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add token usage

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This commit is contained in:
Krrish Dholakia 2023-08-08 21:11:06 -07:00
parent 39efc57d84
commit a9186dc40c
5 changed files with 70 additions and 5 deletions
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24
litellm/utils.py
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@ -133,9 +133,8 @@ def client(original_function):
####### USAGE CALCULATOR ################
def prompt_token_calculator(model, messages):
def token_counter(model, text):
# use tiktoken or anthropic's tokenizer depending on the model
text = " ".join(message["content"] for message in messages)
num_tokens = 0
if "claude" in model:
install_and_import('anthropic')
@ -168,9 +167,15 @@ def cost_per_token(model="gpt-3.5-turbo", prompt_tokens = 0, completion_tokens =
avg_output_cost = output_cost_sum / len(model_cost_ref.keys())
prompt_tokens_cost_usd_dollar = avg_input_cost * prompt_tokens
completion_tokens_cost_usd_dollar = avg_output_cost * completion_tokens
return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar
return prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar
def completion_cost(model="gpt-3.5-turbo", prompt="", completion=""):
prompt_tokens = tokenizer(model=model, text=prompt)
completion_tokens = tokenizer(model=model, text=completion)
prompt_tokens_cost_usd_dollar, completion_tokens_cost_usd_dollar = cost_per_token(model=model, prompt_tokens = prompt_tokens, completion_tokens = completion_tokens)
return prompt_tokens_cost_usd_dollar + completion_tokens_cost_usd_dollar
####### HELPER FUNCTIONS ################
def get_optional_params(
# 12 optional params
@ -466,6 +471,19 @@ def handle_success(args, kwargs, result, start_time, end_time):
print_verbose(f"[Non-Blocking] Success Callback Error - {traceback.format_exc()}")
pass
def prompt_token_calculator(model, messages):
# use tiktoken or anthropic's tokenizer depending on the model
text = " ".join(message["content"] for message in messages)
num_tokens = 0
if "claude" in model:
install_and_import('anthropic')
from anthropic import Anthropic, HUMAN_PROMPT, AI_PROMPT
anthropic = Anthropic()
num_tokens = anthropic.count_tokens(text)
else:
num_tokens = len(encoding.encode(text))
return num_tokens
# integration helper function
def modify_integration(integration_name, integration_params):
global supabaseClient