Upload Albitron-TPH2O_V1.0_app_200limit.py

Albitron-TPH2O_V1.0_app_200limit.py

@@ -0,0 +1,646 @@
+# -*- coding: utf-8 -*-
+from __future__ import annotations
+
+import html
+import os
+import re
+import tempfile
+from datetime import datetime
+from functools import lru_cache
+from pathlib import Path
+from typing import Optional
+
+import gradio as gr
+import pandas as pd
+
+from albitron_runtime import AlbitronRuntime, table_from_ui
+
+BASE = Path(__file__).resolve().parent
+PUBLIC_NAME = "Albitron-TPH2O"
+PUBLIC_VERSION = "V1.0"
+BATCH_ROW_LIMIT = 200
+MODEL_PATH = Path(
+    os.environ.get(
+        "ALBITRON_MODEL_PATH",
+        BASE / "models" / "Albitron-TPH2O_V1.0_model.joblib",
+    )
+)
+SUPPORT_PATH = Path(
+    os.environ.get(
+        "ALBITRON_SUPPORT_PATH",
+        BASE / "models" / "Albitron-TPH2O_V1.0_support.joblib",
+    )
+)
+
+COMPONENTS = [
+    "SiO2", "TiO2", "Al2O3", "FeOt", "MgO", "CaO", "Na2O", "K2O", "Analytical total"
+]
+EMPTY_INPUT = pd.DataFrame(
+    {
+        "Component": COMPONENTS,
+        "Liquid wt.%": [None] * 9,
+        "Plagioclase wt.%": [None] * 9,
+    }
+)
+EXAMPLE_INPUT = pd.DataFrame(
+    {
+        "Component": COMPONENTS,
+        "Liquid wt.%": [64.2, 0.6, 16.8, 3.7, 2.9, 4.9, 4.8, 1.8, 95.6],
+        "Plagioclase wt.%": [51.752117, 0.0, 30.730948, 0.700706, 0.100101, 12.812903, 3.803831, 0.100101, 99.3],
+    }
+)
+
+BATCH_TEMPLATE = BASE / "examples" / "Albitron-TPH2O_V1.0_batch_template.csv"
+BATCH_EXAMPLE = BASE / "examples" / "example_input.csv"
+
+CSS = r"""
+:root {
+  --al-ink: #18212b;
+  --al-text: #344054;
+  --al-muted: #667085;
+  --al-line: #e3e8ef;
+  --al-soft: #f7f9fc;
+  --al-panel: #ffffff;
+  --al-blue: #326e9d;
+  --al-blue-soft: #eef6fc;
+  --al-blue-line: #b9d3e7;
+  --al-red: #b64d4d;
+  --al-gold: #b28722;
+  --al-water: #3978b8;
+  --al-green: #24724c;
+  --al-amber: #886719;
+  --al-low: #993d3d;
+}
+
+.gradio-container {
+  max-width: 1120px !important;
+  margin: 0 auto !important;
+  font-family: Arial, "Helvetica Neue", Helvetica, sans-serif !important;
+  color: var(--al-text);
+}
+
+#al-hero {
+  padding: 30px 4px 18px 4px;
+  border-bottom: 1px solid var(--al-line);
+  margin-bottom: 14px;
+}
+#al-brand-row {
+  display: flex;
+  align-items: center;
+  justify-content: space-between;
+  gap: 16px;
+  flex-wrap: wrap;
+}
+.al-wordmark {
+  font-family: Arial, "Helvetica Neue", Helvetica, sans-serif !important;
+  font-size: 2.02rem;
+  line-height: 1.08;
+  font-weight: 700;
+  letter-spacing: .012em;
+  color: var(--al-ink);
+  font-variant-ligatures: none;
+  text-rendering: geometricPrecision;
+}
+.al-release {
+  display: inline-flex;
+  align-items: center;
+  gap: 8px;
+  padding: 6px 10px;
+  border: 1px solid var(--al-blue-line);
+  border-radius: 999px;
+  font-size: .78rem;
+  font-weight: 700;
+  color: var(--al-blue);
+  background: #f7fbff;
+  white-space: nowrap;
+}
+.al-subtitle {
+  margin-top: 10px;
+  color: var(--al-muted);
+  font-size: 1rem;
+  line-height: 1.5;
+}
+.al-meta {
