Update app.py

app.py

@@ -1,83 +1,82 @@
 import gradio as gr
 import spaces
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
+from transformers import pipeline
 
 # -------------------------------
-# Load Qwen2.5-7B (text-only model, works for both Genie & Wizard replies)
+# Load lightweight AI detection models
 # -------------------------------
-model_id = "Qwen/Qwen2.5-7B-Instruct"
 
-tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
-model = AutoModelForCausalLM.from_pretrained(
-    model_id,
-    torch_dtype=torch.float16,
-    device_map="auto",
-    trust_remote_code=True
-)
+# Text AI detector
+text_detector = pipeline("text-classification", model="roberta-base-openai-detector")
 
-qwen_pipe = pipeline(
-    "text-generation",
-    model=model,
-    tokenizer=tokenizer,
-    device_map="auto"
-)
+# Image AI detector
+image_detector = pipeline("image-classification", model="oripress/ai-image-detector")
 
 # -------------------------------
-# Life Genie: text chat
+# Functions for Oracle of Truth
 # -------------------------------
-@spaces.GPU
-def life_genie(user_input: str) -> str:
-    if not user_input.strip():
-        return "🧞 Please ask me something magical!"
-    prompt = f"You are a witty magical genie. Answer creatively.\nUser: {user_input}\nGenie:"
-    output = qwen_pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7)
-    return output[0]["generated_text"]
 
-# -------------------------------
-# Whisper ASR for voice input
-# -------------------------------
-asr_pipe = pipeline("automatic-speech-recognition", model="openai/whisper-tiny", device=-1)
+@spaces.GPU
+def detect_text(user_text: str):
+    if not user_text.strip():
+        return "🧞 Please provide some text for the Oracle to examine."
+    result = text_detector(user_text)
+    label = result[0]['label']
+    score = round(result[0]['score'] * 100, 2)
+    if label.lower() == "fake":
+        return f"🌌 Oracle’s Vision: {score}% chance this was conjured by AI magic 🤖✨"
+    else:
+        return f"☀️ Oracle’s Vision: {score}% chance this was written by a mortal hand 🧑‍💻"
 
-# -------------------------------
-# Voice Wizard: speech → Genie reply
-# -------------------------------
 @spaces.GPU
-def voice_wizard(audio_file) -> str:
-    if audio_file is None:
-        return "🎤 Please record your voice first!"
-    # Step 1: Transcribe microphone audio
-    transcript = asr_pipe(audio_file)["text"]
-    # Step 2: Ask Genie with that transcript
-    prompt = f"The user spoke: '{transcript}'. Respond like a magical wizard with wisdom and humor.\nWizard:"
-    output = qwen_pipe(prompt, max_new_tokens=256, do_sample=True, temperature=0.7)
-    return f"✨ Voice Transcription: {transcript}\n\n🔮 Wizard Replies:\n{output[0]['generated_text']}"
+def detect_image(user_img):
+    if user_img is None:
+        return "🖼️ Please upload an image for the Oracle to divine."
+    result = image_detector(user_img)
+    label = result[0]['label']
+    score = round(result[0]['score'] * 100, 2)
+    return f"🌠 Oracle’s Gaze: {score}% chance this is {label}."
 
 # -------------------------------
 # Gradio UI
 # -------------------------------
 with gr.Blocks(css="""
-body {
-    background: linear-gradient(135deg, #ff9a9e, #fad0c4);
+body { 
+    background: linear-gradient(135deg, #0f2027, #203a43, #2c5364); 
     font-family: Trebuchet MS, sans-serif;
+    color: white;
 }
+h1, h2, h3 { color: #ffcc00; }
 """) as demo:
 
-    gr.HTML("<h1 style='text-align:center; color:white;'>🌈✨ Magic-Lab ✨🌈</h1>")
-    gr.Markdown("Welcome! Meet the Genie through text or voice. 🧞🔮")
+    gr.HTML("<h1 style='text-align:center;'>🔮 Oracle of Truth 🔮</h1>")
+    gr.Markdown("""
+Welcome to the **Chamber of Truth** ✨.  
+Offer your **text** or **image** to the Oracle,  
+and it will divine whether it was born of **human hands** ☀️  
+or conjured by **AI sorcery** 🤖🌌.
+    """)
+
+    with gr.Tab("📜 Text Divination"):
+        txt_in = gr.Textbox(label="Enter Text", lines=5, placeholder="Paste some text here...")
+        btn_txt = gr.Button("🔍 Ask the Oracle")
+        txt_out = gr.Textbox(label="Oracle's Verdict", lines=4)
+        btn_txt.click(detect_text, inputs=txt_in, outputs=txt_out)
 
-    # Life Genie (Text)
-    with gr.Tab("🧞 Life Genie"):
-        txt_in = gr.Textbox(lines=3, placeholder="Ask me anything...", label="Your Wish")
-        txt_out = gr.Textbox(lines=10, label="Genie's Response")
-        btn_chat = gr.Button("✨ Summon Genie")
-        btn_chat.click(life_genie, inputs=txt_in, outputs=txt_out)
+    with gr.Tab("🖼️ Image Divination"):
+        img_in = gr.Image(type="filepath", label="Upload an Image")
+        btn_img = gr.Button("🔍 Ask the Oracle")
+        img_out = gr.Textbox(label="Oracle's Verdict", lines=2)
+        btn_img.click(detect_image, inputs=img_in, outputs=img_out)
 
-    # Voice Wizard (Voice)
-    with gr.Tab("🔮 Voice Wizard"):
-        aud_in = gr.Audio(sources=["microphone"], type="filepath", label="Speak your spell 🎤")
-        aud_out = gr.Textbox(lines=10, label="Wizard's Reply")
-        btn_voice = gr.Button("🎙️ Cast Spell")
-        btn_voice.click(voice_wizard, inputs=aud_in, outputs=aud_out)
+    # Preloaded examples
+    gr.Examples(
+        examples=[
+            ["Once upon a time in a galaxy far away, a hero rose against the odds."],
+            ["In this paper, we analyze the performance of Transformer models on natural language inference tasks."]
+        ],
+        inputs=txt_in,
+        label="Try sample texts"
+    )
 
 demo.launch()