mirror of https://github.com/THUDM/ChatGLM2-6B
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109 lines
4.2 KiB
109 lines
4.2 KiB
from transformers import AutoModel, AutoTokenizer |
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import gradio as gr |
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import mdtex2html |
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from utils import load_model_on_gpus |
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tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True) |
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model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).cuda() |
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# 多显卡支持，使用下面三行代替上面两行，将num_gpus改为你实际的显卡数量 |
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# model_path = "THUDM/chatglm2-6b" |
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# tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True) |
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# model = load_model_on_gpus(model_path, num_gpus=2) |
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model = model.eval() |
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"""Override Chatbot.postprocess""" |
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def postprocess(self, y): |
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if y is None: |
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return [] |
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for i, (message, response) in enumerate(y): |
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y[i] = ( |
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None if message is None else mdtex2html.convert((message)), |
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None if response is None else mdtex2html.convert(response), |
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) |
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return y |
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gr.Chatbot.postprocess = postprocess |
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def parse_text(text): |
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"""copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/""" |
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lines = text.split("\n") |
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lines = [line for line in lines if line != ""] |
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count = 0 |
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for i, line in enumerate(lines): |
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if "```" in line: |
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count += 1 |
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items = line.split('`') |
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if count % 2 == 1: |
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lines[i] = f'<pre><code class="language-{items[-1]}">' |
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else: |
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lines[i] = f'<br></code></pre>' |
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else: |
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if i > 0: |
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if count % 2 == 1: |
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line = line.replace("`", "\`") |
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line = line.replace("<", "<") |
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line = line.replace(">", ">") |
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line = line.replace(" ", " ") |
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line = line.replace("*", "*") |
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line = line.replace("_", "_") |
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line = line.replace("-", "-") |
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line = line.replace(".", ".") |
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line = line.replace("!", "!") |
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line = line.replace("(", "(") |
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line = line.replace(")", ")") |
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line = line.replace("$", "$") |
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lines[i] = "<br>"+line |
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text = "".join(lines) |
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return text |
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def predict(input, chatbot, max_length, top_p, temperature, history, past_key_values): |
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chatbot.append((parse_text(input), "")) |
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for response, history, past_key_values in model.stream_chat(tokenizer, input, history, past_key_values=past_key_values, |
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return_past_key_values=True, |
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max_length=max_length, top_p=top_p, |
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temperature=temperature): |
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chatbot[-1] = (parse_text(input), parse_text(response)) |
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yield chatbot, history, past_key_values |
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def reset_user_input(): |
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return gr.update(value='') |
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def reset_state(): |
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return [], [], None |
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with gr.Blocks() as demo: |
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gr.HTML("""<h1 align="center">ChatGLM2-6B</h1>""") |
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chatbot = gr.Chatbot() |
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with gr.Row(): |
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with gr.Column(scale=4): |
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with gr.Column(scale=12): |
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user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style( |
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container=False) |
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with gr.Column(min_width=32, scale=1): |
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submitBtn = gr.Button("Submit", variant="primary") |
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with gr.Column(scale=1): |
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emptyBtn = gr.Button("Clear History") |
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max_length = gr.Slider(0, 32768, value=8192, step=1.0, label="Maximum length", interactive=True) |
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top_p = gr.Slider(0, 1, value=0.8, step=0.01, label="Top P", interactive=True) |
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temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True) |
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history = gr.State([]) |
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past_key_values = gr.State(None) |
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submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history, past_key_values], |
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[chatbot, history, past_key_values], show_progress=True) |
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submitBtn.click(reset_user_input, [], [user_input]) |
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emptyBtn.click(reset_state, outputs=[chatbot, history, past_key_values], show_progress=True) |
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demo.queue().launch(share=False, inbrowser=True)
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