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app.py

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+"""
+OncoAgent — Interactive Demo for Hugging Face Spaces.
+
+Simulates the full multi-agent oncology triage pipeline with realistic
+streaming, agent node transitions, and clinical recommendations.
+Runs without GPU/vLLM — pure frontend showcase.
+
+Hardware Target: AMD Instinct MI300X (production)
+Demo Mode: CPU-only simulation for HF Spaces free tier
+"""
+
+import gradio as gr
+import time
+from typing import Generator
+
+# ── Design System (inline for HF Spaces portability) ──────────────────
+
+FONTS_LINK: str = (
+    '<link rel="stylesheet" href="https://fonts.googleapis.com/css2?'
+    'family=Figtree:wght@400;500;600;700&'
+    'family=Inter:wght@300;400;500;600&display=swap">'
+)
+
+CSS: str = """
+/* OncoAgent — Clinical Dark Theme */
+:root {
+    --shadow-drop: none !important;
+    --shadow-drop-lg: none !important;
+    --shadow-inset: none !important;
+    --block-shadow: none !important;
+    --body-background-fill: #0f172a !important;
+    --background-fill-primary: #0f172a !important;
+}
+html, body, gradio-app {
+    background-color: #0f172a !important;
+    margin: 0 !important; padding: 0 !important;
+}
+.gradio-container, .main, .wrap, .contain,
+.gradio-container > div, footer, main {
+    background: #0f172a !important;
+    color: #e2e8f0 !important;
+    font-family: 'Inter', -apple-system, sans-serif !important;
+    box-shadow: none !important;
+}
+.gradio-container {
+    max-width: 960px !important;
+    margin: 0 auto !important;
+    border: none !important;
+}
+* { box-sizing: border-box; }
+
+.gr-group, .gr-block, .gr-box, .gr-panel,
+.block, .wrap, .panel { background: transparent !important; }
+
+/* Header */
+.header-bar {
+    display: flex; justify-content: space-between; align-items: center;
+    padding: 14px 24px;
+    background: #1e293b;
+    border: 1px solid #334155; border-radius: 14px;
+    margin-bottom: 16px;
+}
+.brand-name {
+    font-family: 'Figtree', sans-serif;
+    font-size: 1.6rem; font-weight: 700;
+    color: #f1f5f9; letter-spacing: -0.025em;
+}
+.hw-badge {
+    background: rgba(239, 68, 68, 0.15); color: #fca5a5;
+    padding: 5px 14px; border-radius: 6px;
+    font-size: 0.72rem; font-weight: 600;
+    letter-spacing: 0.05em;
+    border: 1px solid rgba(239, 68, 68, 0.25);
+}
+.demo-badge {
+    background: rgba(14, 165, 233, 0.15); color: #7dd3fc;
+    padding: 5px 14px; border-radius: 6px;
+    font-size: 0.72rem; font-weight: 600;
+    letter-spacing: 0.05em;
+    border: 1px solid rgba(14, 165, 233, 0.25);
+}
+
+/* Cards */
+.card {
+    background: #1e293b !important;
+    border: 1px solid #334155 !important;
+    border-radius: 14px !important;
+    padding: 18px !important;
+}
+.card:hover { border-color: #475569 !important; }
+
+/* Buttons */
+.btn-primary {
+    background: linear-gradient(135deg, #0ea5e9, #0284c7) !important;
+    border: none !important; color: #fff !important;
+    font-weight: 600 !important; border-radius: 10px !important;
+    cursor: pointer !important;
+    transition: transform 0.15s ease-out, box-shadow 0.15s ease-out !important;
+}
+.btn-primary:hover {
+    transform: translateY(-1px) !important;
+    box-shadow: 0 4px 14px rgba(14, 165, 233, 0.4) !important;
+}
+.btn-demo {
+    background: linear-gradient(135deg, #10b981, #059669) !important;
+    border: none !important; color: #fff !important;
+    font-weight: 600 !important; border-radius: 10px !important;
+    cursor: pointer !important; font-size: 1rem !important;
+    padding: 12px 24px !important;
+    transition: transform 0.15s ease-out, box-shadow 0.15s ease-out !important;
+}
+.btn-demo:hover {
+    transform: translateY(-2px) !important;
+    box-shadow: 0 6px 20px rgba(16, 185, 129, 0.4) !important;
+}
+
+/* Chat */
+.gr-chatbot, [class*="chatbot"] {
+    background: transparent !important;
+    border: none !important; box-shadow: none !important;
+}
+.message {
+    padding: 16px 20px !important;
+    border-radius: 18px !important;
