Merge pull request hiyouga#20 from codemayq/main

add web_demo adapted from ChatGLM-6B

README.md

@@ -138,6 +138,12 @@ CUDA_VISIBLE_DEVICES=0 python src/infer.py \
     --checkpoint_dir path_to_checkpoint
 ```
 
+### Web Demo
+```bash
+CUDA_VISIBLE_DEVICES=0 python src/web_demo.py \
+    --checkpoint_dir path_to_checkpoint
+```
+
 ### Deploy the Fine-tuned Model
 ```python
 from .src import load_pretrained, ModelArguments

README_zh.md

@@ -140,6 +140,13 @@ CUDA_VISIBLE_DEVICES=0 python src/infer.py \
     --checkpoint_dir path_to_checkpoint
 ```
 
+### 网页版测试
+
+```bash
+CUDA_VISIBLE_DEVICES=0 python src/web_demo.py \
+    --checkpoint_dir path_to_checkpoint
+```
+
 ### 部署微调模型
 
 ```python

requirements.txt

@@ -9,3 +9,5 @@ jieba
 rouge_chinese
 nltk
 git+https://github.com/huggingface/peft.git
+gradio
+mdtex2html

src/web_demo.py

@@ -0,0 +1,106 @@
+"""copy from https://github.com/THUDM/ChatGLM-6B"""
+import gradio as gr
+import mdtex2html
+
+from utils import ModelArguments, load_pretrained
+from transformers import HfArgumentParser
+
+parser = HfArgumentParser(ModelArguments)
+model_args, = parser.parse_args_into_dataclasses()
+model, tokenizer = load_pretrained(model_args)
+model = model.half().cuda()
+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):
+    chatbot.append((parse_text(input), ""))
+    for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
+                                               temperature=temperature):
+        chatbot[-1] = (parse_text(input), parse_text(response))
+
+        yield chatbot, history
+
+
+def reset_user_input():
+    return gr.update(value='')
+
+
+def reset_state():
+    return [], []
+
+
+with gr.Blocks() as demo:
+    gr.HTML("""<h1 align="center">ChatGLM-Efficient-Tuning</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, 4096, value=2048, step=1.0, label="Maximum length", interactive=True)
+            top_p = gr.Slider(0, 1, value=0.7, 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([])
+
+    submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history],
+                    show_progress=True)
+    submitBtn.click(reset_user_input, [], [user_input])
+
+    emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
+
+demo.queue().launch(server_name="0.0.0.0", share=False, inbrowser=True)