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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>
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tests/integration/recordings/responses/c9667519ad7c.json
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tests/integration/recordings/responses/c9667519ad7c.json
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{
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"request": {
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"method": "POST",
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"url": "http://localhost:11434/v1/v1/completions",
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"headers": {},
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"body": {
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"model": "llama3.2:3b-instruct-fp16",
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"messages": [
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{
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"role": "user",
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"content": "Test trace openai with temperature 1"
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}
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],
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"max_tokens": 100,
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"stream": false,
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"temperature": 0.7
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},
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"endpoint": "/v1/completions",
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"model": "llama3.2:3b-instruct-fp16"
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},
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"response": {
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"body": {
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"__type__": "openai.types.chat.chat_completion.ChatCompletion",
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"__data__": {
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"id": "chatcmpl-521",
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"choices": [
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{
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"finish_reason": "length",
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"index": 0,
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"logprobs": null,
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"message": {
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"content": "You want to test the functionality of OpenAI's Text Completion model, also known as \"text completion\" or \"prompt engineering,\" by setting the temperature parameter to 1.\n\n**What is Temperature?**\n\nTemperature controls how different and diverse the generated text will be. A lower temperature (e.g., 0.5) produces more coherent and similar outputs, while a higher temperature (e.g., 2) produces more varied and less likely outputs. In this case, setting the temperature to ",
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"refusal": null,
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"role": "assistant",
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"annotations": null,
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"audio": null,
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"function_call": null,
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"tool_calls": null
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}
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}
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],
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"created": 1754051837,
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"model": "llama3.2:3b-instruct-fp16",
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"object": "chat.completion",
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"service_tier": null,
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"system_fingerprint": "fp_ollama",
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"usage": {
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"completion_tokens": 100,
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"prompt_tokens": 33,
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"total_tokens": 133,
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"completion_tokens_details": null,
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"prompt_tokens_details": null
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}
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}
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},
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"is_streaming": false
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}
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}
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