Upload mlplo/app.py with huggingface_hub

mlplo/app.py

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+from __future__ import annotations
+
+import argparse
+import csv
+import logging
+import tempfile
+from pathlib import Path
+
+import gradio as gr
+import torch
+from transformers import AutoModelForSeq2SeqLM
+
+from .common import (
+    DEFAULT_APP_FALLBACK_MODEL,
+    DEFAULT_INPUT_MAX_LENGTH,
+    default_device,
+    ensure_project_dirs,
+    existing_default_checkpoint,
+    load_json,
+    load_tokenizer,
+    normalize_text,
+    resolve_model_reference,
+)
+
+LOGGER = logging.getLogger(__name__)
+
+try:
+    import PyPDF2
+
+    HAS_PYPDF2 = True
+except ImportError:
+    HAS_PYPDF2 = False
+
+# ── Generation Presets ────────────────────────────────────────────────────────
+MODE_PRESETS = {
+    "QUICK PULSE": {
+        "max_new_tokens": 72,
+        "min_new_tokens": 18,
+        "num_beams": 4,
+        "length_penalty": 1.25,
+    },
+    "KEY NOTES": {
+        "max_new_tokens": 104,
+        "min_new_tokens": 24,
+        "num_beams": 5,
+        "length_penalty": 1.05,
+    },
+    "DEEP CONTEXT": {
+        "max_new_tokens": 152,
+        "min_new_tokens": 34,
+        "num_beams": 6,
+        "length_penalty": 0.92,
+    },
+}
+
+DEFAULT_MODE = "QUICK PULSE"
+
+# ── Wonder Makers-inspired CSS ────────────────────────────────────────────────
+APP_CSS = """
+@import url('https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700;800;900&family=JetBrains+Mono:wght@400;500&display=swap');
+
+:root {
+  --black: #000000;
+  --white: #FFFFFF;
+  --lime: #D4FF00;
+  --lime-dim: rgba(212, 255, 0, 0.15);
+  --lime-glow: rgba(212, 255, 0, 0.08);
+  --grey-100: #F5F5F5;
+  --grey-400: #9CA3AF;
+  --grey-600: #52525B;
+  --grey-800: #27272A;
+  --grey-900: #18181B;
+  --border: rgba(255, 255, 255, 0.06);
+  --border-hover: rgba(255, 255, 255, 0.12);
+  --fn: 'Inter', -apple-system, BlinkMacSystemFont, sans-serif;
+  --mono: 'JetBrains Mono', monospace;
+  --ease: cubic-bezier(0.16, 1, 0.3, 1);
+}
+
+/* ─── Global Reset ─── */
+*, *::before, *::after { box-sizing: border-box; margin: 0; padding: 0; }
+
+body {
+  background: var(--black) !important;
+  color: var(--white) !important;
+  font-family: var(--fn) !important;
+  -webkit-font-smoothing: antialiased;
+  -moz-osx-font-smoothing: grayscale;
+  overflow-x: hidden;
+}
+
+/* Ambient glow — subtle purple/blue vignette like Wonder Makers */
+body::before {
+  content: '';
+  position: fixed;
+  inset: 0;
+  background:
+    radial-gradient(ellipse 50% 50% at 0% 0%, rgba(120, 80, 255, 0.06), transparent 70%),
+    radial-gradient(ellipse 40% 40% at 100% 100%, rgba(212, 255, 0, 0.03), transparent 60%);
+  pointer-events: none;
+  z-index: -1;
+}
+
+/* ─── Gradio Container Overrides ─── */
+.gradio-container {
+  max-width: 1100px !important;
+  margin: 0 auto !important;
+  padding: 0 !important;
+  background: transparent !important;
+}
+
+footer { display: none !important; }
+
+/* Kill ALL default Gradio backgrounds */
+.gradio-container, .gradio-container *,
+.gr-box, .gr-panel, .gr-form, .gr-block,
+[class*="block"], [class*="form"], [class*="panel"],
+[class*="accordion"], [class*="markdown"] {
+  background: transparent !important;
+  color: var(--white) !important;
+}
+
+/* ─── HERO HEADER ─── */
+.wm-hero {
+  text-align: center;
+  padding: 64px 24px 48px;
+  position: relative;
+}
+.wm-hero h1 {
+  font-family: var(--fn) !important;
+  font-size: 3.2rem !important;
+  font-weight: 900 !important;
+  letter-spacing: -0.04em !important;
+  text-transform: uppercase !important;
+  line-height: 1.05 !important;
+  margin: 0 0 16px 0 !important;
+  background: linear-gradient(135deg, var(--white) 60%, var(--grey-400));
