Setting API Keys, Base, Version
LiteLLM allows you to specify the following:
- API Key
- API Base
- API Version
- API Type
Useful Helper functions:
You can set the API configs using:
- Environment Variables
- litellm variables
litellm.api_key
- Passing args to
completion()
Environment Variables​
Setting API Keys​
Set the liteLLM API key or specific provider key:
import os
# Set OpenAI API key
os.environ["OPENAI_API_KEY"] = "Your API Key"
os.environ["ANTHROPIC_API_KEY"] = "Your API Key"
os.environ["REPLICATE_API_KEY"] = "Your API Key"
os.environ["TOGETHERAI_API_KEY"] = "Your API Key"
Setting API Base, API Version, API Type​
# for azure openai
os.environ['AZURE_API_BASE'] = "https://openai-gpt-4-test2-v-12.openai.azure.com/"
os.environ['AZURE_API_VERSION'] = "2023-05-15" # [OPTIONAL]
os.environ['AZURE_API_TYPE'] = "azure" # [OPTIONAL]
# for openai
os.environ['OPENAI_API_BASE'] = "https://openai-gpt-4-test2-v-12.openai.azure.com/"
litellm variables​
litellm.api_key​
This variable is checked for all providers
import litellm
# openai call
litellm.api_key = "sk-OpenAIKey"
response = litellm.completion(messages=messages, model="gpt-3.5-turbo")
# anthropic call
litellm.api_key = "sk-AnthropicKey"
response = litellm.completion(messages=messages, model="claude-2")
litellm.provider_key (example litellm.openai_key)​
litellm.openai_key = "sk-OpenAIKey"
response = litellm.completion(messages=messages, model="gpt-3.5-turbo")
# anthropic call
litellm.anthropic_key = "sk-AnthropicKey"
response = litellm.completion(messages=messages, model="claude-2")
litellm.api_base​
import litellm
litellm.api_base = "https://hosted-llm-api.co"
response = litellm.completion(messages=messages, model="gpt-3.5-turbo")
litellm.organization​
import litellm
litellm.organization = "LiteLlmOrg"
response = litellm.completion(messages=messages, model="gpt-3.5-turbo")
Passing Args to completion()​
You can pass the API key within completion()
call:
api_key​
from litellm import completion
messages = [{ "content": "Hello, how are you?","role": "user"}]
response = completion("command-nightly", messages, api_key="Your-Api-Key")
api_base​
from litellm import completion
messages = [{ "content": "Hello, how are you?","role": "user"}]
response = completion("command-nightly", messages, api_base="https://hosted-llm-api.co")
api_version​
from litellm import completion
messages = [{ "content": "Hello, how are you?","role": "user"}]
response = completion("command-nightly", messages, api_version="2023-02-15")
Helper Functions​
check_valid_key()
​
Check if a user submitted a valid key for the model they're trying to call.
key = "bad-key"
response = check_valid_key(model="gpt-3.5-turbo", api_key=key)
assert(response == False)
get_valid_models()
​
This helper reads the .env and returns a list of supported llms for user
old_environ = os.environ
os.environ = {'OPENAI_API_KEY': 'temp'} # mock set only openai key in environ
valid_models = get_valid_models()
print(valid_models)
# list of openai supported llms on litellm
expected_models = litellm.open_ai_chat_completion_models + litellm.open_ai_text_completion_models
assert(valid_models == expected_models)
# reset replicate env key
os.environ = old_environ
validate_environment(model: str)
​
This helper tells you if you have all the required environment variables for a model, and if not - what's missing.
from litellm import validate_environment
print(validate_environment("openai/gpt-3.5-turbo"))