import gradio as gr
import spaces
from transformers import pipeline
import fitz  # PyMuPDF for PDF reading

# -------------------------------
# Models
# -------------------------------
text_detector = pipeline("text-classification", model="roberta-base-openai-detector")
image_analyzer = pipeline("image-classification", model="microsoft/resnet-50")
asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device=-1)

# -------------------------------
# Oracle Main Function
# -------------------------------
@spaces.GPU
def oracle_prophecy(user_text, user_img, user_audio, user_pdf):
    prophecy = ""

    # Text
    if user_text and user_text.strip():
        result = text_detector(user_text)
        label = result[0]["label"]
        score = round(result[0]["score"] * 100, 2)
        prophecy += (
            f"📜 **Text Prophecy:** {score}% AI‑generated 🤖✨\n\n"
            if label.lower() == "fake"
            else f"📜 **Text Prophecy:** {score}% Human‑written 🧑‍💻\n\n"
        )

    # Image
    if user_img is not None:
        result = image_analyzer(user_img)
        label = result[0]["label"]
        score = round(result[0]["score"] * 100, 2)
        prophecy += f"🖼️ **Image Prophecy:** {score}% match with {label} 🌠\n\n"

    # Audio
    if user_audio is not None:
        transcript = asr_pipe(user_audio)["text"]
        result = text_detector(transcript)
        label = result[0]["label"]
        score = round(result[0]["score"] * 100, 2)
        prophecy += (
            f"🔊 Transcript: *{transcript}*\n🌌 Prophecy: {score}% AI‑generated 🤖✨\n\n"
            if label.lower() == "fake"
            else f"🔊 Transcript: *{transcript}*\n☀️ Prophecy: {score}% Human‑spoken 🧑‍💻\n\n"
        )

    # PDF
    if user_pdf is not None:
        doc = fitz.open(user_pdf)
        text = "".join([page.get_text() for page in doc])
        if text.strip():
            result = text_detector(text[:800])
            label = result[0]["label"]
            score = round(result[0]["score"] * 100, 2)
            prophecy += (
                f"📑 **PDF Prophecy:** {score}% AI‑generated 🤖✨\n\n"
                if label.lower() == "fake"
                else f"📑 **PDF Prophecy:** {score}% Human‑authored 🧑‍💻\n\n"
            )
        else:
            prophecy += "📑 PDF: ⚠️ No readable text found.\n\n"

    if prophecy.strip() == "":
        prophecy = "⚠️ Please provide text, an image, a voice file, or a PDF."

    return prophecy

# -------------------------------
# Gradio UI (Aligned Card Style like Beat‑Break)
# -------------------------------
with gr.Blocks(css="""
/* Background and Base */
body {
  background: linear-gradient(135deg, #667eea, #764ba2);
  font-family: 'Trebuchet MS', sans-serif;
  margin: 0;
  padding: 0;
  color: #fff;
  text-align: center;
}

/* Container to center, shrink width */
.container {
  max-width: 900px;
  margin: 0 auto;
  padding: 20px;
}

/* Title + Subtitle */
#title {
  font-size: 3em !important;
  color: #FFD700 !important;
  text-shadow: 2px 2px 8px #000;
  margin-bottom: 10px;
}
#subtitle {
  font-size: 1.5em !important;
  color: #E0FFFF !important;
  margin-bottom: 30px;
}

/* Inputs */
label {
  font-size: 1.2em !important;
  color: #fff !important;
}
textarea, input, .gr-textbox {
  font-size: 1.2em !important;
}
audio, .gr-file, .gr-image {
  margin-bottom: 20px;
}

/* Button */
button {
  font-size: 1.3em !important;
  padding: 12px 28px !important;
  border-radius: 12px !important;
  background: linear-gradient(90deg, #ff8a00, #e52e71) !important;
  color: #fff !important;
  font-weight: bold !important;
  border: none !important;
  margin-top: 20px;
}
button:hover {
  opacity: 0.9;
  box-shadow: 0 0 20px #FFD700;
}

/* Result Box */
.result-box {
  background: #fff;
  border-radius: 20px;
  padding: 25px;
  margin: 30px auto;
  font-size: 1.4em;
  color: #222;
  box-shadow: 0px 6px 20px rgba(0,0,0,0.4);
  text-align: left;
  white-space: pre-line;
}
""") as demo:

    with gr.Column(elem_classes="container"):
        gr.HTML("<div id='title'>🔮 Oracle of Truth 🔮</div>")
        gr.HTML("<div id='subtitle'>✨ Offer Text · Image · Voice File · PDF ✨</div>")

        txt_in = gr.Textbox(lines=4, label="📜 Text Offering")
        img_in = gr.Image(type="filepath", label="🖼️ Image Offering")
        # VOICE: file upload only
        aud_in = gr.File(file_types=[".wav", ".mp3"], label="🔊 Voice File Offering")
        pdf_in = gr.File(file_types=[".pdf"], label="📑 PDF Offering")

        btn = gr.Button("✨ Reveal Prophecy")
        output = gr.HTML(elem_classes="result-box")

        btn.click(oracle_prophecy, [txt_in, img_in, aud_in, pdf_in], output)

demo.launch()