+  -webkit-background-clip: text;
+  -webkit-text-fill-color: transparent;
+  background-clip: text;
+}
+.wm-hero .wm-sub {
+  font-size: 0.95rem;
+  color: var(--grey-400);
+  font-weight: 400;
+  letter-spacing: 0.08em;
+  text-transform: uppercase;
+  margin-bottom: 0;
+}
+.wm-hero .wm-accent {
+  display: inline-block;
+  background: var(--lime);
+  color: var(--black);
+  font-weight: 700;
+  font-size: 0.7rem;
+  letter-spacing: 0.15em;
+  text-transform: uppercase;
+  padding: 6px 18px;
+  border-radius: 100px;
+  margin-top: 20px;
+}
+
+/* ─── DIVIDER LINE ─── */
+.wm-divider {
+  height: 1px;
+  background: var(--border);
+  margin: 0 32px;
+}
+
+/* ─── WORKSPACE ─── */
+.wm-workspace {
+  display: grid !important;
+  grid-template-columns: 1fr 1fr;
+  gap: 2px;
+  padding: 0 !important;
+  margin: 0 !important;
+}
+
+.wm-pane {
+  padding: 40px 36px !important;
+  min-height: 480px;
+  display: flex;
+  flex-direction: column;
+  background: transparent !important;
+  border: none !important;
+  border-radius: 0 !important;
+  position: relative;
+}
+
+/* Vertical separator between panes */
+.wm-pane:first-child {
+  border-right: 1px solid var(--border) !important;
+}
+
+.wm-pane-label {
+  font-size: 0.65rem !important;
+  font-weight: 600 !important;
+  letter-spacing: 0.2em !important;
+  text-transform: uppercase !important;
+  color: var(--grey-600) !important;
+  margin-bottom: 24px !important;
+  display: flex;
+  align-items: center;
+  gap: 10px;
+}
+.wm-pane-label .wm-dot {
+  width: 6px;
+  height: 6px;
+  border-radius: 50%;
+  background: var(--lime);
+  box-shadow: 0 0 8px var(--lime);
+}
+.wm-pane-label .wm-dot-cyan {
+  background: #06b6d4;
+  box-shadow: 0 0 8px rgba(6, 182, 212, 0.6);
+}
+
+/* ─── TEXT AREAS ─── */
+.wm-input textarea, .wm-output textarea {
+  background: rgba(255, 255, 255, 0.02) !important;
+  border: 1px solid var(--border) !important;
+  border-radius: 12px !important;
+  color: var(--white) !important;
+  font-family: var(--fn) !important;
+  font-size: 0.95rem !important;
+  line-height: 1.8 !important;
+  padding: 20px 24px !important;
+  resize: none !important;
+  transition: border-color 0.4s var(--ease), box-shadow 0.4s var(--ease) !important;
+}
+.wm-input textarea:focus {
+  border-color: rgba(212, 255, 0, 0.3) !important;
+  box-shadow: 0 0 0 4px var(--lime-glow), inset 0 1px 4px rgba(0,0,0,0.3) !important;
+  outline: none !important;
+}
+.wm-input textarea::placeholder {
+  color: var(--grey-600) !important;
+  font-style: italic;
+}
+
+/* ─── BUTTONS ─── */
+.wm-btn-primary {
+  background: var(--lime) !important;
+  color: var(--black) !important;
+  font-family: var(--fn) !important;
+  font-weight: 700 !important;
+  font-size: 0.75rem !important;
+  letter-spacing: 0.12em !important;
+  text-transform: uppercase !important;
+  border: none !important;
+  border-radius: 100px !important;
+  padding: 16px 40px !important;
+  cursor: pointer !important;
+  transition: transform 0.3s var(--ease), box-shadow 0.3s var(--ease), background 0.3s !important;
+}
+.wm-btn-primary:hover {
+  transform: translateY(-2px) !important;
+  box-shadow: 0 8px 32px rgba(212, 255, 0, 0.25) !important;
+  background: #e0ff33 !important;
+}
+.wm-btn-primary:active {
+  transform: translateY(0) !important;
+}
+
+.wm-btn-ghost {
+  background: transparent !important;
+  color: var(--grey-400) !important;
+  font-family: var(--fn) !important;
+  font-weight: 500 !important;
+  font-size: 0.75rem !important;
+  letter-spacing: 0.1em !important;
+  text-transform: uppercase !important;
+  border: 1px solid var(--border) !important;
+  border-radius: 100px !important;
+  padding: 14px 28px !important;
