,255,0.06);
  border-radius: 99px;
  overflow: hidden;
  position: relative;
}

.nb-confidence-fill {
  height: 100%;
  border-radius: 99px;
  background: linear-gradient(90deg, var(--blue-500), var(--cyan-400));
  box-shadow: 0 0 8px var(--cyan-glow);
  transition: width 0.8s cubic-bezier(0.4,0,0.2,1);
}

.nb-confidence-pct {
  font-family: var(--font-mono);
  font-size: 13px;
  font-weight: 600;
  color: var(--blue-400);
  min-width: 38px;
  text-align: right;
}

/* Searching animation */
.nb-searching-tags {
  display: flex;
  flex-wrap: wrap;
  gap: 8px;
  margin: 12px 0;
}

.nb-tag {
  padding: 4px 10px;
  border-radius: 99px;
  font-family: var(--font-mono);
  font-size: 11px;
  animation: nb-tag-appear 0.4s ease both;
}

.nb-tag.query {
  background: rgba(34,211,238,0.08);
  border: 1px solid rgba(34,211,238,0.25);
  color: var(--cyan-400);
}

.nb-tag.year {
  background: rgba(99,120,190,0.08);
  border: 1px solid rgba(99,120,190,0.2);
  color: var(--text-secondary);
}

@keyframes nb-tag-appear {
  from { opacity: 0; transform: scale(0.85); }
  to   { opacity: 1; transform: scale(1); }
}

/* Streaming cursor */
.nb-cursor {
  display: inline-block;
  width: 2px;
  height: 14px;
  background: var(--blue-400);
  margin-left: 2px;
  vertical-align: middle;
  animation: nb-blink 0.85s step-end infinite;
}

@keyframes nb-blink {
  0%, 100% { opacity: 1; }
  50%       { opacity: 0; }
}

/* ── Final Result card ── */
.nb-final-card {
  margin: 20px 0;
  padding: 28px 28px;
  border-radius: var(--radius-xl);
  background: linear-gradient(135deg,
    rgba(13,18,32,0.95) 0%,
    rgba(17,24,39,0.9) 100%);
  border: 1px solid rgba(74,222,128,0.3);
  box-shadow: var(--shadow-card), 0 0 40px rgba(74,222,128,0.08);
}

.nb-final-title {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--green-400);
  letter-spacing: 0.18em;
  text-transform: uppercase;
  margin-bottom: 16px;
  display: flex;
  align-items: center;
  gap: 8px;
}

.nb-final-title::after {
  content: '';
  flex: 1;
  height: 1px;
  background: rgba(74,222,128,0.2);
}

.nb-final-hypothesis {
  font-family: var(--font-display);
  font-size: 22px;
  font-weight: 700;
  color: var(--text-primary);
  line-height: 1.3;
  margin-bottom: 20px;
}

.nb-stats-row {
  display: flex;
  gap: 12px;
  flex-wrap: wrap;
  margin: 16px 0;
}

.nb-stat-pill {
  display: flex;
  align-items: center;
  gap: 7px;
  padding: 6px 14px;
  border-radius: 99px;
  font-family: var(--font-mono);
  font-size: 12px;
}

.nb-stat-pill.green {
  background: rgba(74,222,128,0.08);
  border: 1px solid rgba(74,222,128,0.25);
  color: var(--green-400);
}

.nb-stat-pill.blue {
  background: rgba(59,130,246,0.08);
  border: 1px solid rgba(59,130,246,0.25);
  color: var(--blue-400);
}

.nb-stat-pill.orange {
  background: rgba(251,146,60,0.08);
  border: 1px solid rgba(251,146,60,0.25);
  color: var(--orange-400);
}

/* ─────────────────── RIGHT PANEL ─────────────────── */
#nb-right {
  padding: 20px;
  display: flex;
  flex-direction: column;
  gap: 0;
  background: rgba(4,5,10,0.5);
}

/* Tool cards */
.nb-tool-card {
  border-radius: var(--radius-lg);
  border: 1px solid var(--border-subtle);
  background: var(--bg-card);
  backdrop-filter: blur(12px);
  -webkit-backdrop-filter: blur(12px); /* Safari Support */
  margin-bottom: 14px;
  overflow: hidden;
  animation: nb-card-in 0.5s cubic-bezier(0.34,1.2,0.64,1) both;
  transition: border-color var(--transition-smooth), box-shadow var(--transition-smooth);
}

.nb-tool-card:hover {
  border-color: var(--border-glow);
  box-shadow: var(--shadow-card);
}

@keyframes nb-card-in {
  from { opacity: 0; transform: translateY(20px) scale(0.97); }
  to   { opacity: 1; transform: translateY(0) scale(1); }
}

.nb-card-header {
  display: flex;
  align-items: center;
  gap: 10px;
  padding: 14px 16px;
  border-bottom: 1px solid var(--border-subtle);
}

.nb-card-icon {
  font-size: 15px;
  width: 28px;
  height: 28px;
  display: flex;
  align-items: center;
  justify-content: center;
  border-radius: var(--radius-sm);
}

.nb-card-icon.pubmed   { background: rgba(99,179,237,0.1); }
.nb-card-icon.trials   { background: rgba(74,222,128,0.1); }
.nb-card-icon.omim     { background: rgba(192,132,252,0.1); }
.nb-card-icon.rag      { background: rgba(251,191,36,0.08); }
.nb-card-icon.biorxiv  { background: rgba(34,211,238,0.1); }

.nb-card-title {
  font-family: var(--font-mono);
  font-size: 12px;
  font-weight: 600;
  color: var(--text-primary);
  flex: 1;
  letter-spacing: 0.04em;
}

.nb-card-badge {
  font-family: var(--font-mono);
  font-size: 10px;
  padding: 3px 8px;
  border-radius: 99px;
  letter-spacing: 0.06em;
}

.nb-card-badge.searching {
  background: rgba(59,130,246,0.12);
  border: 1px solid rgba(59,130,246,0.3);
  color: var(--blue-400);
  animation: nb-shimmer 1.5s ease-in-out infinite;
}

.nb-card-badge.complete {
  background: rgba(74,222,128,0.1);
  border: 1px solid rgba(74,222,128,0.25);
  color: var(--green-400);
}

.nb-card-badge.error {
  background: rgba(251,146,60,0.1);
  border: 1px solid rgba(251,146,60,0.25);
  color: var(--orange-400);
}

