БОТ ДОЛЖЕН БЫТЬ АСИНХРОННЫМ. Нужно реализовать очередь запросов, если модель нагружена и возращается busy, то запрос надо отправить в очередь и после заново отправить пока не получим ответ.
Напиши полноценного телеграм бота который будет Ui для этого api. нужно сделать запоминание контекста модели ai, очистку контекста. температура и top-p, ФОРМАТИРОВАНИЕ ОТВЕТА В ТЕЛЕГРАМ. используй aiogram 3 и сделай легкое добавление других моделей ai (у каждой модели должен быть свой массив комманд. мой токен <TRUFFLEHOG_REDACTED_HUGGINGFACE>. ожидать ответа от модели можно очень долго, в группах должен отвечать только на команды:Find the API endpoint below corresponding to your desired function in the app. Copy the code snippet, replacing the placeholder values with your own input data. If this is a private Space, you may need to pass your Hugging Face token as well (read more). Or use the

to automatically generate your API requests.
api_name: /enable_inputs

from gradio_client import Client

client = Client("yuntian-deng/o1mini")
result = client.predict(
api_name="/enable_inputs"
)
print(result)

Accepts 0 parameters:
Returns 1 element
api_name: /reset_textbox

from gradio_client import Client

client = Client("yuntian-deng/o1mini")
result = client.predict(
api_name="/reset_textbox"
)
print(result)

Accepts 0 parameters:
Returns 1 element

str

The output value that appears in the "Type an input and press Enter" Textbox component.
api_name: /predict

from gradio_client import Client

client = Client("yuntian-deng/o1mini")
result = client.predict(
inputs="Hello!!",
top_p=1,
temperature=1,
chat_counter=0,
chatbot=[],
api_name="/predict"
)
print(result)

Accepts 5 parameters:

inputs str Required

The input value that is provided in the "Type an input and press Enter" Textbox component.

top_p float Default: 1

The input value that is provided in the "Top-p (nucleus sampling)" Slider component.

temperature float Default: 1

The input value that is provided in the "Temperature" Slider component.

chat_counter float Default: 0

The input value that is provided in the "parameter_16" Number component.

chatbot Tuple[str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None, str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None] Default: []

The input value that is provided in the "parameter_4" Chatbot component.
Returns tuple of 4 elements

[0] Tuple[str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None, str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None]

The output value that appears in the "value_4" Chatbot component.

[1] float

The output value that appears in the "value_16" Number component.

[2] str

The output value that appears in the "Status code from OpenAI server" Textbox component.

[3] str

The output value that appears in the "Type an input and press Enter" Textbox component.
api_name: /reset_textbox_1

from gradio_client import Client

client = Client("yuntian-deng/o1mini")
result = client.predict(
api_name="/reset_textbox_1"
)
print(result)

Accepts 0 parameters:
Returns 1 element

str

The output value that appears in the "Type an input and press Enter" Textbox component.
api_name: /predict_1

from gradio_client import Client

client = Client("yuntian-deng/o1mini")
result = client.predict(
inputs="Hello!!",
top_p=1,
temperature=1,
chat_counter=0,
chatbot=[],
api_name="/predict_1"
)
print(result)

Accepts 5 parameters:

inputs str Required

The input value that is provided in the "Type an input and press Enter" Textbox component.

top_p float Default: 1

The input value that is provided in the "Top-p (nucleus sampling)" Slider component.

temperature float Default: 1

The input value that is provided in the "Temperature" Slider component.

chat_counter float Default: 0

The input value that is provided in the "parameter_16" Number component.

chatbot Tuple[str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None, str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None] Default: []

The input value that is provided in the "parameter_4" Chatbot component.
Returns tuple of 4 elements

[0] Tuple[str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None, str | Dict(file: filepath, alt_text: str | None) | Dict(component: str, value: Any, constructor_args: Dict(), props: Dict()) | None]

The output value that appears in the "value_4" Chatbot component.

[1] float

The output value that appears in the "value_16" Number component.

[2] str

The output value that appears in the "Status code from OpenAI server" Textbox component.

[3] str

The output value that appears in the "Type an input and press Enter" Textbox component.