+  cursor: pointer !important;
+  transition: all 0.3s var(--ease) !important;
+}
+.wm-btn-ghost:hover {
+  border-color: var(--grey-400) !important;
+  color: var(--white) !important;
+}
+
+/* ─── ACTION ROW ─── */
+.wm-actions {
+  display: flex;
+  gap: 12px;
+  margin-top: 20px;
+  align-items: center;
+}
+
+/* ─── TOKEN COUNTER ─── */
+.wm-tokens {
+  font-family: var(--mono) !important;
+  font-size: 0.7rem !important;
+  letter-spacing: 0.05em;
+  margin-top: 12px;
+}
+.wm-tokens-normal { color: var(--grey-600) !important; }
+.wm-tokens-warning {
+  color: #FF6B6B !important;
+  text-shadow: 0 0 12px rgba(255, 107, 107, 0.3);
+}
+
+/* ─── SIDEBAR ─── */
+.wm-sidebar {
+  background: rgba(0, 0, 0, 0.95) !important;
+  border-right: 1px solid var(--border) !important;
+  padding: 32px 24px !important;
+}
+.wm-sidebar h3, .wm-sidebar h4 {
+  font-size: 0.6rem !important;
+  font-weight: 600 !important;
+  letter-spacing: 0.2em !important;
+  text-transform: uppercase !important;
+  color: var(--grey-600) !important;
+  margin-bottom: 16px !important;
+}
+
+/* ─── FILE UPLOAD ─── */
+.wm-upload [data-testid="dropzone"] {
+  border: 1px dashed var(--border) !important;
+  border-radius: 12px !important;
+  background: transparent !important;
+  padding: 24px !important;
+  transition: border-color 0.3s var(--ease) !important;
+}
+.wm-upload [data-testid="dropzone"]:hover {
+  border-color: rgba(212, 255, 0, 0.3) !important;
+}
+
+/* ─── TABS ─── */
+.tabs { border: none !important; }
+button.tab-nav {
+  font-family: var(--fn) !important;
+  font-size: 0.65rem !important;
+  font-weight: 600 !important;
+  letter-spacing: 0.18em !important;
+  text-transform: uppercase !important;
+  color: var(--grey-600) !important;
+  border: none !important;
+  background: transparent !important;
+  padding: 12px 24px !important;
+  transition: color 0.3s !important;
+}
+button.tab-nav.selected {
+  color: var(--white) !important;
+  border-bottom: 2px solid var(--lime) !important;
+}
+button.tab-nav:hover { color: var(--white) !important; }
+
+/* ─── ACCORDION ─── */
+.wm-accordion button {
+  font-family: var(--fn) !important;
+  font-size: 0.65rem !important;
+  letter-spacing: 0.15em !important;
+  text-transform: uppercase !important;
+  color: var(--grey-400) !important;
+  background: transparent !important;
+  border: 1px solid var(--border) !important;
+  border-radius: 8px !important;
+}
+
+/* ─── MODEL INFO ─── */
+.wm-model-info {
+  padding: 20px 0;
+  border-top: 1px solid var(--border);
+  margin-top: 24px;
+}
+.wm-model-info p, .wm-model-info li {
+  font-size: 0.8rem !important;
+  color: var(--grey-400) !important;
+  line-height: 1.7 !important;
+}
+.wm-model-info strong {
+  color: var(--white) !important;
+}
+
+/* ─── BATCH TAB ─── */
+.wm-batch-info {
+  background: rgba(212, 255, 0, 0.04);
+  border: 1px solid rgba(212, 255, 0, 0.1);
+  border-radius: 12px;
+  padding: 20px 24px;
+  font-family: var(--mono);
+  font-size: 0.8rem;
+  line-height: 1.8;
+  color: var(--grey-400);
+  margin: 16px 0 24px;
+}
+.wm-batch-info strong {
+  color: var(--lime);
+  font-weight: 600;
+}
+
+/* ─── SLIDERS ─── */
+input[type="range"] {
+  accent-color: var(--lime) !important;
+}
+
+/* ─── RESPONSIVE ─── */
+@media (max-width: 768px) {
+  .wm-workspace { grid-template-columns: 1fr !important; }
+  .wm-pane:first-child {
+    border-right: none !important;
+    border-bottom: 1px solid var(--border) !important;
+  }
+  .wm-hero h1 { font-size: 2rem !important; }
+}
+"""
+
+
+# ── CLI ───────────────────────────────────────────────────────────────────────
+def parse_args() -> argparse.Namespace:
+    parser = argparse.ArgumentParser(description="Launch the ML summarization UI.")
