"""AI Prof — Gradio app.

Vertical slice #1 + text interjection: upload a lecture PDF, AI Prof reads each
slide as an image (MiniCPM-V) and explains it like a TA (Nemotron, streamed).
Ask a question at any time; it answers using the cached slide reading, then you
continue the walkthrough.
"""

from __future__ import annotations

import io
import html
from pathlib import Path
import threading
import time
import uuid
import wave

import numpy as np
import gradio as gr
from openai import OpenAI

from ai_prof.agent import AgentAction, plan_teaching_beat
from ai_prof.brain import explain_slide
from ai_prof.config import CONFIG
from ai_prof.deck_cache import DeckCache
from ai_prof.pdf_utils import Deck, render_pdf
from ai_prof.vision import read_slide

# ---------------------------------------------------------------------------
# Optional WebRTC real-time voice layer (requires: pip install "fastrtc[vad]")
# When fastrtc is installed, replace the push-to-talk gr.Audio mic below with
# a gr.WebRTC component and wire it through build_rtc_handler — see
# ai_prof/rtc.py for full wiring instructions.
# ---------------------------------------------------------------------------
try:
    from ai_prof.rtc import (
        _has_speech,
        build_rtc_handler as _build_rtc_handler,
        reset_tts_voice,
        tts_speak_full,
    )
    _RTC_AVAILABLE = True
except Exception:
    try:
        from ai_prof.rtc import _has_speech, reset_tts_voice, tts_speak_full
    except Exception:
        tts_speak_full = lambda _text, **_kwargs: None  # type: ignore
        reset_tts_voice = lambda _key: None  # type: ignore
        _has_speech = lambda _audio: True  # type: ignore
    _RTC_AVAILABLE = False

# module-level pre-read cache: {session_id: {slide_idx: reading_str}}
_preread: dict[str, dict[int, str]] = {}
_preread_lock = threading.Lock()
_deck_cache = DeckCache(
    root=CONFIG.deck_cache_dir,
    repo_id=CONFIG.hf_deck_cache_repo,
    token=CONFIG.hf_token,
    write_remote=CONFIG.hf_deck_cache_write,
)


def _prepared_deck_choices() -> list[tuple[str, str]]:
    return [
        (f"{item.title} ({item.slide_count} slides)", item.key)
        for item in _deck_cache.list_decks()
    ]


def _new_state() -> dict:
    return {
        "deck": None,
        "index": 0,
        "readings": {},
        "deck_index": "",
        "whiteboard": [],
        "session_id": str(uuid.uuid4()),
    }


def _ensure_reading(state: dict, idx: int) -> str:
    """Read + cache the slide once; reused by both explanation and Q&A."""
    sid = state["session_id"]
    with _preread_lock:
        if sid in _preread and idx in _preread[sid]:
            result = _preread[sid][idx]
            state["readings"][idx] = result
            return result
    cache = state["readings"]
    if idx not in cache:
        slide = state["deck"].slides[idx]
        prior = cache.get(idx - 1) if idx > 0 else None
        cache[idx] = read_slide(slide.image_path, text_layer=slide.text, prior_reading=prior)
    return cache[idx]


def _build_deck_index(state: dict) -> str:
    deck: Deck | None = state["deck"]
    if not deck:
        return ""
    lines = []
    for idx, slide in enumerate(deck.slides):
        reading = state["readings"].get(idx, "")
        title = _reading_field(reading, "TITLE")
        if not title:
            title = next(
                (line.strip() for line in slide.text.splitlines() if line.strip()),
                f"Slide {idx + 1}",
            )
        concepts = _reading_field(reading, "CONCEPTS")
        summary = concepts or " ".join(slide.text.split())[:220] or "(visual slide)"
        lines.append(f"{idx + 1}. {title} — {summary}")
    return "\n".join(lines)


def _slide_view(state: dict):
    deck: Deck | None = state["deck"]
    if not deck:
        return None, "No deck loaded."
    idx = state["index"]
    slide = deck.slides[idx]
    return slide.image_path, f"Slide {idx + 1} / {len(deck)}"


