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By targeting enterprise chat bot, I mean:\n\n* each chat bot has finite list of capabilities,\n* users of chatbots have been communicated with its capabilities,\n* developers behind chatbot has domain knowledge while building chatbot\n\nThese characteristics adding up, means it's very different from public facing general purpose chat bot. And we need a special designed CLI to help enterprise chatbot build.\n\n# What\nIn the heart of `chatbot-cli`, it contains a [Parser](chatbot-cli/src/main/java/com/dopsun/chatbot/cli/Parser.java) parses users input to command with parameters. And from there, enterprise bot developers can implement different functions.\n\nHere are parser features implemented/ planned:\n\n* Command is defined by template with parameter placeholders.\n  * One command can have multiple templates defined.\n  * In a single template, it may have optional/ alternative formates of certain part of the command.\n* Multiple commands can be matched for a certain input\n  * All these matched commands are rated with rank, and highest rank chose by default, but dewveloper of chatbot can choose alternatives if needed.\n* Bot developer can extend the resolve logic to customize the matching logic.\n\n*To be added*\n\n* Command ranking is resolved by predefined rules together with [Reinforcement Machine Learning](https://en.wikipedia.org/wiki/Reinforcement_learning)\n  * Selected command and user feedback can be recorded and as factors for resolving command in future.\n  * User feedback cna be positive and negative, or no feedback.\n\n# How\n\nA simple ChatBot command line parser, trained with templates.\n\n* It's designed for Command Line Interface (CLI) for ChatBot, with predefined list of command syntax.\n  * This is *NOT* a NLP (Natural Language Processing) parser.\n* It's *smart* and predictable.\n* *To Be Added* [Reinforcement learning](https://en.wikipedia.org/wiki/Reinforcement_learning)\n\n## Build\n```java\npublic static void prepareParser() throws URISyntaxException {\n    URL csUrl = ClassLoader.getSystemResource(\"input/command-data.properties\");\n    Path csPath = Paths.get(csUrl.toURI());\n\n    CommandSet commandSet = new FileCommandSet(csPath);\n\n    URL tsUrl = ClassLoader.getSystemResource(\"input/training-data.yml\");\n    Path tsPath = Paths.get(tsUrl.toURI());\n    TrainingSet trainingSet = new FileTrainingSet(tsPath);\n\n    ParserBuilder parserBuilder = Parser.newBuilder();\n    parserBuilder.addCommandSet(commandSet);\n    parserBuilder.addTrainingSet(trainingSet);\n\n    parserBuilder.setTracer(System.out::println);\n    parser = parserBuilder.build();\n }\n```\nIn the above example, a [Parser](chatbot-cli/src/main/java/com/dopsun/chatbot/cli/Parser.java)  is created based on command data set [Example](chatbot-cli/src/test/resources/input/command-data.properties).\n\n## Parse\n```java\nOptional\u003cParseResult\u003e optResult = parser.tryParse(command);\n```\nIf `optResult`, is present, parse succeed. And returned [ParseResult](chatbot-cli/src/main/java/com/dopsun/chatbot/cli/ParseResult.java) includes command.\n\n## Continuous improving\n*To Be Added* Successfully parsing result, along with feedback, will be stored as training set, and improve parser working better next time.\n\n# Comments and suggestions\nRaising issues if you have any feedback or reporting bugs.","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdopsun%2Fchatbot-cli","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdopsun%2Fchatbot-cli","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdopsun%2Fchatbot-cli/lists"}