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# Reference:
# https://github.com/li-plus/chatglm.cpp
# https://github.com/li-plus/chatglm.cpp/blob/main/examples/web_demo.py
import chatglm_cpp
import gradio as gr
import argparse
from pathlib import Path
pipeline = chatglm_cpp.Pipeline("./chatglm3-ggml.bin")
max_length = 2048
top_p = 0.4
temp = 0.95
max_context_length=512
mode = "chat"
top_k = 0
repeat_penalty = 1.0
threads = 0
def postprocess(text):
#if args.plain:
# return f"<pre>{text}</pre>"
return text
def predict(input, chatbot, max_length, top_p, temperature, messages):
chatbot.append((postprocess(input), ""))
messages.append(chatglm_cpp.ChatMessage(role="user", content=input))
generation_kwargs = dict(
max_length=max_length,
max_context_length=max_context_length,
do_sample=temperature > 0,
top_k=top_k,
top_p=top_p,
temperature=temperature,
repetition_penalty=repeat_penalty,
num_threads=threads,
stream=True,
)
response = ""
if mode == "chat":
chunks = []
for chunk in pipeline.chat(messages, **generation_kwargs):
response += chunk.content
chunks.append(chunk)
chatbot[-1] = (chatbot[-1][0], postprocess(response))
yield chatbot, messages
messages.append(pipeline.merge_streaming_messages(chunks))
else:
for chunk in pipeline.generate(input, **generation_kwargs):
response += chunk
chatbot[-1] = (chatbot[-1][0], postprocess(response))
yield chatbot, messages
yield chatbot, messages
def reset_user_input():
return gr.update(value="")
def reset_state():
return [], []
with gr.Blocks() as demo:
gr.HTML("""<h1 align="center">ChatGLM3 Quantized by ChatGLM.cpp. Reduce size from 12G to 3.4G.</h1>""")
chatbot = gr.Chatbot()
with gr.Row():
with gr.Column(scale=4):
user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=8)
submitBtn = gr.Button("Submit", variant="primary")
with gr.Column(scale=1):
max_length = gr.Slider(0, 2048, value=max_length, step=1.0, label="Maximum Length", interactive=True)
top_p = gr.Slider(0, 1, value=top_p, step=0.01, label="Top P", interactive=True)
temperature = gr.Slider(0, 1, value=temp, step=0.01, label="Temperature", interactive=True)
emptyBtn = gr.Button("Clear History")
messages = gr.State([])
submitBtn.click(
predict,
[user_input, chatbot, max_length, top_p, temperature, messages],
[chatbot, messages],
show_progress=True,
)
submitBtn.click(reset_user_input, [], [user_input])
emptyBtn.click(reset_state, outputs=[chatbot, messages], show_progress=True)
demo.queue().launch(share=False, inbrowser=True) |