+    margin-bottom: 12px !important;
+    line-height: 1.7 !important;
+    font-size: 0.94rem !important;
+}
+.message.user {
+    background: rgba(14, 165, 233, 0.08) !important;
+    border: 1px solid rgba(14, 165, 233, 0.15) !important;
+    border-bottom-right-radius: 4px !important;
+    margin-left: 15% !important;
+}
+.message.bot {
+    background: rgba(30, 41, 59, 0.6) !important;
+    border: 1px solid rgba(51, 65, 85, 0.3) !important;
+    border-bottom-left-radius: 4px !important;
+    margin-right: 10% !important;
+    backdrop-filter: blur(12px) !important;
+}
+
+/* Safety Badges */
+.badge-safe {
+    display: inline-flex; align-items: center; gap: 6px;
+    background: rgba(16, 185, 129, 0.12); color: #34d399;
+    border: 1px solid rgba(16, 185, 129, 0.3);
+    padding: 4px 12px; border-radius: 6px;
+    font-weight: 600; font-size: 0.8rem;
+}
+
+/* Node Progress */
+.node-step {
+    display: inline-flex; align-items: center; gap: 6px;
+    font-size: 0.78rem; color: #94a3b8;
+    padding: 4px 10px; border-radius: 6px;
+    background: rgba(14, 165, 233, 0.08);
+    border: 1px solid rgba(14, 165, 233, 0.15);
+    margin-right: 6px; margin-bottom: 4px;
+}
+.node-step.active {
+    color: #38bdf8; border-color: rgba(14, 165, 233, 0.4);
+    animation: pulse-node 1.5s ease-in-out infinite;
+}
+.node-step.done { color: #34d399; border-color: rgba(16,185,129,0.3); }
+@keyframes pulse-node {
+    0%, 100% { opacity: 1; } 50% { opacity: 0.5; }
+}
+
+/* Info panel */
+.info-panel {
+    background: rgba(14, 165, 233, 0.06);
+    border: 1px solid rgba(14, 165, 233, 0.15);
+    border-radius: 12px; padding: 16px;
+    margin-bottom: 12px;
+}
+
+/* Textarea & inputs */
+textarea, input[type="text"] {
+    background: #0f172a !important;
+    border: 1px solid #334155 !important;
+    color: #e2e8f0 !important;
+    border-radius: 10px !important;
+    font-family: 'Inter', sans-serif !important;
+}
+textarea:focus, input[type="text"]:focus {
+    border-color: #0ea5e9 !important;
+    outline: none !important;
+}
+
+/* Labels */
+label, .gr-input-label { color: #94a3b8 !important; }
+
+/* KPI tiles */
+.kpi-row { display: flex; gap: 12px; margin-top: 12px; }
+.kpi-tile {
+    flex: 1; background: #1e293b; border: 1px solid #334155;
+    border-radius: 10px; padding: 14px; text-align: center;
+}
+.kpi-label {
+    font-size: 0.68rem; font-weight: 500; color: #64748b;
+    text-transform: uppercase; letter-spacing: 0.08em; margin-bottom: 4px;
+}
+.kpi-value {
+    font-family: 'Figtree', sans-serif;
+    font-size: 1.3rem; font-weight: 700; color: #f1f5f9;
+}
+
+/* Architecture diagram */
+.arch-flow {
+    display: flex; align-items: center; gap: 8px;
+    flex-wrap: wrap; margin: 12px 0;
+}
+.arch-node {
+    background: #1e293b; border: 1px solid #334155;
+    border-radius: 8px; padding: 8px 14px;
+    font-size: 0.78rem; color: #cbd5e1;
+    font-weight: 500;
+}
+.arch-node.highlight {
+    border-color: #0ea5e9; color: #7dd3fc;
+    background: rgba(14, 165, 233, 0.08);
+}
+.arch-arrow { color: #475569; font-size: 1.2rem; }
+
+/* Scrollbar */
+::-webkit-scrollbar { width: 6px; }
+::-webkit-scrollbar-track { background: #0f172a; }
+::-webkit-scrollbar-thumb { background: #334155; border-radius: 3px; }
+
+/* Footer */
+.footer-text {
+    text-align: center; color: #475569;
+    font-size: 0.72rem; margin-top: 20px;
+    padding: 12px; border-top: 1px solid #1e293b;
+}
+
+/* Reduced motion */
+@media (prefers-reduced-motion: reduce) {
+    *, *::before, *::after {
+        animation-duration: 0.01ms !important;
+        transition-duration: 0.01ms !important;
+    }
+}
+"""
+
+# ── Demo Case Data ────────────────────────────────────────────────────
+
+DEMO_CASE: str = (
+    "55-year-old female patient presents with postmenopausal bleeding. "
+    "Ultrasound shows an endometrial thickening of 12mm. "
+    "The endometrial biopsy report confirms Grade 1 endometrioid "
+    "adenocarcinoma. No evidence of myometrial invasion on MRI. "
+    "CA-125 within normal limits. Patient has BMI of 32 and "
+    "controlled type 2 diabetes."
