Add parameters

app.py

@@ -2,26 +2,35 @@ import gradio as gr
 from transformers import pipeline
 title= "German Flan-T5"
 examples = [
-  ["Erzähl mit eine Geschichte!"]
+  ["Erzähl mit eine Geschichte!",200,2,3,5,"Deutsch"]
 ]
 
 tDeEn = pipeline(model="Helsinki-NLP/opus-mt-de-en")
 tEnDe = pipeline(model="Helsinki-NLP/opus-mt-en-de")
 bot = pipeline(model="google/flan-t5-large")
 
-def solve(text):
-  eng=tDeEn(text)[0]["translation_text"]
-  out=bot(eng,max_length=50)[0]["generated_text"]
-  out=tEnDe(out)[0]["translation_text"]
+def solve(text,max_length,length_penalty,no_repeat_ngram_size,num_beams,language):
+  if(language=="Deutsch"): 
+      text=tDeEn(text)[0]["translation_text"]
+  out=bot(text,max_length=max_length, length_penalty=length_penalty, no_repeat_ngram_size=no_repeat_ngram_size, num_beams=num_beams, early_stopping=True)[0]["generated_text"]
+  if(language=="Deutsch"): 
+      out=tEnDe(out)[0]["translation_text"]
   return out
 
 task = gr.Interface(
   fn=solve,
-  inputs=gr.Textbox(lines=5,max_lines=6,label="Frage"),
+  inputs=[
+      gr.Textbox(lines=5,max_lines=6,label="Frage"),
+      gr.Slider(minimum=1.0,maximum=200.0,value=200.0,step=1,interactive=True,label="max_length"),
+      gr.Slider(minimum=1.0,maximum=20.0,value=1.0,step=1,interactive=True,label="length_penalty"),
+      gr.Slider(minimum=0.0,maximum=20.0,value=3.0,step=1,interactive=True,label="no_repeat_ngram_size"),
+      gr.Slider(minimum=0.0,maximum=20.0,value=1.0,step=1,interactive=True,label="num_beams"),
+      gr.Dropdown(["Deutsch", "Englisch"]),
+  ],
   outputs="text",
   title=title,
   examples=examples
 )
 
 if __name__ == "__main__":
-  task.launch()
+  task.launch()