def _index_choices(state: dict) -> list[tuple[str, int]]:
    deck: Deck | None = state["deck"]
    if not deck:
        return []
    choices = []
    for idx, slide in enumerate(deck.slides):
        reading = state["readings"].get(idx, "")
        title = _reading_field(reading, "TITLE")
        if not title:
            title = next(
                (line.strip() for line in slide.text.splitlines() if line.strip()),
                f"Slide {idx + 1}",
            )
        choices.append((f"{idx + 1}. {title[:90]}", idx))
    return choices


def _reading_field(reading: str, name: str) -> str:
    prefix = f"{name}:"
    for line in reading.splitlines():
        if line.upper().startswith(prefix):
            return line[len(prefix):].strip()
    return ""


def _whiteboard_view(state: dict, reading: str | None = None) -> str:
    deck: Deck | None = state["deck"]
    if not deck:
        return (
            '<div class="whiteboard-empty">'
            "<strong>Professor's whiteboard</strong>"
            "<span>Key ideas and worked notes will appear here.</span>"
            "</div>"
        )
    board = state.get("whiteboard", [])
    if board:
        items = []
        for item in board:
            if item.get("type") == "latex":
                expression = item.get("expression", "").replace("$$", "")
                items.append(
                    '<div class="whiteboard-equation">'
                    f"\n\n$$\n{expression}\n$$\n\n"
                    "</div>"
                )
            else:
                title = html.escape(item.get("title", ""))
                body = html.escape(item.get("body", ""))
                items.append(
                    '<div class="whiteboard-note">'
                    f"<strong>{title}</strong><p>{body}</p>"
                    "</div>"
                )
        return (
            '<div class="whiteboard-sheet">'
            '<div class="whiteboard-kicker">Professor notes</div>'
            + "".join(items)
            + "</div>"
        )

    idx = state["index"]
    reading = reading or state["readings"].get(idx, "")
    title = _reading_field(reading, "TITLE") or f"Slide {idx + 1}"
    concepts = _reading_field(reading, "CONCEPTS")
    if not concepts:
        concepts = "Listening for the central idea..."
    return (
        '<div class="whiteboard-sheet">'
        f'<div class="whiteboard-kicker">Working notes · {idx + 1}/{len(deck)}</div>'
        f"<h3>{html.escape(title)}</h3>"
        f"<p>{html.escape(concepts)}</p>"
        '<div class="whiteboard-line"></div>'
        '<span class="whiteboard-hint">The professor can draw here as the lecture develops.</span>'
        "</div>"
    )


def _execute_actions(
    state: dict,
    actions: tuple[AgentAction, ...],
    *,
    allow_navigation: bool = True,
) -> bool:
    """Apply validated agent actions. Return whether navigation occurred."""
    deck: Deck | None = state["deck"]
    if not deck:
        return False
    navigated = False
    for action in actions:
        if action.tool in {"goto_slide", "next_slide", "prev_slide"} and not allow_navigation:
            continue
        if action.tool == "goto_slide":
            state["index"] = action.args["index"] - 1
            navigated = True
        elif action.tool == "next_slide":
            state["index"] = min(len(deck) - 1, state["index"] + 1)
            navigated = True
        elif action.tool == "prev_slide":
            state["index"] = max(0, state["index"] - 1)
            navigated = True
        elif action.tool == "clear_whiteboard":
            state["whiteboard"] = []
        elif action.tool == "write_note":
            state["whiteboard"].append(
                {
                    "type": "note",
                    "title": action.args.get("title", ""),
                    "body": action.args.get("body", ""),
                }
            )
        elif action.tool == "write_latex":
            state["whiteboard"].append(
                {
                    "type": "latex",
                    "expression": action.args.get("expression", ""),
                }
            )
        state["whiteboard"] = state["whiteboard"][-4:]
    return navigated


# ----------------------------------------------------------------------------- handlers


def on_upload(pdf_file, state):
    old_sid = state.get("session_id")
    state = _new_state()
    sid = state["session_id"]

    if old_sid:
        reset_tts_voice(old_sid)
        with _preread_lock:
            _preread.pop(old_sid, None)

    if pdf_file is None:
        img, caption = _slide_view(state)
        yield state, img, caption, [], _whiteboard_view(state), _STATUS_IDLE, gr.update(choices=[], value=None)
        return