+  margin-top: 8px;
+  color: #7a8491;
+  font-size: .83rem;
+}
+
+.quick-nav {
+  display: grid;
+  grid-template-columns: 1fr 1fr;
+  gap: 10px;
+  margin: 14px 0 16px 0;
+}
+.quick-nav a {
+  text-decoration: none !important;
+  color: var(--al-text) !important;
+  background: white;
+  border: 1px solid var(--al-line);
+  border-radius: 12px;
+  padding: 11px 14px;
+  display: block;
+  transition: border-color .15s ease, box-shadow .15s ease, transform .15s ease;
+}
+.quick-nav a:hover {
+  border-color: #b8c9d8;
+  box-shadow: 0 4px 12px rgba(16, 24, 40, .06);
+  transform: translateY(-1px);
+}
+.quick-nav .nav-title {font-weight: 700; color: var(--al-ink);}
+.quick-nav .nav-sub {font-size: .82rem; color: var(--al-muted); margin-top: 3px;}
+
+.al-status {
+  border: 1px solid var(--al-line);
+  background: white;
+  border-radius: 10px;
+  padding: 9px 12px;
+  margin: 4px 0 12px 0;
+  font-size: .9rem;
+}
+.asset-ok {color: var(--al-green); font-weight: 700;}
+.asset-missing {color: var(--al-low); font-weight: 700;}
+
+.input-note {
+  background: #f8fafc;
+  border: 1px solid var(--al-line);
+  border-radius: 12px;
+  padding: 13px 15px;
+  margin-bottom: 18px;
+  line-height: 1.58;
+  color: #475467;
+}
+
+.section-head {margin: 24px 0 10px 0; padding: 0 2px;}
+.section-kicker {
+  font-size: .75rem;
+  font-weight: 700;
+  color: var(--al-blue);
+  letter-spacing: .075em;
+  text-transform: uppercase;
+}
+.section-title {
+  font-size: 1.38rem;
+  color: var(--al-ink);
+  font-weight: 700;
+  margin-top: 3px;
+}
+.section-desc {color: var(--al-muted); font-size: .91rem; margin-top: 4px; line-height: 1.5;}
+
+.tool-panel {
+  border: 1px solid var(--al-line) !important;
+  border-radius: 14px !important;
+  background: var(--al-panel) !important;
+  padding: 14px !important;
+  box-shadow: 0 1px 3px rgba(16,24,40,.035);
+}
+
+.step-strip {
+  display: flex;
+  flex-wrap: wrap;
+  gap: 7px;
+  margin: 4px 0 12px 0;
+}
+.step-chip {
+  border: 1px solid #d9e1e8;
+  background: #fafcfe;
+  border-radius: 999px;
+  padding: 5px 9px;
+  color: #526273;
+  font-size: .78rem;
+}
+.step-chip b {color: var(--al-blue);}
+
+.batch-banner {
+  background: linear-gradient(180deg, #f6fbff 0%, #eff6fb 100%);
+  border: 1px solid var(--al-blue-line);
+  border-left: 5px solid var(--al-blue);
+  border-radius: 13px;
+  padding: 15px 17px;
+  margin: 30px 0 10px 0;
+}
+.batch-banner .title {font-size: 1.48rem; font-weight: 700; color: #243b53;}
+.batch-banner .desc {margin-top: 5px; color: #526475; font-size: .92rem; line-height: 1.52;}
+.template-callout {
+  background: #fffdf6;
+  border: 1px solid #e8d9a8;
+  border-radius: 11px;
+  padding: 11px 13px;
+  margin: 4px 0 11px 0;
+  color: #63551f;
+  font-size: .9rem;
+  line-height: 1.48;
+}
+
+.result-grid {
+  display: grid;
+  grid-template-columns: repeat(3, minmax(0, 1fr));
+  gap: 12px;
+  margin: 13px 0 10px 0;
+}
+.result-card {
+  background: white;
+  border: 1px solid #e6e8eb;
+  border-radius: 13px;
+  padding: 16px 17px;
