First commit pushed to spaces

README.md

@@ -1,8 +1,8 @@
 ---
-title: BlenderBot UI
-emoji: 📊
-colorFrom: yellow
-colorTo: gray
+title: BlenderBot New UI
+emoji: 🐱‍👓
+colorFrom: purple
+colorTo: pink
 sdk: gradio
 app_file: app.py
 pinned: false
@@ -10,3 +10,5 @@ license: apache-2.0
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces#reference
+
+<a href='https://www.freepik.com/vectors/chat-bot'>Chat bot vector used in app is created by roserodionova - www.freepik.com</a>

app.py

@@ -0,0 +1,44 @@
+import os
+import gradio as gr
+
+title = "Have Fun With ChubbyBot"
+description = """
+<p>
+<center>
+The bot is trained on blended_skill_talk dataset using facebook/blenderbot-400M-distill.
+<img src="https://huggingface.co/spaces/EXFINITE/BlenderBot-UI/resolve/main/img/cover.png" alt="rick" width="250"/>
+</center>
+</p>
+"""
+article = "<p style='text-align: center'><a href='https://arxiv.org/abs/1907.06616' target='_blank'>Recipes for building an open-domain chatbot</a></p><p style='text-align: center'><a href='https://parl.ai/projects/recipes/' target='_blank'>Original PARLAI Code</a></p></center></p>"
+
+from transformers import AutoModelForCausalLM, AutoTokenizer
+import torch
+
+tokenizer = AutoTokenizer.from_pretrained("facebook/blenderbot-400M-distill")
+model = AutoModelForCausalLM.from_pretrained("facebook/blenderbot-400M-distill")
+
+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=1000, 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]).replace("<|endoftext|>", "\n")
+    
+    return response, history
+
+gr.Interface(
+		fn = predict, 
+		inputs = ["textbox","state"], 
+		outputs = ["chatbot","state"],
+		theme ="grass",
+		title = title, 
+		description = description, 
+		article = article 
+		).launch(enable_queue=True)

requirements.txt

@@ -0,0 +1,2 @@
+transformers
+torch