    cache_key = _deck_cache.key(
        pdf_file,
        dpi=CONFIG.slide_dpi,
        vision_model=CONFIG.vision.model,
    )
    cached = _deck_cache.load(cache_key)
    if cached is not None:
        state["deck"] = cached.deck
        state["readings"] = cached.readings
        state["deck_index"] = cached.deck_index or _build_deck_index(state)
        with _preread_lock:
            _preread[sid] = dict(cached.readings)
        img, caption = _slide_view(state)
        yield (
            state,
            img,
            caption,
            [],
            _whiteboard_view(state, state["readings"].get(0, "")),
            _STATUS_CACHE_HIT,
            gr.update(choices=_index_choices(state), value=0),
        )
        return

    deck = render_pdf(pdf_file, dpi=CONFIG.slide_dpi)
    state["deck"] = deck
    img, caption = _slide_view(state)
    yield (
        state,
        img,
        caption,
        [],
        _whiteboard_view(state),
        _status_indexing(0, len(deck)),
        gr.update(choices=_index_choices(state), value=0),
    )

    with _preread_lock:
        _preread[sid] = {}

    for idx, slide in enumerate(deck.slides):
        prior = state["readings"].get(idx - 1) if idx > 0 else None
        reading = read_slide(slide.image_path, text_layer=slide.text, prior_reading=prior)
        state["readings"][idx] = reading
        with _preread_lock:
            _preread[sid][idx] = reading
        yield (
            state,
            img,
            caption,
            [],
            _whiteboard_view(state, reading if idx == 0 else None),
            _status_indexing(idx + 1, len(deck)),
            gr.update(choices=_index_choices(state), value=0),
        )
    state["deck_index"] = _build_deck_index(state)
    _deck_cache.save(
        cache_key,
        deck=deck,
        readings=state["readings"],
        deck_index=state["deck_index"],
        metadata={
            "title": Path(pdf_file).stem,
            "dpi": CONFIG.slide_dpi,
            "vision_model": CONFIG.vision.model,
        },
    )

    img, caption = _slide_view(state)
    yield (
        state,
        img,
        caption,
        [],
        _whiteboard_view(state, state["readings"][0]),
        _STATUS_IDLE,
        gr.update(choices=_index_choices(state), value=0),
    )


def on_load_prepared(cache_key, state):
    old_sid = state.get("session_id")
    state = _new_state()
    sid = state["session_id"]
    if old_sid:
        reset_tts_voice(old_sid)
        with _preread_lock:
            _preread.pop(old_sid, None)

    cached = _deck_cache.load(str(cache_key or ""))
    if cached is None:
        gr.Warning("That prepared lecture could not be loaded.")
        yield (
            state,
            *_slide_view(state),
            [],
            _whiteboard_view(state),
            _STATUS_IDLE,
            gr.update(choices=[], value=None),
        )
        return

    state["deck"] = cached.deck
    state["readings"] = cached.readings
    state["deck_index"] = cached.deck_index or _build_deck_index(state)
    with _preread_lock:
        _preread[sid] = dict(cached.readings)
    yield (
        state,
        *_slide_view(state),
        [],
        _whiteboard_view(state, state["readings"].get(0, "")),
        _STATUS_CACHE_HIT,
        gr.update(choices=_index_choices(state), value=0),
    )


_STATUS_READING = (
    '<div style="background:#f0f9ff;border-left:3px solid #3b82f6;padding:6px 12px;'
    'font-size:0.85rem;color:#1e40af;border-radius:0 4px 4px 0">📖 Reading slide…</div>'
)
_STATUS_EXPLAINING = (
    '<div style="background:#f0fdf4;border-left:3px solid #22c55e;padding:6px 12px;'
    'font-size:0.85rem;color:#166534;border-radius:0 4px 4px 0">💬 Explaining…</div>'
)
_STATUS_SPEAKING = (
    '<div style="background:#fdf4ff;border-left:3px solid #a855f7;padding:6px 12px;'
    'font-size:0.85rem;color:#6b21a8;border-radius:0 4px 4px 0">🔊 Professor speaking…</div>'
)
_STATUS_THINKING = (
    '<div style="background:#fff7ed;border-left:3px solid #f97316;padding:6px 12px;'
    'font-size:0.85rem;color:#9a3412;border-radius:0 4px 4px 0">Thinking…</div>'
)
_STATUS_IDLE = ""
_STATUS_CACHE_HIT = (
    '<div style="background:#ecfdf5;border-left:3px solid #10b981;padding:6px 12px;'
    'font-size:0.85rem;color:#065f46;border-radius:0 4px 4px 0">'
    "Loaded pre-indexed lecture from cache"
    "</div>"
)