+    parser.add_argument("--model-path", default=existing_default_checkpoint())
+    parser.add_argument("--fallback-model", default=DEFAULT_APP_FALLBACK_MODEL)
+    parser.add_argument("--max-input-length", type=int, default=DEFAULT_INPUT_MAX_LENGTH)
+    parser.add_argument("--server-name", default="127.0.0.1")
+    parser.add_argument("--server-port", type=int, default=7860)
+    parser.add_argument("--share", action="store_true")
+    return parser.parse_args()
+
+
+def load_model_info(model_path: str) -> str:
+    path = Path(model_path)
+    if not path.exists():
+        return f"**Hub Model** — `{model_path}`"
+    info = f"**Checkpoint** — `{path.name}`\n"
+    metrics_path = path / "metrics" / "test_metrics.json"
+    if metrics_path.exists():
+        try:
+            m = load_json(metrics_path)
+            r1 = m.get("test_rouge1", 0)
+            rl = m.get("test_rougeL", 0)
+            info += f"- ROUGE-1: **{r1:.4f}**\n- ROUGE-L: **{rl:.4f}**\n"
+        except Exception:
+            pass
+    return info
+
+
+def read_file_content(file_obj) -> str:
+    if file_obj is None:
+        return ""
+    file_path = Path(file_obj.name)
+    if file_path.suffix.lower() == ".pdf":
+        if not HAS_PYPDF2:
+            raise gr.Error("PyPDF2 is not installed. Run `pip install pypdf2` for PDF support.")
+        try:
+            with open(file_path, "rb") as f:
+                reader = PyPDF2.PdfReader(f)
+                return "\n".join(page.extract_text() for page in reader.pages)
+        except Exception as e:
+            raise gr.Error(f"Failed to read PDF: {e}")
+    else:
+        try:
+            return file_path.read_text(encoding="utf-8")
+        except Exception as e:
+            raise gr.Error(f"Failed to read file: {e}")
+
+
+# ── Build the UI ──────────────────────────────────────────────────────────────
+def build_demo(
+    model, tokenizer, model_reference: str, max_input_length: int, device: torch.device
+) -> gr.Blocks:
+    default_preset = MODE_PRESETS[DEFAULT_MODE]
+
+    def count_tokens(text: str) -> str:
+        cleaned = normalize_text(text)
+        if not cleaned:
+            return f"<span class='wm-tokens-normal'>{0:03d} / {max_input_length} TOKENS</span>"
+        tokens = tokenizer(cleaned, truncation=False)["input_ids"]
+        count = len(tokens)
+        if count > max_input_length:
+            return (
+                f"<span class='wm-tokens-warning'>⚠ {count:,} / {max_input_length} TOKENS "
+                f"— INPUT WILL BE TRUNCATED</span>"
+            )
+        return f"<span class='wm-tokens-normal'>{count:,} / {max_input_length} TOKENS</span>"
+
+    @torch.inference_mode()
+    def summarize(text, max_new_tokens, min_new_tokens, num_beams, length_penalty):
+        cleaned_text = normalize_text(text)
+        if not cleaned_text:
+            raise gr.Error("Please enter a document to summarize.")
+
+        tokenized = tokenizer(
+            cleaned_text, return_tensors="pt", truncation=True, max_length=max_input_length
+        ).to(device)
+
+        try:
+            generated = model.generate(
+                **tokenized,
+                max_new_tokens=max_new_tokens,
+                min_length=min_new_tokens,
+                num_beams=num_beams,
+                length_penalty=length_penalty,
+                no_repeat_ngram_size=3,
+                early_stopping=True,
+                max_time=45.0,
+            )
+        except torch.cuda.OutOfMemoryError:
+            raise gr.Error(
+                "CUDA Out of Memory. Reduce input length or beam count."
