docs/my-website/docs/rules.md

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 Endpoints

• 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 rule

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 

Inputs

• input: str: The user input or llm response.

Outputs

• bool: Return True (allow call) or False (fail call)

Example Rules

Example 1: Fail if user input is too long

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 answer

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"])