BerriAI/litellm · error · HTTPException
Invalid fallback_type. Must be one of: {valid_fallback_types
Error message
Invalid fallback_type. Must be one of: {valid_fallback_types} What it means
Enum validation when building model-limit metadata: the fallback_type argument is not one of the recognized values (e.g. 'generic'/'context-window'). The valid set is listed in the message; the caller (or config) supplied an unsupported fallback classification.
Source
Thrown at litellm/proxy/utils.py:7046
configured_input, configured_output = llm_router.get_configured_token_limits(model_id)
if configured_input is not None:
max_input_tokens = configured_input
if configured_output is not None:
max_output_tokens = configured_output
if max_input_tokens is not None:
base["max_input_tokens"] = max_input_tokens
if max_output_tokens is not None:
base["max_output_tokens"] = max_output_tokens
if not include_metadata:
return base
effective_fallback_type: Final = fallback_type if fallback_type is not None else "general"
valid_fallback_types: Final = ["general", "context_window", "content_policy"]
if effective_fallback_type not in valid_fallback_types:
raise HTTPException(
status_code=400,
detail=f"Invalid fallback_type. Must be one of: {valid_fallback_types}",
)
fallbacks: Final = get_all_fallbacks(
model=model_id,
llm_router=llm_router,
fallback_type=effective_fallback_type,
)
return {**base, "metadata": {"fallbacks": fallbacks}}
def validate_model_access(
model_id: str,
available_models: list[str],
) -> None:
"""
Validate that a model is accessible to the user.View on GitHub (pinned to 77b7c6c40c)
Solutions
- Set fallback_type to one of the listed valid values.
Defensive patterns
Strategy: validation
When it happens
Trigger: Thrown at litellm/proxy/utils.py:7046 when the library encounters an invalid state.
Common situations: See trigger scenarios.
AI-assisted analysis of BerriAI/litellm@77b7c6c40c (2026-08-18).
Data as JSON: /api/errors/f11443ff2c939e18.
Report an issue: GitHub.