Update app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer
+from inference import load_model, predict
+
+# Load tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+model, device = load_model("evo_hellaswag.pt")
+
+# Interface logic
+def evo_decision(prompt, option1, option2):
+    result = predict(model, tokenizer, prompt, option1, option2, device)
+    choice = option1 if result["choice"] == 0 else option2
+    score_0 = round(result["scores"][0] * 100, 2)
+    score_1 = round(result["scores"][1] * 100, 2)
+    return (
+        f"✅ Evo Suggests: **{choice}**\n\n"
+        f"🧠 Confidence Scores:\n"
+        f"- Option 1: {score_0}%\n"
+        f"- Option 2: {score_1}%"
+    )
+
+# UI
+with gr.Blocks() as demo:
+    gr.Markdown("# 🧬 EvoTransformer – Reasoning API\nAsk Evo a question with 2 choices.")
+    
+    with gr.Row():
+        prompt = gr.Textbox(label="🧠 Scenario or Question", placeholder="e.g. You spilled juice on the floor.")
+    with gr.Row():
+        option1 = gr.Textbox(label="Option 1", placeholder="Wipe it with a cloth.")
+        option2 = gr.Textbox(label="Option 2", placeholder="Ignore and walk away.")
+    
+    with gr.Row():
+        output = gr.Markdown()
+    
+    with gr.Row():
+        btn = gr.Button("Ask Evo")
+        btn.click(fn=evo_decision, inputs=[prompt, option1, option2], outputs=[output])
+
+# Launch app
+demo.launch()