Update app.py

app.py

@@ -1,46 +1,22 @@
-from transformers import AutoModelForCausalLM, AutoTokenizer
 import gradio as gr
-import torch
+from transformers import Conversation, pipeline
 
+message_list = []
+response_list = []
 
-title = "Chatbot with AI Service"
-description = "A State-of-the-Art Large-scale Pretrained Response generation model (DialoGPT)"
-examples = [["How are you?"]]
+# Initialize the chatbot pipeline
+chatbot = pipeline(model="facebook/blenderbot-400M-distill",
+                   task="conversational")
 
 
-tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-large")
-model = AutoModelForCausalLM.from_pretrained("microsoft/DialoGPT-large")
+def chat_with_bot(message, history):
+    conversation = Conversation(
+        text=message, past_user_inputs=message_list, generated_responses=response_list)
+    conversation = chatbot(conversation)
 
+    return conversation.generated_responses[-1]
 
-def predict(input, history=[]):
-    # tokenize the new input sentence
-    new_user_input_ids = tokenizer.encode(
-        input + tokenizer.eos_token, return_tensors="pt"
-    )
 
-    # append the new user input tokens to the chat history
-    bot_input_ids = torch.cat([torch.LongTensor(history), new_user_input_ids], dim=-1)
-
-    # generate a response
-    history = model.generate(
-        bot_input_ids, max_length=4000, pad_token_id=tokenizer.eos_token_id
-    ).tolist()
-
-    # convert the tokens to text, and then split the responses into lines
-    response = tokenizer.decode(history[0]).split("<|endoftext|>")
-    # print('decoded_response-->>'+str(response))
-    response = [
-        (response[i], response[i + 1]) for i in range(0, len(response) - 1, 2)
-    ]  # convert to tuples of list
-    # print('response-->>'+str(response))
-    return response, history
-
-
-gr.Interface(
-    fn=predict,
-    title=title,
-    description=description,
-    examples=examples,
-    inputs=["text", "state"],
-    outputs=["chatbot", "state"]
-).launch()
+iface = gr.ChatInterface(
+    chat_with_bot, title="My Conversational AI", description="A chatbot powered by Hugging Face Transformers!")
+iface.launch()