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| # -*- coding: utf-8 -*- | |
| """Meena_A_Multilingual_Chatbot (1).ipynb | |
| Automatically generated by Colaboratory. | |
| Original file is located at | |
| https://colab.research.google.com/drive/1-IfUcnDUppyMArHonc_iesEcN2gSKU-j | |
| """ | |
| #!pip3 install transformers | |
| #!pip install -q translate | |
| #!pip install polyglot | |
| #!pip install Pyicu | |
| #!pip install Morfessor | |
| #!pip install pycld2 | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| import torch | |
| from translate import Translator | |
| from polyglot.detect import Detector | |
| # model_name = "microsoft/DialoGPT-large" | |
| model_name = "microsoft/DialoGPT-large" | |
| # model_name = "microsoft/DialoGPT-small" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| # # chatting 5 times with nucleus sampling & tweaking temperature | |
| # step=-1 | |
| # while(True): | |
| # step+=1 | |
| # # take user input | |
| # text = input(">> You:>") | |
| # detected_language=Detector(text,quiet=True).language.code | |
| # translator=Translator(from_lang=detected_language,to_lang="en") | |
| # translated_input=translator.translate(text) | |
| # print(translated_input) | |
| # if text.lower().find("bye")!=-1: | |
| # print(f">> Meena:> Bye Bye!") | |
| # break; | |
| # # encode the input and add end of string token | |
| # input_ids = tokenizer.encode(translated_input+tokenizer.eos_token, return_tensors="pt") | |
| # # concatenate new user input with chat history (if there is) | |
| # bot_input_ids = torch.cat([chat_history_ids, input_ids], dim=-1) if step > 0 else input_ids | |
| # # generate a bot response | |
| # chat_history_ids = model.generate(bot_input_ids, max_length=1000, pad_token_id=tokenizer.eos_token_id,do_sample=True,top_p=0.9,top_k=50,temperature=0.7,num_beams=5,no_repeat_ngram_size=2) | |
| # #print the output | |
| # output = tokenizer.decode(chat_history_ids[:, bot_input_ids.shape[-1]:][0], skip_special_tokens=True) | |
| # print(output) | |
| # translator=Translator(from_lang="en",to_lang=detected_language) | |
| # translated_output=translator.translate(output) | |
| # print(f">> Meena:> {translated_output}") | |
| #!pip install gradio | |
| import gradio as gr | |
| with gr.Blocks() as meena: | |
| chatbot = gr.Chatbot(label="Meena- A Multilingual Chatbot") | |
| msg = gr.Textbox(label="You") | |
| clear = gr.Button("Clear") | |
| def set(chat_history_ids1): | |
| global chat_history_ids | |
| chat_history_ids=chat_history_ids1 | |
| def get(): | |
| return chat_history_ids | |
| def set2(step1): | |
| global step | |
| step=step1 | |
| def get2(): | |
| return step | |
| def generate_text(text,chat_history): | |
| step=-1 | |
| if len(chat_history)==0: | |
| step=-1 | |
| else: | |
| step=get2() | |
| step+=1 | |
| set2(step) | |
| print(step) | |
| if step!=0: | |
| chat_history_ids=get() | |
| if text.isdigit(): | |
| detected_language='en' | |
| else: | |
| detected_language=Detector(text,quiet=True).language.code | |
| translator=Translator(from_lang=detected_language,to_lang="en") | |
| translated_input=translator.translate(text) | |
| # encode the input and add end of string token | |
| input_ids=tokenizer.encode(translated_input+tokenizer.eos_token,return_tensors="pt") | |
| # concatenate new user input with chat history (if there is) | |
| bot_input_ids=torch.cat([chat_history_ids,input_ids],dim=-1) if step>0 else input_ids | |
| # generate a bot response | |
| chat_history_ids=model.generate(bot_input_ids,max_length=1000,pad_token_id=tokenizer.eos_token_id,do_sample=True,top_p=0.9,top_k=50,temperature=0.7,num_beams=5,no_repeat_ngram_size=2) | |
| print(chat_history_ids) | |
| set(chat_history_ids) | |
| #print the output | |
| output=tokenizer.decode(chat_history_ids[:,bot_input_ids.shape[-1]:][0],skip_special_tokens=True) | |
| translator=Translator(from_lang="en",to_lang=detected_language) | |
| translated_output=translator.translate(output) | |
| chat_history.append((text,translated_output)) | |
| if step==5: | |
| set(-1) | |
| set2(-1) | |
| return "",chat_history | |
| msg.submit(generate_text, [msg, chatbot], [msg, chatbot]) | |
| clear.click(lambda: None, None, chatbot, queue=False) | |
| meena.queue().launch() |