def _status_indexing(done: int, total: int) -> str:
    return (
        '<div style="background:#f5f3ff;border-left:3px solid #625ce7;padding:6px 12px;'
        'font-size:0.85rem;color:#4c46a8;border-radius:0 4px 4px 0">'
        f"Indexing lecture… {done} / {total} slides"
        "</div>"
    )


def on_explain(state, chat):
    deck: Deck | None = state["deck"]
    if not deck:
        gr.Warning("Upload a lecture PDF first.")
        yield chat, _STATUS_IDLE, None
        return
    idx = state["index"]
    yield chat, _STATUS_READING, None
    reading = _ensure_reading(state, idx)
    yield chat, _STATUS_EXPLAINING, None
    chat = chat + [{"role": "assistant", "content": ""}]
    acc = ""
    for tok in explain_slide(
        reading,
        slide_no=idx + 1,
        total=len(deck),
        outline=deck.outline(),
        history=chat,
    ):
        acc += tok
        chat[-1]["content"] = acc
        yield chat, _STATUS_EXPLAINING, None
    audio = tts_speak_full(acc, voice_key=state["session_id"])
    if audio is not None:
        yield chat, _STATUS_SPEAKING, gr.update(value=audio, visible=True)
        time.sleep(len(audio[1]) / audio[0])
    yield chat, _STATUS_IDLE, gr.update(value=None, visible=False)


def on_teach_deck(state, chat):
    """Run professor-planned teaching beats with navigation, board tools, and TTS."""
    deck: Deck | None = state["deck"]
    if not deck:
        gr.Warning("Upload a lecture PDF first.")
        img, caption = _slide_view(state)
        yield state, img, caption, chat, _STATUS_IDLE, _whiteboard_view(state), None
        return

    max_beats = max(1, len(deck) * 2)
    for _ in range(max_beats):
        idx = state["index"]
        img, caption = _slide_view(state)
        yield state, img, caption, chat, _STATUS_READING, _whiteboard_view(state), None

        reading = _ensure_reading(state, idx)
        beat = plan_teaching_beat(
            trigger="continue",
            deck_index=state["deck_index"],
            current_slide=idx + 1,
            total_slides=len(deck),
            current_reading=reading,
            whiteboard_state=state["whiteboard"],
            history=chat,
        )
        _execute_actions(state, beat.actions, allow_navigation=False)
        img, caption = _slide_view(state)
        board = _whiteboard_view(state)
        chat = chat + [{"role": "assistant", "content": beat.narration}]
        yield state, img, caption, chat, _STATUS_EXPLAINING, board, None

        audio = tts_speak_full(beat.narration, voice_key=state["session_id"])
        if audio is not None:
            sr, pcm = audio
            yield state, img, caption, chat, _STATUS_SPEAKING, board, gr.update(value=audio, visible=True)
            time.sleep(len(pcm) / sr)

        if not beat.continue_lecture:
            break
        if state["index"] >= len(deck) - 1:
            break
        state["index"] += 1

    yield state, *_slide_view(state), chat, _STATUS_IDLE, _whiteboard_view(state), gr.update(value=None, visible=False)


def on_ask(question, state, chat):
    deck: Deck | None = state["deck"]
    if not deck:
        gr.Warning("Upload a lecture PDF first.")
        yield state, *_slide_view(state), chat, "", _whiteboard_view(state), None, ""
        return
    question = (question or "").strip()
    if not question:
        yield state, *_slide_view(state), chat, "", _whiteboard_view(state), None, ""
        return
    idx = state["index"]
    reading = _ensure_reading(state, idx)
    history = chat + [{"role": "user", "content": question}]
    img, caption = _slide_view(state)
    yield (
        state,
        img,
        caption,
        history,
        _STATUS_THINKING,
        _whiteboard_view(state),
        None,
        "",
    )
    beat = plan_teaching_beat(
        trigger="question",
        deck_index=state["deck_index"],
        current_slide=idx + 1,
        total_slides=len(deck),
        current_reading=reading,
        whiteboard_state=state["whiteboard"],
        history=history,
        question=question,
    )
    _execute_actions(state, beat.actions)
    chat = history + [{"role": "assistant", "content": beat.narration}]
    img, caption = _slide_view(state)
    board = _whiteboard_view(state)
    yield state, img, caption, chat, _STATUS_EXPLAINING, board, None, ""
    audio = tts_speak_full(beat.narration, voice_key=state["session_id"])
    if audio is not None:
        sr, pcm = audio
        yield state, img, caption, chat, _STATUS_SPEAKING, board, gr.update(value=audio, visible=True), ""
        time.sleep(len(pcm) / sr)
    yield state, img, caption, chat, _STATUS_IDLE, board, gr.update(value=None, visible=False), ""


