create app.py

app.py

@@ -1,44 +1,7 @@
-import gradio as gr
-from utils import *
-import openai
-
-def greet(task, human_input, cooperate_style):
-    merged_answer = "xxx"
-    return f"Given task :{task},\nthe {cooperate_style} answer based of ai and human input \"{human_input}\" is:\n {merged_answer}. "
-
-def get_answer(task, human_input, cooperate_style):
-    if cooperate_style=="sequential":
-            merged_text = merge_texts_sequential(task, human_input)
-            print(f"AI merged text: {merged_text}")
-    else:
-        generated_text = generate_text_with_gpt(task)
-        print(f"AI provided text: {generated_text}")    
-        merged_text = merge_texts_parallel(task, human_input, generated_text)
-    return merged_text
-
-def main():
-    with gr.Blocks() as demo:
-        task = gr.Textbox(label="Please Give a task description.")
-        human_input = gr.Textbox(label="Please provide a human answer.", value = "Write a poem about the moon.")
-        cooperate_style = gr.Radio(['sequential', 'parallel'], label="What type of cooperation would you like?")
-        greet_btn = gr.Button("Think!")
-        output = gr.Textbox(label="Answer with cooperation")
-        
-        greet_btn.click(fn=get_answer, 
-                        inputs=[task, human_input, cooperate_style], 
-                        outputs=output, 
-                        api_name="answer")
-        
-        evaluate_btn = gr.Button("Evaluate")
-        evaluation_results = gr.Textbox(label="Evaluation results.")
-        evaluate_btn.click(fn= evaluation,
-                           inputs=[task, output],
-                           outputs= evaluation_results,
-                           api_name = "evaluate")
-        demo.launch(share=True)
-    
-if __name__ == "__main__":
-    main()
-    
-
-
+import gradio as gr
+
+def greet(name):
+    return "Hello " + name + "!!"
+
+iface = gr.Interface(fn=greet, inputs="text", outputs="text")
+iface.launch()