Skip to main content
Version: v1.6.1 🚧

View performance metrics for configured and unconfigured LLMs

Overview​

Users can view the performance metrics of large language models (LLMs) configured or no longer configured within the environment.

Example​

from h2ogpte import H2OGPTE

client = H2OGPTE(
    address="https://h2ogpte.genai.h2o.ai",
    api_key='sk-XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX',
)

# The `get_llm_performance_by_llm` method returns a list containing performance metrics for each configured or no longer configured LLM within the environment.
# The available units for time intervals are:
# - minute / minutes (for example, 5 minutes)
# - hour / hours (for example, 2 hours)
# - day / days (for example, 3 days)
# - week / weeks (for example, 1 week)
# - year / years (for example, 1 year)
list_of_performance_metrics = client.get_llm_performance_by_llm(interval="3 months") 

for performance in list_of_performance_metrics[:1]:
    print(
        f"LLM name: {performance.llm_name}\n"
        f"Input tokens: {performance.input_tokens}\n"
        f"Model computed fields: {performance.model_computed_fields}\n"
        f"Model config: {performance.model_config}\n"
        f"Model fields: {performance.model_fields}\n"
        f"Output tokens: {performance.output_tokens}\n"
        f"Time to first token: {performance.time_to_first_token}\n"
        f"Tokens per second: {performance.tokens_per_second}"
    )
LLM name: claude-3-5-sonnet-20240620
Input tokens: 347003436
Model computed fields: {}
Model config: {}
Model fields: {'llm_name': FieldInfo(annotation=str, required=True), 'call_count': FieldInfo(annotation=int, required=True), 'input_tokens': FieldInfo(annotation=int, required=True), 'output_tokens': FieldInfo(annotation=int, required=True), 'tokens_per_second': FieldInfo(annotation=float, required=True), 'time_to_first_token': FieldInfo(annotation=float, required=True)}
Output tokens: 34691224
Time to first token: 1.7457449999999999
Tokens per second: 45.505
Feedback