def on_nav(delta, state):
    deck: Deck | None = state["deck"]
    if deck:
        state["index"] = max(0, min(len(deck) - 1, state["index"] + delta))
    img, caption = _slide_view(state)
    return state, img, caption, _whiteboard_view(state), state["index"] if deck else None


def on_index_select(index, state):
    deck: Deck | None = state["deck"]
    if deck and index is not None:
        state["index"] = max(0, min(len(deck) - 1, int(index)))
    img, caption = _slide_view(state)
    return state, img, caption, _whiteboard_view(state)


def on_transcribe(audio):
    if audio is None:
        return ""
    if not CONFIG.stt.is_live:
        return "[voice input]"
    sr, data = audio
    if data is None or len(data) == 0:
        return ""
    if not _has_speech(data):
        return ""
    buf = io.BytesIO()
    if data.dtype != np.int16:
        data = (data * 32767).astype(np.int16)
    if data.ndim > 1:
        data = data[:, 0]
    with wave.open(buf, "wb") as wf:
        wf.setnchannels(1)
        wf.setsampwidth(2)
        wf.setframerate(sr)
        wf.writeframes(data.tobytes())
    buf.seek(0)
    buf.name = "audio.wav"
    client = OpenAI(base_url=CONFIG.stt.openai_base_url, api_key=CONFIG.stt.api_key)
    transcript = client.audio.transcriptions.create(model=CONFIG.stt.model, file=buf)
    return transcript.text


# ----------------------------------------------------------------------------- UI

_BANNER = (
    "⚠️ Running in **mock mode** — set `VISION_BASE_URL` / `BRAIN_BASE_URL` (see `.env.example`) "
    "to plug in real MiniCPM-V + Nemotron."
    if CONFIG.fully_mocked
    else None
)

