Snips NLU C#

Snips NLU C# wrapper library to extract meaning from text

References

• https://snips.ai/
• https://github.com/snipsco/snips-nlu
• https://github.com/snipsco/snips-nlu-rs/

What is Snips NLU about ?

[From https://github.com/snipsco/snips-nlu/blob/develop/README.rst]

Behind every chatbot and voice assistant lies a common piece of technology: Natural Language Understanding (NLU). Anytime a user interacts with an AI using natural language, their words need to be translated into a machine-readable description of what they meant.

The NLU engine first detects what the intention of the user is (a.k.a. intent), then extracts the parameters (called slots) of the query. The developer can then use this to determine the appropriate action or response.

Version

0.64.3

x86 and x64 libraries

The pre-built DLL files are available in there respective directories.

Some useful resources:

• https://www.reddit.com/r/rust/comments/78vpxg/help_cross_compiling_for_32_bit_on_windows/
• https://www.reddit.com/r/rust/comments/a5guk3/cant_use_i686pcwindowsmsvc/
• https://gist.github.com/InNoHurryToCode/955d63db0d79699fed63fe18eeebf17e
• https://github.com/japaric/rust-cross#the-target-triple

Building the DLLs

For Windows

To build the dll, in Cargo.toml set crate-type to ["cdylib"]. In \.rustup\settings.toml, it might be necessary to change default_host_triple to i686-pc-windows-msvc or to x86_64-pc-windows-msvc.

To check if the necessary toolchains are installed, run rustup toolchain list.

• x86 build
  If necessary, run the following to install the toolchain:

  rustup install stable-i686-pc-windows-msvc
  

  Then run:

  cargo build --release --target=i686-pc-windows-msvc
  

• x64 build

  If necessary, run the following to install the toolchain:

  rustup install stable-x86_64-pc-windows-msvc
  

  Then run:

  cargo build --release --target=x86_64-pc-windows-msvc
  

Code Examples

Load a Model from a folder:

using (var snipsNLUEngine = SnipsNLUEngine.CreateFromDirectory(@"Data\Tests\Models\nlu_engine"))
{
    IntentClassifierResult[] intents = snipsNLUEngine.GetIntents("Can you make 3 cups of coffee?");
    Slot[] slots = snipsNLUEngine.GetSlots("Can you make 3 cups of coffee?", intents[0].IntentName);
    // or
    IntentParserResult parsed = snipsNLUEngine.Parse("Can you make 3 cups of coffee?");
    Console.WriteLine(parsed);
}

or

using (var snipsNLUEngine = new SnipsNLUEngine(@"Data\Tests\Models\nlu_engine"))
{
    IntentClassifierResult[] intents = snipsNLUEngine.GetIntents("Can you make 3 cups of coffee?");
    Slot[] slots = snipsNLUEngine.GetSlots("Can you make 3 cups of coffee?", intents[0].IntentName);
    // or
    IntentParserResult parsed = snipsNLUEngine.Parse("Can you make 3 cups of coffee?");
    Console.WriteLine(parsed);
}

Load a Model from a Zip file:

using (var snipsNLUEngine = SnipsNLUEngine.CreateFromZip(@"Data\Tests\Models\nlu_engine.zip"))
{
    IntentParserResult parsed = snipsNLUEngine.Parse("Can you make 3 cups of coffee?");
    Console.WriteLine(parsed);
}

Output will be:

Can you make 3 cups of coffee?
        MakeCoffee (61.43%)
                '3 (Number)', '3', snips/number, number_of_cups @ [13;14]

TO DO list

• Load model from zip file
• Implement CStringArray class
• Implement intentsWhitelist and intentsBlacklist in SnipsNLUEngine.Parse()

License