+            )
+        except Exception as e:
+            raise gr.Error(f"Generation failed: {e}")
+
+        return tokenizer.decode(generated[0], skip_special_tokens=True).strip()
+
+    def batch_summarize(file_obj, max_new_tokens, min_new_tokens, num_beams, length_penalty):
+        if file_obj is None:
+            raise gr.Error("Upload a .txt file with one document per line.")
+        try:
+            lines = Path(file_obj.name).read_text(encoding="utf-8").splitlines()
+        except Exception as e:
+            raise gr.Error(f"Failed to read file: {e}")
+
+        results = []
+        for line in lines:
+            if not line.strip():
+                continue
+            summary = summarize(line, max_new_tokens, min_new_tokens, num_beams, length_penalty)
+            results.append({"source": line.strip(), "summary": summary})
+
+        out_path = Path(tempfile.gettempdir()) / "batch_results.csv"
+        with open(out_path, "w", newline="", encoding="utf-8") as f:
+            writer = csv.DictWriter(f, fieldnames=["source", "summary"])
+            writer.writeheader()
+            writer.writerows(results)
+        return str(out_path)
+
+    # ── Theme ─────────────────────────────────────────────────────────────────
+    theme = gr.themes.Base(
+        primary_hue=gr.themes.colors.lime,
+        secondary_hue=gr.themes.colors.cyan,
+        neutral_hue=gr.themes.colors.zinc,
+    ).set(
+        body_background_fill="#000000",
+        block_background_fill="transparent",
+        input_background_fill="rgba(255,255,255,0.02)",
+        body_text_color="#FFFFFF",
+        block_label_text_color="#52525B",
+    )
+
+    with gr.Blocks(title="Prism Studio", theme=theme) as demo:
+
+        # Inject CSS via HTML since Gradio 6 moved css= to launch()
+        gr.HTML(f"<style>{APP_CSS}</style>")
+
+        # ── Hero Header ──────────────────────────────────────────────────────
+        gr.HTML("""
+        <div class="wm-hero">
+            <h1>PRISM<br>STUDIO.</h1>
+            <p class="wm-sub">Neural Text Summarization · Engineered</p>
+            <span class="wm-accent">BART Fine-Tuned on XSum</span>
+        </div>
+        <div class="wm-divider"></div>
+        """)
+
+        # ── Sidebar ──────────────────────────────────────────────────────────
+        with gr.Sidebar(elem_classes=["wm-sidebar"]):
+            gr.HTML("<h3>Control Panel</h3>")
+            mode_selector = gr.Dropdown(
+                choices=list(MODE_PRESETS.keys()),
+                value=DEFAULT_MODE,
+                label="Generation Preset",
+            )
+
+            with gr.Accordion("Advanced Tuning", open=False, elem_classes=["wm-accordion"]):
+                max_new_tokens = gr.Slider(
+                    32, 256, value=default_preset["max_new_tokens"], step=8, label="Max tokens"
+                )
+                min_new_tokens = gr.Slider(
+                    8, 96, value=default_preset["min_new_tokens"], step=4, label="Min tokens"
+                )
+                num_beams = gr.Slider(
+                    1, 8, value=default_preset["num_beams"], step=1, label="Beams"
+                )
+                length_penalty = gr.Slider(
+                    0.6, 2.0, value=default_preset["length_penalty"], step=0.05, label="Length penalty"
+                )
+
+            gr.HTML("<div class='wm-model-info'></div>")
+            gr.HTML("<h4>Active Model</h4>")
+            gr.Markdown(load_model_info(model_reference))
+
+        # ── Tabs ─────────────────────────────────────────────────────────────
+        with gr.Tabs():
+            # ── STUDIO TAB ───────────────────────────────────────────────────
+            with gr.Tab("STUDIO"):
+                with gr.Row(elem_classes=["wm-workspace"]):
+                    # Left — Source
+                    with gr.Column(elem_classes=["wm-pane"]):
+                        gr.HTML("""
+                            <div class="wm-pane-label">
+                                <span class="wm-dot"></span> SOURCE DOCUMENT
+                            </div>
+                        """)
+                        file_upload = gr.File(
+                            label="Upload .txt or .pdf",
+                            file_types=[".txt", ".pdf"],
+                            elem_classes=["wm-upload"],
+                        )
+                        input_text = gr.Textbox(
+                            show_label=False,
+                            placeholder="Paste your document here...",
+                            lines=16,
+                            elem_classes=["wm-input"],