_CSS = """
.gradio-container {
    --app-text: #24283b;
    --app-muted: #667085;
    --app-card: #ffffff;
    --app-border: #e1e5eb;
    --app-panel-title: #ecebff;
    --app-panel-title-border: #dedcff;
    --app-accent-text: #5b55c7;
    --app-slide-bg: #f8f9fb;
    --app-nav-bg: #f7f6ff;
    --app-nav-border: #d8d6ff;
}
.dark .gradio-container {
    --app-text: #f2f4f7;
    --app-muted: #a7b0c0;
    --app-card: #171923;
    --app-border: #303442;
    --app-panel-title: #24213d;
    --app-panel-title-border: #3a3560;
    --app-accent-text: #c6c2ff;
    --app-slide-bg: #10121a;
    --app-nav-bg: #27243f;
    --app-nav-border: #4b4678;
}
.gradio-container {
    max-width: 1320px !important;
    margin: 0 auto !important;
    padding-inline: 24px !important;
}
.app-title {
    max-width: 1280px;
    margin: 0 auto 18px;
    padding: 4px 2px 8px;
}
.app-title h1 {
    margin: 0 0 4px !important;
    color: var(--app-text);
    font-size: 2.15rem !important;
    font-weight: 800 !important;
    letter-spacing: -.035em;
}
.app-title p {
    margin: 0 !important;
    color: var(--app-muted);
    font-size: 1rem;
}
.workspace-row {
    width: 100%;
    max-width: 1280px;
    margin-inline: auto;
    align-items: stretch !important;
}
.panel-card {
    min-width: 0 !important;
    overflow: hidden;
    gap: 0 !important;
    border: 1px solid var(--app-border);
    border-radius: 14px;
    background: var(--app-card);
}
.panel-title {
    flex: 0 0 46px !important;
    min-height: 46px !important;
    height: 46px !important;
    display: flex !important;
    align-items: center !important;
    margin: 0 !important;
    padding: 0 14px !important;
    background: var(--app-panel-title);
    border-bottom: 1px solid var(--app-panel-title-border);
    color: var(--app-accent-text);
}
.panel-title p {
    margin: 0 !important;
    font-size: .86rem;
    font-weight: 700;
    line-height: 1.35;
}
.panel-body {
    padding: 12px !important;
}
.teaching-panel { min-height: 655px; }
.slide-frame {
    flex: 0 0 550px !important;
    height: 550px !important;
    min-height: 550px !important;
    border: 0 !important;
    border-radius: 0 !important;
}
.slide-frame img {
    height: 550px !important;
    object-fit: contain !important;
    background: var(--app-slide-bg);
}
.slide-footer {
    padding: 0 12px 12px !important;
}
.slide-caption {
    min-height: 24px;
    margin: 0 !important;
    color: var(--app-muted);
}
.slide-index {
    margin: 2px 0 8px !important;
}
.slide-controls {
    gap: 10px !important;
}
.slide-controls button {
    min-height: 42px !important;
    border-radius: 10px !important;
    font-weight: 700 !important;
}
.nav-button button {
    color: var(--app-accent-text) !important;
    border: 1px solid var(--app-nav-border) !important;
    background: var(--app-nav-bg) !important;
}
.nav-button button:hover {
    border-color: #7770ef !important;
    background: color-mix(in srgb, var(--app-nav-bg) 82%, #625ce7) !important;
}
.explain-button button {
    color: #fff !important;
    border-color: #625ce7 !important;
    background: #625ce7 !important;
    box-shadow: 0 5px 14px rgb(98 92 231 / 20%) !important;
}
.whiteboard {
    flex: 1 1 auto !important;
    min-height: 550px;
    border: 0;
    border-radius: 0;
    overflow: hidden;
    background:
        linear-gradient(#e8edf3 1px, transparent 1px),
        linear-gradient(90deg, #e8edf3 1px, transparent 1px),
        #fbfcfe;
    background-size: 28px 28px;
}
.whiteboard-empty, .whiteboard-sheet {
    min-height: 550px;
    padding: 28px 32px;
    color: #172033;
}
.whiteboard-empty {
    display: flex;
    flex-direction: column;
    align-items: center;
    justify-content: center;
    gap: 8px;
    color: #667085;
}
.whiteboard-sheet h3 { font-size: 1.8rem; margin: 24px 0 18px; }
.whiteboard-sheet p { font-size: 1.2rem; line-height: 1.7; max-width: 90%; }
.whiteboard-note {
    margin-top: 22px;
    padding: 16px 18px;
    border-left: 4px solid #625ce7;
    border-radius: 0 10px 10px 0;
    background: rgb(255 255 255 / 82%);
}
.whiteboard-note strong { font-size: 1.08rem; }
.whiteboard-note p { margin: 6px 0 0; font-size: 1rem; line-height: 1.55; }
.whiteboard-equation {
    margin-top: 22px;
    padding: 18px;
    border-radius: 10px;
    background: rgb(255 255 255 / 86%);
    text-align: center;
}
.whiteboard-equation code {
    color: #24283b;
    font-size: 1.15rem;
    white-space: normal;
}
.whiteboard-kicker {
    color: #3157a4;
    font-size: .78rem;
    font-weight: 700;
    letter-spacing: .08em;
    text-transform: uppercase;
}
.whiteboard-line { width: 72px; height: 4px; margin: 30px 0 14px; background: #f4b740; }
.whiteboard-hint { color: #7a8496; font-size: .82rem; }
.bottom-panel {
    min-height: 382px;
}
.transcript-panel {
    flex: 1 1 auto !important;
    height: 334px !important;
    min-height: 334px !important;
    border: 0 !important;
    border-radius: 0 !important;
}
.transcript-panel .placeholder {
    height: 100% !important;
    display: flex !important;
    align-items: center !important;
    justify-content: center !important;
    padding: 24px !important;
    color: #8a94a6 !important;
    text-align: center !important;
}
.question-body, .upload-body {
    flex: 1 1 auto !important;
    min-height: 334px;
    padding: 18px !important;
}
.question-body {
    display: flex !important;
    flex-direction: column !important;
    gap: 12px !important;
}
.question-row {
    align-items: stretch !important;
    gap: 10px !important;
}
.question-input textarea {
    min-height: 58px !important;
}
.question-input {
    flex: 1 1 auto !important;
}
.ask-button {
    min-width: 96px !important;
    max-width: 110px !important;
}
.ask-button button {
    height: 100% !important;
    min-height: 58px !important;
    font-weight: 750 !important;
}
.mic-label {
    margin: 2px 0 -4px !important;
    color: var(--app-muted);
    font-size: .82rem;
    font-weight: 650;
}
.mic-control {
    min-height: 108px !important;
    max-height: 122px !important;
    overflow: hidden !important;
}
.mic-control button[aria-label="Record"],
.mic-control button.record {
    min-width: 150px !important;
    min-height: 58px !important;
    border-radius: 999px !important;
    color: #fff !important;
    background: #625ce7 !important;
    border-color: #625ce7 !important;
    font-size: 1rem !important;
    font-weight: 750 !important;
}
.teach-button {
    margin-top: auto !important;
}
.upload-body {
    display: flex !important;
    flex-direction: column !important;
    gap: 12px !important;
}
.upload-control {
    min-height: 210px !important;
}
.upload-copy {
    margin: 0 !important;
    color: var(--app-muted);
    font-size: .88rem;
}
.dark .panel-card input,
.dark .panel-card textarea,
.dark .panel-card select {
    color-scheme: dark;
}
.dark .status-strip > div[style] {
    filter: brightness(.72) saturate(.9);
    color: #f3f4f6 !important;
}
@media (max-width: 900px) {
    .gradio-container { padding-inline: 12px !important; }
    .teaching-panel, .bottom-panel { min-width: 100% !important; }
}
"""

