OpenAI

LiteLLM supports OpenAI Chat + Text completion and embedding calls.

API Keys

import os 

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

Need a dedicated key? Email us @ krrish@berri.ai

See all supported models by the litellm api key

Usage

import os 
from litellm import completion

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


messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion("gpt-3.5-turbo", messages)

OpenAI Chat Completion Models

Model Name	Function Call	Required OS Variables
gpt-3.5-turbo	`completion('gpt-3.5-turbo', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-3.5-turbo-0301	`completion('gpt-3.5-turbo-0301', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-3.5-turbo-0613	`completion('gpt-3.5-turbo-0613', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-3.5-turbo-16k	`completion('gpt-3.5-turbo-16k', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-3.5-turbo-16k-0613	`completion('gpt-3.5-turbo-16k-0613', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4	`completion('gpt-4', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4-0314	`completion('gpt-4-0314', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4-0613	`completion('gpt-4-0613', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4-32k	`completion('gpt-4-32k', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4-32k-0314	`completion('gpt-4-32k-0314', messages)`	`os.environ['OPENAI_API_KEY']`
gpt-4-32k-0613	`completion('gpt-4-32k-0613', messages)`	`os.environ['OPENAI_API_KEY']`

These also support the OPENAI_API_BASE environment variable, which can be used to specify a custom API endpoint.

OpenAI Text Completion Models / Instruct Models

Model Name	Function Call	Required OS Variables
gpt-3.5-turbo-instruct	`completion('gpt-3.5-turbo-instruct', messages)`	`os.environ['OPENAI_API_KEY'`
text-davinci-003	`completion('text-davinci-003', messages)`	`os.environ['OPENAI_API_KEY']`
ada-001	`completion('ada-001', messages)`	`os.environ['OPENAI_API_KEY']`
curie-001	`completion('curie-001', messages)`	`os.environ['OPENAI_API_KEY']`
babbage-001	`completion('babbage-001', messages)`	`os.environ['OPENAI_API_KEY']`
babbage-002	`completion('ada-001', messages)`	`os.environ['OPENAI_API_KEY']`
davinci-002	`completion('davinci-002', messages)`	`os.environ['OPENAI_API_KEY']`

Using Helicone Proxy with LiteLLM

import os 
import litellm
from litellm import completion

os.environ["OPENAI_API_KEY"] = ""

# os.environ["OPENAI_API_BASE"] = ""
litellm.api_base = "https://oai.hconeai.com/v1"
litellm.headers = {
    "Helicone-Auth": f"Bearer {os.getenv('HELICONE_API_KEY')}",
    "Helicone-Cache-Enabled": "true",
}

messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion("gpt-3.5-turbo", messages)

Using OpenAI Proxy with LiteLLM

import os 
import litellm
from litellm import completion

os.environ["OPENAI_API_KEY"] = ""

# set custom api base to your proxy
# either set .env or litellm.api_base
# os.environ["OPENAI_API_BASE"] = ""
litellm.api_base = "https://openai-proxy.berriai.repl.co"


messages = [{ "content": "Hello, how are you?","role": "user"}]

# openai call
response = completion("gpt-3.5-turbo", messages)

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