+                        )
+                        token_display = gr.HTML(
+                            f"<div class='wm-tokens'>"
+                            f"<span class='wm-tokens-normal'>000 / {max_input_length} TOKENS</span>"
+                            f"</div>"
+                        )
+                        with gr.Row(elem_classes=["wm-actions"]):
+                            clear_btn = gr.Button("CLEAR", elem_classes=["wm-btn-ghost"])
+                            summarize_btn = gr.Button("SUMMARIZE →", elem_classes=["wm-btn-primary"])
+
+                    # Right — Output
+                    with gr.Column(elem_classes=["wm-pane"]):
+                        gr.HTML("""
+                            <div class="wm-pane-label">
+                                <span class="wm-dot wm-dot-cyan"></span> GENERATED OUTPUT
+                            </div>
+                        """)
+                        output_text = gr.Textbox(
+                            show_label=False,
+                            interactive=False,
+                            lines=20,
+                            elem_classes=["wm-output"],
+                        )
+
+            # ── BATCH TAB ────────────────────────────────────────────────────
+            with gr.Tab("BATCH"):
+                gr.HTML("""
+                    <div class="wm-pane-label" style="padding: 32px 0 8px;">
+                        <span class="wm-dot"></span> BULK INFERENCE
+                    </div>
+                """)
+                gr.HTML("""
+                    <div class="wm-batch-info">
+                        <strong>TEMPLATE FORMAT</strong><br>
+                        Line 1: First document to summarize.<br>
+                        Line 2: Second document to summarize.<br>
+                        Line 3: Third document to summarize.
+                    </div>
+                """)
+                batch_upload = gr.File(
+                    label="Upload batch .txt",
+                    file_types=[".txt"],
+                    elem_classes=["wm-upload"],
+                )
+                batch_btn = gr.Button("RUN BATCH →", elem_classes=["wm-btn-primary"])
+                batch_download = gr.File(label="Download CSV Results", interactive=False)
+
+        # ── Event Wiring ─────────────────────────────────────────────────────
+        def update_params(mode):
+            p = MODE_PRESETS[mode]
+            return p["max_new_tokens"], p["min_new_tokens"], p["num_beams"], p["length_penalty"]
+
+        mode_selector.change(
+            update_params,
+            inputs=[mode_selector],
+            outputs=[max_new_tokens, min_new_tokens, num_beams, length_penalty],
+        )
+        file_upload.change(read_file_content, inputs=[file_upload], outputs=[input_text])
+        input_text.change(count_tokens, inputs=[input_text], outputs=[token_display])
+        summarize_btn.click(
+            summarize,
+            inputs=[input_text, max_new_tokens, min_new_tokens, num_beams, length_penalty],
+            outputs=[output_text],
+        )
+        clear_btn.click(
+            lambda: (
+                None,
+                "",
+                f"<div class='wm-tokens'><span class='wm-tokens-normal'>000 / {max_input_length} TOKENS</span></div>",
+                "",
+            ),
+            inputs=None,
+            outputs=[file_upload, input_text, token_display, output_text],
+        )
+        batch_btn.click(
+            batch_summarize,
+            inputs=[batch_upload, max_new_tokens, min_new_tokens, num_beams, length_penalty],
+            outputs=[batch_download],
+        )
+
+    return demo
+
+
+# ── Entrypoint ────────────────────────────────────────────────────────────────
+def main() -> None:
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
+    )
+    args = parse_args()
+    ensure_project_dirs()
+
+    model_reference = resolve_model_reference(args.model_path, fallback=args.fallback_model)
+    device = default_device()
+
+    LOGGER.info("Loading model from %s", model_reference)
+    tokenizer = load_tokenizer(model_reference)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_reference)
+    if getattr(model.generation_config, "max_length", None) == 20:
+        model.generation_config.max_length = None
+    model.to(device)
+    model.eval()
+
+    demo = build_demo(model, tokenizer, model_reference, args.max_input_length, device)
+    demo.queue().launch(
+        server_name=args.server_name,
+        server_port=args.server_port,
+        share=args.share,
+    )
+
+
+if __name__ == "__main__":
+    main()