with gr.Blocks(title="AI Prof", theme=gr.themes.Soft(), css=_CSS) as demo:
    state = gr.State(_new_state())

    gr.Markdown(
        "# AI Prof\nA live, guided walkthrough of your lecture.",
        elem_classes=["app-title"],
    )
    if _BANNER:
        gr.Markdown(_BANNER)

    with gr.Row(equal_height=True, elem_classes=["workspace-row"]):
        with gr.Column(scale=1, elem_classes=["panel-card", "teaching-panel"]):
            gr.Markdown("Lecture slides", elem_classes=["panel-title"])
            slide_img = gr.Image(
                show_label=False,
                height=470,
                elem_classes=["slide-frame"],
            )
            with gr.Column(elem_classes=["slide-footer"]):
                caption = gr.Markdown("No deck loaded.", elem_classes=["slide-caption"])
                slide_index = gr.Dropdown(
                    label="Lecture index",
                    choices=[],
                    value=None,
                    interactive=True,
                    elem_classes=["slide-index"],
                )
                with gr.Row(elem_classes=["slide-controls"]):
                    prev_btn = gr.Button("Previous", elem_classes=["nav-button"])
                    explain_btn = gr.Button(
                        "Explain slide",
                        variant="primary",
                        elem_classes=["explain-button"],
                    )
                    next_btn = gr.Button("Next", elem_classes=["nav-button"])

        with gr.Column(scale=1, elem_classes=["panel-card", "teaching-panel"]):
            gr.Markdown("Whiteboard", elem_classes=["panel-title"])
            whiteboard = gr.Markdown(
                value=_whiteboard_view(_new_state()),
                elem_classes=["whiteboard"],
            )

    with gr.Row(equal_height=True, elem_classes=["workspace-row"]):
        with gr.Column(scale=5, elem_classes=["panel-card", "bottom-panel"]):
            gr.Markdown("Lecture transcript", elem_classes=["panel-title"])
            status_strip = gr.HTML(value=_STATUS_IDLE, elem_classes=["status-strip"])
            prof_audio = gr.Audio(
                autoplay=True,
                show_label=False,
                visible=False,  # hidden; plays automatically via autoplay
                interactive=False,
            )
            chat = gr.Chatbot(
                show_label=False,
                height=320,
                type="messages",
                layout="panel",
                placeholder=(
                    "Upload a lecture to begin. The professor's explanation "
                    "will appear here as it is spoken."
                ),
                elem_classes=["transcript-panel"],
            )

