---
title: "Rules"
url: "/docs/rules"
canonical_url: "https://docs.litellm.ai/docs/rules"
type: "docs"
last_updated: "2026-10-05"
summary: "Use this to fail a request based on the input or output of an llm api call."
related:
  - "/docs/extras/code_quality"
  - "/docs/proxy/team_based_routing"
---
# Rules

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


Use this to fail a request based on the input or output of an llm api call. 

```python
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-5.6-luna", 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 

```python
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 

```python
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-5.6-luna", messages=[{"role": "user", "content": "Hey, how's it going?"}])
```

### Example 2: Fallback to uncensored model if llm refuses to answer

```python
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-5.6-luna", messages=[{"role": "user", 
"content": "Hey, how's it going?"}], fallbacks=["openrouter/gryphe/mythomax-l2-13b"])
```

## Related pages

- [Code Quality](https://docs.litellm.ai/docs/extras/code_quality.md)
- [[DEPRECATED] Team-based Routing](https://docs.litellm.ai/docs/proxy/team_based_routing.md)