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fix(vertex_httpx.py): check if model supports system messages before sending separately

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Krrish Dholakia 2024-06-17 17:30:38 -07:00
parent a80520004e
commit 3d9ef689e7
7 changed files with 190 additions and 73 deletions
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82
litellm/utils.py
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@ -1823,6 +1823,32 @@ def supports_httpx_timeout(custom_llm_provider: str) -> bool:
return False
def supports_system_messages(model: str, custom_llm_provider: Optional[str]) -> bool:
"""
Check if the given model supports function calling and return a boolean value.
Parameters:
model (str): The model name to be checked.
Returns:
bool: True if the model supports function calling, False otherwise.
Raises:
Exception: If the given model is not found in model_prices_and_context_window.json.
"""
try:
model_info = litellm.get_model_info(
model=model, custom_llm_provider=custom_llm_provider
)
if model_info.get("supports_system_messages", False) is True:
return True
return False
except Exception:
raise Exception(
f"Model not in model_prices_and_context_window.json. You passed model={model}, custom_llm_provider={custom_llm_provider}."
)
def supports_function_calling(model: str) -> bool:
"""
Check if the given model supports function calling and return a boolean value.
@ -1838,7 +1864,7 @@ def supports_function_calling(model: str) -> bool:
"""
if model in litellm.model_cost:
model_info = litellm.model_cost[model]
if model_info.get("supports_function_calling", False):
if model_info.get("supports_function_calling", False) is True:
return True
return False
else:
@ -1862,7 +1888,7 @@ def supports_vision(model: str):
"""
if model in litellm.model_cost:
model_info = litellm.model_cost[model]
if model_info.get("supports_vision", False):
if model_info.get("supports_vision", False) is True:
return True
return False
else:
@ -1884,7 +1910,7 @@ def supports_parallel_function_calling(model: str):
"""
if model in litellm.model_cost:
model_info = litellm.model_cost[model]
if model_info.get("supports_parallel_function_calling", False):
if model_info.get("supports_parallel_function_calling", False) is True:
return True
return False
else:
@ -4319,14 +4345,17 @@ def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> Mod
)
if custom_llm_provider == "huggingface":
max_tokens = _get_max_position_embeddings(model_name=model)
return {
"max_tokens": max_tokens, # type: ignore
"input_cost_per_token": 0,
"output_cost_per_token": 0,
"litellm_provider": "huggingface",
"mode": "chat",
"supported_openai_params": supported_openai_params,
}
return ModelInfo(
max_tokens=max_tokens, # type: ignore
max_input_tokens=None,
max_output_tokens=None,
input_cost_per_token=0,
output_cost_per_token=0,
litellm_provider="huggingface",
mode="chat",
supported_openai_params=supported_openai_params,
supports_system_messages=None,
)
else:
"""
Check if: (in order of specificity)
@ -4361,6 +4390,21 @@ def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> Mod
pass
else:
raise Exception
return ModelInfo(
max_tokens=_model_info.get("max_tokens", None),
max_input_tokens=_model_info.get("max_input_tokens", None),
max_output_tokens=_model_info.get("max_output_tokens", None),
input_cost_per_token=_model_info.get("input_cost_per_token", 0),
output_cost_per_token=_model_info.get("output_cost_per_token", 0),
litellm_provider=_model_info.get(
"litellm_provider", custom_llm_provider
),
mode=_model_info.get("mode"),
supported_openai_params=supported_openai_params,
supports_system_messages=_model_info.get(
"supports_system_messages", None
),
)
return _model_info
elif split_model in litellm.model_cost:
_model_info = litellm.model_cost[split_model]
@ -4375,7 +4419,21 @@ def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> Mod
pass
else:
raise Exception
return _model_info
return ModelInfo(
max_tokens=_model_info.get("max_tokens", None),
max_input_tokens=_model_info.get("max_input_tokens", None),
max_output_tokens=_model_info.get("max_output_tokens", None),
input_cost_per_token=_model_info.get("input_cost_per_token", 0),
output_cost_per_token=_model_info.get("output_cost_per_token", 0),
litellm_provider=_model_info.get(
"litellm_provider", custom_llm_provider
),
mode=_model_info.get("mode"),
supported_openai_params=supported_openai_params,
supports_system_messages=_model_info.get(
"supports_system_messages", None
),
)
else:
raise ValueError(
"This model isn't mapped yet. Add it here - https://github.com/BerriAI/litellm/blob/main/model_prices_and_context_window.json"