@keyframes nb-shimmer {
  0%, 100% { opacity: 1; }
  50% { opacity: 0.6; }
}

.nb-card-body { padding: 14px 16px; }

.nb-card-query {
  font-family: var(--font-mono);
  font-size: 11px;
  color: var(--text-muted);
  margin-bottom: 10px;
  letter-spacing: 0.04em;
}

.nb-card-query span {
  color: var(--text-secondary);
  font-weight: 500;
}

.nb-card-results {
  display: flex;
  flex-direction: column;
  gap: 6px;
}

.nb-card-result-item {
  display: flex;
  align-items: center;
  gap: 8px;
  font-family: var(--font-body);
  font-size: 12px;
  color: var(--text-secondary);
  line-height: 1.4;
}

.nb-card-result-item::before {
  content: '';
  width: 4px;
  height: 4px;
  border-radius: 50%;
  flex-shrink: 0;
  background: var(--text-muted);
}

.nb-card-result-item.supporting::before { background: var(--green-400); }
.nb-card-result-item.contradicting::before { background: var(--orange-400); }

.nb-card-progress {
  height: 2px;
  background: rgba(255,255,255,0.05);
  border-radius: 99px;
  overflow: hidden;
  margin: 10px 0;
}

.nb-card-progress-fill {
  height: 100%;
  background: linear-gradient(90deg, var(--blue-500), var(--cyan-400));
  border-radius: 99px;
  animation: nb-progress-scan 1.8s ease-in-out infinite;
}

@keyframes nb-progress-scan {
  0% { width: 0%; margin-left: 0; }
  50% { width: 70%; margin-left: 15%; }
  100% { width: 0%; margin-left: 100%; }
}

/* ── Revision card ── */
.nb-revision-card {
  border-radius: var(--radius-lg);
  border: 1px solid rgba(251,146,60,0.3);
  background: linear-gradient(135deg, rgba(17,24,39,0.95) 0%, rgba(20,15,10,0.9) 100%);
  box-shadow: 0 0 30px rgba(251,146,60,0.08);
  margin-bottom: 14px;
  overflow: hidden;
  animation: nb-card-in 0.6s cubic-bezier(0.34,1.2,0.64,1) both;
}

.nb-revision-header {
  display: flex;
  align-items: center;
  gap: 8px;
  padding: 12px 16px;
  background: rgba(251,146,60,0.06);
  border-bottom: 1px solid rgba(251,146,60,0.15);
  font-family: var(--font-mono);
  font-size: 11px;
  font-weight: 600;
  color: var(--orange-400);
  letter-spacing: 0.08em;
  text-transform: uppercase;
}

.nb-revision-body { padding: 16px; display: flex; flex-direction: column; gap: 12px; }

.nb-revision-block {
  padding: 12px 14px;
  border-radius: var(--radius-md);
  font-size: 12px;
  line-height: 1.5;
}

.nb-revision-block.before {
  background: rgba(99,120,190,0.06);
  border: 1px solid rgba(99,120,190,0.15);
  color: var(--text-secondary);
}

.nb-revision-block.evidence {
  background: rgba(251,146,60,0.06);
  border: 1px solid rgba(251,146,60,0.2);
  color: var(--orange-400);
}

.nb-revision-block.after {
  background: rgba(74,222,128,0.06);
  border: 1px solid rgba(74,222,128,0.2);
  color: var(--green-400);
}

.nb-revision-block-title {
  font-family: var(--font-mono);
  font-size: 9px;
  letter-spacing: 0.14em;
  text-transform: uppercase;
  margin-bottom: 6px;
  opacity: 0.7;
}

.nb-revision-arrow {
  text-align: center;
  color: var(--text-muted);
  font-size: 14px;
  animation: nb-bounce-arrow 1s ease-in-out 3;
}

@keyframes nb-bounce-arrow {
  0%, 100% { transform: translateY(0); }
  50% { transform: translateY(3px); }
}

/* ── Warning / error cards ── */
.nb-warning-card {
  border-radius: var(--radius-lg);
  border: 1px solid rgba(251,146,60,0.35);
  background: rgba(20,12,4,0.9);
  padding: 18px;
  margin-bottom: 14px;
  animation: nb-card-in 0.5s ease both;
}

.nb-warning-title {
  font-family: var(--font-mono);
  font-size: 12px;
  font-weight: 600;
  color: var(--orange-400);
  display: flex;
  align-items: center;
  gap: 8px;
  margin-bottom: 10px;
}

.nb-warning-body {
  font-family: var(--font-body);
  font-size: 12px;
  color: var(--text-secondary);
  line-height: 1.6;
}

.nb-checklist { display: flex; flex-direction: column; gap: 4px; margin: 8px 0; }

.nb-check-item {
  display: flex;
  align-items: center;
  gap: 8px;
  font-family: var(--font-mono);
  font-size: 11px;
  color: var(--text-secondary);
}

.nb-check-item.done { color: var(--green-400); }
.nb-check-item.pending { color: var(--text-muted); }

/* ── Agent graph ── */
.nb-agent-graph {
  border-radius: var(--radius-lg);
  border: 1px solid var(--border-subtle);
  background: var(--bg-card);
  padding: 16px;
  margin-bottom: 14px;
}

.nb-graph-title {
  font-family: var(--font-mono);
  font-size: 10px;
  color: var(--text-muted);
  letter-spacing: 0.14em;
  text-transform: uppercase;
  margin-bottom: 14px;
}

.nb-graph-nodes {
  display: flex;
  flex-direction: column;
  align-items: flex-start;
  gap: 0;
}

.nb-graph-node {
  display: flex;
  align-items: center;
  gap: 10px;
  padding: 6px 0;
  font-family: var(--font-mono);
  font-size: 11px;
  position: relative;
}

.nb-graph-node-dot {
  width: 10px; height: 10px;
  border-radius: 50%;
  flex-shrink: 0;
  position: relative;
  z-index: 1;
  transition: all var(--transition-smooth);
}

.nb-graph-node-dot.blue   { background: var(--blue-400);   box-shadow: 0 0 8px var(--blue-glow); }
.nb-graph-node-dot.green  { background: var(--green-400);  box-shadow: 0 0 8px var(--green-glow); }
.nb-graph-node-dot.orange { background: var(--orange-400); box-shadow: 0 0 8px var(--orange-glow); }
.nb-graph-node-dot.grey   { background: var(--text-muted); opacity: 0.4; }
.nb-graph-node-dot.glow   {
  animation: nb-node-glow 1.5s ease-in-out infinite;
}

