OpenAI-O1-Preview: 
API documentation
yuntian-deng/o1

API Recorder

5 API endpoints


Choose a language to see the code snippets for interacting with the API.

1. Install the python client (docs) if you don't already have it installed.

copy
$ pip install gradio_client
2. 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 
API Recorder

 to automatically generate your API requests.

api_name: /enable_inputs
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from gradio_client import Client

client = Client("yuntian-deng/o1")
result = client.predict(
		api_name="/enable_inputs"
)
print(result)
Accepts 0 parameters:
Returns 1 element
api_name: /reset_textbox
copy
from gradio_client import Client

client = Client("yuntian-deng/o1")
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
copy
from gradio_client import Client

client = Client("yuntian-deng/o1")
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
copy
from gradio_client import Client

client = Client("yuntian-deng/o1")
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
copy
from gradio_client import Client

client = Client("yuntian-deng/o1")
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.



"""""""""""""""""" Claro! Aqui está um código Python simples que solicita o nome do usuário e exibe uma saudação personalizada:<br/><pre><code class="python"><br/># Programa que cumprimenta o usuário<br/><br/># Solicita o nome do usuário<br/>nome = input("Qual é o seu nome? ")<br/><br/># Exibe a saudação personalizada<br/>print(f"Olá, {nome}! Seja bem-vindo(a).")</code></pre><br/><br/>**Como funciona:**<br/><br/>1. O programa utiliza a função `input()` para capturar o nome digitado pelo usuário.<br/>2. Em seguida, utiliza a função `print()` para exibir uma mensagem que inclui o nome fornecido.<br/><br/>Este é um exemplo básico de como interagir com o usuário e exibir mensagens na tela usando Python. """"""""""""""


Aqui está todo o jeito que ele manda uma mensagem em syntax ou algo assim então vendo isso você já sabe como deve ser feito um gradio funcional que por padrão já tem o copiar e as syntax de código

Crie o código usando a api pra gerar as respostas.