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import gradio as gr | |
import os | |
from pathlib import Path | |
os.environ["CMAKE_ARGS"] = "-DLLAMA_CUBLAS=on" | |
os.system('CMAKE_ARGS="-DLLAMA_CUBLAS=on" pip install llama-cpp-python[server]') | |
import argparse | |
model_file = "yi-chat-6b.Q4_K_M.gguf" | |
if not os.path.isfile(model_file): | |
os.system("wget -c https://huggingface.co/XeIaso/yi-chat-6B-GGUF/resolve/main/yi-chat-6b.Q4_K_M.gguf") | |
DEFAULT_MODEL_PATH = model_file | |
from llama_cpp import Llama | |
llm = Llama(model_path=model_file, model_type="mistral") | |
llm._token_eos = 7 | |
def predict(input, chatbot, max_length, top_p, temperature, history): | |
chatbot.append((input, "")) | |
response = "" | |
history.append(input) | |
for output in llm(input, stream=True, temperature=temperature, top_p=top_p, max_tokens=max_length, stop=["<|im_end|>"]): | |
piece = output['choices'][0]['text'] | |
response += piece | |
chatbot[-1] = (chatbot[-1][0], response) | |
yield chatbot, history | |
history.append(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">Yi-6B-Chat by llama-cpp-python</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, 32048, 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) | |
emptyBtn = gr.Button("Clear History") | |
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(share=False, inbrowser=True) |