+  box-shadow: 0 2px 6px rgba(16,24,40,.045);
+}
+.result-card.t {border-top: 5px solid var(--al-red);}
+.result-card.p {border-top: 5px solid var(--al-gold);}
+.result-card.h {border-top: 5px solid var(--al-water);}
+.result-title {font-size: .82rem; color: #667085; font-weight: 700; letter-spacing: .025em;}
+.result-value {font-size: 1.73rem; font-weight: 700; margin: 6px 0; color: #202b33;}
+.support {font-size: .91rem; font-weight: 700;}
+.support.high {color: var(--al-green);}
+.support.mid {color: var(--al-amber);}
+.support.low {color: var(--al-low);}
+.diag {
+  font-size: .91rem;
+  line-height: 1.62;
+  color: #475467;
+  background: #fbfcfd;
+  border: 1px solid var(--al-line);
+  border-radius: 10px;
+  padding: 11px 13px;
+}
+.batch-status {
+  font-size: .9rem;
+  line-height: 1.55;
+  color: #475467;
+  background: #f8fafc;
+  border: 1px solid var(--al-line);
+  border-radius: 9px;
+  padding: 9px 11px;
+}
+.micro-note {font-size: .81rem; color: var(--al-muted); line-height: 1.45;}
+.footer {
+  margin-top: 30px;
+  padding: 15px 2px 22px 2px;
+  border-top: 1px solid var(--al-line);
+  color: #7a8491;
+  font-size: .82rem;
+  line-height: 1.55;
+}
+
+@media (max-width: 760px) {
+  .result-grid, .quick-nav {grid-template-columns: 1fr;}
+  .al-wordmark {font-size: 1.7rem;}
+}
+"""
+
+
+@lru_cache(maxsize=1)
+def runtime() -> AlbitronRuntime:
+    return AlbitronRuntime(MODEL_PATH, SUPPORT_PATH)
+
+
+def asset_status_html() -> str:
+    model_ok = MODEL_PATH.exists()
+    support_ok = SUPPORT_PATH.exists()
+    if model_ok and support_ok:
+        return (
+            '<div class="al-status"><span class="asset-ok">运行资产已加载 / Runtime assets ready.</span> '
+            'Albitron-TPH2O V1.0 可进行单点和批量预测。</div>'
+        )
+    missing = []
+    if not model_ok:
+        missing.append(MODEL_PATH.name)
+    if not support_ok:
+        missing.append(SUPPORT_PATH.name)
+    return (
+        '<div class="al-status"><span class="asset-missing">运行资产缺失 / Runtime assets missing: '
+        + html.escape(", ".join(missing))
+        + '.</span> 请先运行 <code>python prepare_local_models.py</code> 或将文件放入 models/。</div>'
+    )
+
+
+def bilingual_support(label: str) -> str:
+    mapping = {
+        "High support": "高支持 / High support",
+        "Intermediate support": "中等支持 / Intermediate support",
+        "Low support": "低支持 / Low support",
+    }
+    return mapping.get(str(label), str(label))
+
+
+def support_class(label: str) -> str:
+    label = str(label)
+    if "High" in label or "高支持" in label:
+        return "high"
+    if "Intermediate" in label or "中等支持" in label:
+        return "mid"
+    return "low"
+
+
+def render_results(row: pd.Series, warnings: list[str]) -> tuple[str, str]:
+    t_sup = bilingual_support(str(row["T_support"]))
+    p_sup = bilingual_support(str(row["P_support"]))
+    h_sup = bilingual_support(str(row["H2O_support"]))
+    cards = f"""
+    <div class="result-grid">
+      <div class="result-card t">
+        <div class="result-title">温度 / Temperature</div>
