Function apply

packages/core/src/tracing/langgraph/utils.ts:78–154

(target, thisArg, args: unknown[])

    const wrappedInvoke = new Proxy(originalInvoke as (...args: unknown[]) => unknown, {
      apply(target, thisArg, args: unknown[]): unknown {
        const spanAttributes: SpanAttributes = {
          [SEMANTIC_ATTRIBUTE_SENTRY_ORIGIN]: LANGGRAPH_ORIGIN,
          [SEMANTIC_ATTRIBUTE_SENTRY_OP]: GEN_AI_EXECUTE_TOOL_OPERATION_ATTRIBUTE,
          [GEN_AI_OPERATION_NAME_ATTRIBUTE]: 'execute_tool',
          [GEN_AI_TOOL_NAME_ATTRIBUTE]: toolName,
          [GEN_AI_TOOL_TYPE_ATTRIBUTE]: 'function',
        };

        // Read agent name from LangChain's propagated config metadata at call time,
        // so shared tools get the correct agent name for each invocation
        const callConfig = args[1] as Record<string, unknown> | undefined;
        const callAgentName = (callConfig?.metadata as Record<string, unknown>)?.lc_agent_name ?? agentName;
        if (typeof callAgentName === 'string') {
          spanAttributes[GEN_AI_AGENT_NAME_ATTRIBUTE] = callAgentName;
        }

        if (toolDescription) {
          spanAttributes[GEN_AI_TOOL_DESCRIPTION_ATTRIBUTE] = toolDescription;
        }

        // LangGraph ToolNode passes { name, args, id, type: "tool_call" }
        const input = args[0] as Record<string, unknown> | undefined;
        if (typeof input === 'object' && !!input) {
          if ('id' in input && typeof input.id === 'string') {
            spanAttributes[GEN_AI_TOOL_CALL_ID_ATTRIBUTE] = input.id;
          }

          if (options.recordInputs) {
            const toolArgs = 'args' in input && typeof input.args === 'object' ? input.args : input;
            try {
              spanAttributes[GEN_AI_TOOL_INPUT_ATTRIBUTE] = JSON.stringify(toolArgs);
            } catch {
              // skip if not serializable
            }
          }
        }

        return startSpan(
          {
            op: GEN_AI_EXECUTE_TOOL_OPERATION_ATTRIBUTE,
            name: `execute_tool ${toolName}`,
            attributes: spanAttributes,
          },
          async span => {
            try {
              const result = await Reflect.apply(target, thisArg, args);

              if (options.recordOutputs) {
                try {
                  // ToolMessage objects wrap the result in .content
                  const resultObj = result as Record<string, unknown> | undefined;
                  const content =
                    resultObj && typeof resultObj === 'object' && 'content' in resultObj ? resultObj.content : result;
                  span.setAttribute(
                    GEN_AI_TOOL_OUTPUT_ATTRIBUTE,
                    typeof content === 'string' ? content : JSON.stringify(content),
                  );