Tracking LM Usage

Print and Reset LM Usage Stats

To track usage of the LLM you’ve configured, you can simply access the built-in print_total_usage

lotus.settings.lm.print_total_usage()

You can also reset the LLM usage stats as follows:

lotus.settings.lm.reset_stats()

Setting Usage Limits

As a safety measure, the LM class supports setting usage limits to control costs and token consumption. You can set limits on:

• Prompt tokens

• Completion tokens

• Total tokens

• Total cost

When any limit is exceeded, a LotusUsageLimitException will be raised.

Example setting usage limits:

from lotus.models import LM
from lotus.types import UsageLimit, LotusUsageLimitException

# Set limits
usage_limit = UsageLimit(
    prompt_tokens_limit=4000,
    completion_tokens_limit=1000,
    total_tokens_limit=3000,
    total_cost_limit=1.00
)
lm = LM(model="gpt-4o", physical_usage_limit=usage_limit)

try:
    course_df = pd.read_csv("course_df.csv")
    course_df = course_df.sem_filter("What {Course Name} requires a lot of math")
except LotusUsageLimitException as e:
    print(f"Usage limit exceeded: {e}")
    # Handle the exception as needed