+        <div class="result-value">{row['T_C']:.1f} °C</div>
+        <div class="support {support_class(t_sup)}">{html.escape(t_sup)}</div>
+      </div>
+      <div class="result-card p">
+        <div class="result-title">压力 / Pressure</div>
+        <div class="result-value">{row['P_MPa']:.1f} MPa</div>
+        <div class="support {support_class(p_sup)}">{html.escape(p_sup)}</div>
+      </div>
+      <div class="result-card h">
+        <div class="result-title">溶解水 / Dissolved H₂O</div>
+        <div class="result-value">{row['H2O_wt']:.2f} wt.%</div>
+        <div class="support {support_class(h_sup)}">{html.escape(h_sup)}</div>
+      </div>
+    </div>
+    """
+    warning_html = ""
+    if warnings:
+        warning_html = "<br><b>输入提示 / Input note:</b> " + " ".join(html.escape(w) for w in warnings)
+    diagnostics = f"""
+    <div class="diag">
+      <b>诊断信息 / Diagnostics</b><br>
+      ΔAn = {row['delta_An']:.2f} mol.% &nbsp;·&nbsp;
+      档案距离百分位 / Archive-distance percentile = {row['archive_distance_percentile']:.1f}<br>
+      模型分歧百分位 / Disagreement percentile:
+      T {row['T_disagreement_percentile']:.1f} &nbsp;·&nbsp;
+      P {row['P_disagreement_percentile']:.1f} &nbsp;·&nbsp;
+      H₂O {row['H2O_disagreement_percentile']:.1f}<br>
+      支持等级是经验性资格标记，不是正确概率或置信区间。ΔAn 不改变 T、P、H₂O 或支持等级。<br>
+      Support is an empirical qualification label, not a probability or confidence interval. ΔAn does not alter T, P, H₂O, or support classification.
+      {warning_html}
+    </div>
+    """
+    return cards, diagnostics
+
+
+def predict_single(ui_table: pd.DataFrame):
+    try:
+        raw = table_from_ui(ui_table)
+        result = runtime().predict(raw)
+        cards, diag = render_results(result.table.iloc[0], result.warnings)
+        return cards, diag, ""
+    except Exception as exc:
+        return "", "", f"预测失败 / Prediction failed: {exc}"
+
+
+def clear_single():
+    return EMPTY_INPUT.copy(), "", "", ""
+
+
+def read_batch(path: str) -> pd.DataFrame:
+    p = Path(path)
+    if p.suffix.lower() in {".xlsx", ".xls"}:
+        return pd.read_excel(p)
+    return pd.read_csv(p)
+
+
+def safe_output_stem(value: Optional[str]) -> str:
+    text = str(value or "").strip()
+    text = re.sub(r"\.csv$", "", text, flags=re.IGNORECASE)
+    text = re.sub(r"[^A-Za-z0-9._-]+", "_", text).strip("._-")
+    return text[:80] or "Albitron-TPH2O_batch_prediction"
+
+
+def predict_batch(file_path: Optional[str], output_name: Optional[str]):
+    if not file_path:
+        raise gr.Error("请先上传 CSV 或 XLSX 文件。 / Upload a CSV or XLSX file first.")
+    try:
+        df = read_batch(file_path)
+        if len(df) == 0:
+            raise ValueError("The uploaded table contains no data rows.")
+        if len(df) > BATCH_ROW_LIMIT:
+            raise ValueError(
+                f"This file contains {len(df)} rows, exceeding the online batch limit of {BATCH_ROW_LIMIT} pairs per run. "
+                f"Please split the dataset into files with no more than {BATCH_ROW_LIMIT} rows each."
