"""
app.py — Maai's interface.

A minimal Gradio skin over the proven pipeline:
paste a symptom description in any language -> see the advocacy
record -> download the clinician-ready PDF.
Function today; theming (palette, Fraunces/Inter) is weekend work.
"""

import gradio as gr
from chain import build_record
from make_pdf import make_pdf
from speak import speak_record
from socrates import annotate_socrates
from contribute import make_contribution, save_contribution
from aggregate import aggregate


def run_maai(description: str):
    """Full pipeline: description -> record -> PDF. Returns display text + PDF path."""
    if not description or not description.strip():
        return "Please describe what you've been experiencing.", None, None

    record = build_record(description)

    lines = [
        f"Language detected: {record['language_detected']}",
        "",
        "HER WORDS  →  CLINICAL TERMS",
        "",
    ]
    for item in record["items"]:
        lines.append(f'"{item["verbatim"]}"')
        lines.append(f"    →  {item['clinical']}")
        lines.append("")

    annotated = annotate_socrates(record)
    lines.append("")
    lines.append("CLINICAL FRAMEWORK (SOCRATES)")
    lines.append("")
    for item in annotated["items"]:
        if item["dimensions"]:
            lines.append(f'"{item["verbatim"]}" — {", ".join(item["dimensions"])}')
    lines.append("")
    lines.append("Not yet described — your doctor may ask about:")
    for dim in annotated["not_yet_described"]:
        lines.append(f"  · {dim}")
    pdf_path = make_pdf(record, annotated)
    return "\n".join(lines), pdf_path, record

css = """
@import url('https://fonts.googleapis.com/css2?family=Fraunces:opsz,wght@9..144,400;9..144,600&display=swap');

.gradio-container {
    background-color: #F7F4EF !important;
    max-width: 780px !important;
    margin: 0 auto !important;
}

#header { text-align: center; }
#header h1 {
    font-family: 'Fraunces', serif !important;
    font-size: 3.2em !important;
    font-weight: 600 !important;
    color: #2B2A26 !important;
    margin-bottom: 0.1em !important;
}

.block, .form, textarea, input {
    border-radius: 12px !important;
    border-color: #DCCFBC !important;
}

button.primary {
    font-family: 'Fraunces', serif !important;
    font-size: 1.1em !important;
}
"""

theme = gr.themes.Soft(
    primary_hue=gr.themes.Color(
        c50="#F7F4EF", c100="#EFE9DF", c200="#DCCFBC", c300="#C6B29A",
        c400="#A98F73", c500="#8C7355", c600="#7A6349", c700="#65523C",
        c800="#514230", c900="#3D3124", c950="#2B2A26",
    ),
    neutral_hue="stone",
    font=gr.themes.GoogleFont("Inter"),
    font_mono=gr.themes.GoogleFont("Inter"),
)

with gr.Blocks(title="Maai", theme=theme, css=css) as demo:
    gr.Markdown(
        "# Maai\n"
        "*See what time reveals.*\n\n"
        "**The AI health advocate for endometriosis**",
        elem_id="header",
    )

    gr.Markdown(
        "Maai means the meaningful interval between things — the space where "
        "health patterns emerge.\n\n"
        "Endometriosis takes an average of **9 years and 4 months** to diagnose "
        "in the UK — and 11 years for women from ethnically diverse communities. "
        "83% of women were told by a healthcare practitioner they were making "
        "a fuss about nothing. Almost half visited their GP ten or more times "
        "before anyone joined the dots.\n\n"
        "Maai helps you be harder to dismiss. Describe what you've been "
        "experiencing over recent weeks or months, in your own words, in any "
        "language. Maai maps your words to clinical terms a doctor recognises — "
        "never replacing them, never drawing conclusions. Bring a record to "
        "every appointment; the pattern builds. The clinician interprets. "
        "Maai helps you be heard.\n\n"
        "**Maai is for patterns over time, not a medical emergency. If you have "
        "severe or sudden symptoms right now, call 111 — or 999 if it's urgent.**"
    )
    

    description = gr.Textbox(
        label="In your own words",
        placeholder="e.g. For months I've had a deep dragging pain low in my belly, not just during my period, and I'm exhausted all the time...",
        lines=5,
    )
    submit = gr.Button("Prepare my record")

    record_display = gr.Textbox(label="Your advocacy record", lines=14)
    pdf_file = gr.File(label="Download for your appointment")

    record_state = gr.State()
    listen = gr.Button("Hear my record read aloud")
    audio_out = gr.Audio(label="Your record, read back", type="filepath")

    submit.click(fn=run_maai, inputs=description,
                 outputs=[record_display, pdf_file, record_state])

    def read_aloud(record):
        if not record:
            raise gr.Error("Prepare a record first, then listen.")
        return speak_record(record)

    listen.click(fn=read_aloud, inputs=record_state, outputs=audio_out)

    gr.Markdown("---")
    gr.Markdown("### Contribute to what women are revealing")
    consent = gr.Checkbox(
        label=(
            "Contribute your pattern (anonymous) — adds your symptom pattern, "
            "never your words, name, or any identifying detail, to a shared "
            "dataset of women's heart-health experiences."
        ),
        value=False,
    )
    age_band = gr.Dropdown(
        choices=["not_given", "25-34", "35-44", "45-54", "55-64", "65-74", "75+"],
        value="not_given",
        label="Age band (optional)",
    )
    contribute_btn = gr.Button("Contribute my pattern")
    feedback = gr.Markdown()

    def contribute(record, consented, band):
        if not record:
            raise gr.Error("Prepare a record first.")
        if not consented:
            raise gr.Error("Tick the consent box if you'd like to contribute — it's entirely optional.")
        total = save_contribution(make_contribution(record, age_band=band))
        view = aggregate()
        top = next(iter(view["symptom_prevalence"]))
        return (
            f"**Your pattern joins {total - 1} others.** Together they're showing "
            f"how often *{top}* appears in women's patterns — years before "
            f"diagnosis. Thank you for helping make it visible."
        )

    contribute_btn.click(fn=contribute, inputs=[record_state, consent, age_band], outputs=feedback)

    gr.Markdown("---")
    gr.Markdown("### What women are revealing")
    gr.Markdown(
        "*Seeded with representative synthetic data to show what the aggregate "
        "view reveals at scale. Descriptive only — Maai counts and reveals, "
        "never predicts.*"
    )

    def render_aggregate():
        view = aggregate()
        if view["total"] == 0:
            return "No contributions yet."
        lines = [f"**{view['total']} contributed patterns**\n"]
        lines.append("| Symptom | Appears in |")
        lines.append("|---|---|")
        for symptom, pct in view["symptom_prevalence"].items():
            lines.append(f"| {symptom} | {pct}% |")
        langs = ", ".join(view["languages"].keys())
        lines.append(f"\nContributed in **{len(view['languages'])} languages**: {langs}")
        return "\n".join(lines)

    aggregate_display = gr.Markdown(render_aggregate())
    refresh = gr.Button("Refresh the collective picture")
    refresh.click(fn=render_aggregate, outputs=aggregate_display)

if __name__ == "__main__":
    demo.launch(ssr_mode=False)