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add embedding cost tracking to gigachat proxy route

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This commit is contained in:
KnyazSh 2026-05-08 14:35:16 +00:00
parent 120f51a39d
commit 9ecfac90de
1 changed files with 48 additions and 22 deletions
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70
litellm/llms/gigachat/passthrough/transformation.py
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@ -9,6 +9,8 @@ from litellm.llms.gigachat.chat.streaming import GigaChatModelResponseIterator
from litellm.llms.gigachat.utils import get_api_base
from litellm.secret_managers.main import get_secret_str
from litellm.types.llms.openai import AllMessageValues
from litellm.types.utils import EmbeddingResponse
if TYPE_CHECKING:
from httpx import URL, Response
@ -80,32 +82,56 @@ class GigaChatPassthroughConfig(BasePassthroughConfig):
from litellm.types.utils import LlmProviders, ModelResponse
from litellm.utils import ProviderConfigManager
# cost tracking only for completions
if "completions" not in endpoint:
return None
# cost tracking only for completions and embeddings
if "completions" in endpoint:
provider_chat_config = ProviderConfigManager.get_provider_chat_config(
provider=LlmProviders(custom_llm_provider),
model=model,
)
provider_chat_config = ProviderConfigManager.get_provider_chat_config(
provider=LlmProviders(custom_llm_provider),
model=model,
)
if provider_chat_config is None:
raise ValueError(f"No provider config found for model: {model}")
if provider_chat_config is None:
raise ValueError(f"No provider config found for model: {model}")
litellm_model_response: ModelResponse = provider_chat_config.transform_response(
model=model,
messages=request_data.get("messages", []),
raw_response=httpx_response,
model_response=ModelResponse(),
logging_obj=logging_obj,
optional_params={},
litellm_params={},
api_key="",
request_data=request_data,
encoding=encoding,
)
litellm_model_response: ModelResponse = provider_chat_config.transform_response(
model=model,
messages=request_data.get("messages", []),
raw_response=httpx_response,
model_response=ModelResponse(),
logging_obj=logging_obj,
optional_params={},
litellm_params={},
api_key="",
request_data=request_data,
encoding=encoding,
)
return litellm_model_response
return litellm_model_response
if "embeddings" in endpoint:
provider_embedding_config = ProviderConfigManager.get_provider_embedding_config(
provider=LlmProviders(custom_llm_provider),
model=model,
)
if provider_embedding_config is None:
raise ValueError(f"No provider config found for model: {model}")
litellm_embedding_response: EmbeddingResponse = provider_embedding_config.transform_embedding_response(
model=model,
raw_response=httpx_response,
model_response=EmbeddingResponse(),
logging_obj=logging_obj,
optional_params={},
api_key="",
request_data=request_data,
litellm_params={},
)
return litellm_embedding_response
return None
def handle_logging_collected_chunks(
self,