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Update app.py
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import gradio as gr
import copy
import random
import os
import requests
import time
import sys
from huggingface_hub import snapshot_download
from llama_cpp import Llama
SYSTEM_PROMPT = "Ты — Сайга, русскоязычный автоматический ассистент. Ты разговариваешь с людьми и помогаешь им."
SYSTEM_TOKEN = 1788
USER_TOKEN = 1404
BOT_TOKEN = 9225
LINEBREAK_TOKEN = 13
def get_message_tokens(model, role, content):
message_tokens = model.tokenize(content.encode("utf-8"))
message_tokens.insert(1, ROLE_TOKENS[role])
message_tokens.insert(2, LINEBREAK_TOKEN)
message_tokens.append(model.token_eos())
return message_tokens
def get_system_tokens(model):
system_message = {"role": "system", "content": SYSTEM_PROMPT}
return get_message_tokens(model, **system_message)
repo_name = "IlyaGusev/saiga2_13b_ggml"
model_name = "ggml-model-q4_1.bin"
snapshot_download(repo_id=repo_name, local_dir=".", allow_patterns=model_name)
model = Llama(
model_path=model_name,
n_ctx=2000,
n_parts=1,
)
max_new_tokens = 1500
def user(message, history):
new_history = history + [[message, None]]
return "", new_history
def bot(
history,
system_prompt,
top_p,
top_k,
temp
):
tokens = get_system_tokens(model)[:]
tokens.append(LINEBREAK_TOKEN)
for user_message, bot_message in history[:-1]:
message_tokens = get_message_tokens(model=model, role="user", content=user_message)
tokens.extend(message_tokens)
if bot_message:
message_tokens = get_message_tokens(model=model, role="bot", content=bot_message)
tokens.extend(message_tokens)
last_user_message = history[-1][0]
if retrieved_docs:
last_user_message = f"Контекст: {retrieved_docs}\n\nИспользуя контекст, ответь на вопрос: {last_user_message}"
message_tokens = get_message_tokens(model=model, role="user", content=last_user_message)
tokens.extend(message_tokens)
role_tokens = [model.token_bos(), BOT_TOKEN, LINEBREAK_TOKEN]
tokens.extend(role_tokens)
generator = model.generate(
tokens,
top_k=top_k,
top_p=top_p,
temp=temp
)
partial_text = ""
for i, token in enumerate(generator):
if token == model.token_eos() or (max_new_tokens is not None and i >= max_new_tokens):
break
partial_text += model.detokenize([token]).decode("utf-8", "ignore")
history[-1][1] = partial_text
yield history
with gr.Blocks(
theme=gr.themes.Soft()
) as demo:
favicon = '<img src="https://cdn.midjourney.com/b88e5beb-6324-4820-8504-a1a37a9ba36d/0_1.png" width="48px" style="display: inline">'
gr.Markdown(
f"""<h1><center>{favicon}Saiga2 13B</center></h1>
This is a demo of a **Russian**-speaking LLaMA2-based model. If you are interested in other languages, please check other models, such as [MPT-7B-Chat](https://huggingface.co/spaces/mosaicml/mpt-7b-chat).
Это демонстрационная версия версии [Сайги-2 с 13 миллиардами параметров](https://huggingface.co/IlyaGusev/saiga_13b_lora).
Сайга — это разговорная языковая модель, которая основана на [LLaMA](https://research.facebook.com/publications/llama-open-and-efficient-foundation-language-models/) и дообучена на корпусах, сгенерированных ChatGPT, таких как [ru_turbo_alpaca](https://huggingface.co/datasets/IlyaGusev/ru_turbo_alpaca), [ru_turbo_saiga](https://huggingface.co/datasets/IlyaGusev/ru_turbo_saiga) и [gpt_roleplay_realm](https://huggingface.co/datasets/IlyaGusev/gpt_roleplay_realm).
"""
)
with gr.Row():
with gr.Column(scale=5):
system_prompt = gr.Textbox(label="Системный промпт", placeholder="", value=SYSTEM_PROMPT, interactive=False)
chatbot = gr.Chatbot(label="Диалог").style(height=400)
with gr.Column(min_width=80, scale=1):
with gr.Tab(label="Параметры генерации"):
top_p = gr.Slider(
minimum=0.0,
maximum=1.0,
value=0.9,
step=0.05,
interactive=True,
label="Top-p",
)
top_k = gr.Slider(
minimum=10,
maximum=100,
value=30,
step=5,
interactive=True,
label="Top-k",
)
temp = gr.Slider(
minimum=0.0,
maximum=2.0,
value=0.1,
step=0.1,
interactive=True,
label="Temp"
)
with gr.Row():
with gr.Column():
msg = gr.Textbox(
label="Отправить сообщение",
placeholder="Отправить сообщение",
show_label=False,
).style(container=False)
with gr.Column():
with gr.Row():
submit = gr.Button("Отправить")
stop = gr.Button("Остановить")
clear = gr.Button("Очистить")
with gr.Row():
gr.Markdown(
"""ПРЕДУПРЕЖДЕНИЕ: Модель может генерировать фактически или этически некорректные тексты. Мы не несём за это ответственность."""
)
# Pressing Enter
submit_event = msg.submit(
fn=user,
inputs=[msg, chatbot],
outputs=[msg, chatbot],
queue=False,
).success(
fn=bot,
inputs=[
chatbot,
system_prompt,
top_p,
top_k,
temp
],
outputs=chatbot,
queue=True,
)
# Pressing the button
submit_click_event = submit.click(
fn=user,
inputs=[msg, chatbot, system_prompt],
outputs=[msg, chatbot],
queue=False,
).success(
fn=bot,
inputs=[
chatbot,
system_prompt,
top_p,
top_k,
temp
],
outputs=chatbot,
queue=True,
)
# Stop generation
stop.click(
fn=None,
inputs=None,
outputs=None,
cancels=[submit_event, submit_click_event],
queue=False,
)
# Clear history
clear.click(lambda: None, None, chatbot, queue=False)
demo.queue(max_size=128, concurrency_count=1)
demo.launch()