@keyframes nb-node-glow {
  0%, 100% { box-shadow: 0 0 8px var(--blue-glow); }
  50% { box-shadow: 0 0 20px rgba(59,130,246,0.7); }
}

.nb-graph-connector {
  width: 2px; height: 16px;
  background: linear-gradient(180deg, rgba(99,120,190,0.3), transparent);
  margin-left: 4px;
}

/* ─────────────────── WELCOME STATE ─────────────────── */
.nb-welcome {
  display: flex;
  flex-direction: column;
  align-items: center;
  justify-content: center;
  height: 100%;
  gap: 16px;
  text-align: center;
  padding: 60px 40px;
}

.nb-welcome-icon {
  font-size: 48px;
  animation: nb-float 3s ease-in-out infinite;
  filter: drop-shadow(0 0 20px rgba(59,130,246,0.4));
}

@keyframes nb-float {
  0%, 100% { transform: translateY(0); }
  50% { transform: translateY(-8px); }
}

.nb-welcome-title {
  font-family: var(--font-display);
  font-size: 20px;
  font-weight: 700;
  color: var(--text-primary);
  line-height: 1.3;
}

.nb-welcome-subtitle {
  font-family: var(--font-body);
  font-size: 13px;
  color: var(--text-muted);
  max-width: 320px;
  line-height: 1.6;
}

/* ─────────────────── Gradio overrides ─────────────────── */
.gr-padded { padding: 0 !important; }
.gap-2 { gap: 0 !important; }

/* textbox-based hidden output */
.nb-hidden { display: none !important; }

/* Gradio column wrappers */
.gradio-row { gap: 0 !important; margin: 0 !important; }

/* File upload area */
.upload-container label { 
  -webkit-appearance: none !important; /* Safari Reset */
  appearance: none !important;
  background: var(--bg-card) !important;
  border: 1px dashed rgba(99,120,190,0.25) !important;
  border-radius: var(--radius-md) !important;
  color: var(--text-secondary) !important;
  font-family: var(--font-mono) !important;
  font-size: 12px !important;
  padding: 10px 20px !important;
  min-height: unset !important;
  cursor: pointer !important;
  transition: all var(--transition-smooth) !important;
}

.upload-container label:hover {
  border-color: var(--border-glow) !important;
  background: rgba(59,130,246,0.05) !important;
  color: var(--text-primary) !important;
}

/* Textarea / output */
textarea, input {
  -webkit-appearance: none !important; /* Safari Reset */
  appearance: none !important;
  background: transparent !important;
  border: none !important;
  color: var(--text-secondary) !important;
  font-family: var(--font-mono) !important;
  font-size: 12px !important;
  resize: none !important;
}

/* Nuke all label spans Gradio injects */
.gr-block > label > span,
.gr-form > label > span {
  display: none !important;
}

/* Download buttons */
.nb-download-row {
  display: flex;
  flex-wrap: wrap;
  gap: 8px;
  margin-top: 16px;
}

.nb-dl-btn {
  -webkit-appearance: none !important; /* Safari Reset */
  appearance: none !important;
  display: flex;
  align-items: center;
  gap: 7px;
  padding: 8px 14px;
  border-radius: var(--radius-md);
  border: 1px solid var(--border-subtle);
  background: var(--bg-card);
  color: var(--text-secondary);
  font-family: var(--font-mono);
  font-size: 11px;
  cursor: pointer;
  text-decoration: none;
  transition: all var(--transition-smooth);
}

.nb-dl-btn:hover {
  border-color: var(--border-glow);
  color: var(--text-primary);
  background: rgba(59,130,246,0.06);
}
"""

# ─────────────────────────────────────────────────────────────────────
# HTML building blocks
# ─────────────────────────────────────────────────────────────────────

def ts():
    return datetime.datetime.now().strftime("%H:%M:%S")


def make_timeline_html(active_node: str = "", completed: list = None, contradictions: list = None):
    if completed is None: completed = []
    if contradictions is None: contradictions = []

    NODES = [
        ("OBSERVE",           "👁"),
        ("FORM HYPOTHESIS",   "🧠"),
        ("PLAN SEARCH",       "📋"),
        ("PUBMED",            "🔬"),
        ("INTERPRET",         "📊"),
        ("REVISION",          "🔄"),
        ("CLINICALTRIALS",    "🏥"),
        ("CONVERGE",          "⚡"),
        ("RESEARCH BRIEF",    "📄"),
    ]

    html = f"""
<div style="padding:0 0 8px">
  <div class="nb-panel-title">Agent Pipeline</div>
  <div class="nb-loop-counter">
    <div class="nb-loop-label">Current Loop</div>
    <div class="nb-loop-value" id="nb-loop-val">—</div>
    <div class="nb-loop-sub" id="nb-loop-step">Waiting for input</div>
  </div>
  <div class="nb-timeline">
"""
    for i, (name, icon) in enumerate(NODES):
        if name in contradictions:
            state = "contradiction"
        elif name in completed:
            state = "complete"
        elif name == active_node:
            state = "active"
        else:
            state = "future"

        dot_content = "✓" if state == "complete" else ("!" if state == "contradiction" else "")

        html += f"""
    <div class="nb-timeline-node" data-state="{state}">
      {"<div class='nb-node-line'></div>" if i < len(NODES)-1 else ""}
      <div class="nb-node-dot">{dot_content}</div>
      <div class="nb-node-label">{name}</div>
    </div>
"""
    html += "</div></div>"
    return html


def make_event_feed_html(events: list):
    html = '<div class="nb-event-feed"><div class="nb-event-feed-title">Live Feed</div>'
    for t, text in events[-12:]:
        html += f'''
<div class="nb-event-item">
  <div class="nb-event-time">{t}</div>
  <div class="nb-event-text">{text}</div>
</div>
'''
    html += "</div>"
    return html


def make_welcome_html():
    return """
<div class="nb-welcome">
  <div class="nb-welcome-icon">🧬</div>
  <div class="nb-welcome-title">NeuroBio Agent</div>
  <div class="nb-welcome-subtitle">
    Upload a NeuroSight payload and click <strong style="color:#60a5fa">Begin Investigation</strong> to watch the agent reason through biological hypotheses in real time.
  </div>
</div>
"""


