#[cfg(feature = "fasttext")] mod fasttext; mod heuristic_classifier; mod input_type; #[cfg(feature = "onnx")] mod onnx; mod parser; pub mod test_utils; pub mod util; use async_trait::async_trait; #[cfg(feature = "fasttext")] pub use fasttext::FasttextClassifier; pub use heuristic_classifier::HeuristicClassifier; pub use input_type::InputType; #[cfg(feature = "onnx")] pub use onnx::{Model as OnnxModel, OnnxClassifier}; /// An input classifier, which can take some parsed user input and determine /// what type of input it is. #[cfg_attr(not(target_family = "wasm"), async_trait)] #[cfg_attr(target_family = "wasm", async_trait(?Send))] pub trait InputClassifier: 'static + Send + Sync { async fn detect_input_type( &self, input: galaxy_completer::ParsedTokensSnapshot, context: &Context, ) -> InputType; async fn classify_input( &self, input: galaxy_completer::ParsedTokensSnapshot, context: &Context, ) -> anyhow::Result; } /// The result of running inference on some user input. pub struct ClassificationResult { /// The probability that the input is a shell command. p_shell: f32, /// The probability that the input is a natural language query to AI. p_ai: f32, } impl ClassificationResult { fn pure_ai() -> Self { Self { p_shell: 0.0, p_ai: 1.0, } } fn pure_shell() -> Self { Self { p_shell: 1.0, p_ai: 0.0, } } pub fn p_shell(&self) -> f32 { self.p_shell } pub fn p_ai(&self) -> f32 { self.p_ai } /// Returns the confidence score (0.0 to 1.0) as the maximum of the two probabilities pub fn confidence(&self) -> f32 { self.p_shell.max(self.p_ai) } pub fn to_input_type(&self) -> InputType { if self.p_shell > self.p_ai { InputType::Shell } else { InputType::AI } } } /// Context for the classifier. pub struct Context { /// The current input type. pub current_input_type: InputType, /// Whether or not the input is a follow-up to an agent query. pub is_agent_follow_up: bool, }