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| from transformers import AutoModel, AutoTokenizer | |
| import gradio as gr | |
| tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) | |
| model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) | |
| #.half().cuda() | |
| model = model.eval() | |
| # def add_text(history, text): | |
| # history = history + [(text, None)] | |
| # return history, "" | |
| # def add_file(history, file): | |
| # history = history + [((file.name,), None)] | |
| # return history | |
| # def bot(history): | |
| # response = "**That's cool!**" | |
| # history[-1][1] = response | |
| # return history | |
| def predict(input, history=None): | |
| if history is None: | |
| history = [] | |
| response, history = model.chat(tokenizer, input, history) | |
| return history, history | |
| with gr.Blocks() as demo: | |
| chatbot = gr.Chatbot() | |
| msg = gr.Textbox() | |
| clear = gr.Button("Clear") | |
| def user(user_message, history): | |
| return "", history + [[user_message, None]] | |
| def bot(msg, history): | |
| # bot_message = random.choice(["How are you?", "I love you", "I'm very hungry"]) | |
| bot_message = predict(msg, history) | |
| history[-1][1] = "" | |
| for character in bot_message: | |
| history[-1][1] += character | |
| time.sleep(0.05) | |
| yield history | |
| msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then( | |
| bot, [msg, chatbot], [msg, chatbot] | |
| ) | |
| clear.click(lambda: None, None, chatbot, queue=False) | |
| demo.queue() | |
| demo.launch() | |
| # txt.submit(predict, [txt, state], [chatbot, state]) | |
| # button.click(predict, [txt, state], [chatbot, state]) | |
| # btn.upload(add_file, [chatbot, btn], [chatbot]).then( | |
| # bot, chatbot, chatbot | |
| # ) | |
| demo.launch() |