add gradio webui.py

webui.py

@@ -0,0 +1,128 @@
+import gradio as gr
+#pip install gradio==3.28.3
+import mdtex2html
+
+import torch
+# torch.cuda.set_device(2) 
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers.generation.utils import GenerationConfig
+
+MODEL_PATH='./'
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_PATH, use_fast=False, trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained(MODEL_PATH, device_map="auto", torch_dtype=torch.float16, trust_remote_code=True)
+model.generation_config = GenerationConfig.from_pretrained(MODEL_PATH)
+print(model.generation_config)
+# model = model.quantize(8).cuda()
+
+
+"""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
+
+stream = True
+
+def predict(input, chatbot, max_length, top_p, temperature, history, past_key_values):
+    model.generation_config.temperature = temperature
+    model.generation_config.top_p = top_p
+    model.generation_config.max_new_tokens = max_length
+    chatbot.append((parse_text(input), ""))
+
+    history.append({"role": "user", "content": parse_text(input)})
+    if stream:
+        position = 0
+        for response in model.chat(tokenizer, history, stream=True):
+            chatbot[-1] = (parse_text(input), parse_text(response))
+            if torch.backends.mps.is_available():
+                torch.mps.empty_cache()
+            yield chatbot, history, past_key_values
+        print(response)
+        history.append({"role": "assistant", "content": response})
+    else:
+        response = model.chat(tokenizer, history)
+        print(response)
+        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">Baichuan-13B-Chat</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, 2048, value=1024, step=1.0, label="Maximum length", interactive=True)
+            top_p = gr.Slider(0, 1, value=0.85, step=0.01, label="Top P", interactive=True)
+            temperature = gr.Slider(0, 1, value=0.9, 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=True, inbrowser=True,server_name="0.0.0.0", server_port=8891)