Update app.py

app.py

@@ -1,147 +1,147 @@
 import gradio as gr
 import spaces
 from transformers import pipeline
-import fitz  # PyMuPDF for PDF reading
+import fitz  # PyMuPDF for PDF
 
 # -------------------------------
-# Load Models
+# Models
 # -------------------------------
-# Text AI detector
 text_detector = pipeline("text-classification", model="roberta-base-openai-detector")
-
-# Image classifier (placeholder for "AI detection", but works publicly)
 image_analyzer = pipeline("image-classification", model="microsoft/resnet-50")
-
-# Whisper tiny for audio transcription
 asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device=-1)
 
 # -------------------------------
-# Oracle Function
+# Main Oracle Function
 # -------------------------------
 @spaces.GPU
 def oracle_prophecy(user_text, user_img, user_audio, user_pdf):
-
     prophecy = ""
 
-    # TEXT check
+    # Text check
     if user_text and user_text.strip():
         result = text_detector(user_text)
         label = result[0]['label']
         score = round(result[0]['score'] * 100, 2)
-        if label.lower() == "fake":
-            prophecy += f"📜 Text: 🌌 **Prophecy:** {score}% AI‑generated 🤖✨\n\n"
-        else:
-            prophecy += f"📜 Text: ☀️ **Prophecy:** {score}% Human‑written 🧑‍💻\n\n"
+        prophecy += (
+            f"📜 **Text Prophecy:** {score}% AI‑generated 🤖✨\n\n"
+            if label.lower() == "fake"
+            else f"📜 **Text Prophecy:** {score}% Human‑written 🧑‍💻\n\n"
+        )
 
-    # IMAGE check
+    # Image check
     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: Oracle’s Sight → {score}% match with **{label}** 🌠\n\n"
+        prophecy += f"🖼️ **Image Prophecy:** {score}% match with {label} 🌠\n\n"
 
-    # AUDIO check
+    # Audio check
     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)
-        if label.lower() == "fake":
-            prophecy += f"🔊 Voice transcript: *{transcript}* — 🌌 {score}% AI‑generated 🤖\n\n"
-        else:
-            prophecy += f"🔊 Voice transcript: *{transcript}* — ☀️ {score}% Human‑spoken 🧑‍💻\n\n"
+        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 check
     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])  # only analyze first 800 chars
+            result = text_detector(text[:800])
             label = result[0]['label']
             score = round(result[0]['score'] * 100, 2)
-            if label.lower() == "fake":
-                prophecy += f"📑 PDF: 🌌 Prophecy: {score}% AI‑generated 🤖\n\n"
-            else:
-                prophecy += f"📑 PDF: ☀️ Prophecy: {score}% Human‑authored 🧑‍💻\n\n"
+            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"
+            prophecy += "📑 No readable text in PDF.\n\n"
 
     if prophecy.strip() == "":
-        prophecy = "⚠️ Please provide text, image, audio, or PDF for the Oracle."
+        prophecy = "⚠️ Please provide text, image, voice, or PDF to the Oracle."
 
-    return f"<div class='result-box'>{prophecy}</div>"
+    return prophecy
 
 # -------------------------------
-# Gradio UI (Theme like Awesome‑Pet‑Talk)
+# UI Inspired by Beat‑Break
 # -------------------------------
 with gr.Blocks(css="""
-/* Background Gradient */
+/* Background */
 body {
-  background: linear-gradient(135deg, #fbc2eb, #a6c1ee);
+  background: linear-gradient(135deg, #667eea, #764ba2);
   font-family: 'Trebuchet MS', sans-serif;
-  color: #2c003e;
+  color: #fff !important;
   text-align: center;
+  margin: 0;
+  padding: 0;
 }
 
-/* Title + subtitle */
+/* Title */
 #title {
   font-size: 3em !important;
-  color: #ff0080;
-  text-shadow: 2px 2px 8px #00000055;
-  margin-top: 20px;
+  color: #FFD700 !important;
+  text-shadow: 2px 2px 8px #000 !important;
+  margin: 20px 0;
 }
+
+/* Subtitle */
 #subtitle {
-  font-size: 1.4em !important;
-  color: #4b0082;
-  margin-bottom: 20px;
+  font-size: 1.5em !important;
+  color: #E0FFFF !important;
+  margin-bottom: 30px;
 }
 
-/* Bigger inputs */
+/* Input labels + fields */
+label {
+  font-size: 1.3em !important;
+  color: #fff !important;
+}
 textarea, input, .gr-textbox {
   font-size: 1.2em !important;
 }
 
-/* Results Box */
+/* Big button style */
+button {
+  font-size: 1.4em !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;
+}
+
+/* Result Box */
 .result-box {
-  background: rgba(255,255,255,0.95);
-  border-radius: 20px;
-  padding: 20px;
-  margin-top: 25px;
-  font-size: 1.4em;
-  color: #222;
-  box-shadow: 0px 4px 15px rgba(0,0,0,0.3);
-  text-align: left;
-  white-space: pre-line;
+  background: rgba(255, 255, 255, 0.95) !important;
+  border-radius: 20px !important;
+  padding: 30px !important;
+  margin-top: 30px !important;
+  font-size: 1.5em !important;
+  color: #222 !important;
+  box-shadow: 0px 4px 20px rgba(0,0,0,0.4) !important;
+  text-align: left !important;
+  white-space: pre-line !important;
 }
 """) as demo:
 
-    # Title
     gr.HTML("<div id='title'>🔮 Oracle of Truth 🔮</div>")
-    gr.HTML("<div id='subtitle'>✨ Offer your text, image, voice, or PDF — receive the Oracle's prophecy ✨</div>")
-
-    gr.Markdown("""
-👋 Welcome, Seeker!  
-
-Place your offerings before the Oracle:  
-- 📜 Paste *text* (essay, blog, email, story)  
-- 🖼️ Upload an *image*  
-- 🔊 Speak with your *voice*  
-- 📑 Upload a *PDF*  
-
-Then click **Reveal Prophecy ✨** and watch the Oracle’s vision unfold.  
-""")
+    gr.HTML("<div id='subtitle'>✨ Offer Text · Image · Voice · PDF to Reveal the Prophecy ✨</div>")
 
-    with gr.Row():
-        with gr.Column():
-            txt_in = gr.Textbox(lines=6, label="📝 Text Offering")
-            img_in = gr.Image(type="filepath", label="🖼️ Image Offering")
-            aud_in = gr.Audio(sources=["microphone"], type="filepath", label="🎤 Voice Offering")
-            pdf_in = gr.File(file_types=[".pdf"], label="📄 PDF Offering")
-            btn = gr.Button("✨ Reveal Prophecy", variant="primary")
+    txt_in = gr.Textbox(lines=4, label="📜 Text Offering")
+    img_in = gr.Image(type="filepath", label="🖼️ Image Offering")
+    aud_in = gr.Audio(sources=["microphone"], type="filepath", label="🔊 Voice Offering")
+    pdf_in = gr.File(file_types=[".pdf"], label="📑 PDF Offering")
 
-        with gr.Column():
-            result = gr.HTML(label="Oracle's Prophecy")
+    btn = gr.Button("✨ Reveal Prophecy")
+    output = gr.HTML(elem_classes="result-box")
 
-    btn.click(oracle_prophecy, inputs=[txt_in, img_in, aud_in, pdf_in], outputs=result)
+    btn.click(oracle_prophecy, [txt_in, img_in, aud_in, pdf_in], output)
 
 demo.launch()