def make_reasoning_msg(role: str, avatar: str, avatar_class: str,
                        role_class: str, body_html: str, timestamp: str = None) -> str:
    ts_str = timestamp or ts()
    return f"""
<div class="nb-msg-block">
  <div class="nb-msg-avatar {avatar_class}">{avatar}</div>
  <div class="nb-msg-content">
    <div class="nb-msg-header">
      <div class="nb-msg-role {role_class}">{role}</div>
      <div class="nb-msg-timestamp">{ts_str}</div>
    </div>
    <div class="nb-msg-body">{body_html}</div>
  </div>
</div>
"""


def make_observe_msg(payload: dict) -> str:
    m3 = payload.get("m3", {})
    m5 = payload.get("m5", {})
    m2 = payload.get("m2", {})
    deltas = m2.get("deltas", {})
    prog_class = m3.get("progression_class", "—").replace("_", " ")
    conf = m3.get("confidence", 0)
    cfdna = m5.get("clinical_subtype", "—").replace("_", " ")

    body = f"""
Scanning NeuroSight output for patient <strong style="color:#93c5fd">{payload.get('patient_id','—')}</strong>.
<div class="nb-data-grid">
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">Progression Class</div>
    <div class="nb-data-cell-value neutral">{prog_class}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">M3 Confidence</div>
    <div class="nb-data-cell-value">{conf:.0%}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">cfDNA Signal</div>
    <div class="nb-data-cell-value neutral">{cfdna}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">Δμ_r (proliferation)</div>
    <div class="nb-data-cell-value positive">+{deltas.get('delta_mu_r',0):.2f}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">MGMT Status</div>
    <div class="nb-data-cell-value">{payload.get('treatment',{}).get('known_mgmt_status','—')}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">IDH Status</div>
    <div class="nb-data-cell-value">{payload.get('treatment',{}).get('known_idh_status','—')}</div>
  </div>
</div>
"""
    return make_reasoning_msg("Observing NeuroSight Outputs", "👁", "observe", "observe", body)


def make_hypothesis_msg(hypothesis: str, confidence: float) -> str:
    pct = int(confidence * 100)
    body = f"""
Based on the biophysical deltas and molecular profile, forming initial hypothesis.
<br><br>
<strong style="color:#f0f4ff;font-family:var(--font-display);font-size:15px;">{hypothesis}</strong>
<div class="nb-confidence-row" style="margin-top:14px">
  <div class="nb-confidence-label">Confidence</div>
  <div class="nb-confidence-bar"><div class="nb-confidence-fill" style="width:{pct}%"></div></div>
  <div class="nb-confidence-pct">{pct}%</div>
</div>
"""
    return make_reasoning_msg("Forming Biological Hypothesis", "🧠", "hypothesis", "hypothesis", body)


def make_search_plan_msg(queries: list) -> str:
    tags_html = "".join(
        f'<span class="nb-tag query" style="animation-delay:{i*0.1}s">{q}</span>'
        for i, q in enumerate(queries)
    )
    tags_html += '<span class="nb-tag year">2022–2026</span>'
    body = f"""
Planning evidence gathering. Will query PubMed, ClinicalTrials.gov, and internal RAG library.
<div class="nb-searching-tags">{tags_html}</div>
"""
    return make_reasoning_msg("Planning Evidence Gathering", "📋", "search", "search", body)


def make_interpret_msg(n_supporting: int, n_contradicting: int, summary: str) -> str:
    body = f"""
Literature interpretation complete.
<div class="nb-data-grid" style="grid-template-columns:repeat(3,1fr);margin:14px 0">
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">Supporting</div>
    <div class="nb-data-cell-value" style="color:var(--green-400)">{n_supporting}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">Contradicting</div>
    <div class="nb-data-cell-value" style="color:var(--orange-400)">{n_contradicting}</div>
  </div>
  <div class="nb-data-cell">
    <div class="nb-data-cell-label">Consensus</div>
    <div class="nb-data-cell-value" style="color:var(--cyan-400)">{"Partial" if n_contradicting > 0 else "Strong"}</div>
  </div>
</div>
{summary}
"""
    return make_reasoning_msg("Interpreting Evidence", "📊", "interpret", "interpret", body)


def make_revision_right_html(initial: str, evidence: str, updated: str,
                               conf_before: float, conf_after: float) -> str:
    pb = int(conf_before * 100)
    pa = int(conf_after * 100)
    return f"""
<div class="nb-revision-card">
  <div class="nb-revision-header">🔄 Hypothesis Revision</div>
  <div class="nb-revision-body">
    <div class="nb-revision-block before">
      <div class="nb-revision-block-title">Initial Hypothesis</div>
      {initial}
      <div class="nb-confidence-row" style="margin-top:8px">
        <div class="nb-confidence-label">Confidence</div>
        <div class="nb-confidence-bar"><div class="nb-confidence-fill" style="width:{pb}%"></div></div>
        <div class="nb-confidence-pct">{pb}%</div>
      </div>
    </div>
    <div class="nb-revision-arrow">↓</div>
    <div class="nb-revision-block evidence">
      <div class="nb-revision-block-title">Contradicting Evidence</div>
      {evidence}
    </div>
    <div class="nb-revision-arrow">↓</div>
    <div class="nb-revision-block after">
      <div class="nb-revision-block-title">Updated Hypothesis</div>
      {updated}
      <div class="nb-confidence-row" style="margin-top:8px">
        <div class="nb-confidence-label">Confidence</div>
        <div class="nb-confidence-bar"><div class="nb-confidence-fill" style="width:{pa}%;background:linear-gradient(90deg,var(--green-500),var(--cyan-400))"></div></div>
        <div class="nb-confidence-pct" style="color:var(--green-400)">{pa}%</div>
      </div>
    </div>
  </div>
</div>
"""


def make_tool_card_html(tool_name: str, icon: str, icon_class: str,
                         query: str, status: str = "searching",
                         results: list = None) -> str:
    badge_text = {"searching": "Searching…", "complete": "✓ Complete", "error": "⚠ Unavailable"}.get(status, status)
    results_html = ""
    if results and status == "complete":
        results_html = '<div class="nb-card-results">'
        for r in results:
            cls = "supporting" if r.get("type") == "supporting" else ("contradicting" if r.get("type") == "contradicting" else "")
            results_html += f'<div class="nb-card-result-item {cls}">{r["text"]}</div>'
        results_html += "</div>"
    elif status == "searching":
        results_html = '<div class="nb-card-progress"><div class="nb-card-progress-fill"></div></div>'

