"""
Character Studio — a ZeroGPU Hugging Face Space.

A multi-model character generator: pick a model from an editable registry,
type a prompt, optionally drop a reference image, and generate. Supports
SD1.5 / SDXL / FLUX bases and txt2img / img2img / IP-Adapter / FaceID modes.

Add or remove models by editing models.json (no code change needed), then
click "🔄 Reload models" or restart the Space.
"""

import random
import traceback

import spaces  # must be imported before torch on ZeroGPU
import gradio as gr

# --- Workaround for a gradio_client bug: "argument of type 'bool' is not iterable".
# Some component api_info schemas carry a boolean `additionalProperties`, which the
# schema-to-type walker chokes on, crashing get_api_info() and the whole launch.
# Short-circuit any non-dict schema to "Any". Version-independent and harmless. ---
import gradio_client.utils as _gcu

_orig_get_type = _gcu.get_type
def _safe_get_type(schema):
    if not isinstance(schema, dict):
        return "Any"
    return _orig_get_type(schema)
_gcu.get_type = _safe_get_type

_orig_j2pt = _gcu._json_schema_to_python_type
def _safe_j2pt(schema, *args, **kwargs):
    if isinstance(schema, bool):
        return "Any"
    return _orig_j2pt(schema, *args, **kwargs)
_gcu._json_schema_to_python_type = _safe_j2pt

import pipeline_manager as pm

MAX_SEED = 2**31 - 1


# ---------------------------------------------------------------------------
# Registry helpers
# ---------------------------------------------------------------------------
def load_models():
    return pm.load_registry()


MODELS = load_models()


def model_choices(models):
    return [(m["label"], m["id"]) for m in models]


# Placeholder shown in the picker when a model has no `preview` image.
_FALLBACK_PREVIEW = "https://placehold.co/400x520/1e293b/93c5fd/png?text=Model"


def gallery_items(models):
    """List of (image_url, caption) for the model picker gallery."""
    return [(m.get("preview") or _FALLBACK_PREVIEW, m["label"]) for m in models]


def model_ids(models):
    return [m["id"] for m in models]


def modes_for(models, model_id):
    m = pm.get_model(models, model_id)
    if not m:
        return [("Text → Image", "txt2img")]
    return [(pm.MODE_LABELS[k], k) for k in pm.SUPPORTED_MODES[m["base"]]]


# ---------------------------------------------------------------------------
# GPU generation
# ---------------------------------------------------------------------------
@spaces.GPU(duration=120)
def generate(model_id, mode, prompt, negative_prompt, ref_image,
             steps, guidance, denoise, ip_scale, width, height, seed, randomize,
             translator):
    models = load_models()
    cfg = pm.get_model(models, model_id)
    if cfg is None:
        raise gr.Error("ไม่พบโมเดลที่เลือก โปรด Reload models / Selected model not found.")

    if randomize or seed is None or int(seed) < 0:
        seed = random.randint(0, MAX_SEED)

    # Thai → English so the (English) text encoders understand the prompt.
    note = ""
    orig_prompt = prompt
    prompt = pm.translate_prompt(prompt, translator)
    negative_prompt = pm.translate_prompt(negative_prompt, translator)

    # --- Post-translation fixes (the translator often drops/softens these) ---
    # 1) Full-body framing: detect intent from the ORIGINAL Thai (translator tends to
    #    drop "เต็มตัว/ทั้งตัว"); inject an explicit English tag up front so the model AND
    #    the auto-tall-canvas logic in run_generation reliably honor it.
    if pm.wants_full_body(orig_prompt) or pm.wants_full_body(prompt):
        if "full body" not in prompt.lower():
            prompt = "full body shot, head to toe, full body visible, " + prompt
    # 2) Gaze: SD1.5 obeys the booru tag "looking at viewer" far better than "...camera".
    if "looking at the camera" in prompt.lower() or "looking at camera" in prompt.lower():
        prompt = (prompt.replace("looking at the camera", "looking at viewer, eye contact")
                        .replace("looking at camera", "looking at viewer, eye contact"))
    elif "มองกล้อง" in (orig_prompt or "") and "looking at viewer" not in prompt.lower():
        prompt = "looking at viewer, eye contact, " + prompt

