AI based AutoComplete for network node configuration

1 . A method of providing Artificial Intelligence (AI) based AutoComplete for network node configuration, comprising:

predicting a configuration to use for a network node based on a model, wherein predicting the configuration comprises:

accepting user inputs;

converting, by a tokenizer, the user inputs into word tokens;

taking, by the model, the word tokens as input sequences and using transfer learning methods calculating parameters of occurrences of next words; and

ranking the word tokens according to values of their parameters wherein word tokens with a highest value are suggested to a user for auto completion of the network node configuration.

2 . The method of claim 1 wherein accepting user inputs comprises accepting user inputs at a Command Line Interface (CLI) interface.

3 . The method of claim 1 wherein accepting user inputs comprises accepting user inputs at a Graphical User Interface (GUI).

4 . The method of claim 1 further comprising suggesting a next probable configuration line.

5 . The method of claim 1 wherein the model is a trained model.

6 . The method of claim 5 wherein a cell network configuration node, coupled to the network node, provides the trained model by:

providing inputs to a cell network configuration node tokenizer from a CLI syntax file and from a CLI configuration file;

converting, by the cell network configuration node tokenizer, configuration lines into word tokens at the cell network configuration node;

processing the word tokens at the cell network configuration node received from the cell network configuration node tokenizer to calculate AI parameters; and

storing the AI parameters to be used for network node configuration predictions.

7 . The method of claim 1 wherein the network node takes into account a state machine or rule tree for which parameter values logically exclude other values.

8 . A non-transitory computer-readable medium containing instructions for providing Artificial Intelligence (AI) based AutoComplete for network node configuration, which, when executed, cause the network node to perform steps including:

predicting a configuration to use for a network node based on a model, wherein predicting the configuration comprises:

accepting user inputs;

converting, by a tokenizer, the user inputs into word tokens;

taking, by the model, the word tokens as input sequences and using transfer learning methods calculating parameters of occurrences of next words; and

ranking the word tokens according to values of their parameters wherein word tokens with a highest value are suggested to a user for auto completion of the network node configuration.

9 . The computer-readable medium of claim 8 wherein the instructions for accepting user inputs comprises instructions for accepting user inputs at a Command Line Interface (CLI) interface.

10 . The computer-readable medium of claim 8 wherein the instructions for accepting user inputs comprises instructions for accepting user inputs at a Graphical User Interface (GUI).

11 . The computer-readable medium of claim 8 further comprising instructions which, when executed, cause the network node to perform a step of suggesting a next probable configuration line.

12 . The computer-readable medium of claim 8 wherein the model is a trained model.

13 . The computer-readable medium of claim 12 wherein a cell network configuration node, coupled to the network node, provides the trained model by:

providing inputs to a cell network configuration node tokenizer from a CLI syntax file from a CLI configuration file;

converting, by the cell network configuration node tokenizer, configuration lines into word tokens at the cell network configuration node;

processing the word tokens at the cell network configuration node received from the cell network configuration node tokenizer to calculate AI parameters; and

storing the AI parameters to be used for network node configuration predictions.

14 . The computer-readable medium of claim 8 further comprising instructions for taking into account a state machine or rule tree for which parameter values logically exclude other values.

15 . A system for providing Artificial Intelligence (AI) based AutoComplete for network node configuration comprising:

an interface, including a memory coupled to a processor, accepting user inputs;

a tokenizer in communication with the interface, converting the user inputs into word tokens;

a model, in communication with the tokenizer, taking the word tokens as input sequences and using transfer learning methods calculate parameters of occurrences of next words; and

a prediction filter, in communication with the model, ranking the word tokens according to values of their parameters and wherein word tokens with a highest value are suggested to a user for auto completion of the network node configuration for a network node.

16 . The system of claim 15 wherein the interface comprises one of a Command Line Interface (CLI) interface and a Graphical User Interface (GUI).

17 . The system of claim 15 wherein the prediction filter further to suggests a next probable configuration line.

18 . The system of claim 15 wherein the model is a trained model.

19 . The system of claim 18 wherein a cell network configuration node, coupled to the network node, provides the trained model by:

providing inputs to a cell network configuration node tokenizer from a CLI syntax file and from a CLI configuration file;

converting, by the cell network configuration node tokenizer, configuration lines into word tokens at the cell network configuration node;

processing the word tokens at the cell network configuration node received from the cell network configuration node tokenizer to calculate AI parameters; and

storing the AI parameters to be used for network node configuration predictions.

20 . The system of claim 15 wherein the network node takes into account a state machine or rule tree for which parameter values logically exclude other values.