Semantic search v2 (#2789)

Move semantic search from navigation modal, to project search option.
This PR is intended to be released in Preview only, and requires an
opt-in semantic_index option to enable. Without this opt-in setting
enable, the user should perceive no differences between previous project
search.

Release Notes: (Preview-only)

- Added Semantic Search as a opt-in feature within Project Search
- Show indexing feedback on indexing process within project search view
This commit is contained in:
Kyle Caverly
2023-07-26 10:34:58 -04:00
committed by GitHub
31 changed files with 3900 additions and 2204 deletions
Generated
+770 -709
View File
File diff suppressed because it is too large Load Diff
+2 -2
View File
@@ -63,7 +63,7 @@ members = [
"crates/theme",
"crates/theme_selector",
"crates/util",
"crates/vector_store",
"crates/semantic_index",
"crates/vim",
"crates/vcs_menu",
"crates/workspace",
@@ -133,7 +133,7 @@ tree-sitter-yaml = { git = "https://github.com/zed-industries/tree-sitter-yaml",
tree-sitter-lua = "0.0.14"
[patch.crates-io]
tree-sitter = { git = "https://github.com/tree-sitter/tree-sitter", rev = "49226023693107fba9a1191136a4f47f38cdca73" }
tree-sitter = { git = "https://github.com/tree-sitter/tree-sitter", rev = "1c65ca24bc9a734ab70115188f465e12eecf224e" }
async-task = { git = "https://github.com/zed-industries/async-task", rev = "341b57d6de98cdfd7b418567b8de2022ca993a6e" }
# TODO - Remove when a version is released with this PR: https://github.com/servo/core-foundation-rs/pull/457
+2 -2
View File
@@ -324,8 +324,8 @@
// the terminal will default to matching the buffer's font family.
// "font_family": "Zed Mono"
},
// Difference settings for vector_store
"vector_store": {
// Difference settings for semantic_index
"semantic_index": {
"enabled": false,
"reindexing_delay_seconds": 600
},
+24 -6
View File
@@ -339,6 +339,8 @@ pub struct LanguageConfig {
#[serde(default)]
pub line_comment: Option<Arc<str>>,
#[serde(default)]
pub collapsed_placeholder: String,
#[serde(default)]
pub block_comment: Option<(Arc<str>, Arc<str>)>,
#[serde(default)]
pub overrides: HashMap<String, LanguageConfigOverride>,
@@ -408,6 +410,7 @@ impl Default for LanguageConfig {
line_comment: Default::default(),
block_comment: Default::default(),
overrides: Default::default(),
collapsed_placeholder: Default::default(),
}
}
}
@@ -523,9 +526,10 @@ pub struct OutlineConfig {
pub struct EmbeddingConfig {
pub query: Query,
pub item_capture_ix: u32,
pub name_capture_ix: u32,
pub name_capture_ix: Option<u32>,
pub context_capture_ix: Option<u32>,
pub extra_context_capture_ix: Option<u32>,
pub collapse_capture_ix: Option<u32>,
pub keep_capture_ix: Option<u32>,
}
struct InjectionConfig {
@@ -1247,23 +1251,26 @@ impl Language {
let mut item_capture_ix = None;
let mut name_capture_ix = None;
let mut context_capture_ix = None;
let mut extra_context_capture_ix = None;
let mut collapse_capture_ix = None;
let mut keep_capture_ix = None;
get_capture_indices(
&query,
&mut [
("item", &mut item_capture_ix),
("name", &mut name_capture_ix),
("context", &mut context_capture_ix),
("context.extra", &mut extra_context_capture_ix),
("keep", &mut keep_capture_ix),
("collapse", &mut collapse_capture_ix),
],
);
if let Some((item_capture_ix, name_capture_ix)) = item_capture_ix.zip(name_capture_ix) {
if let Some(item_capture_ix) = item_capture_ix {
grammar.embedding_config = Some(EmbeddingConfig {
query,
item_capture_ix,
name_capture_ix,
context_capture_ix,
extra_context_capture_ix,
collapse_capture_ix,
keep_capture_ix,
});
}
Ok(self)
@@ -1548,9 +1555,20 @@ impl Language {
