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fix: remove recursive call #8225

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fix: remove recursive call #8225

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82472fd
fix: update model_prices_and_context_backup.json to match the base file
theGitNoob Feb 4, 2025
9db90b5
fix: remove recursive call
theGitNoob Feb 4, 2025
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8 changes: 4 additions & 4 deletions litellm/llms/together_ai/chat.py
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Original file line number Diff line number Diff line change
Expand Up @@ -8,7 +8,8 @@

from typing import Optional

from litellm import get_model_info, verbose_logger
from litellm import verbose_logger
from litellm.utils import get_model_param_support

from ..openai.chat.gpt_transformation import OpenAIGPTConfig

Expand All @@ -22,9 +23,8 @@ def get_supported_openai_params(self, model: str) -> list:
"""
supports_function_calling: Optional[bool] = None
try:
model_info = get_model_info(model, custom_llm_provider="together_ai")
supports_function_calling = model_info.get(
"supports_function_calling", False
supports_function_calling = get_model_param_support(
model, "supports_function_calling", custom_llm_provider="together_ai"
)
except Exception as e:
verbose_logger.debug(f"Error getting supported openai params: {e}")
Expand Down
29 changes: 17 additions & 12 deletions litellm/model_prices_and_context_window_backup.json
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Original file line number Diff line number Diff line change
Expand Up @@ -1956,7 +1956,7 @@
},
"mistral/open-mixtral-8x22b": {
"max_tokens": 8191,
"max_input_tokens": 64000,
"max_input_tokens": 65336,
"max_output_tokens": 8191,
"input_cost_per_token": 0.000002,
"output_cost_per_token": 0.000006,
Expand Down Expand Up @@ -2038,7 +2038,7 @@
},
"deepseek/deepseek-reasoner": {
"max_tokens": 8192,
"max_input_tokens": 64000,
"max_input_tokens": 65536,
"max_output_tokens": 8192,
"input_cost_per_token": 0.00000055,
"input_cost_per_token_cache_hit": 0.00000014,
Expand All @@ -2051,9 +2051,9 @@
"supports_prompt_caching": true
},
"deepseek/deepseek-chat": {
"max_tokens": 4096,
"max_input_tokens": 128000,
"max_output_tokens": 4096,
"max_tokens": 8192,
"max_input_tokens": 65536,
"max_output_tokens": 8192,
"input_cost_per_token": 0.00000014,
"input_cost_per_token_cache_hit": 0.000000014,
"cache_read_input_token_cost": 0.000000014,
Expand Down Expand Up @@ -3064,7 +3064,8 @@
"supports_function_calling": true,
"supports_tool_choice": true,
"supports_response_schema": true,
"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-1.5-pro"
"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-1.5-pro",
"deprecation_date": "2025-09-24"
},
"gemini-1.5-pro-001": {
"max_tokens": 8192,
Expand Down Expand Up @@ -3265,7 +3266,9 @@
"supports_function_calling": true,
"supports_vision": true,
"supports_response_schema": true,
"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-1.5-flash"
"source": "https://cloud.google.com/vertex-ai/generative-ai/docs/learn/models#gemini-1.5-flash",
"deprecation_date": "2025-09-24",
"deprecation_date": "2025-09-24"
},
"gemini-1.5-flash-001": {
"max_tokens": 8192,
Expand Down Expand Up @@ -4128,7 +4131,8 @@
"supports_prompt_caching": true,
"tpm": 4000000,
"rpm": 2000,
"source": "https://ai.google.dev/pricing"
"source": "https://ai.google.dev/pricing",
"deprecation_date": "2025-09-24"
},
"gemini/gemini-1.5-flash-001": {
"max_tokens": 8192,
Expand Down Expand Up @@ -4412,7 +4416,8 @@
"supports_prompt_caching": true,
"tpm": 4000000,
"rpm": 1000,
"source": "https://ai.google.dev/pricing"
"source": "https://ai.google.dev/pricing",
"deprecation_date": "2025-09-24"
},
"gemini/gemini-1.5-pro-001": {
"max_tokens": 8192,
Expand Down Expand Up @@ -4837,7 +4842,7 @@
},
"openrouter/deepseek/deepseek-r1": {
"max_tokens": 8192,
"max_input_tokens": 64000,
"max_input_tokens": 65336,
"max_output_tokens": 8192,
"input_cost_per_token": 0.00000055,
"input_cost_per_token_cache_hit": 0.00000014,
Expand All @@ -4851,8 +4856,8 @@
},
"openrouter/deepseek/deepseek-chat": {
"max_tokens": 8192,
"max_input_tokens": 66000,
"max_output_tokens": 4096,
"max_input_tokens": 65536,
"max_output_tokens": 8192,
"input_cost_per_token": 0.00000014,
"output_cost_per_token": 0.00000028,
"litellm_provider": "openrouter",
Expand Down
24 changes: 19 additions & 5 deletions litellm/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -419,7 +419,6 @@ def _custom_logger_class_exists_in_failure_callbacks(
def function_setup( # noqa: PLR0915
original_function: str, rules_obj, start_time, *args, **kwargs
): # just run once to check if user wants to send their data anywhere - PostHog/Sentry/Slack/etc.

### NOTICES ###
from litellm import Logging as LiteLLMLogging
from litellm.litellm_core_utils.litellm_logging import set_callbacks
Expand Down Expand Up @@ -4216,7 +4215,6 @@ def _get_model_info_helper( # noqa: PLR0915
):
_model_info = None
if _model_info is None and model in litellm.model_cost:

key = model
_model_info = _get_model_info_from_model_cost(key=key)
if not _check_provider_match(
Expand All @@ -4227,23 +4225,20 @@ def _get_model_info_helper( # noqa: PLR0915
_model_info is None
and combined_stripped_model_name in litellm.model_cost
):

key = combined_stripped_model_name
_model_info = _get_model_info_from_model_cost(key=key)
if not _check_provider_match(
model_info=_model_info, custom_llm_provider=custom_llm_provider
):
_model_info = None
if _model_info is None and stripped_model_name in litellm.model_cost:

key = stripped_model_name
_model_info = _get_model_info_from_model_cost(key=key)
if not _check_provider_match(
model_info=_model_info, custom_llm_provider=custom_llm_provider
):
_model_info = None
if _model_info is None and split_model in litellm.model_cost:

key = split_model
_model_info = _get_model_info_from_model_cost(key=key)
if not _check_provider_match(
Expand Down Expand Up @@ -4362,6 +4357,25 @@ def _get_model_info_helper( # noqa: PLR0915
)


def get_model_param_support(
model: str, param: str, custom_llm_provider: Optional[str]
) -> bool:
model_info = litellm.model_cost.get(model)
potential_model_names = _get_potential_model_names(
model=model, custom_llm_provider=custom_llm_provider
)

verbose_logger.debug(
f"checking potential_model_names in litellm.model_cost: {potential_model_names}"
)
# iterate over potential model names to get the model cost
for key, value in potential_model_names.items():
if value in litellm.model_cost and key != "custom_llm_provider":
return litellm.model_cost[value].get(param, False)

return False


def get_model_info(model: str, custom_llm_provider: Optional[str] = None) -> ModelInfo:
"""
Get a dict for the maximum tokens (context window), input_cost_per_token, output_cost_per_token for a given model.
Expand Down