TypePHP 编译器
https://swoole.com/aot/
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119 lines
4.9 KiB
119 lines
4.9 KiB
"""
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This script creates an interactive web demo for the ChatGLM3-6B model using Gradio, a Python library for building quick and easy UI components for machine learning models. It's designed to showcase the capabilities of the ChatGLM3-6B model in a user-friendly interface, allowing users to interact with the model through a chat-like interface.
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Usage:
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- Run the script to start the Gradio web server.
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- Interact with the model by typing questions and receiving responses.
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Requirements:
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- Gradio (required with 3.39 version, not support for 4.x), Transformers, and other necessary Python libraries should be installed.
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- The model checkpoint should be accessible at the specified paths.
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Note: The script includes a modification to the Chatbot's postprocess method to handle markdown to HTML conversion, ensuring that the chat interface displays formatted text correctly.
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"""
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import os
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import mdtex2html
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from transformers import AutoModel, AutoTokenizer
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import gradio as gr
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MODEL_PATH = os.environ.get('MODEL_PATH', 'THUDM/chatglm3-6b')
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TOKENIZER_PATH = os.environ.get("TOKENIZER_PATH", MODEL_PATH)
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tokenizer = AutoTokenizer.from_pretrained(TOKENIZER_PATH, trust_remote_code=True)
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model = AutoModel.from_pretrained(MODEL_PATH, trust_remote_code=True, device_map="auto").eval()
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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,
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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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#
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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">ChatGLM3-6B</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=0.6, 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, server_name="127.0.0.1", server_port=8501, inbrowser=True)
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