Update app.py

app.py

@@ -0,0 +1,59 @@
+import gradio as gr
+from transformers import pipeline
+
+# Add a print statement to confirm initialization
+print("Initializing model...")
+
+# Load AI model
+try:
+    model = pipeline("text2text-generation", model="google/flan-t5-base")
+    print("Model loaded successfully.")
+except Exception as e:
+    print(f"Error loading model: {e}")
+
+def ai_vote(poll_title, choices, num_ais):
+    try:
+        results = {}
+        explanations = []
+
+        for _ in range(num_ais):
+            input_text = f"Poll Title: {poll_title}\nChoices: {', '.join(choices)}\nChoose the best option and explain why."
+            response = model(input_text, max_length=100, num_return_sequences=1)[0]['generated_text']
+            
+            # Extract the chosen option and explanation
+            chosen_option = response.split("\n")[0].strip()
+            explanation = "\n".join(response.split("\n")[1:]).strip()
+
+            results[chosen_option] = results.get(chosen_option, 0) + 1
+            explanations.append((chosen_option, explanation))
+
+        return results, explanations
+    except Exception as e:
+        return {"Error": str(e)}, []
+
+# Gradio interface
+def gradio_interface(title, choices, num_ais):
+    try:
+        choices = [choice.strip() for choice in choices.split(",")]
+        results, explanations = ai_vote(title, choices, num_ais)
+        return results, explanations
+    except Exception as e:
+        return {"Error": str(e)}, "An error occurred."
+
+interface = gr.Interface(
+    fn=gradio_interface,
+    inputs=[
+        gr.Textbox(label="Poll Title"),
+        gr.Textbox(label="Choices (comma-separated)"),
+        gr.Slider(label="Number of AIs", minimum=1, maximum=10, step=1)
+    ],
+    outputs=[
+        gr.Label(label="Poll Results"),
+        gr.Textbox(label="AI Explanations")
+    ]
+)
+
+# Launch app
+if __name__ == "__main__":
+    print("Launching interface...")
+    interface.launch()