+)
+
+# Simulated agent outputs — based on real NCCN Uterine guidelines
+DEMO_STEPS: list = [
+    {
+        "node": "🔀 Router Agent",
+        "delay": 0.8,
+        "output": (
+            "**Classification:** Oncological case detected.\n\n"
+            "- **Cancer Type:** Endometrial (Uterine)\n"
+            "- **Confidence:** 0.96\n"
+            "- **Routing Decision:** → Specialist Agent (Tier 2 — Qwen3.6-27B)\n"
+            "- **Rationale:** Confirmed histopathology requires advanced reasoning."
+        ),
+    },
+    {
+        "node": "🔍 Clinical Extraction",
+        "delay": 1.0,
+        "output": (
+            "**Extracted Clinical Entities:**\n\n"
+            "| Field | Value |\n"
+            "|---|---|\n"
+            "| Age | 55 years |\n"
+            "| Sex | Female |\n"
+            "| Chief Complaint | Postmenopausal bleeding |\n"
+            "| Imaging | Endometrial thickening 12mm (US) |\n"
+            "| MRI | No myometrial invasion |\n"
+            "| Pathology | **Grade 1 endometrioid adenocarcinoma** |\n"
+            "| Biomarker | CA-125 normal |\n"
+            "| Comorbidities | BMI 32, T2DM (controlled) |\n"
+            "| FIGO Stage | Likely IA (pending surgical staging) |"
+        ),
+    },
+    {
+        "node": "📚 Corrective RAG",
+        "delay": 1.5,
+        "output": (
+            "**Retrieval Results** — NCCN Uterine Cancer Guidelines v2.2025\n\n"
+            "- 📄 **Source:** `uterine.pdf` — Pages 12-18 (Endometrioid Adenocarcinoma)\n"
+            "- 🎯 **Bi-Encoder Score:** 0.89 | **Cross-Encoder Score:** 0.94\n"
+            "- ✅ **Distance Gate:** PASSED (threshold: 0.65)\n"
+            "- 📊 **Chunks Retrieved:** 6 / 2,847 total\n\n"
+            "**Key Guideline Excerpts:**\n"
+            "> *\"For Grade 1 endometrioid adenocarcinoma confined to the endometrium "
+            "(Stage IA), total hysterectomy with bilateral salpingo-oophorectomy "
+            "(TH/BSO) is the primary treatment. Lymph node assessment should be "
+            "considered based on institutional protocols.\"*\n\n"
+            "> *\"Sentinel lymph node mapping is preferred over comprehensive "
+            "lymphadenectomy for clinically uterine-confined disease.\"*"
+        ),
+    },
+    {
+        "node": "🧠 Specialist Agent",
+        "delay": 2.0,
+        "output": (
+            "**OncoAgent — Clinical Recommendation**\n\n"
+            "---\n\n"
+            "## 📋 Clinical Summary\n\n"
+            "55-year-old postmenopausal female with biopsy-confirmed Grade 1 "
+            "endometrioid adenocarcinoma. MRI shows no myometrial invasion. "
+            "Tumor markers within normal limits. Comorbidities include obesity "
+            "(BMI 32) and controlled T2DM.\n\n"
+            "## 🔬 Diagnostic Findings\n\n"
+            "- **Histology:** Endometrioid adenocarcinoma, Grade 1 (well-differentiated)\n"
+            "- **Probable FIGO Stage:** IA — disease confined to endometrium\n"
+            "- **Myometrial Invasion:** Not detected on MRI\n"
+            "- **Lymphovascular Space Invasion (LVSI):** Not reported\n\n"
+            "## 💊 Treatment Recommendation\n\n"