+            )
+        result = runtime().predict(df)
+        out = result.table.copy()
+
+        stamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+        stem = safe_output_stem(output_name)
+        export_dir = Path(tempfile.mkdtemp(prefix="albitron_tph2o_"))
+        export = export_dir / f"{stem}_{stamp}.csv"
+        out.to_csv(export, index=False, encoding="utf-8-sig")
+
+        notes = ""
+        if result.warnings:
+            notes = "**输入警告 / Input warnings:** " + " | ".join(result.warnings[:20])
+        status = (
+            '<div class="batch-status"><b>批量预测完成 / Batch prediction complete.</b> '
+            f'共处理 {len(out)} 行 / {len(out)} rows processed.<br>'
+            f'输出文件 / Output file: <code>{html.escape(export.name)}</code><br>'
+            '下载表使用稳定的英文列名，便于后续脚本与复现。 / '
+            'The downloaded table keeps stable English column names for reproducibility.</div>'
+        )
+        return out, str(export), notes, status
+    except Exception as exc:
+        raise gr.Error(f"批量预测失败 / Batch prediction failed: {exc}")
+
+
+def clear_batch_results():
+    return (
+        pd.DataFrame(),
+        None,
+        "",
+        '<div class="batch-status">批量结果已清除；当前上传文件仍保留，可直接再次运行。 / Batch results cleared; the current upload is retained and can be run again.</div>',
+    )
+
+
+def reset_batch():
+    return (
+        None,
+        "Albitron-TPH2O_batch_prediction",
+        pd.DataFrame(),
+        None,
+        "",
+        '<div class="batch-status">批量区域已重置，可上传新的数据表。 / Batch workspace reset; upload a new table to continue.</div>',
+    )
+
+
+def build_demo() -> gr.Blocks:
+    with gr.Blocks(title="Albitron-TPH2O V1.0") as demo:
+        gr.HTML(
+            f"""
+            <div id="al-hero">
+              <div id="al-brand-row">
+                <div class="al-wordmark">Albitron-TPH2O</div>
+                <div class="al-release">V1.0 · Natural-sample mode</div>
+              </div>
+              <div class="al-subtitle">
+                斜长石–液相联合 T–P–H₂O 预测与目标特异支持评估<br>
+                Joint T–P–H₂O prediction and target-specific support from paired plagioclase–liquid chemistry
+              </div>
+              <div class="al-meta">作者 / Author: Bowei Yang &nbsp;·&nbsp; © 2026 Bowei Yang</div>
+            </div>
+            <div class="quick-nav">
+              <a href="#single-workspace"><div class="nav-title">单点预测 / Single pair</div><div class="nav-sub">输入一对分析，直接查看 T–P–H₂O 与支持等级。</div></a>
+              <a href="#batch-workspace"><div class="nav-title">批量预测 / Batch prediction</div><div class="nav-sub">下载模板、上传数据、连续生成独立预测表。</div></a>
+            </div>
+            """
+        )
+        gr.HTML(asset_status_html())
+        gr.HTML(
+            """
+            <div class="input-note">
+              <b>输入说明 / Input note.</b>
+              请使用经过质量控制、矩阵校正的 EPMA 氧化物 wt.% 数据，并保留原始分析总量；不要在外部先归一化到 100%。
+              Albitron-TPH2O 会在内部为 CLR 表示执行组成闭合。<br>
+              Use quality-controlled, matrix-corrected EPMA oxide wt.% and retain the reported analytical totals.
+              Do not externally renormalize analyses to 100%; Albitron-TPH2O performs compositional closure internally.
+              <b>FeOᵀ</b> 表示以 FeO 计的全铁 / total Fe expressed as FeO.