        with gr.Column(scale=3, elem_classes=["panel-card", "bottom-panel"]):
            gr.Markdown("Ask a question", elem_classes=["panel-title"])
            with gr.Column(elem_classes=["question-body"]):
                with gr.Row(equal_height=True, elem_classes=["question-row"]):
                    question = gr.Textbox(
                        placeholder="Type a question...",
                        show_label=False,
                        lines=1,
                        elem_classes=["question-input"],
                        scale=5,
                    )
                    ask_btn = gr.Button(
                        "Ask",
                        variant="primary",
                        elem_classes=["ask-button"],
                        scale=1,
                    )
                gr.Markdown("Or ask out loud", elem_classes=["mic-label"])
                mic = gr.Audio(
                    sources=["microphone"],
                    type="numpy",
                    streaming=False,
                    show_label=False,
                    elem_classes=["mic-control"],
                )
                teach_btn = gr.Button(
                    "Teach from current slide",
                    variant="secondary",
                    elem_classes=["teach-button"],
                )
            # TODO: wire fastrtc when installed — replace `mic` above with:
            #
            #   if _RTC_AVAILABLE:
            #       _rtc_handler = _build_rtc_handler(state_getter=lambda: state.value)
            #       webrtc = gr.WebRTC(
            #           label="Live voice (real-time)",
            #           rtc_configuration=_rtc_handler.rtc_configuration,
            #           mode="send-receive",
            #       )
            #       webrtc.stream(
            #           _rtc_handler,
            #           inputs=[webrtc, state],
            #           outputs=[webrtc],
            #           time_limit=120,
            #       )
            #
            # See ai_prof/rtc.py for the full pipeline:
            #   student mic → STT (/v1/audio/transcriptions)
            #               → brain.answer_question (streamed text)
            #               → TTS (/v1/audio/speech, PCM chunks)
            #               → student speaker (sub-second latency)

        with gr.Column(scale=2, elem_classes=["panel-card", "bottom-panel"]):
            gr.Markdown("Choose a lecture", elem_classes=["panel-title"])
            with gr.Column(elem_classes=["upload-body"]):
                prepared_deck = gr.Dropdown(
                    label="Prepared lectures",
                    choices=_prepared_deck_choices(),
                    value=None,
                    interactive=True,
                )
                load_prepared_btn = gr.Button(
                    "Load prepared lecture",
                    variant="primary",
                )
                gr.Markdown("Or upload your own PDF", elem_classes=["mic-label"])
                pdf = gr.File(
                    label="Drop a PDF to begin",
                    file_types=[".pdf"],
                    type="filepath",
                    height=130,
                    elem_classes=["upload-control"],
                )
                gr.Markdown(
                    "The professor starts at slide 1 and advances automatically. "
                    "Use the slide controls to revisit anything.",
                    elem_classes=["upload-copy"],
                )

    lecture_outputs = [state, slide_img, caption, chat, status_strip, whiteboard, prof_audio]
    question_outputs = [
        state,
        slide_img,
        caption,
        chat,
        status_strip,
        whiteboard,
        prof_audio,
        question,
    ]
    upload_event = pdf.change(
        on_upload,
        [pdf, state],
        [state, slide_img, caption, chat, whiteboard, status_strip, slide_index],
    ).then(
        on_teach_deck,
        [state, chat],
        lecture_outputs,
    )
    prepared_event = load_prepared_btn.click(
        on_load_prepared,
        [prepared_deck, state],
        [state, slide_img, caption, chat, whiteboard, status_strip, slide_index],
    ).then(
        on_teach_deck,
        [state, chat],
        lecture_outputs,
    )

    explain_event = explain_btn.click(
        on_explain,
        [state, chat],
        [chat, status_strip, prof_audio],
    )
    teach_event = teach_btn.click(on_teach_deck, [state, chat], lecture_outputs)
    question.submit(
        on_ask,
        [question, state, chat],
        question_outputs,
        cancels=[upload_event, prepared_event, explain_event, teach_event],
    )
    ask_btn.click(
        on_ask,
        [question, state, chat],
        question_outputs,
        cancels=[upload_event, prepared_event, explain_event, teach_event],
    )
    prev_btn.click(
        on_nav,
        [gr.State(-1), state],
        [state, slide_img, caption, whiteboard, slide_index],
    )
    next_btn.click(
        on_nav,
        [gr.State(1), state],
        [state, slide_img, caption, whiteboard, slide_index],
    )
    slide_index.change(
        on_index_select,
        [slide_index, state],
        [state, slide_img, caption, whiteboard],
    )
    mic.stop_recording(on_transcribe, inputs=[mic], outputs=[question])


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