RAdapt pass_to_input to tasks

app.py

@@ -1,7 +1,7 @@
 import gradio as gr
 from gradio.components import Slider
 import torch
-from transformers import pipeline, AutoTokenizer, AutoModelForCausalLM
+from transformers import pipeline
 
 # Model, information and examples ----------------------------------------------
 model_id = "proxectonos/FLOR-1.3B-GL"
@@ -54,18 +54,7 @@ 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 (
         gr.update(value=30), # max_length
@@ -78,6 +67,28 @@ 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.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():
@@ -118,7 +129,7 @@ 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], 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)
         
         with gr.Row():
             with gr.Column(scale=0.5):