2973ff8be9
* fix: remove slow string operation * fix: behavior change * fix: behavior change * fix: avoid default call
56 lines
2.2 KiB
Python
56 lines
2.2 KiB
Python
from typing import Optional
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import litellm
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class Rules:
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"""
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Fail calls based on the input or llm api output
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Example usage:
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import litellm
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def my_custom_rule(input): # receives the model response
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if "i don't think i can answer" in input: # trigger fallback if the model refuses to answer
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return False
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return True
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litellm.post_call_rules = [my_custom_rule] # have these be functions that can be called to fail a call
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response = litellm.completion(model="gpt-3.5-turbo", messages=[{"role": "user",
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"content": "Hey, how's it going?"}], fallbacks=["openrouter/mythomax"])
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"""
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def __init__(self) -> None:
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pass
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@staticmethod
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def has_pre_call_rules() -> bool:
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"""Check if any pre-call rules are configured"""
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return len(litellm.pre_call_rules) > 0
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def pre_call_rules(self, input: str, model: str):
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for rule in litellm.pre_call_rules:
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if callable(rule):
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decision = rule(input)
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if decision is False:
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raise litellm.APIResponseValidationError(message="LLM Response failed post-call-rule check", llm_provider="", model=model) # type: ignore
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return True
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def post_call_rules(self, input: Optional[str], model: str) -> bool:
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if input is None:
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return True
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for rule in litellm.post_call_rules:
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if callable(rule):
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decision = rule(input)
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if isinstance(decision, bool):
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if decision is False:
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raise litellm.APIResponseValidationError(message="LLM Response failed post-call-rule check", llm_provider="", model=model) # type: ignore
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elif isinstance(decision, dict):
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decision_val = decision.get("decision", True)
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decision_message = decision.get(
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"message", "LLM Response failed post-call-rule check"
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)
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if decision_val is False:
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raise litellm.APIResponseValidationError(message=decision_message, llm_provider="", model=model) # type: ignore
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return True
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