+            </div>
+            """
+        )
+
+        gr.HTML(
+            """
+            <div class="section-head" id="single-workspace">
+              <div class="section-kicker">Single pair</div>
+              <div class="section-title">单点预测 / Single-pair prediction</div>
+              <div class="section-desc">适用于一组明确配对的斜长石与液相分析。 / For one explicitly paired plagioclase and liquid analysis.</div>
+            </div>
+            <div class="step-strip">
+              <span class="step-chip"><b>1</b> 填写组成 / Enter chemistry</span>
+              <span class="step-chip"><b>2</b> 运行预测 / Predict</span>
+              <span class="step-chip"><b>3</b> 查看支持 / Read support</span>
+            </div>
+            """
+        )
+        with gr.Group(elem_classes=["tool-panel"]):
+            input_table = gr.Dataframe(
+                value=EMPTY_INPUT,
+                headers=["组分 / Component", "液相 wt.% / Liquid wt.%", "斜长石 wt.% / Plagioclase wt.%"],
+                datatype=["str", "number", "number"],
+                row_count=9,
+                column_count=3,
+                interactive=True,
+                static_columns=[0],
+                show_row_numbers=False,
+                wrap=False,
+                label=None,
+                column_widths=["34%", "33%", "33%"],
+            )
+            with gr.Row():
+                example_btn = gr.Button("载入示例 / Load example", variant="secondary")
+                clear_btn = gr.Button("清除 / Clear", variant="secondary")
+                predict_btn = gr.Button("开始预测 / Predict", variant="primary")
+
+            result_html = gr.HTML()
+            diagnostic_html = gr.HTML()
+            error_box = gr.Markdown()
+
+        example_btn.click(lambda: EXAMPLE_INPUT.copy(), outputs=input_table)
+        clear_btn.click(clear_single, outputs=[input_table, result_html, diagnostic_html, error_box])
+        predict_btn.click(predict_single, inputs=input_table, outputs=[result_html, diagnostic_html, error_box])
+
+        gr.HTML(
+            """
+            <div class="batch-banner" id="batch-workspace">
+              <div class="title">批量预测 / Batch Prediction</div>
+              <div class="desc">
+                一次处理多组已明确配对的斜长石–液相分析。<b>在线版单次最多 200 对分析</b>；更大的数据集请拆分为多个文件。每次运行生成独立、带时间戳的 CSV；清除结果不会清除当前上传文件，因此可在同一页面反复运行并输出不同预测表。<br>
+                Process many explicitly paired analyses at once. <b>The online interface accepts up to 200 analysis pairs per run.</b> Split larger datasets into multiple files. Each run creates an independent timestamped CSV; clearing results keeps the current upload so the same workspace can be reused repeatedly.
+              </div>
+            </div>
+            <div class="step-strip">
+              <span class="step-chip"><b>1</b> 下载模板 / Get template</span>
+              <span class="step-chip"><b>2</b> 上传数据 / Upload</span>
+              <span class="step-chip"><b>3</b> 运行并下载 / Run & download</span>
+              <span class="step-chip"><b>4</b> 清除后复用 / Clear & reuse</span>
+            </div>
+            """
+        )
+        with gr.Group(elem_classes=["tool-panel"]):
+            gr.HTML(
+                """
+                <div class="template-callout">
+                  <b>建议先下载标准模板 / Start with the standard template.</b>
+                  模板包含固定机器列名；Sample 列可选，并会保留到输出结果中。<b>每个文件最多 200 行数据。</b><br>
+                  The template contains the stable machine-readable schema; the optional Sample column is preserved in the output. <b>Each uploaded file may contain up to 200 data rows.</b>
+                </div>
+                """
+            )
+            with gr.Row():
+                template_btn = gr.DownloadButton(
+                    "⬇ 下载批量导入模板 / Download Batch Template",
+                    value=str(BATCH_TEMPLATE),
+                    variant="primary",
+                )
+                example_csv_btn = gr.DownloadButton(
+                    "下载示例 CSV / Download Example CSV",