pub fn grammar(&self) -> Option<&Arc<Grammar>> {
self.grammar.as_ref()
}
pub fn default_scope(self: &Arc<Self>) -> LanguageScope {
LanguageScope {
language: self.clone(),
override_id: None,
}
}
}
impl LanguageScope {
pub fn collapsed_placeholder(&self) -> &str {
self.language.config.collapsed_placeholder.as_ref()
}
pub fn line_comment_prefix(&self) -> Option<&Arc<str>> {
Override::as_option(
self.config_override().map(|o| &o.line_comment),
+1
View File
@@ -20,6 +20,7 @@ settings = { path = "../settings" }
theme = { path = "../theme" }
util = { path = "../util" }
workspace = { path = "../workspace" }
semantic_index = { path = "../semantic_index" }
anyhow.workspace = true
futures.workspace = true
log.workspace = true
+239 -10
View File
@@ -18,7 +18,9 @@ use gpui::{
Task, View, ViewContext, ViewHandle, WeakModelHandle, WeakViewHandle,
};
use menu::Confirm;
use postage::stream::Stream;
use project::{search::SearchQuery, Entry, Project};
use semantic_index::SemanticIndex;
use smallvec::SmallVec;
use std::{
any::{Any, TypeId},
@@ -36,7 +38,10 @@ use workspace::{
ItemNavHistory, Pane, ToolbarItemLocation, ToolbarItemView, Workspace, WorkspaceId,
};
actions!(project_search, [SearchInNew, ToggleFocus, NextField]);
actions!(
project_search,
[SearchInNew, ToggleFocus, NextField, ToggleSemanticSearch]
);
#[derive(Default)]
struct ActiveSearches(HashMap<WeakModelHandle<Project>, WeakViewHandle<ProjectSearchView>>);
@@ -89,6 +94,7 @@ pub struct ProjectSearchView {
model: ModelHandle<ProjectSearch>,
query_editor: ViewHandle<Editor>,
results_editor: ViewHandle<Editor>,
semantic: Option<SemanticSearchState>,
search_options: SearchOptions,
panels_with_errors: HashSet<InputPanel>,
active_match_index: Option<usize>,
@@ -98,6 +104,12 @@ pub struct ProjectSearchView {
excluded_files_editor: ViewHandle<Editor>,
}
struct SemanticSearchState {
file_count: usize,
outstanding_file_count: usize,
_progress_task: Task<()>,
}
pub struct ProjectSearchBar {
active_project_search: Option<ViewHandle<ProjectSearchView>>,
subscription: Option<Subscription>,
@@ -172,6 +184,63 @@ impl ProjectSearch {
}));
cx.notify();
}
fn semantic_search(
&mut self,
query: String,
include_files: Vec<GlobMatcher>,
exclude_files: Vec<GlobMatcher>,
cx: &mut ModelContext<Self>,
) {
let search = SemanticIndex::global(cx).map(|index| {
index.update(cx, |semantic_index, cx| {
semantic_index.search_project(
self.project.clone(),
query.clone(),
10,
include_files,
exclude_files,
cx,
)
})
});
self.search_id += 1;
self.match_ranges.clear();
self.pending_search = Some(cx.spawn(|this, mut cx| async move {
let results = search?.await.log_err()?;
let (_task, mut match_ranges) = this.update(&mut cx, |this, cx| {
this.excerpts.update(cx, |excerpts, cx| {
excerpts.clear(cx);
let matches = results
.into_iter()
.map(|result| (result.buffer, vec![result.range.start..result.range.start]))
.collect();
excerpts.stream_excerpts_with_context_lines(matches, 3, cx)
})
});
while let Some(match_range) = match_ranges.next().await {
this.update(&mut cx, |this, cx| {
this.match_ranges.push(match_range);
while let Ok(Some(match_range)) = match_ranges.try_next() {
this.match_ranges.push(match_range);
}
cx.notify();
});
}
this.update(&mut cx, |this, cx| {
this.pending_search.take();
cx.notify();
});
None
}));
cx.notify();
}
}
pub enum ViewEvent {
@@ -195,13 +264,24 @@ impl View for ProjectSearchView {
enum Status {}
let theme = theme::current(cx).clone();
let text = if self.query_editor.read(cx).text(cx).is_empty() {
""
} else if model.pending_search.is_some() {
"Searching..."
let text = if model.pending_search.is_some() {
Cow::Borrowed("Searching...")
