If you collect feedback from your users, such as thumbs up or down, you can record that feedback on your trace logs.

​
Record feedback

To record feedback you need the trace_id of the trace log you want to record feedback on. You can get the trace_id using the get_current_trace_id() helper function, or from the completion method’s response. 
from parea.schemas import FeedbackRequest
from parea import Parea, get_current_trace_id, trace

p = Parea(api_key="PAREA_API_KEY")

@trace
def argument_chain(messages: list[dict]) -> tuple[str, str]:
    # get_current_trace_id will return the trace_id of the most recent trace
    trace_id = get_current_trace_id()
    return call_llm(messages), trace_id

result, trace_id = argument_chain([{"role": "user", "content": "Hello"}])
p.record_feedback(
    FeedbackRequest(
        trace_id=trace_id,
        # insert your user score here, score must be float
        score=USER_SCORE,
        # Optionally, you can also provide a ground truth or
        # target answer. This could also be from your user.
        target="ground_truth",
    )
)
Alternatively, if you used p.completion for your LLM request, you can access the inference_id field on the response to get the trace_id.
from parea.schemas import LLMInputs, Message, Role, Completion, CompletionResponse, FeedbackRequest

result: CompletionResponse = p.completion(
    Completion(
        llm_configuration=LLMInputs(
            model="gpt-3.5-turbo",
            messages=[Message(role=Role.user, content="Hello")],
        )
    )
)
p.record_feedback(
    FeedbackRequest(
        trace_id=result.inference_id,
        score=USER_SCORE,
    )
)