Rules
Use this to fail a request based on the input or output of an llm api call.
import litellm
import os
# set env vars
os.environ["OPENAI_API_KEY"] = "your-api-key"
os.environ["OPENROUTER_API_KEY"] = "your-api-key"
def my_custom_rule(input): # receives the model response
if "i don't think i can answer" in input: # trigger fallback if the model refuses to answer
return False
return True
litellm.post_call_rules = [my_custom_rule] # have these be functions that can be called to fail a call
response = litellm.completion(model="gpt-3.5-turbo", messages=[{"role": "user",
"content": "Hey, how's it going?"}], fallbacks=["openrouter/gryphe/mythomax-l2-13b"])
Available Endpointsβ
-
litellm.pre_call_rules = []- A list of functions to iterate over before making the api call. Each function is expected to return either True (allow call) or False (fail call). -
litellm.post_call_rules = []- List of functions to iterate over before making the api call. Each function is expected to return either True (allow call) or False (fail call).
Expected format of ruleβ
def my_custom_rule(input: str) -> bool: # receives the model response
if "i don't think i can answer" in input: # trigger fallback if the model refuses to answer
return False
return True
Inputsβ
input: str: The user input or llm response.
Outputsβ
bool: Return True (allow call) or False (fail call)
Example Rulesβ
Example 1: Fail if user input is too longβ
import litellm
import os
# set env vars
os.environ["OPENAI_API_KEY"] = "your-api-key"
def my_custom_rule(input): # receives the model response
if len(input) > 10: # fail call if too long
return False
return True
litellm.pre_call_rules = [my_custom_rule] # have these be functions that can be called to fail a call
response = litellm.completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hey, how's it going?"}])
Example 2: Fallback to uncensored model if llm refuses to answerβ
import litellm
import os
# set env vars
os.environ["OPENAI_API_KEY"] = "your-api-key"
os.environ["OPENROUTER_API_KEY"] = "your-api-key"
def my_custom_rule(input): # receives the model response
if "i don't think i can answer" in input: # trigger fallback if the model refuses to answer
return False
return True
litellm.post_call_rules = [my_custom_rule] # have these be functions that can be called to fail a call
response = litellm.completion(model="gpt-3.5-turbo", messages=[{"role": "user",
"content": "Hey, how's it going?"}], fallbacks=["openrouter/gryphe/mythomax-l2-13b"])