Added pytorch

app.py

@@ -1,5 +1,6 @@
 import gradio as gr
-from transformers import pipeline
+from transformers import pipeline, Conversation
+# from transformers.pipelines.conversational import Conversation
 
 # def greet(name):
 #     return "Hello " + name + "!!"
@@ -11,14 +12,38 @@ chatbot_model = "facebook/blenderbot-400M-distill"
 
 chatbot = pipeline(model=chatbot_model)
 
+past_user_inputs = []
+generated_responses = []
+
 def echo(message, history):
     return message
 
 def chatbot_response(message, chat_history):
+    # print(message)
+    # return message + "??" # message, chat_history
+    # conversation = Conversation(text=message, past_user_inputs=past_user_inputs, generated_responses=generated_responses)
+    # conv = Conversation(chat_history)
+    # conv = Conversation(text=message)
+    # print(chatbot)
+    # print("---")
+    # conv.add_user_input(message)
+    # print(conv)
+    # print("---")
     chat_history.append(message)
-    bot_message = chatbot(chat_history)
-    chat_history.append(bot_message)
-    return bot_message, chat_history
+    # print(chat_history)
+    # print("---")
+    conv = chatbot(chat_history)
+    # generated_text = conv[-1]["generated_text"]
+    # print(generated_text)
+    return message + "??"
+    # return chat_history
+    # generated_text # , chat_history # , chat_history
+    # conv.append_response(bot_message)
+
+    # past_user_inputs.append(message)
+    # generated_responses.append(bot_message)
+
+    # chat_history.append((message, bot_message))
 
-app = gr.ChatInterface(fn=chatbot_response, examples=["hello", "hola", "merhaba"], title="Chat Bot")
+app = gr.ChatInterface(fn=chatbot_response, examples=["hi", "hola", "merhaba"], title="Chat Bot")
 app.launch()

requirements.txt

@@ -1 +1,2 @@
 transformers
+pytorch