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| """ | |
| Helper util for handling databricks-specific cost calculation | |
| - e.g.: handling 'dbrx-instruct-*' | |
| """ | |
| from typing import Tuple | |
| from litellm.types.utils import Usage | |
| from litellm.utils import get_model_info | |
| def cost_per_token(model: str, usage: Usage) -> Tuple[float, float]: | |
| """ | |
| Calculates the cost per token for a given model, prompt tokens, and completion tokens. | |
| Input: | |
| - model: str, the model name without provider prefix | |
| - usage: LiteLLM Usage block, containing anthropic caching information | |
| Returns: | |
| Tuple[float, float] - prompt_cost_in_usd, completion_cost_in_usd | |
| """ | |
| base_model = model | |
| if model.startswith("databricks/dbrx-instruct") or model.startswith( | |
| "dbrx-instruct" | |
| ): | |
| base_model = "databricks-dbrx-instruct" | |
| elif model.startswith("databricks/meta-llama-3.1-70b-instruct") or model.startswith( | |
| "meta-llama-3.1-70b-instruct" | |
| ): | |
| base_model = "databricks-meta-llama-3-1-70b-instruct" | |
| elif model.startswith( | |
| "databricks/meta-llama-3.1-405b-instruct" | |
| ) or model.startswith("meta-llama-3.1-405b-instruct"): | |
| base_model = "databricks-meta-llama-3-1-405b-instruct" | |
| elif model.startswith("databricks/mixtral-8x7b-instruct-v0.1") or model.startswith( | |
| "mixtral-8x7b-instruct-v0.1" | |
| ): | |
| base_model = "databricks-mixtral-8x7b-instruct" | |
| elif model.startswith("databricks/mixtral-8x7b-instruct-v0.1") or model.startswith( | |
| "mixtral-8x7b-instruct-v0.1" | |
| ): | |
| base_model = "databricks-mixtral-8x7b-instruct" | |
| elif model.startswith("databricks/bge-large-en") or model.startswith( | |
| "bge-large-en" | |
| ): | |
| base_model = "databricks-bge-large-en" | |
| elif model.startswith("databricks/gte-large-en") or model.startswith( | |
| "gte-large-en" | |
| ): | |
| base_model = "databricks-gte-large-en" | |
| elif model.startswith("databricks/llama-2-70b-chat") or model.startswith( | |
| "llama-2-70b-chat" | |
| ): | |
| base_model = "databricks-llama-2-70b-chat" | |
| ## GET MODEL INFO | |
| model_info = get_model_info(model=base_model, custom_llm_provider="databricks") | |
| ## CALCULATE INPUT COST | |
| prompt_cost: float = usage["prompt_tokens"] * model_info["input_cost_per_token"] | |
| ## CALCULATE OUTPUT COST | |
| completion_cost = usage["completion_tokens"] * model_info["output_cost_per_token"] | |
| return prompt_cost, completion_cost | |