flearc commented on PR #12841:
URL: https://github.com/apache/apisix/pull/12841#issuecomment-3692459038
> Another possible solution is to check if `request_type` is `ai_stream` or
`ai_chat`, and report accordingly. I tried changing the check to report if
`ctx.var.llm_time_to_first_token != 0`, but this might affect abnormal
requests. If possible, I can continue to refine this issue based on the
discussion.
```
if llm_time_to_first_token ~= "0" then
metrics.llm_latency:observe(tonumber(llm_time_to_first_token),
gen_arr(route_id, service_id, consumer_name, balancer_ip,
vars.request_type, vars.request_llm_model, vars.llm_model,
unpack(extra_labels("llm_latency", ctx))))
end
if vars.llm_prompt_tokens ~= "0" then
metrics.llm_prompt_tokens:inc(tonumber(vars.llm_prompt_tokens),
gen_arr(route_id, service_id, consumer_name, balancer_ip,
vars.request_type, vars.request_llm_model, vars.llm_model,
unpack(extra_labels("llm_prompt_tokens", ctx))))
end
if vars.llm_completion_tokens ~= "0" then
metrics.llm_completion_tokens:inc(tonumber(vars.llm_completion_tokens),
gen_arr(route_id, service_id, consumer_name, balancer_ip,
vars.request_type, vars.request_llm_model, vars.llm_model,
unpack(extra_labels("llm_completion_tokens", ctx))))
end
```
Adjust the if statement might help
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