Function check_llm_spans

agentops/validation.py:157–206

Check if any LLM spans are present in the trace. Args: spans: List of span dictionaries Returns: Tuple of (has_llm_spans, llm_span_names)

(spans: List[Dict[str, Any]])

def check_llm_spans(spans: List[Dict[str, Any]]) -> Tuple[bool, List[str]]:
    """
    Check if any LLM spans are present in the trace.

    Args:
        spans: List of span dictionaries

    Returns:
        Tuple of (has_llm_spans, llm_span_names)
    """
    llm_spans = []

    for span in spans:
        span_name = span.get("span_name", "unnamed_span")
        span_attributes = span.get("span_attributes", {})
        is_llm_span = False

        if span_attributes:
            # Check for LLM span kind - handle both flat and nested structures
            span_kind = span_attributes.get("agentops.span.kind", "")
            if not span_kind:
                # Check nested structure: agentops.span.kind or agentops -> span -> kind
                agentops_attrs = span_attributes.get("agentops", {})
                if isinstance(agentops_attrs, dict):
                    span_attrs = agentops_attrs.get("span", {})
                    if isinstance(span_attrs, dict):
                        span_kind = span_attrs.get("kind", "")

            is_llm_span = span_kind == "llm"

            # Alternative check: Look for gen_ai attributes
            if not is_llm_span:
                gen_ai_attrs = span_attributes.get("gen_ai", {})
                if isinstance(gen_ai_attrs, dict):
                    if "prompt" in gen_ai_attrs or "completion" in gen_ai_attrs:
                        is_llm_span = True

            # Check for LLM request type
            if not is_llm_span:
                llm_request_type = span_attributes.get("gen_ai.request.type", "")
                if not llm_request_type:
                    # Also check for older llm.request.type format
                    llm_request_type = span_attributes.get("llm.request.type", "")
                if llm_request_type in ["chat", "completion"]:
                    is_llm_span = True

        if is_llm_span:
            llm_spans.append(span_name)

    return len(llm_spans) > 0, llm_spans


def validate_trace_spans(