    if prompt != orig_prompt:
        note = f"  ·  🌐 {translator}: _{prompt[:120]}_"

    try:
        img = pm.run_generation(
            cfg=cfg, mode=mode, prompt=prompt, negative_prompt=negative_prompt,
            ref_image=ref_image, steps=steps, guidance=guidance, denoise=denoise,
            ip_scale=ip_scale, width=width, height=height, seed=seed,
        )
    except Exception as e:
        traceback.print_exc()
        raise gr.Error(str(e))

    status = f"✅ {cfg['label']} · {pm.MODE_LABELS.get(mode, mode)} · seed {seed}{note}"
    return img, seed, status


# ---------------------------------------------------------------------------
# UI callbacks
# ---------------------------------------------------------------------------
def _apply_model(models, model_id):
    """Shared: given a selected model id, return the dependent UI updates."""
    cfg = pm.get_model(models, model_id)
    if not cfg:
        return (*[gr.update() for _ in range(7)], "ไม่พบโมเดล / model not found")
    choices = modes_for(models, model_id)
    return (
        gr.update(choices=choices, value=choices[0][1]),           # mode radio
        gr.update(placeholder=cfg.get("recommended_prompt", "")),  # prompt
        gr.update(value=cfg.get("negative_prompt", "")),           # negative
        gr.update(value=cfg.get("default_steps", 28)),             # steps
        gr.update(value=cfg.get("default_guidance", 6.0)),         # guidance
        gr.update(value=cfg.get("default_width", 768)),            # width
        gr.update(value=cfg.get("default_height", 768)),           # height
        f"**เลือก / Selected:** {cfg['label']}",                   # selected label
    )


def on_gallery_select(ids, evt: gr.SelectData):
    """A model card was clicked. evt.index → model id."""
    models = load_models()
    mid = ids[evt.index] if ids and 0 <= evt.index < len(ids) else None
    return (mid, *_apply_model(models, mid))


def reload_registry():
    global MODELS
    MODELS = load_models()
    first = MODELS[0]["id"] if MODELS else None
    return (
        gr.update(value=gallery_items(MODELS)),   # gallery
        model_ids(MODELS),                         # ids state
        first,                                     # selected id state
        f"🔄 โหลดแล้ว {len(MODELS)} โมเดล",
    )


def _field(v):
    """Normalise a Prompt Builder field to a clean string. Dropdowns with
    multiselect return a list — join those; plain Textboxes return a string."""
    if isinstance(v, (list, tuple)):
        return ", ".join(str(x).strip() for x in v if x and str(x).strip())
    return str(v).strip() if v is not None else ""


def build_prompt(subject, age, ethnicity, skin, face, body, hair, eyes, outfit, pose,
                 expression, scene, lighting, shot):
    """Assemble form fields into a prompt. Thai values are fine — the auto-translator
    turns the whole thing into English at generate time. Dropdown fields already carry
    model-friendly English tags (e.g. 'hourglass figure')."""
    parts = []
    # Framing/shot goes FIRST so "full body / head to toe" survives CLIP's 77-token cut
    # (it's the key compositional cue; if truncated, SD1.5 defaults to a portrait crop).
    shot = _field(shot)
    if shot:
        parts.append(shot)
    who = _field(subject) or "ผู้หญิง"
    ethnicity, age = _field(ethnicity), _field(age)
    if ethnicity:
        who = f"{ethnicity} {who}"
    if age:
        who = f"{who} อายุ {age} ปี"
    parts.append(who)
    # Priority order for CLIP's 77-token budget: compositional anchors first
    # (location/lighting/outfit/pose), fine appearance details last (least harmful
    # if truncated). Skin texture realism is carried by the model's style_prefix anyway.
    for v in (scene, lighting, outfit, pose, expression, body, hair, skin, face, eyes):
        s = _field(v)
        if s:
            parts.append(s)
    thai = ", ".join(parts)
    # Photographic suffix (NOT "masterpiece/best quality" — those art tokens push the model
    # toward an illustrated/CG look. The model's style_prefix + negative do the heavy lifting).
    return thai + ", realistic candid photograph, natural skin texture, soft natural light"


