Fazendo requisições a modelos DeepSeek

Trabalhando com DeepSeek em Python

James Chapman

AI Curriculum Lead, DataCamp

Recapitulando

Um computador enviando uma requisição para a API da Together.ai, que contém o modelo e quaisquer dados e parâmetros do modelo.

Trabalhando com DeepSeek em Python

Criando uma requisição

from openai import OpenAI

# To send to DeepSeek API: base_url="https://api.deepseek.com" client = OpenAI(api_key="<TogetherAI API Key>", base_url="https://api.together.xyz/v1")
  • Crie requisições usando a biblioteca openai
  • OpenAI: desenvolvedores de modelos e apps de IA (por exemplo, ChatGPT)
  • base_url: redirecione a requisição de OpenAI para o provedor de modelos DeepSeek
  • api_key: autenticação da API (veja a documentação do provedor)
1 https://platform.deepseek.com/api_keys
Trabalhando com DeepSeek em Python

Criando uma requisição

from openai import OpenAI
# To send to DeepSeek API: base_url="https://api.deepseek.com"
client = OpenAI(api_key="<TogetherAI API Key>", base_url="https://api.together.xyz/v1")


response = client.chat.completions.create(
model="deepseek-ai/DeepSeek-V4-Pro",
messages=[{"role": "user", "content": "In one sentence, what is hallucination in AI?"}]
)
print(response)
Trabalhando com DeepSeek em Python

A resposta

ChatCompletion(id='onVWeEx-gBAtS-a09121fcae54578c', choices=[Choice(finish_reason='stop', index=0,
logprobs=None, message=ChatCompletionMessage(content='Hallucination in AI is when a model confidently
generates information that sounds plausible but is factually incorrect, misleading, or entirely
fabricated.', refusal=None, role='assistant', annotations=None, audio=None, function_call=None,
tool_calls=[]), seed=None)], created=1781018557, model='deepseek-ai/DeepSeek-V4-Pro',
object='chat.completion', moderation=None, service_tier=None, system_fingerprint='default',
usage=CompletionUsage(completion_tokens=28, prompt_tokens=15, total_tokens=43,
completion_tokens_details=None, prompt_tokens_details=PromptTokensDetails(audio_tokens=None,
cached_tokens=0)), prompt=[])
Trabalhando com DeepSeek em Python

A resposta

ChatCompletion(id='onVWeEx-gBAtS-a09121fcae54578c',
               choices=[Choice(finish_reason='stop', index=0, logprobs=None,
                               message=ChatCompletionMessage(content='Hallucination in AI refers...',
                               refusal=None, role='assistant', annotations=None, audio=None,
                               function_call=None, tool_calls=[]), seed=None)],
               created=1781018557,
               model='deepseek-ai/DeepSeek-V4-Pro',
               object='chat.completion',
               moderation=None,
               service_tier=None,
               system_fingerprint='default',
               usage=CompletionUsage(completion_tokens=28, prompt_tokens=15, total_tokens=43,
                                     completion_tokens_details=None,
                                     prompt_tokens_details=PromptTokensDetails(audio_tokens=None,
                                          cached_tokens=0)),
               prompt=[])
Trabalhando com DeepSeek em Python

Interpretando a resposta

print(response.choices)
[Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(
content='Hallucination in AI refers to the generation of false or nonsensical information
that is presented as factual, often due to limitations in training data, model biases, or
inference errors.', refusal=None, role='assistant', annotations=None, audio=None,
function_call=None, tool_calls=[]), seed=None)]
Trabalhando com DeepSeek em Python

Interpretando a resposta

print(response.choices[0])
Choice(finish_reason='stop', index=0, logprobs=None, message=ChatCompletionMessage(
content='Hallucination in AI refers to the generation of false or nonsensical information
that is presented as factual, often due to limitations in training data, model biases, or
inference errors.', refusal=None, role='assistant', annotations=None, audio=None,
function_call=None, tool_calls=[]), seed=None)
Trabalhando com DeepSeek em Python

Interpretando a resposta

print(response.choices[0].message)
ChatCompletionMessage(content='Hallucination in AI refers to the generation of false or
nonsensical information that is presented as factual, often due to limitations in training
data, model biases, or inference errors.', refusal=None, role='assistant', annotations=None,
audio=None, function_call=None, tool_calls=[])
print(response.choices[0].message.content)
Hallucination in AI refers to the generation of false or nonsensical information that is
presented as factual, often due to limitations in training data, model biases, or inference
errors.
Trabalhando com DeepSeek em Python

Custos de uso da API

 

  • Para DeepSeek:
    • Provedor (ex.: together.ai)
    • Modelo
    • Entradas + saídas maiores = custo maior

Uma estrada com pedágio.

1 https://api-docs.deepseek.com/quick_start/pricing
Trabalhando com DeepSeek em Python

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Trabalhando com DeepSeek em Python

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