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That indicate that a user "does something". We track this with EBT. However, for capacity planning, we need to be able to predict usage at a lower level: LLM requests and token counts.
We can add the following metrics to these events:
input_tokens
output_tokens
llm_requests
We can also separately track LLM requests (in order to have a baseline, regardless of which event they belong to), with the following metrics:
input_tokens
output_tokens
response_time
Additionally, we can also track tool calls:
tool_name
input_tokens
output_tokens
response_time
is_error
The text was updated successfully, but these errors were encountered:
Currently, we have the following events:
observability_ai_assistant_user_sent_prompt_in_chat
observability_ai_assistant_insight_response
That indicate that a user "does something". We track this with EBT. However, for capacity planning, we need to be able to predict usage at a lower level: LLM requests and token counts.
We can add the following metrics to these events:
input_tokens
output_tokens
llm_requests
We can also separately track LLM requests (in order to have a baseline, regardless of which event they belong to), with the following metrics:
input_tokens
output_tokens
response_time
Additionally, we can also track tool calls:
tool_name
input_tokens
output_tokens
response_time
is_error
The text was updated successfully, but these errors were encountered: