Update app.py

app.py

@@ -1,102 +1,161 @@
 import gradio as gr
 import spaces
 from transformers import pipeline
+import fitz  # PyMuPDF for PDF extraction
 
 # -------------------------------
-# Load Text AI Detector
+# Load Models
 # -------------------------------
+# Text detector (public)
 text_detector = pipeline("text-classification", model="roberta-base-openai-detector")
 
+# Image classifier (public baseline, since AI-specific detectors are often gated)
+image_analyzer = pipeline("image-classification", model="microsoft/resnet-50")
+
+# Whisper tiny for audio → text transcription
+asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device=-1)
+
 # -------------------------------
-# Oracle Function
+# Oracle Functions
 # -------------------------------
+
 @spaces.GPU
 def oracle_text(user_text: str):
     if not user_text or not user_text.strip():
-        return "🧞 Please provide some text for the Oracle to examine."
-    
+        return "⚠️ Please provide some text for the Oracle."
     result = text_detector(user_text)
     label = result[0]['label']
     score = round(result[0]['score'] * 100, 2)
+    if label.lower() == "fake":
+        return f"🌌 **Prophecy:** {score}% chance this was **conjured by AI sorcery** 🤖✨"
+    else:
+        return f"☀️ **Prophecy:** {score}% chance this was **crafted by a mortal hand** 🧑‍💻"
+
+@spaces.GPU
+def oracle_image(user_img):
+    if user_img is None:
+        return "⚠️ Please upload an image!"
+    result = image_analyzer(user_img)
+    label = result[0]['label']
+    score = round(result[0]['score'] * 100, 2)
+    return f"🌠 **Oracle’s Gaze:** {score}% resemblance to *{label}*.\n(Note: Image prophecy = experimental 🌌)"
 
+@spaces.GPU
+def oracle_audio(audio_file):
+    if audio_file is None:
+        return "⚠️ Please record your voice."
+    transcript = asr_pipe(audio_file)["text"]
+    result = text_detector(transcript)
+    label = result[0]['label']
+    score = round(result[0]['score'] * 100, 2)
     if label.lower() == "fake":
-        verdict = f"🌌 **Prophecy:** {score}% chance this was **conjured by AI sorcery** 🤖✨"
+        verdict = f"🔊 Transcript: *{transcript}*\n\n🌌 Prophecy: {score}% AI-generated."
     else:
-        verdict = f"☀️ **Prophecy:** {score}% chance this was **crafted by a mortal hand** 🧑‍💻"
-    
+        verdict = f"🔊 Transcript: *{transcript}*\n\n☀️ Prophecy: {score}% Human-written."
     return verdict
 
+@spaces.GPU
+def oracle_pdf(pdf_file):
+    if pdf_file is None:
+        return "⚠️ Please upload a PDF."
+    doc = fitz.open(pdf_file)
+    text = ""
+    for page in doc:
+        text += page.get_text()
+    if not text.strip():
+        return "⚠️ Could not extract text from PDF."
+    # Detect
+    result = text_detector(text[:800])  # limit chars for speed
+    label = result[0]['label']
+    score = round(result[0]['score'] * 100, 2)
+    if label.lower() == "fake":
+        return f"📑 PDF Analysis: {score}% chance this was made by AI 🤖"
+    else:
+        return f"📑 PDF Analysis: {score}% chance this was human-authored 🧑‍💻"
+
 # -------------------------------
 # Gradio Immersive UI
 # -------------------------------
 with gr.Blocks(css="""
 body {
-    background: linear-gradient(135deg, #0f2027, #2c5364);
+    background: linear-gradient(135deg, #ff9a9e, #fad0c4, #a18cd1, #fbc2eb);
     font-family: 'Trebuchet MS', sans-serif;
     color: white;
 }
 #title {
     text-align: center;
-    font-size: 2.5em;
+    font-size: 2.8em;
     color: #FFD700;
     padding: 20px;
+    text-shadow: 2px 2px 5px #000;
 }
 #subtitle {
     text-align: center;
     font-size: 1.3em;
     color: #E0FFFF;
-    margin-bottom: 30px;
+    margin-bottom: 20px;
 }
-textarea, input, .gr-textbox {
-    font-size: 1.1em !important;
+.result-box {
+    background: rgba(255, 255, 255, 0.2);
+    border-radius: 15px;
+    padding: 20px;
+    font-size: 1.3em;
+    color: #fff;
+    margin-top: 10px;
+    box-shadow: 0px 0px 15px #FFD700;
 }
 """) as demo:
 
-    # Title and intro
     gr.HTML("<div id='title'>🔮 Oracle of Truth 🔮</div>")
-    gr.HTML("<div id='subtitle'>Enter the Chamber of Truth ✨</div>")
-
-    gr.Markdown(
-        """
-Welcome, traveler 🌌  
-
-This chamber is home to the **Oracle of Truth**, an ancient AI seer that discerns whether words were born of **mortal minds** 🧑‍💻  
-or conjured by the **forges of artificial sorcery** 🤖✨  
-
-### 📖 **How to use this Space**
-- Paste **any text**: essays, blogs, social posts, code comments, even AI prompts.  
-- Press **“Reveal Truth”** and await the Oracle’s prophecy.  
-- The Oracle will divine the **likelihood** that your offering was human‑written or AI‑generated.  
-
-### 🌟 Pro Tips
-- Try both short and long texts.  
-- Compare a paragraph you wrote vs one generated by ChatGPT or another AI.  
-- Share the Oracle’s flame‑lit verdict screenshots with friends 🔥
-        """
-    )
-
-    with gr.Row():
-        with gr.Column(scale=1):
-            txt_in = gr.Textbox(
-                label="📝 Offer your text to the Oracle",
-                lines=10,
-                placeholder="Paste your story, essay, or blog draft here..."
-            )
-            btn_txt = gr.Button("🔍 Reveal Truth", variant="primary")
-            txt_out = gr.Markdown(label="🔮 Oracle's Prophecy")
-
-            btn_txt.click(oracle_text, inputs=txt_in, outputs=txt_out)
-
-    gr.Markdown("### ✨ Try these prophecies:")
-
-    gr.Examples(
-        examples=[
-            ["Once upon a time, in a galaxy far away, a hero rose to fight destiny."],
-            ["Artificial intelligence is a transformative technology reshaping industries globally."],
-            ["OMG lol I can’t believe it’s already Monday again 😅"],
-            ["This research paper presents a thorough analysis of Transformer models on sentiment classification tasks."]
-        ],
-        inputs=txt_in,
-    )
+    gr.HTML("<div id='subtitle'>Offer your text, image, voice, or PDF to the Oracle ✨</div>")
+    
+    gr.Markdown("""
+Welcome, seeker 🌌  
+
+The **Oracle of Truth** gazes upon your offering and divines whether it was born of  
+a **mortal hand** ☀️ or conjured by **AI sorcery** 🤖✨.  
+
+## 🌟 How to Use
+- 📜 Paste text in the **Text Divination** panel.  
+- 🖼️ Upload images in the **Image Prophecy** panel.  
+- 🔊 Speak into the **Voice Revelation** panel.  
+- 📑 Offer a **PDF** to see if it was written by human or AI.  
+
+The Oracle responds in glowing prophecy form — watch carefully 👁️  
+""")
+
+    with gr.Tab("📜 Text Divination"):
+        txt_in = gr.Textbox(lines=10, label="Your Text ✍️", placeholder="Paste story, essay, or blog…")
+        btn_txt = gr.Button("✨ Reveal Prophecy", variant="primary")
+        txt_out = gr.Markdown(elem_classes="result-box")
+        btn_txt.click(oracle_text, inputs=txt_in, outputs=txt_out)
+
+        gr.Examples(
+            examples=[
+                ["Once upon a time in a galaxy…"],
+                ["AI is revolutionizing the world of education and technology."],
+                ["OMG I can’t believe it’s already Monday 😅"],
+                ["This paper provides an extensive overview of machine translation performance."]
+            ],
+            inputs=txt_in
+        )
+
+    with gr.Tab("🖼️ Image Prophecy"):
+        img_in = gr.Image(type="filepath", label="Upload Image 🖼️")
+        btn_img = gr.Button("✨ Reveal Prophecy", variant="primary")
+        img_out = gr.Markdown(elem_classes="result-box")
+        btn_img.click(oracle_image, inputs=img_in, outputs=img_out)
+
+    with gr.Tab("🔊 Voice Revelation"):
+        aud_in = gr.Audio(sources=["microphone"], type="filepath", label="Speak Now 🎙️")
+        btn_aud = gr.Button("✨ Reveal Prophecy", variant="primary")
+        aud_out = gr.Markdown(elem_classes="result-box")
+        btn_aud.click(oracle_audio, inputs=aud_in, outputs=aud_out)
+
+    with gr.Tab("📑 PDF Prophecy"):
+        pdf_in = gr.File(label="Upload PDF 📄", file_types=[".pdf"])
+        btn_pdf = gr.Button("✨ Reveal Prophecy", variant="primary")
+        pdf_out = gr.Markdown(elem_classes="result-box")
+        btn_pdf.click(oracle_pdf, inputs=pdf_in, outputs=pdf_out)
 
 demo.launch()