# ---------------------------------------------------------------------------
# Layout (mirrors the FLUX LoRA DLC reference UI)
# ---------------------------------------------------------------------------
CSS = """
#gen-btn {height: 100%; font-size: 1.3rem; font-weight: 700;}
.card {border-radius: 14px;}
footer {visibility: hidden;}
"""

with gr.Blocks(css=CSS, theme=gr.themes.Soft(primary_hue="blue"),
               title="Character Studio") as demo:
    gr.Markdown("## 🎭 Character Studio — multi-model character generator (ZeroGPU)")

    with gr.Row():
        prompt = gr.Textbox(
            label="Edit Prompt", lines=2, scale=4,
            placeholder="✦ เลือกโมเดลแล้วพิมพ์ prompt / Choose a model and type the prompt",
        )
        gen_btn = gr.Button("Generate", variant="primary", scale=1, elem_id="gen-btn")

    # ---- Prompt Builder: fill blanks instead of writing sentences ----
    with gr.Accordion("📝 ตัวช่วยสร้าง prompt / Prompt Builder — กรอกช่อง ไม่ต้องเขียนประโยค",
                      open=False):
        gr.Markdown("กรอกเฉพาะช่องที่ต้องการ (เป็นภาษาไทยได้) แล้วกดปุ่มด้านล่าง "
                    "ระบบจะประกอบเป็น prompt ให้ในช่องด้านบน · เว้นว่างช่องที่ไม่ใช้ได้")
        with gr.Row():
            b_subject = gr.Textbox(label="ใคร / ตัวละคร", value="ผู้หญิง")
            b_age = gr.Textbox(label="อายุ", placeholder="เช่น 25")
            b_ethnicity = gr.Textbox(label="เชื้อชาติ / สัญชาติ", placeholder="เช่น เกาหลี, ไทย")
        with gr.Row():
            b_body = gr.Dropdown(
                label="รูปร่าง / สัดส่วน (เลือกได้หลายอัน · พิมพ์เองได้)",
                choices=[
                    ("ผอมเพรียว / slim", "slim, slender figure"),
                    ("ตัวเล็กบอบบาง / petite", "petite, small frame"),
                    ("ทรงนาฬิกาทราย / hourglass", "hourglass figure, narrow waist"),
                    ("อวบอั๋นเว้าโค้ง / curvy", "curvy, voluptuous"),
                    ("ฟิตมีกล้าม / athletic", "athletic, toned, fit body"),
                    ("อึ๋มอกใหญ่ / busty", "busty, large breasts"),
                    ("ท้วมอวบ / chubby", "chubby, plump"),
                    ("สูงขายาวทรงนางแบบ / tall model", "tall, long legs, model body"),
                    ("สะโพกผาย / wide hips", "wide hips"),
                    ("ต้นขาหนา / thick thighs", "thick thighs"),
                    ("เอวเล็ก / slim waist", "slim waist"),
                    ("อกเล็ก / small breasts", "small breasts"),
                    ("ทรงผู้ใหญ่ / mature", "mature body"),
                ],
                value=None, multiselect=True, allow_custom_value=True)
            b_hair = gr.Textbox(label="ทรงผม / สีผม", placeholder="เช่น ผมยาวสีดำ, ผมบลอนด์")
            b_eyes = gr.Textbox(label="สีตา", placeholder="เช่น ตาสีน้ำตาล")
        with gr.Row():
            b_skin = gr.Textbox(label="สีผิว", placeholder="เช่น ผิวขาว, ผิวสองสี, ผิวแทนทอง, ผิวเนียน")
            b_face = gr.Textbox(label="โครงหน้า", placeholder="เช่น หน้าเรียว, หน้ารูปไข่, หน้ากลม, คางแหลม")