+            "**Primary Treatment (NCCN Category 1):**\n"
+            "1. **Total Hysterectomy with Bilateral Salpingo-Oophorectomy (TH/BSO)**\n"
+            "   - Minimally invasive approach (laparoscopic/robotic) preferred\n"
+            "   - Consider peritoneal washings at time of surgery\n\n"
+            "2. **Sentinel Lymph Node (SLN) Mapping**\n"
+            "   - Preferred over comprehensive lymphadenectomy\n"
+            "   - Per NCCN institutional SLN algorithm\n\n"
+            "**Adjuvant Therapy Considerations:**\n"
+            "- If final pathology confirms Stage IA, Grade 1: **Observation only**\n"
+            "- No adjuvant radiation or chemotherapy indicated for this stage\n"
+            "- If upstaged post-surgery: Refer to NCCN adjuvant guidelines\n\n"
+            "## ⚠️ Additional Considerations\n\n"
+            "- **Obesity Management:** BMI 32 — perioperative risk optimization recommended\n"
+            "- **Diabetes Control:** HbA1c target < 7% pre-surgery\n"
+            "- **Genetic Counseling:** Consider Lynch syndrome screening "
+            "(immunohistochemistry for MMR proteins or MSI testing)\n"
+            "- **Fertility Preservation:** Not applicable (postmenopausal)\n\n"
+            "## 📚 Evidence Level\n\n"
+            "- **NCCN Evidence Category:** 1 (High-level evidence, uniform consensus)\n"
+            "- **Guideline Source:** NCCN Uterine Neoplasms v2.2025, Pages 12-18\n"
+            "- **RAG Confidence:** 0.94 (Cross-Encoder validated)"
+        ),
+    },
+    {
+        "node": "✅ Critic (Reflexion Loop)",
+        "delay": 1.0,
+        "output": (
+            "**Critic Validation — PASSED ✅**\n\n"
+            "| Check | Status |\n"
+            "|---|---|\n"
+            "| Clinical Summary present | ✅ |\n"
+            "| Diagnostic Findings present | ✅ |\n"
+            "| Treatment Recommendation present | ✅ |\n"
+            "| Evidence/Citations present | ✅ |\n"
+            "| Diagnostic Rigor (biopsy confirmed) | ✅ |\n"
+            "| Anti-Hallucination (RAG-grounded) | ✅ |\n"
+            "| PHI Sanitization | ✅ |\n\n"
+            "**Verdict:** Recommendation is clinically grounded and safe for review.\n\n"
+            "---\n"
+            "### Decision Status: "
+            "<span class='badge-safe'>"
+            "✅ Clinically Validated"
+            "</span>"
+        ),
+    },
+]
+
+
+def _node_progress_html(current_idx: int) -> str:
+    """Generate the agent pipeline progress bar HTML."""
+    nodes = ["Router", "Extraction", "RAG", "Specialist", "Critic"]
+    icons = ["🔀", "🔍", "📚", "🧠", "✅"]
+    parts = []
+    for i, (name, icon) in enumerate(zip(nodes, icons)):
+        if i < current_idx:
+            cls = "done"
+        elif i == current_idx:
+            cls = "active"
+        else:
+            cls = ""
+        parts.append(f"<span class='node-step {cls}'>{icon} {name}</span>")
+        if i < len(nodes) - 1:
+            parts.append("<span style='color:#475569;'>→</span>")
+    return " ".join(parts)
+
+
+def run_demo() -> Generator:
+    """Simulate the full OncoAgent pipeline with streaming."""
