repo_description: ChatGLM2-6B: An Open Bilingual Chat LLM | 开源双语对话语言模型
repo_topics: chatglm chatglm-6b large-language-models llm
code: from transformers import AutoModel, AutoTokenizer
  import gradio as gr
  import mdtex2html
  from utils import load_model_on_gpus
  
  tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True)
  model = AutoModel.from_pretrained("THUDM/chatglm2-6b", trust_remote_code=True).cuda()
  # 多显卡支持，使用下面两行代替上面一行，将num_gpus改为你实际的显卡数量
  # from utils import load_model_on_gpus
  # model = load_model_on_gpus("THUDM/chatglm2-6b", num_gpus=2)
  model = model.eval()
  
  """Override Chatbot.postprocess"""
  
  
  def postprocess(self, y):
      if y is None:
          return []
      for i, (message, response) in enumerate(y):
          y[i] = (
              None if message is None else mdtex2html.convert((message)),
              None if response is None else mdtex2html.convert(response),
          )
      return y
  
  
  gr.Chatbot.postprocess = postprocess
  
  
  def parse_text(text):
      """copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
      lines = text.split("\n")
      lines = [line for line in lines if line != ""]
      count = 0
      for i, line in enumerate(lines):
          if "```" in line:
              count += 1
              items = line.split('`')
              if count % 2 == 1:
                  lines[i] = f'<pre><code class="language-{items[-1]}">'
              else:
                  lines[i] = f'<br></code></pre>'
          else:
              if i > 0:
                  if count % 2 == 1:
                      line = line.replace("`", "\`")
                      line = line.replace("<", "&lt;")
                      line = line.replace(">", "&gt;")
                      line = line.replace(" ", "&nbsp;")
                      line = line.replace("*", "&ast;")
                      line = line.replace("_", "&lowbar;")
                      line = line.replace("-", "&#45;")
                      line = line.replace(".", "&#46;")
                      line = line.replace("!", "&#33;")
                      line = line.replace("(", "&#40;")
                      line = line.replace(")", "&#41;")
                      line = line.replace("$", "&#36;")
                  lines[i] = "<br>"+line
      text = "".join(lines)
      return text
  
  
  def predict(input, chatbot, max_length, top_p, temperature, history, past_key_values):
      chatbot.append((parse_text(input), ""))
      for response, history, past_key_values in model.stream_chat(tokenizer, input, history, past_key_values=past_key_values,
                                                                  return_past_key_values=True,
                                                                  max_length=max_length, top_p=top_p,
                                                                  temperature=temperature):
          chatbot[-1] = (parse_text(input), parse_text(response))
  
          yield chatbot, history, past_key_values
  
  
  def reset_user_input():
      return gr.update(value='')
  
  
  def reset_state():
      return [], [], None
  
  
  with gr.Blocks() as demo:
      gr.HTML("""<h1 align="center">ChatGLM2-6B</h1>""")
  
      chatbot = gr.Chatbot()
      with gr.Row():
          with gr.Column(scale=4):
              with gr.Column(scale=12):
                  user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
                      container=False)
              with gr.Column(min_width=32, scale=1):
                  submitBtn = gr.Button("Submit", variant="primary")
          with gr.Column(scale=1):
              emptyBtn = gr.Button("Clear History")
              max_length = gr.Slider(0, 32768, value=8192, step=1.0, label="Maximum length", interactive=True)
              top_p = gr.Slider(0, 1, value=0.8, step=0.01, label="Top P", interactive=True)
              temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
  
      history = gr.State([])
      past_key_values = gr.State(None)
  
      submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history, past_key_values],
                      [chatbot, history, past_key_values], show_progress=True)
      submitBtn.click(reset_user_input, [], [user_input])
  
      emptyBtn.click(reset_state, outputs=[chatbot, history, past_key_values], show_progress=True)
  
  demo.queue().launch(share=False, inbrowser=True)
  