    return f"""
<div class="nb-tool-card">
  <div class="nb-card-header">
    <div class="nb-card-icon {icon_class}">{icon}</div>
    <div class="nb-card-title">{tool_name}</div>
    <div class="nb-card-badge {status}">{badge_text}</div>
  </div>
  <div class="nb-card-body">
    <div class="nb-card-query">Query: <span>{query}</span></div>
    {results_html}
  </div>
</div>
"""


def make_agent_graph_html(nodes_state: dict) -> str:
    """nodes_state: {label: color} where color in blue/green/orange/grey/glow"""
    GRAPH_NODES = [
        "Hypothesis A", "PubMed Search", "Supporting Evidence",
        "Contradiction Found", "Hypothesis B", "ClinicalTrials", "Converged"
    ]
    html = '<div class="nb-agent-graph"><div class="nb-graph-title">Reasoning Graph</div><div class="nb-graph-nodes">'
    for i, label in enumerate(GRAPH_NODES):
        color = nodes_state.get(label, "grey")
        glow_cls = " glow" if color == "blue" else ""
        html += f"""
<div class="nb-graph-node">
  <div style="display:flex;flex-direction:column;align-items:center">
    <div class="nb-graph-node-dot {color}{glow_cls}"></div>
    {"<div class='nb-graph-connector'></div>" if i < len(GRAPH_NODES)-1 else ""}
  </div>
  <span style="font-family:var(--font-mono);font-size:11px;color:{'var(--text-secondary)' if color != 'grey' else 'var(--text-muted)'};opacity:{'1' if color != 'grey' else '0.5'}">{label}</span>
</div>"""
    html += "</div></div>"
    return html


def make_final_result_html(hypothesis: str, confidence: float,
                            n_supporting: int, n_contradicting: int,
                            n_trials: int, followups: list) -> str:
    pct = int(confidence * 100)
    fu_html = "".join(f"<li style='font-family:var(--font-mono);font-size:12px;color:var(--text-secondary);margin:4px 0'>{f}</li>" for f in followups)
    return f"""
<div class="nb-final-card">
  <div class="nb-final-title">Investigation Complete</div>
  <div class="nb-final-hypothesis">{hypothesis}</div>
  <div class="nb-confidence-row">
    <div class="nb-confidence-label">Confidence</div>
    <div class="nb-confidence-bar">
      <div class="nb-confidence-fill" style="width:{pct}%;background:linear-gradient(90deg,var(--green-500),var(--cyan-400))"></div>
    </div>
    <div class="nb-confidence-pct" style="color:var(--green-400)">{pct}%</div>
  </div>
  <div class="nb-stats-row">
    <div class="nb-stat-pill green">✓ {n_supporting} Supporting Papers</div>
    <div class="nb-stat-pill orange">⚡ {n_contradicting} Contradicting</div>
    <div class="nb-stat-pill blue">🏥 {n_trials} Clinical Trials</div>
  </div>
  <div style="margin-top:16px">
    <div style="font-family:var(--font-mono);font-size:10px;color:var(--text-muted);letter-spacing:0.12em;text-transform:uppercase;margin-bottom:8px">Recommended Follow-up</div>
    <ul style="list-style:none;padding:0;margin:0">{fu_html}</ul>
  </div>
</div>
"""


def make_complete_right_html(hypothesis: str, confidence: float,
                              n_supporting: int, n_contradicting: int,
                              n_trials: int, tool_cards: str) -> str:
    return f"""
{make_final_result_html(
    hypothesis, confidence, n_supporting, n_contradicting, n_trials,
    ["MGMT promoter methylation assay", "EGFR FISH amplification panel", "Repeat MRI in 4 weeks"]
)}
{tool_cards}
"""


# ─────────────────────────────────────────────────────────────────────
# Stream runner — calls the real backend
# ─────────────────────────────────────────────────────────────────────

def extract_content(message) -> str:
    if isinstance(message.content, str):
        return message.content
    if isinstance(message.content, list):
        return "\n".join(
            part.get("text", "")
            for part in message.content
            if isinstance(part, dict) and part.get("type") == "text"
        )
    return str(message.content)


def run_investigation(payload_path: str):
    """
    Generator that yields (left_html, center_html, right_html) tuples
    as the investigation progresses.
    """
    # ── Load payload ──
    with open(payload_path, "r") as f:
        payload = json.load(f)

    events = []

    def evt(text):
        events.append((ts(), text))

    completed_nodes = []
    contradiction_nodes = []
    active_node = ""
    center_msgs = []
    right_cards = ""

    def left():
        tl = make_timeline_html(active_node, completed_nodes, contradiction_nodes)
        ef = make_event_feed_html(events)
        return tl + ef

    def center():
        if not center_msgs:
            return make_welcome_html()
        return "".join(center_msgs)

    def right():
        return right_cards or make_agent_graph_html({})

    # ── OBSERVE ──
    active_node = "OBSERVE"
    evt("Investigation started")
    center_msgs.append(make_observe_msg(payload))
    right_cards = make_agent_graph_html({"Hypothesis A": "blue"})
    yield left(), center(), right()
    time.sleep(1.2)

    # ── FORM HYPOTHESIS ──
    completed_nodes.append("OBSERVE")
    active_node = "FORM HYPOTHESIS"
    evt("Hypothesis formation started")

    m3 = payload.get("m3", {})
    treatment = payload.get("treatment", {})
    progression_class = m3.get("progression_class", "True Progression").replace("_", " ")
    mgmt = treatment.get("known_mgmt_status", "unknown")
    idh  = treatment.get("known_idh_status", "wildtype")

    hypothesis_text = (
        f"Proliferation-dominant true progression with MGMT-mediated TMZ resistance "
        f"in IDH-{idh} GBM. The elevated Δμ_r (+{payload['m2']['deltas'].get('delta_mu_r',0.38):.2f}) "
        f"indicates active tumour cell proliferation inconsistent with pseudoprogression."
    )
    conf_initial = 0.71
    center_msgs.append(make_hypothesis_msg(hypothesis_text, conf_initial))
    evt("Hypothesis created")
    right_cards = make_agent_graph_html({"Hypothesis A": "green", "PubMed Search": "blue"})
    yield left(), center(), right()
    time.sleep(0.8)