+    history = []
+
+    # Step 1: User message appears
+    history.append({"role": "user", "content": DEMO_CASE})
+    yield history
+
+    time.sleep(0.5)
+
+    # Step 2: Stream each agent node
+    for step_idx, step in enumerate(DEMO_STEPS):
+        node_name = step["node"]
+        delay = step["delay"]
+        output = step["output"]
+
+        # Build progress bar
+        progress = _node_progress_html(step_idx)
+
+        # Start with node header + progress
+        header = f"### {node_name}\n{progress}\n\n"
+
+        # Stream the output character by character (in chunks for speed)
+        full_text = header
+        chunk_size = 8
+        for i in range(0, len(output), chunk_size):
+            full_text += output[i:i + chunk_size]
+            # Update the last bot message
+            display_history = history.copy()
+            display_history.append({"role": "assistant", "content": full_text})
+            yield display_history
+            time.sleep(0.015)
+
+        # Finalize this step
+        history.append({"role": "assistant", "content": full_text})
+        yield history
+
+        # Pause between nodes
+        time.sleep(delay * 0.3)
+
+    # Final summary message
+    time.sleep(0.3)
+    final_msg = (
+        "---\n\n"
+        "### 🏁 Pipeline Complete\n\n"
+        "<div class='kpi-row'>"
+        "<div class='kpi-tile'><div class='kpi-label'>Agents Used</div>"
+        "<div class='kpi-value'>5</div></div>"
+        "<div class='kpi-tile'><div class='kpi-label'>RAG Sources</div>"
+        "<div class='kpi-value'>6</div></div>"
+        "<div class='kpi-tile'><div class='kpi-label'>Confidence</div>"
+        "<div class='kpi-value'>0.94</div></div>"
+        "<div class='kpi-tile'><div class='kpi-label'>Safety</div>"
+        "<div class='kpi-value'>✅</div></div>"
+        "</div>\n\n"
+        "<div style='margin-top:12px; font-size:0.8rem; color:#64748b;'>"
+        "⚡ In production, this pipeline runs on AMD Instinct™ MI300X with "
+        "vLLM (PagedAttention) serving Qwen3.5-9B + Qwen3.6-27B models. "
+        "This demo simulates the agent flow for showcase purposes."
+        "</div>"
+    )
+    history.append({"role": "assistant", "content": final_msg})
+    yield history
+
+
+def handle_user_message(
+    message: str,
+    history: list,
+) -> Generator:
+    """Handle custom user messages with a simulated response."""
+    if not message.strip():
+        yield history
+        return
+
+    history = history or []
+    history.append({"role": "user", "content": message})
+    yield history
+
+    time.sleep(0.5)
+
+    # Simulated response for any custom input
+    response = (
+        "### 🔀 Router Agent\n\n"
+        "**Note:** This is a demo environment running on HF Spaces "
+        "without GPU acceleration.\n\n"
+        "In the **production deployment** on AMD Instinct™ MI300X, "
+        "your clinical case would be processed through our full "
+        "5-agent pipeline:\n\n"
+        "1. **Router** — Classifies oncological vs. non-oncological\n"
+        "2. **Clinical Extraction** — Extracts structured entities\n"
+        "3. **Corrective RAG** — Retrieves from NCCN/ESMO guidelines\n"
+        "4. **Specialist** — Generates evidence-based recommendation\n"
+        "5. **Critic (Reflexion)** — Validates safety and completeness\n\n"
+        "👉 Click **▶ View Demo** to see a complete simulated triage "
+        "with the endometrial cancer case.\n\n"
+        "🔗 **Production:** Deploy with `docker compose up` on MI300X hardware.\n"
+        "📖 **Source:** [GitHub](https://github.com/maximolopezchenlo-lab/OncoAgent)"
+    )
+
+    # Stream it
+    partial = ""
+    chunk_size = 12
+    for i in range(0, len(response), chunk_size):
+        partial += response[i:i + chunk_size]
+        display = history.copy()
+        display.append({"role": "assistant", "content": partial})
+        yield display
+        time.sleep(0.01)
+
+    history.append({"role": "assistant", "content": response})
+    yield history
+
+
+# ── Build the UI ──────────────────────────────────────────────────────
+
+HEADER_HTML: str = """
+<div class="header-bar">
+    <div style="display:flex; align-items:center; gap:12px;">
+        <span class="brand-name">🧬 OncoAgent</span>
+        <span class="demo-badge">INTERACTIVE DEMO</span>
+    </div>
+    <div style="display:flex; gap:8px; align-items:center;">
+        <span class="hw-badge">AMD INSTINCT™ MI300X</span>
+        <span class="hw-badge">ROCm 7.2</span>
+    </div>
+</div>
+"""
+
+INFO_HTML: str = """
+<div class="info-panel">
+    <div style="font-size:0.95rem; font-weight:600; color:#e2e8f0; margin-bottom:8px;">
+        🏥 Multi-Agent Oncology Triage System
+    </div>
+    <div style="font-size:0.82rem; color:#94a3b8; line-height:1.6;">
+        OncoAgent uses a <strong style="color:#7dd3fc;">5-agent LangGraph pipeline</strong>
+        to analyze clinical cases against <strong style="color:#7dd3fc;">NCCN/ESMO guidelines</strong>
+        with built-in safety validation and anti-hallucination guardrails.
