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2f48f2a
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Upload folder using huggingface_hub

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  1. web_demo_old.py +82 -26
web_demo_old.py CHANGED
@@ -1,45 +1,101 @@
1
  from transformers import AutoModel, AutoTokenizer
2
  import gradio as gr
 
3
 
4
- tokenizer = AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)
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- model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
6
  model = model.eval()
7
 
8
- MAX_TURNS = 20
9
- MAX_BOXES = MAX_TURNS * 2
10
 
11
 
12
- def predict(input, max_length, top_p, temperature, history=None):
13
- if history is None:
14
- history = []
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
15
  for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
16
  temperature=temperature):
17
- updates = []
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- for query, response in history:
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- updates.append(gr.update(visible=True, value="用户:" + query))
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- updates.append(gr.update(visible=True, value="ChatGLM-6B:" + response))
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- if len(updates) < MAX_BOXES:
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- updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
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- yield [history] + updates
 
 
 
 
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25
 
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  with gr.Blocks() as demo:
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- state = gr.State([])
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- text_boxes = []
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- for i in range(MAX_BOXES):
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- if i % 2 == 0:
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- text_boxes.append(gr.Markdown(visible=False, label="提问:"))
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- else:
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- text_boxes.append(gr.Markdown(visible=False, label="回复:"))
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  with gr.Row():
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  with gr.Column(scale=4):
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- txt = gr.Textbox(show_label=True, placeholder="Enter text and press enter", lines=11).style(
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- container=False)
 
 
 
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  with gr.Column(scale=1):
 
40
  max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
41
  top_p = gr.Slider(0, 1, value=0.7, 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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- button = gr.Button("Generate")
44
- button.click(predict, [txt, max_length, top_p, temperature, state], [state] + text_boxes)
45
- demo.queue().launch(share=False, inbrowser=True)
 
 
 
 
 
 
 
 
1
  from transformers import AutoModel, AutoTokenizer
2
  import gradio as gr
3
+ import mdtex2html
4
 
5
+ 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).half().cuda()
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  model = model.eval()
8
 
9
+ """Override Chatbot.postprocess"""
 
10
 
11
 
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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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+
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+
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+ gr.Chatbot.postprocess = postprocess
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+
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+
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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("<", "&lt;")
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+ line = line.replace(">", "&gt;")
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+ line = line.replace(" ", "&nbsp;")
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+ line = line.replace("*", "&ast;")
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+ line = line.replace("_", "&lowbar;")
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+ line = line.replace("-", "&#45;")
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+ line = line.replace(".", "&#46;")
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+ line = line.replace("!", "&#33;")
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+ line = line.replace("(", "&#40;")
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+ line = line.replace(")", "&#41;")
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+ line = line.replace("$", "&#36;")
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+ lines[i] = "<br>"+line
55
+ text = "".join(lines)
56
+ return text
57
+
58
+
59
+ def predict(input, chatbot, max_length, top_p, temperature, history):
60
+ chatbot.append((parse_text(input), ""))
61
  for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
62
  temperature=temperature):
63
+ chatbot[-1] = (parse_text(input), parse_text(response))
64
+
65
+ yield chatbot, history
66
+
67
+
68
+ def reset_user_input():
69
+ return gr.update(value='')
70
+
71
+
72
+ def reset_state():
73
+ return [], []
74
 
75
 
76
  with gr.Blocks() as demo:
77
+ gr.HTML("""<h1 align="center">ChatGLM</h1>""")
 
 
 
 
 
 
78
 
79
+ chatbot = gr.Chatbot()
80
  with gr.Row():
81
  with gr.Column(scale=4):
82
+ with gr.Column(scale=12):
83
+ user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
84
+ container=False)
85
+ with gr.Column(min_width=32, scale=1):
86
+ submitBtn = gr.Button("Submit", variant="primary")
87
  with gr.Column(scale=1):
88
+ emptyBtn = gr.Button("Clear History")
89
  max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
90
  top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
91
  temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
92
+
93
+ history = gr.State([])
94
+
95
+ submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history],
96
+ show_progress=True)
97
+ submitBtn.click(reset_user_input, [], [user_input])
98
+
99
+ emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
100
+
101
+ demo.queue().launch(share=True, inbrowser=True)