        with gr.Row():
            b_outfit = gr.Textbox(label="ชุด / เสื้อผ้า", placeholder="เช่น เดรสสีขาว, ชุดนักเรียน")
            b_pose = gr.Dropdown(
                label="ท่าโพส (เลือกผสมได้ · พิมพ์เองได้)",
                choices=[
                    ("ยืนตรง / standing", "standing"),
                    ("ยืนมือเท้าเอว / hands on hips", "standing, hands on hips"),
                    ("ยืนเอียงสะโพก / contrapposto", "standing, contrapposto pose"),
                    ("ยืนพิงกำแพง / leaning on wall", "leaning against wall"),
                    ("นั่งเก้าอี้ / sitting (chair)", "sitting on chair"),
                    ("นั่งพื้น / sitting (floor)", "sitting on floor"),
                    ("นั่งไขว่ห้าง / crossed legs", "sitting, crossed legs"),
                    ("นั่งชันเข่า / knees up", "sitting, knees up, hugging knees"),
                    ("คุกเข่า / kneeling", "kneeling"),
                    ("นอนหงาย / lying on back", "lying on back"),
                    ("นอนคว่ำ / on stomach", "lying on stomach"),
                    ("นอนตะแคง / on side", "lying on side"),
                    ("เดิน / walking", "walking"),
                    ("วิ่ง / running", "running"),
                    ("มือรวบผม / hand in hair", "hand in own hair, arm up"),
                    ("กอดอก / arms crossed", "crossed arms"),
                    ("โบกมือ / waving", "waving hand"),
                ],
                value=None, multiselect=True, allow_custom_value=True)
            b_expr = gr.Textbox(label="สีหน้า / อารมณ์", placeholder="เช่น ยิ้มอ่อนๆ")
        with gr.Row():
            b_scene = gr.Textbox(label="สถานที่ / ฉาก", placeholder="เช่น คาเฟ่, ริมทะเล, ในสวน")
            b_light = gr.Textbox(label="แสง", placeholder="เช่น แสงเช้านุ่มๆ, แสงสตูดิโอ")
            b_shot = gr.Dropdown(
                label="มุมกล้อง / ช็อต (เลือกได้หลายอัน · พิมพ์เองได้)",
                choices=[
                    ("โคลสอัพใบหน้า / close-up", "close-up portrait, face focus, headshot"),
                    ("ครึ่งตัวบน / upper body", "upper body shot, bust"),
                    ("ครึ่งตัว เอวขึ้นไป / half body", "half body shot, waist up"),
                    ("เต็มตัว หัวถึงเท้า / full body", "full body shot, head to toe, full body visible"),
                    ("ระยะไกล เห็นรอบตัว / wide shot", "wide shot, full body, distant, environmental"),
                    ("มุมเงย / low angle", "from below, low angle shot"),
                    ("มุมก้ม / high angle", "from above, high angle shot"),
                    ("มุมข้าง โปรไฟล์ / side", "from side, profile view"),
                    ("มุมหลัง / from behind", "from behind, back view"),
                    ("เซลฟี่ / selfie", "selfie, pov, arm extended"),
                ],
                value=None, multiselect=True, allow_custom_value=True)
        build_btn = gr.Button("✨ สร้าง prompt → ใส่ในช่องด้านบน", variant="secondary")

