app.py

"""
🎭 Story DNA Analyzer — app.py
================================
Gradio web UI — deploy directly to HuggingFace Spaces.
Run locally:  python app.py
"""

import gradio as gr
import json
from model import StoryDNAAnalyzer, StoryDNA

# Load model once at startup
analyzer = StoryDNAAnalyzer()

GRADIO_MAJOR = int(gr.__version__.split(".", 1)[0])
APP_THEME = gr.themes.Soft(primary_hue="purple", neutral_hue="slate")
APP_CSS = """
    .title { text-align: center; }
    .subtitle { text-align: center; color: #888; }
    footer { display: none !important; }
"""

EXAMPLES = [
    ["A young orphan discovers he is a wizard and is accepted into a magical school, "
     "where he makes lifelong friends, faces a dark wizard who killed his parents, "
     "and learns that love is the most powerful magic of all."],

    ["Detective Sarah Lund receives a call at 2 AM. A senator's daughter is missing. "
     "As she digs deeper, the trail leads to the highest levels of government. "
     "Everyone is lying. The killer is someone she trusts."],

    ["In 2157, humanity's last colony ship drifts through space after Earth's destruction. "
     "When the AI pilot starts making strange decisions, engineer Mara must choose between "
     "following orders and saving 4,000 sleeping passengers from a fate worse than death."],

    ["Two rival bakers in a small Italian village have hated each other for forty years. "
     "When their grandchildren fall in love, old secrets surface — and so do feelings "
     "they buried long ago. The village holds its breath."],

    ["The kingdom was built on a lie. When seventeen-year-old Asha uncovers the truth "
     "beneath the palace — that the king sacrifices a child every decade to maintain power — "
     "she must decide how far she will go to burn it all down."],
]


def format_results(dna: StoryDNA) -> tuple:
    """Convert StoryDNA into nicely formatted Gradio outputs."""

    def bar(score: float) -> str:
        filled = int(score * 10)
        return "█" * filled + "░" * (10 - filled)

    # ── Genre ──
    genre_md = "### 📚 Genre\n"
    for label, score in sorted(dna.genre.items(), key=lambda x: -x[1])[:4]:
        genre_md += f"`{bar(score)}` **{score:.0%}** — {label}\n\n"

    # ── Tropes ──
    tropes_md = "### 🧬 Top Narrative Tropes\n"
    for t in dna.top_tropes[:5]:
        tropes_md += f"`{bar(t['score'])}` **{t['score']:.0%}** — {t['label']}\n\n"

    # ── Mood ──
    mood_md = "### 🎨 Story Mood\n"
    for label, score in sorted(dna.mood.items(), key=lambda x: -x[1])[:3]:
        mood_md += f"`{bar(score)}` **{score:.0%}** — {label}\n\n"

    # ── Audience ──
    audience_md = "### 👥 Target Audience\n"
    for label, score in sorted(dna.audience.items(), key=lambda x: -x[1])[:3]:
        audience_md += f"`{bar(score)}` **{score:.0%}** — {label}\n\n"

    # ── Villain ──
    villain_md = "### 😈 Villain Archetype\n"
    for label, score in sorted(dna.villain.items(), key=lambda x: -x[1])[:3]:
        villain_md += f"`{bar(score)}` **{score:.0%}** — {label}\n\n"

    # ── Ending prediction ──
    ending_md = "### 🔮 Predicted Ending\n"
    for label, score in sorted(dna.predicted_ending.items(), key=lambda x: -x[1]):
        ending_md += f"`{bar(score)}` **{score:.0%}** — {label}\n\n"

    return genre_md, tropes_md, mood_md, audience_md, villain_md, ending_md


def analyze(text: str):
    if not text or len(text.strip()) < 20:
        empty = "*Please enter a story description (at least 20 characters).*"
        return empty, empty, empty, empty, empty, empty

    try:
        dna = analyzer.analyze(text)
        return format_results(dna)
    except Exception as e:
        err = f"❌ Error: {str(e)}"
        return err, err, err, err, err, err


# ──────────────────────────────────────────
# GRADIO UI
# ──────────────────────────────────────────

blocks_kwargs = {"title": "🎭 Story DNA Analyzer"}
if GRADIO_MAJOR < 6:
    blocks_kwargs.update(theme=APP_THEME, css=APP_CSS)

with gr.Blocks(**blocks_kwargs) as demo:

    gr.Markdown(
        "# 🎭 Story DNA Analyzer\n"
        "### Paste any story snippet, book blurb, or movie description — get its full narrative DNA.\n"
        "*Powered by HuggingFace zero-shot NLI · No training required*",
        elem_classes=["title"]
    )

    with gr.Row():
        with gr.Column(scale=2):
            text_input = gr.Textbox(
                label="📖 Story Text",
                placeholder="Paste any story, book blurb, movie synopsis, or description here...",
                lines=7,
                max_lines=20,
            )
            analyze_btn = gr.Button("🔬 Analyze Story DNA", variant="primary", size="lg")
            gr.Examples(examples=EXAMPLES, inputs=text_input, label="📝 Try these examples")

        with gr.Column(scale=3):
            with gr.Row():
                genre_out   = gr.Markdown(label="Genre")
                tropes_out  = gr.Markdown(label="Tropes")
            with gr.Row():
                mood_out    = gr.Markdown(label="Mood")
                audience_out= gr.Markdown(label="Audience")
            with gr.Row():
                villain_out = gr.Markdown(label="Villain")
                ending_out  = gr.Markdown(label="Ending")

    analyze_btn.click(
        fn=analyze,
        inputs=text_input,
        outputs=[genre_out, tropes_out, mood_out, audience_out, villain_out, ending_out],
    )

    gr.Markdown(
        "---\n"
        "**Model:** `cross-encoder/nli-MiniLM2-L6-H768` via zero-shot classification  \n"
        "**No fine-tuning needed** — works on any story in any language."
    )

if __name__ == "__main__":
    launch_kwargs = {"share": False}
    if GRADIO_MAJOR >= 6:
        launch_kwargs.update(theme=APP_THEME, css=APP_CSS)
    demo.launch(**launch_kwargs)