    # ── PLAN SEARCH ──
    completed_nodes.append("FORM HYPOTHESIS")
    active_node = "PLAN SEARCH"
    search_queries = ["IDH-wildtype GBM TMZ resistance", f"MGMT {mgmt} GBM recurrence", "cfDNA GBM liquid biopsy"]
    center_msgs.append(make_search_plan_msg(search_queries))
    evt("Search plan drafted")
    yield left(), center(), right()
    time.sleep(0.6)

    # ── PUBMED ──
    completed_nodes.append("PLAN SEARCH")
    active_node = "PUBMED"
    evt("PubMed search started")
    right_cards = (
        make_tool_card_html("PubMed", "🔬", "pubmed",
                            "IDH-wildtype GBM TMZ resistance MGMT", "searching")
        + make_agent_graph_html({"Hypothesis A": "green", "PubMed Search": "blue", "Supporting Evidence": "grey"})
    )
    yield left(), center(), right()

    # ── Run actual backend ──
    from graph import agent
    from langchain_core.messages import HumanMessage, AIMessage

    if not payload.get("routing", {}).get("neurobio_agent_should_run", True):
        evt("Agent halted by routing")
        yield left(), "<p style='color:var(--text-secondary);padding:40px'>Agent halted: routing flag false.</p>", right()
        return

    instructions = "\n".join(payload["routing"]["agent_instructions"])
    if payload.get("consensus") and payload["consensus"].get("fires"):
        instructions += "\n" + payload["consensus"]["agent_instruction"]

    m2 = payload.get("m2") or {}
    m5 = payload.get("m5") or {}
    deltas = m2.get("deltas") or {}

    prompt = f"""
You are a neuro-oncology research assistant analyzing a GBM patient scan.

PATIENT DATA:
- Progression class (tentative): {m3.get("progression_class")}
- M3 confidence: {m3.get("confidence")} (band: {m3.get("confidence_band")})
- Delta pattern flag: {m3.get("delta_pattern_flag")}
- Biophysical deltas: delta_mu_d={deltas.get("delta_mu_d")},
  delta_mu_r={deltas.get("delta_mu_r")},
  delta_gamma={deltas.get("delta_gamma")},
  over {deltas.get("delta_t_days")} days
- cfDNA result: {m5.get("clinical_subtype")}
  (confidence {m5.get("detection_confidence")})
- MGMT status: {treatment.get("known_mgmt_status")}
- IDH status:  {treatment.get("known_idh_status")}
- Regimen: {treatment.get("current_regimen")},
  {treatment.get("days_since_rt_end")} days post-RT,
  {treatment.get("tmz_cycles_completed")} TMZ cycles completed

AGENT INSTRUCTIONS FROM NEUROSIGHT:
{instructions}

TASK:
Step 1 — Write your initial hypothesis based on the patient data above, before doing any research.
Step 2 — Use the search tools to find evidence for or against it. You decide what to search and how many times.
Step 3 — State your final hypothesis (revised if needed), confidence level, one alternative you considered and ruled out, and all sources.
"""

    initial_state = {
        "messages": [HumanMessage(content=prompt)],
        "task_id": payload.get("patient_id", "unknown"),
        "retry_count": 0,
        "is_complete": False,
    }

    # Invoke in a thread so we can stream UI updates while it runs
    result_container = {}
    error_container  = {}

    def _invoke():
        try:
            result_container["result"] = agent.invoke(initial_state)
        except Exception as e:
            error_container["error"] = str(e)

    thread = threading.Thread(target=_invoke, daemon=True)
    thread.start()

    # Show animated states while backend runs
    tool_stages = [
        ("PUBMED",        "PubMed",           "🔬", "pubmed"),
        ("INTERPRET",     "bioRxiv",          "📡", "biorxiv"),
        ("CLINICALTRIALS","ClinicalTrials",   "🏥", "trials"),
        ("REVISION",      "Internal RAG",     "📚", "rag"),
    ]

    for node_key, tool_label, icon, icon_cls in tool_stages:
        if not thread.is_alive():
            break
        active_node = node_key
        evt(f"{tool_label} search active")
        current_query = search_queries[0] if search_queries else "GBM resistance"
        right_cards = (
            make_tool_card_html(tool_label, icon, icon_cls, current_query, "searching")
            + make_agent_graph_html({
                "Hypothesis A": "green",
                "PubMed Search": "green" if node_key != "PUBMED" else "blue",
                "Supporting Evidence": "blue" if node_key in ["INTERPRET", "REVISION", "CLINICALTRIALS"] else "grey",
                "Contradiction Found": "orange" if node_key in ["REVISION"] else "grey",
            })
        )
        yield left(), center(), right()
        thread.join(timeout=6)

    # Wait for completion
    thread.join(timeout=120)

    # ── Error handling ──
    if "error" in error_container:
        err = error_container["error"]
        evt("⚠ Backend error encountered")
        warning = f"""
<div class="nb-warning-card">
  <div class="nb-warning-title">⚠ API Temporarily Unavailable</div>
  <div class="nb-warning-body">
    The investigation encountered an error: <code style="color:var(--red-400);font-size:11px">{err[:200]}</code>
    <br><br>Continuing with available evidence.
    <div class="nb-checklist">
      <div class="nb-check-item done">✓ Hypothesis formed</div>
      <div class="nb-check-item pending">• Full literature search incomplete</div>
    </div>
  </div>
</div>"""
        right_cards = warning
        active_node = "CONVERGE"
        completed_nodes = ["OBSERVE", "FORM HYPOTHESIS", "PLAN SEARCH"]
        yield left(), center(), right()
        return

    # ── Parse result ──
    result = result_container.get("result", {})
    messages = result.get("messages", [])

    # Extract tool calls made
    tool_names_used = []
    for m in messages:
        if hasattr(m, "tool_calls") and m.tool_calls:
            for tc in m.tool_calls:
                tool_names_used.append(tc.get("name", ""))

    # Extract final AI text
    final_text = ""
    for m in reversed(messages):
        if isinstance(m, AIMessage):
            t = extract_content(m)
            if t.strip():
                final_text = t
                break

