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import gradio as gr |
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import torch |
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from transformers import AutoTokenizer, AutoModelForCausalLM, TextIteratorStreamer, pipeline |
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from threading import Thread |
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checkpoint = "microsoft/phi-2" |
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tokenizer = AutoTokenizer.from_pretrained(checkpoint, trust_remote_code=True) |
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model = AutoModelForCausalLM.from_pretrained(checkpoint, torch_dtype=torch.float32, device_map="cpu", trust_remote_code=True) |
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phi2 = pipeline( |
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"text-generation", |
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tokenizer=tokenizer, |
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model=model, |
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pad_token_id=tokenizer.eos_token_id, |
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eos_token_id=tokenizer.eos_token_id, |
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device_map="cpu" |
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) |
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def generate(prompt, chat_history, max_new_tokens): |
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instruction = "You are a helpful assistant to 'User'. You do not respond as 'User' or pretend to be 'User'. You only respond once as 'Assistant'." |
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final_prompt = f"Instruction: {instruction}\n" |
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for sent, received in chat_history: |
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final_prompt += "User: " + sent + "\n" |
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final_prompt += "Assistant: " + received + "\n" |
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final_prompt += "User: " + prompt + "\n" |
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final_prompt += "Output:" |
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streamer = TextIteratorStreamer(tokenizer=tokenizer, skip_prompt=True, skip_special_tokens=True, timeout=300.0) |
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thread = Thread(target=phi2, kwargs={"text_inputs":final_prompt, "max_new_tokens":max_new_tokens, "streamer":streamer}) |
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thread.start() |
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generated_text = "" |
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chat_history.append((prompt, "")) |
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for word in streamer: |
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generated_text += word |
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response = generated_text.strip() |
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if "User:" in response: |
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response = response.split("User:")[0].strip() |
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if "Assistant:" in response: |
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response = response.split("Assistant:")[1].strip() |
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chat_history.pop() |
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chat_history.append((prompt, response)) |
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yield "", chat_history |
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with gr.Blocks() as demo: |
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gr.Markdown(""" |
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# Phi-2 Chatbot Demo |
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This chatbot was created using Microsoft's 2.7 billion parameter [phi-2](https://huggingface.co/microsoft/phi-2) Transformer model. |
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In order to reduce the response time on this hardware, `max_new_tokens` has been set to `21` in the text generation pipeline. With this default configuration, it takes approximately `60 seconds` for the response to start being generated, and streamed one word at a time. Use the slider below to increase or decrease the length of the generated text. |
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""") |
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tokens_slider = gr.Slider(8, 128, value=21, label="Maximum new tokens", info="A larger `max_new_tokens` parameter value gives you longer text responses but at the cost of a slower response time.") |
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chatbot = gr.Chatbot(label="Phi-2 Chatbot") |
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msg = gr.Textbox(label="Message", placeholder="Enter text here") |
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with gr.Row(): |
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with gr.Column(): |
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btn = gr.Button("Send") |
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with gr.Column(): |
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clear = gr.ClearButton([msg, chatbot]) |
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btn.click(fn=generate, inputs=[msg, chatbot, tokens_slider], outputs=[msg, chatbot]) |
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examples = gr.Examples(examples=["Who is Leonhard Euler?"], inputs=[msg]) |
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demo.queue().launch() |