Rebrand to Galaxy, major improvements to Bedrock support, still needs some TLC though

crates/input_classifier/src/bin/evaluate.rs

@@ -66,7 +66,7 @@ fn get_binary_confidence_color(is_correct: bool, is_low_confidence: bool) -> Str
         "\x1b[31m".to_string() // Red for incorrect
     }
 }
-use warp_completer::{ParsedTokensSnapshot, util::parse_current_commands_and_tokens};
+use galaxy_completer::{ParsedTokensSnapshot, util::parse_current_commands_and_tokens};
 
 #[cfg(feature = "fasttext")]
 use input_classifier::FasttextClassifier;

crates/input_classifier/src/fasttext/mod.rs

@@ -52,7 +52,7 @@ impl FasttextClassifier {
 impl InputClassifier for FasttextClassifier {
     async fn detect_input_type(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         context: &Context,
     ) -> InputType {
         let word_tokens = parse_query_into_tokens(input.buffer_text.as_str());
@@ -80,7 +80,7 @@ impl InputClassifier for FasttextClassifier {
 
     async fn classify_input(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         context: &Context,
     ) -> anyhow::Result<ClassificationResult> {
         if let Ok(classification_result) =

crates/input_classifier/src/heuristic_classifier/mod.rs

@@ -3,7 +3,7 @@ use std::borrow::Cow;
 use async_trait::async_trait;
 use itertools::Itertools as _;
 use natural_language_detection::natural_language_words_score;
-use warp_completer::ParsedTokensSnapshot;
+use galaxy_completer::ParsedTokensSnapshot;
 
 use crate::{
     ClassificationResult, Context, InputClassifier, InputType,
@@ -61,7 +61,7 @@ impl InputClassifier for HeuristicClassifier {
 
     async fn classify_input(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         context: &Context,
     ) -> anyhow::Result<super::ClassificationResult> {
         let word_tokens = parse_query_into_tokens(input.buffer_text.as_str());

crates/input_classifier/src/heuristic_classifier/mod_tests.rs

@@ -1,4 +1,4 @@
-use warp_completer::util::parse_current_commands_and_tokens;
+use galaxy_completer::util::parse_current_commands_and_tokens;
 
 use crate::{Context, test_utils::CompletionContext};
 

crates/input_classifier/src/lib.rs

@@ -24,13 +24,13 @@ pub use onnx::{Model as OnnxModel, OnnxClassifier};
 pub trait InputClassifier: 'static + Send + Sync {
     async fn detect_input_type(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         context: &Context,
     ) -> InputType;
 
     async fn classify_input(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         context: &Context,
     ) -> anyhow::Result<ClassificationResult>;
 }

crates/input_classifier/src/onnx/candle.rs

@@ -5,7 +5,7 @@ use candle_core::{IndexOp as _, Tensor};
 use candle_onnx::onnx::ModelProto;
 use prost::Message as _;
 use tokenizers::Tokenizer;
-use warp_completer::ParsedTokensSnapshot;
+use galaxy_completer::ParsedTokensSnapshot;
 
 use super::ClassificationResult;
 

crates/input_classifier/src/onnx/mod.rs

@@ -8,7 +8,7 @@ use std::borrow::Cow;
 use anyhow::Result;
 use async_trait::async_trait;
 use rust_embed::RustEmbed;
-use warp_completer::ParsedTokensSnapshot;
+use galaxy_completer::ParsedTokensSnapshot;
 
 use crate::{
     ClassificationResult, Context, InputClassifier, InputType,
@@ -119,7 +119,7 @@ impl InputClassifier for OnnxClassifier {
 
     async fn classify_input(
         &self,
-        input: warp_completer::ParsedTokensSnapshot,
+        input: galaxy_completer::ParsedTokensSnapshot,
         _context: &Context,
     ) -> anyhow::Result<ClassificationResult> {
         // If we ever panicked while running inference, we should fall back to the heuristic classifier.

crates/input_classifier/src/onnx/ort.rs

@@ -6,7 +6,7 @@ use ort::{
 };
 use parking_lot::Mutex;
 use tokenizers::Tokenizer;
-use warp_completer::ParsedTokensSnapshot;
+use galaxy_completer::ParsedTokensSnapshot;
 
 use super::ClassificationResult;
 

crates/input_classifier/src/test_utils.rs

@@ -1,7 +1,7 @@
 use std::{collections::HashSet, sync::Arc};
 
 use smol_str::SmolStr;
-use warp_completer::{
+use galaxy_completer::{
     completer::{GeneratorContext, PathCompletionContext},
     signatures::CommandRegistry,
 };
@@ -20,7 +20,7 @@ impl CompletionContext {
     }
 }
 
-impl warp_completer::completer::CompletionContext for CompletionContext {
+impl galaxy_completer::completer::CompletionContext for CompletionContext {
     fn top_level_commands(&self) -> Box<dyn Iterator<Item = &str> + '_> {
         Box::new(self.command_registry.registered_commands())
     }

crates/input_classifier/src/util.rs

@@ -2,7 +2,7 @@ use std::collections::HashSet;
 
 use lazy_static::lazy_static;
 use natural_language_detection::check_if_token_has_shell_syntax;
-use warp_completer::ParsedTokensSnapshot;
+use galaxy_completer::ParsedTokensSnapshot;
 
 /// The percentage of input tokens that can be described by our completion engine before
 /// we consider the input as a shell command. This could be tuned.