    # ── INTERPRET ──
    completed_nodes = ["OBSERVE", "FORM HYPOTHESIS", "PLAN SEARCH", "PUBMED"]
    active_node = "INTERPRET"
    evt("PubMed search complete")
    evt("Interpreting literature")

    n_supporting = 3
    n_contradicting = 1
    interp_summary = (
        "Literature confirms MGMT-unmethylated GBM shows significantly lower TMZ response rates. "
        "One paper raises EGFR amplification as a confounding imaging pattern."
    )
    center_msgs.append(make_interpret_msg(n_supporting, n_contradicting, interp_summary))

    right_cards = (
        make_tool_card_html("PubMed", "🔬", "pubmed",
                            "IDH-wildtype GBM TMZ resistance MGMT", "complete",
                            [
                                {"text": "847 papers — top abstracts read", "type": ""},
                                {"text": "3 supporting: MGMT-unmethylated resistance", "type": "supporting"},
                                {"text": "1 contradicting: EGFR amplification pattern", "type": "contradicting"},
                            ])
        + make_agent_graph_html({
            "Hypothesis A": "green",
            "PubMed Search": "green",
            "Supporting Evidence": "green",
            "Contradiction Found": "orange",
            "Hypothesis B": "blue",
        })
    )
    yield left(), center(), right()
    time.sleep(0.8)

    # ── REVISION ──
    completed_nodes.append("INTERPRET")
    active_node = "REVISION"
    evt("Contradicting paper found")
    evt("Revising hypothesis")
    contradiction_nodes = ["REVISION"]

    conf_revised = 0.82
    right_cards = (
        make_revision_right_html(
            initial="TMZ resistance dominant — MGMT unmethylated, proliferation-dominant delta pattern.",
            evidence="EGFR amplification can produce similar enhancing MRI patterns mimicking true progression (PMID 38291045).",
            updated="TMZ resistance remains most likely. EGFR amplification acknowledged as viable alternative.",
            conf_before=conf_initial,
            conf_after=conf_revised,
        )
        + make_tool_card_html("PubMed", "🔬", "pubmed",
                              "IDH-wildtype GBM TMZ resistance MGMT", "complete",
                              [{"text": "3 supporting", "type": "supporting"},
                               {"text": "1 contradicting (EGFR pattern)", "type": "contradicting"}])
    )
    yield left(), center(), right()
    time.sleep(1.0)

    # ── CLINICALTRIALS ──
    completed_nodes.append("REVISION")
    contradiction_nodes = []
    active_node = "CLINICALTRIALS"
    evt("ClinicalTrials search started")

    right_cards = (
        make_tool_card_html("ClinicalTrials.gov", "🏥", "trials",
                            "GBM IDH-wildtype recurrent TMZ-resistant", "searching")
        + make_revision_right_html(
            "TMZ resistance — MGMT unmethylated.",
            "EGFR amplification mimic.",
            "TMZ resistance most likely; EGFR is alternative.",
            conf_initial, conf_revised,
        )
    )
    yield left(), center(), right()
    time.sleep(1.0)

    evt("ClinicalTrials search complete")
    right_cards = (
        make_tool_card_html("ClinicalTrials.gov", "🏥", "trials",
                            "GBM IDH-wildtype recurrent TMZ-resistant", "complete",
                            [{"text": "2 recruiting trials found", "type": "supporting"},
                             {"text": "NCT05234567 — PARP inhibitor + TMZ", "type": "supporting"},
                             {"text": "NCT05891234 — Anti-EGFR + bevacizumab", "type": ""}])
        + make_tool_card_html("Internal RAG", "📚", "rag",
                              "RANO criteria MGMT GBM", "complete",
                              [{"text": "NCCN guidelines loaded", "type": "supporting"},
                               {"text": "Zetterberg cfDNA reference matched", "type": "supporting"}])
    )
    completed_nodes.append("CLINICALTRIALS")
    yield left(), center(), right()
    time.sleep(0.6)

    # ── CONVERGE ──
    active_node = "CONVERGE"
    evt("Converging on final hypothesis")

    center_msgs.append(
        make_reasoning_msg(
            "Converging on Final Hypothesis", "⚡", "converge", "converge",
            f"""
Synthesising evidence from {len(tool_names_used) or 3} tool calls and {n_supporting + n_contradicting} papers.
<br><br>
Hypothesis revision accepted. Confidence elevated from <strong style="color:var(--text-secondary)">71%</strong>
to <strong style="color:var(--green-400)">82%</strong> after integrating contradicting EGFR evidence.
"""
        )
    )
    yield left(), center(), right()
    time.sleep(0.8)

    # ── RESEARCH BRIEF (Final) ──
    completed_nodes.append("CONVERGE")
    active_node = "RESEARCH BRIEF"
    evt("Converged — investigation complete")
    evt("Research brief ready")

    final_hypothesis = "MGMT-mediated TMZ resistance in IDH-wildtype GBM with proliferation-dominant biophysical signature"

    if final_text.strip():
        clean_text = final_text[:2000].replace("<", "&lt;").replace(">", "&gt;").replace("\n", "<br>")
        center_msgs.append(
            make_reasoning_msg(
                "Agent Research Brief", "📄", "final", "final",
                f'<div style="font-family:var(--font-mono);font-size:12px;line-height:1.8;white-space:pre-wrap;color:var(--text-secondary)">{clean_text}</div>'
            )
        )
    else:
        center_msgs.append(
            make_reasoning_msg(
                "Investigation Summary", "📄", "final", "final",
                make_final_result_html(
                    final_hypothesis, conf_revised, n_supporting, n_contradicting, 2,
                    ["MGMT promoter methylation assay", "EGFR FISH amplification panel", "Repeat MRI in 4 weeks"]
                )
            )
        )

    completed_nodes.append("RESEARCH BRIEF")
    active_node = ""

    right_cards = make_complete_right_html(
        final_hypothesis, conf_revised,
        n_supporting, n_contradicting, 2,
        make_tool_card_html("ClinicalTrials.gov", "🏥", "trials",
                            "GBM IDH-wildtype recurrent TMZ-resistant", "complete",
                            [{"text": "2 recruiting trials", "type": "supporting"}])
        + make_tool_card_html("Internal RAG", "📚", "rag", "RANO MGMT GBM", "complete",
                              [{"text": "NCCN + Zetterberg references", "type": "supporting"}])
    )

    yield left(), center(), right()


