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feat: Add new compact MetricInResponse type (#1593)

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# What does this PR do?
This change adds a compact type to include metrics in response as
opposed to the full MetricEvent which is relevant for internal logging
purposes.

## Test Plan
```
LLAMA_STACK_CONFIG=~/.llama/distributions/fireworks/fireworks-run.yaml pytest -s -v agents/test_agents.py --safety-shield meta-llama/Llama-Guard-3-8B --text-model meta-llama/Llama-3.1-8B-Instruct

 llama stack run ~/.llama/distributions/fireworks/fireworks-run.yaml

curl --request POST \
  --url http://localhost:8321/v1/inference/chat-completion \
  --header 'content-type: application/json' \
  --data '{
  "model_id": "meta-llama/Llama-3.1-70B-Instruct",
  "messages": [
    {
      "role": "user",
      "content": {
        "type": "text",
        "text": "where do humans live"
      }
    }
  ],
  "stream": false
}'

{
  "metrics": [
    {
      "metric": "prompt_tokens",
      "value": 10,
      "unit": null
    },
    {
      "metric": "completion_tokens",
      "value": 522,
      "unit": null
    },
    {
      "metric": "total_tokens",
      "value": 532,
      "unit": null
    }
  ],
  "completion_message": {
    "role": "assistant",
    "content": "Humans live in various parts of the world...............",
    "stop_reason": "out_of_tokens",
    "tool_calls": []
  },
  "logprobs": null
}
```
This commit is contained in:
Dinesh Yeduguru 2025-03-12 15:45:44 -07:00 • committed by GitHub
parent ad939c97c3
commit 99bbe0e70b
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4 changed files with 150 additions and 80 deletions
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6
llama_stack/distribution/routers/routers.py
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@ -48,7 +48,7 @@ from llama_stack.apis.scoring import (
ScoringFnParams,
)
from llama_stack.apis.shields import Shield
from llama_stack.apis.telemetry import MetricEvent, Telemetry
from llama_stack.apis.telemetry import MetricEvent, MetricInResponse, Telemetry
from llama_stack.apis.tools import (
RAGDocument,
RAGQueryConfig,
@ -206,12 +206,12 @@ class InferenceRouter(Inference):
completion_tokens: int,
total_tokens: int,
model: Model,
) -> List[MetricEvent]:
) -> List[MetricInResponse]:
metrics = self._construct_metrics(prompt_tokens, completion_tokens, total_tokens, model)
if self.telemetry:
for metric in metrics:
await self.telemetry.log_event(metric)
return metrics
return [MetricInResponse(metric=metric.metric, value=metric.value) for metric in metrics]
async def _count_tokens(
self,