Undo refactor pass_to_input

app.py

@@ -54,6 +54,18 @@ def predict(prompt, max_length, repetition_penalty=1.3):
     return generated_sequence
 
 # Gradio app ---------------------------------------------------------
+def clear(): 
+    return (
+        None, 
+        None,
+        gr.update(value=20),
+        gr.update(value=1.3)
+    )
+def pass_to_input(generated_gl):
+    return (
+        gr.update(value=generated_gl),
+        None
+    )
 
 def parameters_default(text):
     return (
@@ -67,28 +79,6 @@ def parameters_fewshot_prompt(text):
         gr.update(value=1) # repetition_penalty
     )
 
-def clear(): 
-    return (
-        None, 
-        None,
-        gr.update(value=20),
-        gr.update(value=1.3)
-    )
-def pass_to_input(generated_gl):
-    few_shot_tasks = [example[0].splitlines()[0] for example in few_shot_prompts_examples]
-    if generated_gl.splitlines()[0] in few_shot_tasks:
-        return (
-            gr.update(value=generated_gl),
-            None,
-            parameters_fewshot_prompt(generated_gl)
-        )
-    else:
-        return (
-        gr.update(value=generated_gl),
-        None,
-        parameters_fewshot_prompt(generated_gl)
-    )
-
 def gradio_app():
     with gr.Blocks(theme=fronted_theme) as demo:
         with gr.Row():
@@ -129,7 +119,7 @@ def gradio_app():
 
         generator_btn.click(predict, inputs=[text_gl,max_length, repetition_penalty], outputs=generated_gl, api_name="generate-flor-gl")
         clean_btn.click(fn=clear, inputs=[], outputs=[text_gl, generated_gl, max_length, repetition_penalty], queue=False, api_name=False)
-        pass_btn.click(fn=pass_to_input, inputs=[generated_gl], outputs=[text_gl,generated_gl, max_length, repetition_penalty], queue=False, api_name=False)
+        pass_btn.click(fn=pass_to_input, inputs=[generated_gl], outputs=[text_gl,generated_gl], queue=False, api_name=False)
         
         with gr.Row():
             with gr.Column(scale=0.5):