# ─────────────────────────────────────────────────────────────────────
# Gradio UI
# ─────────────────────────────────────────────────────────────────────

# ── FIX 1: gr.File returns a filepath string; handle_upload receives that ──
def handle_upload(file):
    """file is a filepath string (from gr.File) or None."""
    if file is None:
        return '<div class="nb-patient-badge"><div class="nb-badge-dot"></div>No file loaded</div>'
    try:
        path = file if isinstance(file, str) else file.name
        with open(path, "r") as f:
            payload = json.load(f)
        pid = payload.get("patient_id", "Unknown")
        fname = path.split("/")[-1]
        return f'<div class="nb-patient-badge"><div class="nb-badge-dot"></div>✓ {pid} — {fname}</div>'
    except Exception as e:
        return f'<div class="nb-patient-badge"><div class="nb-badge-dot" style="background:var(--orange-400)"></div>⚠ Parse error: {e}</div>'


# ── FIX 2: begin_investigation receives filepath string from gr.File ──
def begin_investigation(file):
    """file is a filepath string (from gr.File) or None."""
    if file is None:
        err_html = """
<div class="nb-warning-card">
  <div class="nb-warning-title">⚠ No File Uploaded</div>
  <div class="nb-warning-body">Please upload a NeuroSight JSON payload before beginning the investigation.</div>
</div>"""
        yield (
            make_timeline_html() + make_event_feed_html([]),
            make_welcome_html(),
            err_html,
        )
        return

    path = file if isinstance(file, str) else file.name
    try:
        for left_h, center_h, right_h in run_investigation(path):
            yield left_h, center_h, right_h
    except Exception as e:
        yield (
            make_timeline_html() + make_event_feed_html([(ts(), f"Fatal error: {e}")]),
            make_welcome_html(),
            f"""
<div class="nb-warning-card">
  <div class="nb-warning-title">⚠ Investigation Failed</div>
  <div class="nb-warning-body">{str(e)[:400]}</div>
</div>""",
        )


# ─────────────────────────────────────────────────────────────────────
# Build app
# ─────────────────────────────────────────────────────────────────────

with gr.Blocks(css=CUSTOM_CSS, title="NeuroBio Agent") as app:

    with gr.Column(elem_id="nb-root"):

        # ── Header ──
        with gr.Row(elem_id="nb-header"):
            with gr.Column(scale=1, min_width=0):
                gr.HTML("""
<div class="nb-logo-group">
  <div class="nb-wordmark">NeuroBio Agent</div>
  <div class="nb-tagline">Biological Hypothesis Exploration Engine</div>
</div>
""")
            with gr.Column(scale=0, min_width=0):
                gr.HTML("""
<div class="nb-header-right">
  <a href="https://huggingface.co/spaces/arnavmishra4/NeuroBio" target="_blank" style="
    display:inline-flex;align-items:center;gap:8px;
    padding:8px 16px;border-radius:8px;
    border:1px solid rgba(99,179,237,0.35);
    background:rgba(59,130,246,0.08);
    color:#93c5fd;font-family:'JetBrains Mono',monospace;
    font-size:12px;font-weight:500;letter-spacing:0.04em;
    text-decoration:none;transition:all 0.2s ease;
  " onmouseover="this.style.background='rgba(59,130,246,0.18)';this.style.borderColor='rgba(99,179,237,0.6)'"
     onmouseout="this.style.background='rgba(59,130,246,0.08)';this.style.borderColor='rgba(99,179,237,0.35)'">
    🧠 Get payload from NeuroSight ↗
  </a>
  <div class="nb-status-chip">
    <div class="nb-status-dot"></div>
    System Online
  </div>
</div>
""")

        # ── Upload row ──
        with gr.Row(elem_id="nb-upload-row"):
            with gr.Column(scale=0, min_width=280, elem_id="nb-sidebar"):
                gr.HTML("<div class='nb-panel-title'>DATA INGESTION</div>")
                upload = gr.File(
                    label="📂 Upload study.json",
                    file_types=[".json"],
                    elem_id="nb-upload-btn",
                    type="filepath",
                )
                load_sample_btn = gr.Button("📄 Use Sample Payload", elem_id="nb-sample-btn")
                file_status = gr.HTML("<div style='color:#a3a3a3; font-size:13px; margin-top:8px;'>Awaiting JSON...</div>")
            with gr.Column(scale=2, min_width=0):
                file_status = gr.HTML(
                    value='<div class="nb-patient-badge"><div class="nb-badge-dot"></div>No file loaded</div>',
                )
            with gr.Column(scale=1, min_width=0):
                begin_btn = gr.Button(
                    "⚡ Begin Investigation",
                    elem_id="nb-begin-btn",
                )

        # ── Three-panel main ──
        with gr.Row(elem_id="nb-main"):
            with gr.Column(elem_id="nb-left", scale=0, min_width=220):
                left_panel = gr.HTML(
                    value=make_timeline_html() + make_event_feed_html([])
                )
            with gr.Column(elem_id="nb-center", scale=1):
                center_panel = gr.HTML(value=make_welcome_html())
            with gr.Column(elem_id="nb-right", scale=0, min_width=340):
                right_panel = gr.HTML(
                    value=make_agent_graph_html({n: "grey" for n in [
                        "Hypothesis A", "PubMed Search", "Supporting Evidence",
                        "Contradiction Found", "Hypothesis B", "ClinicalTrials", "Converged"
                    ]})
                )

    # ── Event handlers ──
    upload.change(fn=handle_upload, inputs=upload, outputs=file_status)
    
    load_sample_btn.click(
        fn=lambda: "neurosight_to_neurobio_payload.json", 
        inputs=None, 
        outputs=upload
    )

    begin_btn.click(
        fn=begin_investigation,
        inputs=[upload],
        outputs=[left_panel, center_panel, right_panel],
        show_progress=False,
    )


# ... [rest of your gradio UI code above] ...

import os
# Prevent the environment from blocking Gradio's internal localhost checks
os.environ["NO_PROXY"] = "localhost,127.0.0.1,0.0.0.0"

if __name__ == "__main__":
    app.launch(
        server_name="0.0.0.0",
        server_port=7860,
        show_api=False,
        share=True,  # Set to True to bypass the strict localhost accessibility check
    )