+    </div>
+    <div class="arch-flow">
+        <span class="arch-node highlight">🔀 Router</span>
+        <span class="arch-arrow">→</span>
+        <span class="arch-node">🔍 Extraction</span>
+        <span class="arch-arrow">→</span>
+        <span class="arch-node">📚 Corrective RAG</span>
+        <span class="arch-arrow">→</span>
+        <span class="arch-node">🧠 Specialist</span>
+        <span class="arch-arrow">→</span>
+        <span class="arch-node">✅ Critic</span>
+    </div>
+    <div style="font-size:0.72rem; color:#64748b; margin-top:8px;">
+        ⚡ Production: Qwen3.5-9B (Tier 1) + Qwen3.6-27B (Tier 2) via vLLM PagedAttention
+        &nbsp;|&nbsp; 📄 162 NCCN + 16 ESMO guidelines indexed
+    </div>
+</div>
+"""
+
+FOOTER_HTML: str = """
+<div class="footer-text">
+    🧬 OncoAgent — AMD Developer Hackathon 2026<br>
+    Built with LangGraph · vLLM · Gradio · ROCm 7.2<br>
+    <a href="https://github.com/maximolopezchenlo-lab/OncoAgent"
+       style="color:#0ea5e9; text-decoration:none;" target="_blank">
+       GitHub Repository</a>
+    &nbsp;·&nbsp;
+    <span style="color:#64748b;">100% Open Source · Apache 2.0</span>
+</div>
+"""
+
+
+with gr.Blocks(
+    css=CSS,
+    head=FONTS_LINK,
+    title="OncoAgent — Oncology Triage Demo",
+    theme=gr.themes.Base(),
+) as demo:
+    # Header
+    gr.HTML(HEADER_HTML)
+    gr.HTML(INFO_HTML)
+
+    # Chat
+    chatbot = gr.Chatbot(
+        type="messages",
+        label="Clinical Triage Chat",
+        height=520,
+        show_label=False,
+        show_copy_button=True,
+        render_markdown=True,
+        elem_classes=["card"],
+    )
+
+    # Controls
+    with gr.Row():
+        with gr.Column(scale=3):
+            txt = gr.Textbox(
+                placeholder="Enter a clinical case or click '▶ View Demo'...",
+                show_label=False,
+                lines=2,
+                max_lines=5,
+            )
+        with gr.Column(scale=1, min_width=180):
+            demo_btn = gr.Button(
+                "▶ View Demo",
+                elem_classes=["btn-demo"],
+                size="lg",
+            )
+
+    with gr.Row():
+        send_btn = gr.Button("Send", elem_classes=["btn-primary"], size="sm")
+        clear_btn = gr.Button("🗑 Clear", variant="secondary", size="sm")
+
+    # Footer
+    gr.HTML(FOOTER_HTML)
+
+    # ── Event Handlers ────────────────────────────────────────────────
+
+    demo_btn.click(
+        fn=run_demo,
+        inputs=None,
+        outputs=chatbot,
+    )
+
+    send_btn.click(
+        fn=handle_user_message,
+        inputs=[txt, chatbot],
+        outputs=chatbot,
+    ).then(lambda: "", outputs=txt)
+
+    txt.submit(
+        fn=handle_user_message,
+        inputs=[txt, chatbot],
+        outputs=chatbot,
+    ).then(lambda: "", outputs=txt)
+
+    clear_btn.click(lambda: [], outputs=chatbot)
+
+
+if __name__ == "__main__":
+    demo.launch(server_name="0.0.0.0", server_port=7860)