OpenAI
LiteLLM supports OpenAI Chat + Text completion and embedding calls.
API KEYS
import os
os.environ["OPENAI_API_KEY"] = ""
Usage
import os
from litellm import completion
os.environ["OPENAI_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
| Model Name | Function Call | Required OS Variables |
|---|---|---|
| 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 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)