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# Подключение клиентов
# - - - - - - - - - - - - - -
from huggingface_hub import InferenceClient
from together import Together
# Подключение библиотек
# - - - - - - - - - - - - - -
import gradio as gr
import os
import json
#============================
#============================
# Список доступных моделей
# - - - - - - - - - - - - - -
models = {
"together": [
"deepseek-ai/DeepSeek-R1-Distill-Llama-70B-free",
"meta-llama/Llama-3.3-70B-Instruct-Turbo-Free"
],
"huggingface": [
"google/gemma-3-27b-it",
"Qwen/QwQ-32B",
"Qwen/QwQ-32B-Preview",
"mistralai/Mistral-Small-24B-Instruct-2501",
"deepseek-ai/deepseek-llm-67b-chat",
"mistralai/Mixtral-8x22B-Instruct-v0.1",
"NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO",
"google/gemma-2-9b-it",
"google/gemma-2-27b-it"
]
}
#============================
#============================
# Функции для работы с сообщениями
# - - - - - - - - - - - - - -
def add_message(role, content, messages):
messages.append({"role": role, "content": content})
return messages, len(messages), str(messages)
def clear_messages(messages):
return [], 0, "[]"
def show_messages(messages):
return str(messages)
def get_messages_api(messages):
return json.dumps(messages, indent=4)
def run_huggingface_model(model, messages, max_tokens, temperature, top_p):
client = InferenceClient(model)
response = client.chat_completion(
messages,
max_tokens=max_tokens,
stream=False,
temperature=temperature,
top_p=top_p,
)
return response.choices[0].message.content
def run_together_model(model, messages, max_tokens, temperature, top_p):
client = Together()
response = client.chat.completions.create(
model=model,
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
top_p=top_p,
)
return response.choices[0].message.content
#============================
#============================
# Создаем интерфейс с вкладками
demo = gr.Blocks()
with demo:
gr.Markdown("# Chat Interface")
# Вкладки для Together и HuggingFace
with gr.Tabs():
with gr.Tab("Together"):
together_model_input = gr.Radio(
label="Select a Together model",
choices=models["together"],
value=models["together"][0],
)
together_run_button = gr.Button("Run Together")
with gr.Tab("HuggingFace"):
huggingface_model_input = gr.Radio(
label="Select a HuggingFace model",
choices=models["huggingface"],
value=models["huggingface"][0],
)
huggingface_run_button = gr.Button("Run HuggingFace")
# Общие элементы интерфейса
role_input = gr.Dropdown(
label="Role",
choices=["system", "user", "assistant"], # Список ролей
value="user" # Значение по умолчанию
)
content_input = gr.Textbox(label="Content")
messages_state = gr.State(value=[])
messages_output = gr.Textbox(label="Messages", value="[]")
count_output = gr.Number(label="Count", value=0)
response_output = gr.Textbox(label="Response")
messages_api_output = gr.Textbox(label="Messages API")
add_button = gr.Button("Add")
clear_button = gr.Button("Clear")
show_button = gr.Button("Show messages")
get_api_button = gr.Button("Get messages API")
max_tokens_slider = gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens")
temperature_slider = gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature")
top_p_slider = gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)")
# Обработчики событий для кнопок
add_button.click(
add_message,
inputs=[role_input, content_input, messages_state],
outputs=[messages_state, count_output, messages_output],
)
clear_button.click(
clear_messages,
inputs=[messages_state],
outputs=[messages_state, count_output, messages_output],
)
show_button.click(
show_messages,
inputs=[messages_state],
outputs=[messages_output],
)
get_api_button.click(
get_messages_api,
inputs=[messages_state],
outputs=[messages_api_output],
)
# Обработчики событий для кнопок "Run"
together_run_button.click(
run_together_model,
inputs=[together_model_input, messages_state, max_tokens_slider, temperature_slider, top_p_slider],
outputs=[response_output],
)
huggingface_run_button.click(
run_huggingface_model,
inputs=[huggingface_model_input, messages_state, max_tokens_slider, temperature_slider, top_p_slider],
outputs=[response_output],
)
#============================
#============================
if __name__ == "__main__":
demo.launch() |