Update app.py

app.py

@@ -244,6 +244,38 @@ app = gr.Interface(
     outputs=["text", "number"],
 )
 
+
+
+#####
+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,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"),
+      gr.Slider(minimum=1.0,maximum=200.0,value=50.0,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=5.0,value=3.0,step=1,interactive=True,label="no_repeat_ngram_size"),
+      gr.Slider(minimum=1.0,maximum=20.0,value=1.0,step=1,interactive=True,label="num_beams"),
+      gr.Dropdown(["Deutsch", "Englisch"],value="Deutsch"),
+  ],
+  outputs="text",
+  title=title,
+  description=desc,
+  examples=examples
+).launch()
+
+
 ####
 from transformers import AutoModelForCausalLM, AutoTokenizer, GenerationConfig, TextIteratorStreamer
 from threading import Thread
@@ -349,12 +381,12 @@ def topic_sale_inform (text):
 #conversation = Conversation("Welcome")
 
 def callChains(current_message):
-    final_answer = generate(current_message,  1.0,  256,  0.9,  1.0)
-    sentiment_analysis_result = "3"#pipeline_predict_sentiment(current_message)
-    topic_sale_inform_result = "4"# topic_sale_inform(current_message)
+    #final_answer = generate(current_message,  1.0,  256,  0.9,  1.0)
+    sentiment_analysis_result = pipeline_predict_sentiment(current_message)
+    topic_sale_inform_result = topic_sale_inform(current_message)
     #conversation.append_response("The Big lebowski.")
     #conversation.add_user_input("Is it good?")
-    #final_answer = func(current_message)
+    final_answer = func(current_message)
     return final_answer, sentiment_analysis_result, topic_sale_inform_result
 
 
@@ -366,7 +398,7 @@ topic_sale_inform_result_inputfield = gr.Textbox(label="Thema ")
 
 chat_bot = gr.Interface(fn=callChains , inputs=current_message_inputfield, outputs=[final_answer_inputfield,sentiment_analysis_result_inputfield,topic_sale_inform_result_inputfield], title="Conversation Bot with extra")
 # create a public link, set `share=True` in `launch()
-chat_bot.launch()
+#chat_bot.launch()
 ####################