+                    value=str(BATCH_EXAMPLE),
+                    variant="secondary",
+                )
+
+            with gr.Row(equal_height=False):
+                with gr.Column(scale=1, min_width=300):
+                    batch_file = gr.File(
+                        label="上传批量数据（最多 200 行） / Upload batch CSV or XLSX (max 200 rows)",
+                        file_types=[".csv", ".xlsx", ".xls"],
+                        type="filepath",
+                    )
+                    output_name = gr.Textbox(
+                        value="Albitron-TPH2O_batch_prediction",
+                        label="输出表名称 / Output table name",
+                        info="系统自动追加时间戳，因此重复运行不会覆盖之前的输出。 / A timestamp is appended automatically.",
+                    )
+                    batch_btn = gr.Button("运行批量预测 / Run Batch Prediction", variant="primary")
+                    with gr.Row():
+                        batch_clear_btn = gr.Button("清除结果 / Clear Results", variant="secondary")
+                        batch_reset_btn = gr.Button("全部重置 / Reset All", variant="secondary")
+                    gr.HTML('<div class="micro-note">“清除结果”保留上传文件；“全部重置”清空上传与结果。<br>Clear Results retains the upload; Reset All clears both input and output.</div>')
+
+                with gr.Column(scale=2, min_width=420):
+                    batch_status = gr.HTML('<div class="batch-status">等待批量输入 / Ready for batch input.</div>')
+                    batch_table = gr.Dataframe(
+                        label="批量结果预览 / Batch Results Preview",
+                        interactive=False,
+                        wrap=False,
+                    )
+                    batch_download = gr.File(label="下载本次预测表 / Download This Prediction Table")
+                    batch_notes = gr.Markdown()
+
+        batch_btn.click(
+            predict_batch,
+            inputs=[batch_file, output_name],
+            outputs=[batch_table, batch_download, batch_notes, batch_status],
+        )
+        batch_clear_btn.click(
+            clear_batch_results,
+            outputs=[batch_table, batch_download, batch_notes, batch_status],
+        )
+        batch_reset_btn.click(
+            reset_batch,
+            outputs=[batch_file, output_name, batch_table, batch_download, batch_notes, batch_status],
+        )
+
+        with gr.Accordion("方法与边界 / Method and limits", open=False):
+            gr.Markdown(
+                """
+**运行模式 / Mode:** 仅使用自然样品部署模式；预测端不提供实验 study identity。 / Natural-sample deployment only; experimental study identity is not supplied to the prediction head.
+
+**输出 / Outputs:** 使用同一对主量元素化学组成预测 T、P 与溶解 H₂O，并基于档案代表性和模型分歧给出目标特异的支持等级。 / T, P and dissolved H₂O are predicted from the same paired major-element chemistry, with target-specific support from archive representation and branch disagreement.
+
+**解释边界 / Interpretation:** 支持等级不是正确概率或置信区间。压力的 study-held-out transfer 弱于 T 和 H₂O，因此不应过度解释细小压力差异。 / Support is not a probability of correctness or a confidence interval. Pressure has weaker study-held-out transfer than T and H₂O, so fine pressure differences should be interpreted cautiously.
+
+**批量模式 / Batch mode:** 每一行必须是用户明确提供的一对 crystal–liquid analysis。在线界面单次最多处理 **200 对分析**；超过 200 行的数据请拆分为多个文件。Albitron-TPH2O 不自动推断配对，也不自动构造 Cartesian products。 / Each row must be an explicitly supplied crystal–liquid pair. The online interface processes at most **200 analysis pairs per run**; split larger datasets into multiple files. Albitron-TPH2O does not infer pairings or construct Cartesian products automatically.
+                """
+            )
+
+        gr.HTML(
+            f"""
+            <div class="footer">
+              <b>Albitron-TPH2O {PUBLIC_VERSION}</b> · Natural-sample prediction interface<br>
+              作者 / Author: Bowei Yang &nbsp;·&nbsp; © 2026 Bowei Yang. All rights reserved.
+            </div>
+            """
+        )
+    return demo
+
+
+demo = build_demo()
+
+if __name__ == "__main__":
+    demo.launch(css=CSS)