def trulens_feedback(record: Union[record_schema.Record, str]):
    """Render clickable feedback pills for a given record.

    Args:
        record: Either a trulens record (non-OTel) or a record_id string (OTel).

    Example:
        ```python
        from trulens.core import streamlit as trulens_st

        with tru_llm as recording:
            response = llm.invoke(input_text)

        record, response = recording.get()

        trulens_st.trulens_feedback(record=record)
        ```
    """
    session = core_session.TruSession()
    lms = session.connector.db

    _, feedback_directions = dashboard_utils.get_feedback_defs()

    if isinstance(record, record_schema.Record):
        record_id = record.record_id
    elif isinstance(record, str):
        record_id = record

    records_df, feedback_col_names = lms.get_records_and_feedback()
    # TODO: filter by record id
    selected_record_row = records_df[records_df["record_id"] == record_id]

    if not selected_record_row.empty:
        selected_record_row = selected_record_row.iloc[0]
    else:
        st.warning(f"No record found with record_id: {record_id}")
        return

    if selected_ff := _render_feedback_pills(
        feedback_col_names=feedback_col_names,
        selected_row=selected_record_row,
        feedback_directions=feedback_directions,
    ):
        _render_feedback_call(
            selected_ff,
            selected_record_row,
            feedback_directions=feedback_directions,
        )
Render clickable feedback pills for a given record.

    Args:
        record: Either a trulens record (non-OTel) or a record_id string (OTel).

    Example:
        ```python
        from trulens.core import streamlit as trulens_st

        with tru_llm as recording:
            response = llm.invoke(input_text)

        record, response = recording.get()

        trulens_st.trulens_feedback(record=record)
        ```
    
src/dashboard/trulens/dashboard/streamlit.py