OpenAI

OpenAI (텍스트 Completion)

LiteLLM은 OpenAI 텍스트 completion 모델을 지원해요.

필요한 API 키 (Required API Keys)

import os
os.environ["OPENAI_API_KEY"] = "your-api-key"

사용법 (Usage)

import os
from litellm import completion

os.environ["OPENAI_API_KEY"] = "your-api-key"

# openai call
response = completion(
    model = "gpt-3.5-turbo-instruct",
    messages=[{ "content": "Hello, how are you?","role": "user"}]
)

사용법 - LiteLLM Proxy Server

LiteLLM Proxy Server로 OpenAI 모델을 호출하는 방법이에요.

1. 환경에 키 저장

export OPENAI_API_KEY=""

2. 프록시 시작

  • config.yaml
  • config.yaml - 모든 OpenAI 모델 프록시
  • CLI
model_list:
  - model_name: gpt-5.6-luna
    litellm_params:
      model: openai/gpt-5.6-luna                          # The `openai/` prefix will call openai.chat.completions.create
      api_key: os.environ/OPENAI_API_KEY
  - model_name: gpt-3.5-turbo-instruct
    litellm_params:
      model: text-completion-openai/gpt-3.5-turbo-instruct # The `text-completion-openai/` prefix will call openai.completions.create
      api_key: os.environ/OPENAI_API_KEY

하나의 API 키로 모든 openai 모델을 추가하려면 다음을 사용해요. 경고: 로드밸런싱은 하지 않아요. 즉, gpt-5.6-terra, gpt-5.6-luna 요청이 모두 이 라우트로 가요.

model_list:
  - model_name: "*"             # all requests where model not in your config go to this deployment
    litellm_params:
      model: openai/*           # set `openai/` to use the openai route
      api_key: os.environ/OPENAI_API_KEY

$ litellm --model gpt-3.5-turbo-instruct

# Server running on http://0.0.0.0:4000

3. 테스트

  • Curl Request
  • OpenAI v1.0.0+
  • Langchain
curl --location 'http://0.0.0.0:4000/chat/completions' \
--header 'Content-Type: application/json' \
--data ' {
      "model": "gpt-3.5-turbo-instruct",
      "messages": [
        {
          "role": "user",
          "content": "what llm are you"
        }
      ]
    }
'

import openai
client = openai.OpenAI(
    api_key="anything",
    base_url="http://0.0.0.0:4000"
)

# request sent to model set on litellm proxy, `litellm --model`
response = client.chat.completions.create(model="gpt-3.5-turbo-instruct", messages = [
    {
        "role": "user",
        "content": "this is a test request, write a short poem"
    }
])

print(response)

from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import (
    ChatPromptTemplate,
    HumanMessagePromptTemplate,
    SystemMessagePromptTemplate,
)
from langchain.schema import HumanMessage, SystemMessage

chat = ChatOpenAI(
    openai_api_base="http://0.0.0.0:4000", # set openai_api_base to the LiteLLM Proxy
    model = "gpt-3.5-turbo-instruct",
    temperature=0.1
)

messages = [
    SystemMessage(
        content="You are a helpful assistant that im using to make a test request to."
    ),
    HumanMessage(
        content="test from litellm. tell me why it's amazing in 1 sentence"
    ),
]
response = chat(messages)

print(response)

OpenAI 텍스트 Completion 모델 / Instruct 모델

모델명 함수 호출
gpt-3.5-turbo-instruct response = completion(model="gpt-3.5-turbo-instruct", messages=messages)
gpt-3.5-turbo-instruct-0914 response = completion(model="gpt-3.5-turbo-instruct-0914", messages=messages)
babbage-002 response = completion(model="babbage-002", messages=messages)
davinci-002 response = completion(model="davinci-002", messages=messages)

출처: 문서

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