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Update app.py
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app.py
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@@ -27,7 +27,7 @@ def oracle_text(user_text: str):
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return verdict
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# -------------------------------
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# Gradio UI
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# -------------------------------
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with gr.Blocks(css="""
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body {
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@@ -55,8 +55,9 @@ textarea, input, .gr-textbox {
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# Title and intro
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gr.HTML("<div id='title'>🔮 Oracle of Truth 🔮</div>")
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gr.HTML("<div id='subtitle'>Enter the Chamber of Truth ✨</div>")
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gr.Markdown(
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Welcome, traveler 🌌
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This chamber is home to the **Oracle of Truth**, an ancient AI seer that discerns whether words were born of **mortal minds** 🧑💻
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@@ -70,4 +71,32 @@ or conjured by the **forges of artificial sorcery** 🤖✨
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### 🌟 Pro Tips
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- Try both short and long texts.
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- Compare a paragraph you wrote vs one generated by ChatGPT or another AI.
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- Share the Oracle’s flame‑lit
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return verdict
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# -------------------------------
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# Gradio Immersive UI
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# -------------------------------
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with gr.Blocks(css="""
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body {
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# Title and intro
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gr.HTML("<div id='title'>🔮 Oracle of Truth 🔮</div>")
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gr.HTML("<div id='subtitle'>Enter the Chamber of Truth ✨</div>")
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gr.Markdown(
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"""
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Welcome, traveler 🌌
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This chamber is home to the **Oracle of Truth**, an ancient AI seer that discerns whether words were born of **mortal minds** 🧑💻
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### 🌟 Pro Tips
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- Try both short and long texts.
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- Compare a paragraph you wrote vs one generated by ChatGPT or another AI.
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- Share the Oracle’s flame‑lit verdict screenshots with friends 🔥
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"""
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)
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with gr.Row():
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with gr.Column(scale=1):
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txt_in = gr.Textbox(
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label="📝 Offer your text to the Oracle",
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lines=10,
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placeholder="Paste your story, essay, or blog draft here..."
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)
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btn_txt = gr.Button("🔍 Reveal Truth", variant="primary")
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txt_out = gr.Markdown(label="🔮 Oracle's Prophecy")
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btn_txt.click(oracle_text, inputs=txt_in, outputs=txt_out)
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gr.Markdown("### ✨ Try these prophecies:")
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gr.Examples(
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examples=[
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["Once upon a time, in a galaxy far away, a hero rose to fight destiny."],
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["Artificial intelligence is a transformative technology reshaping industries globally."],
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["OMG lol I can’t believe it’s already Monday again 😅"],
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["This research paper presents a thorough analysis of Transformer models on sentiment classification tasks."]
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],
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inputs=txt_in,
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)
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demo.launch()
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