    # State: ordered list of model ids (matches gallery order) + current selection.
    ids_state = gr.State(model_ids(MODELS))
    selected_id = gr.State(MODELS[0]["id"] if MODELS else None)

    with gr.Row(equal_height=False):
        # ---- left: model picker ----
        with gr.Column(scale=1):
            with gr.Group():
                gr.Markdown("### 🧩 เลือกโมเดล / Models")
                model_gallery = gr.Gallery(
                    value=gallery_items(MODELS),
                    label=None, show_label=False, columns=2, height="auto",
                    object_fit="cover", allow_preview=False, container=False,
                    elem_classes="card",
                )
                selected_md = gr.Markdown(
                    f"**เลือก / Selected:** {MODELS[0]['label']}" if MODELS else ""
                )
                reload_btn = gr.Button("🔄 Reload models", size="sm")
                reload_status = gr.Markdown("")

            mode_radio = gr.Radio(
                choices=modes_for(MODELS, MODELS[0]["id"]) if MODELS else [],
                value="txt2img",
                label="โหมดรูปต้นแบบ / Input mode",
            )

            translator = gr.Radio(
                choices=[("ปิด / Off", "off"),
                         ("NLLB-200 (เร็ว)", "nllb"),
                         ("Typhoon 2 (ไทยแน่น)", "typhoon")],
                value="typhoon",
                label="แปลไทย→อังกฤษ / Auto-translate (พิมพ์ไทยได้เลย)",
            )

        # ---- right: output ----
        with gr.Column(scale=1):
            output = gr.Image(label="Generated Image", height=560, elem_classes="card")
            status = gr.Markdown("")

    # ---- advanced ----
    with gr.Accordion("Advanced Settings", open=False):
        with gr.Row():
            with gr.Column():
                ref_image = gr.Image(label="Input image (รูปต้นแบบ)", type="pil", height=240)
                ip_scale = gr.Slider(0.0, 1.5, value=0.7, step=0.05,
                                     label="Reference strength (IP-Adapter / FaceID)")
                denoise = gr.Slider(0.1, 1.0, value=0.65, step=0.01,
                                    label="Denoise strength (img2img · ต่ำ = อิงรูปมาก)")
            with gr.Column():
                negative_prompt = gr.Textbox(label="Negative prompt", lines=2)
                with gr.Row():
                    steps = gr.Slider(1, 50, value=28, step=1, label="Steps")
                    guidance = gr.Slider(0.0, 15.0, value=6.5, step=0.1, label="Guidance (CFG)")
                with gr.Row():
                    width = gr.Slider(384, 1280, value=512, step=64, label="Width")
                    height = gr.Slider(384, 1280, value=768, step=64, label="Height")
                with gr.Row():
                    seed = gr.Number(value=-1, label="Seed (-1 = random)", precision=0)
                    randomize = gr.Checkbox(value=True, label="Randomize seed")

    # ---- wiring ----
    model_gallery.select(
        on_gallery_select, inputs=[ids_state],
        outputs=[selected_id, mode_radio, prompt, negative_prompt,
                 steps, guidance, width, height, selected_md],
    )
    reload_btn.click(
        reload_registry,
        outputs=[model_gallery, ids_state, selected_id, reload_status],
    )
    build_btn.click(
        build_prompt,
        inputs=[b_subject, b_age, b_ethnicity, b_skin, b_face, b_body, b_hair, b_eyes,
                b_outfit, b_pose, b_expr, b_scene, b_light, b_shot],
        outputs=prompt,
    )

    gen_inputs = [selected_id, mode_radio, prompt, negative_prompt, ref_image,
                  steps, guidance, denoise, ip_scale, width, height, seed, randomize,
                  translator]
    gen_btn.click(generate, inputs=gen_inputs, outputs=[output, seed, status])
    prompt.submit(generate, inputs=gen_inputs, outputs=[output, seed, status])


if __name__ == "__main__":
    # allowed_paths lets Gradio serve the local model preview thumbnails.
    demo.queue(max_size=12).launch(allowed_paths=["previews"])