llama-stack-mirror/tests/integration/recordings/responses/d0ac68cbde69.json
Charlie Doern 0caef40e0d
fix: telemetry fixes (inference and core telemetry) (#2733)
# What does this PR do?

I found a few issues while adding new metrics for various APIs:

currently metrics are only propagated in `chat_completion` and
`completion`

since most providers use the `openai_..` routes as the default in
`llama-stack-client inference chat-completion`, metrics are currently
not working as expected.

in order to get them working the following had to be done:

1. get the completion as usual
2. use new `openai_` versions of the metric gathering functions which
use `.usage` from the `OpenAI..` response types to gather the metrics
which are already populated.
3. define a `stream_generator` which counts the tokens and computes the
metrics (only for stream=True)
5. add metrics to response


NOTE: I could not add metrics to `openai_completion` where stream=True
because that ONLY returns an `OpenAICompletion` not an AsyncGenerator
that we can manipulate.


acquire the lock, and add event to the span as the other `_log_...`
methods do

some new output:

`llama-stack-client inference chat-completion --message hi`

<img width="2416" height="425" alt="Screenshot 2025-07-16 at 8 28 20 AM"
src="https://github.com/user-attachments/assets/ccdf1643-a184-4ddd-9641-d426c4d51326"
/>


and in the client:

<img width="763" height="319" alt="Screenshot 2025-07-16 at 8 28 32 AM"
src="https://github.com/user-attachments/assets/6bceb811-5201-47e9-9e16-8130f0d60007"
/>

these were not previously being recorded nor were they being printed to
the server due to the improper console sink handling

---------

Signed-off-by: Charlie Doern <cdoern@redhat.com>
2025-08-06 13:37:40 -07:00

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JSON

{
"request": {
"method": "POST",
"url": "http://localhost:11434/api/ps",
"headers": {},
"body": {},
"endpoint": "/api/ps",
"model": ""
},
"response": {
"body": {
"__type__": "ollama._types.ProcessResponse",
"__data__": {
"models": [
{
"model": "llama3.2:3b",
"name": "llama3.2:3b",
"digest": "a80c4f17acd55265feec403c7aef86be0c25983ab279d83f3bcd3abbcb5b8b72",
"expires_at": "2025-08-06T15:57:21.573326-04:00",
"size": 4030033920,
"size_vram": 4030033920,
"details": {
"parent_model": "",
"format": "gguf",
"family": "llama",
"families": [
"llama"
],
"parameter_size": "3.2B",
"quantization_level": "Q4_K_M"
}
}
]
}
},
"is_streaming": false
}
}