} else if let Some(semantic) = &self.semantic {
if semantic.outstanding_file_count > 0 {
Cow::Owned(format!(
"Indexing. {} of {}...",
semantic.file_count - semantic.outstanding_file_count,
semantic.file_count
))
} else {
Cow::Borrowed("Indexing complete")
}
} else if self.query_editor.read(cx).text(cx).is_empty() {
Cow::Borrowed("")
} else {
"No results"
Cow::Borrowed("No results")
};
MouseEventHandler::<Status, _>::new(0, cx, |_, _| {
Label::new(text, theme.search.results_status.clone())
.aligned()
@@ -490,6 +570,7 @@ impl ProjectSearchView {
model,
query_editor,
results_editor,
semantic: None,
search_options: options,
panels_with_errors: HashSet::new(),
active_match_index: None,
@@ -577,11 +658,59 @@ impl ProjectSearchView {
}
fn search(&mut self, cx: &mut ViewContext<Self>) {
if let Some(semantic) = &mut self.semantic {
if semantic.outstanding_file_count > 0 {
return;
}
let query = self.query_editor.read(cx).text(cx);
if let Some((included_files, exclude_files)) =
self.get_included_and_excluded_globsets(cx)
{
self.model.update(cx, |model, cx| {
model.semantic_search(query, included_files, exclude_files, cx)
});
}
return;
}
if let Some(query) = self.build_search_query(cx) {
self.model.update(cx, |model, cx| model.search(query, cx));
}
}
fn get_included_and_excluded_globsets(
&mut self,
cx: &mut ViewContext<Self>,
) -> Option<(Vec<GlobMatcher>, Vec<GlobMatcher>)> {
let included_files =
match Self::load_glob_set(&self.included_files_editor.read(cx).text(cx)) {
Ok(included_files) => {
self.panels_with_errors.remove(&InputPanel::Include);
included_files
}
Err(_e) => {
self.panels_with_errors.insert(InputPanel::Include);
cx.notify();
return None;
}
};
let excluded_files =
match Self::load_glob_set(&self.excluded_files_editor.read(cx).text(cx)) {
Ok(excluded_files) => {
self.panels_with_errors.remove(&InputPanel::Exclude);
excluded_files
}
Err(_e) => {
self.panels_with_errors.insert(InputPanel::Exclude);
cx.notify();
return None;
}
};
Some((included_files, excluded_files))
}
fn build_search_query(&mut self, cx: &mut ViewContext<Self>) -> Option<SearchQuery> {
let text = self.query_editor.read(cx).text(cx);
let included_files =
@@ -873,6 +1002,7 @@ impl ProjectSearchBar {
if let Some(search_view) = self.active_project_search.as_ref() {
search_view.update(cx, |search_view, cx| {
search_view.search_options.toggle(option);
search_view.semantic = None;
search_view.search(cx);
});
cx.notify();
@@ -882,6 +1012,61 @@ impl ProjectSearchBar {
}
}
fn toggle_semantic_search(&mut self, cx: &mut ViewContext<Self>) -> bool {
if let Some(search_view) = self.active_project_search.as_ref() {
search_view.update(cx, |search_view, cx| {
if search_view.semantic.is_some() {
search_view.semantic = None;
} else if let Some(semantic_index) = SemanticIndex::global(cx) {
// TODO: confirm that it's ok to send this project
search_view.search_options = SearchOptions::none();
let project = search_view.model.read(cx).project.clone();
let index_task = semantic_index.update(cx, |semantic_index, cx| {
semantic_index.index_project(project, cx)
});
cx.spawn(|search_view, mut cx| async move {
let (files_to_index, mut files_remaining_rx) = index_task.await?;
search_view.update(&mut cx, |search_view, cx| {
cx.notify();
search_view.semantic = Some(SemanticSearchState {
file_count: files_to_index,
outstanding_file_count: files_to_index,
_progress_task: cx.spawn(|search_view, mut cx| async move {
while let Some(count) = files_remaining_rx.recv().await {
search_view
.update(&mut cx, |search_view, cx| {
if let Some(semantic_search_state) =
&mut search_view.semantic
{
semantic_search_state.outstanding_file_count =
count;
cx.notify();
if count == 0 {
return;
}
}
})
.ok();
}
}),
});
})?;
anyhow::Ok(())
})
.detach_and_log_err(cx);
}
cx.notify();
});
cx.notify();
true
} else {
false
}
}
fn render_nav_button(
&self,
icon: &'static str,
@@ -959,6 +1144,42 @@ impl ProjectSearchBar {
.into_any()
}
fn render_semantic_search_button(&self, cx: &mut ViewContext<Self>) -> AnyElement<Self> {
let tooltip_style = theme::current(cx).tooltip.clone();
let is_active = if let Some(search) = self.active_project_search.as_ref() {
let search = search.read(cx);
search.semantic.is_some()
} else {
false
};
let region_id = 3;
MouseEventHandler::<Self, _>::new(region_id, cx, |state, cx| {
let theme = theme::current(cx);
let style = theme
.search
.option_button
.in_state(is_active)
.style_for(state);
Label::new("Semantic", style.text.clone())
.contained()
.with_style(style.container)
})
.on_click(MouseButton::Left, move |_, this, cx| {
this.toggle_semantic_search(cx);
})
.with_cursor_style(CursorStyle::PointingHand)
.with_tooltip::<Self>(
region_id,
format!("Toggle Semantic Search"),
Some(Box::new(ToggleSemanticSearch)),
tooltip_style,
cx,
)
.into_any()
}
fn is_option_enabled(&self, option: SearchOptions, cx: &AppContext) -> bool {
if let Some(search) = self.active_project_search.as_ref() {
search.read(cx).search_options.contains(option)
@@ -1048,8 +1269,14 @@ impl View for ProjectSearchBar {
.with_child(self.render_nav_button(">", Direction::Next, cx))
.aligned(),
)
.with_child(
Flex::row()
.with_child({
let row = if SemanticIndex::enabled(cx) {
Flex::row().with_child(self.render_semantic_search_button(cx))
} else {
Flex::row()
};
let row = row
.with_child(self.render_option_button(
"Case",
SearchOptions::CASE_SENSITIVE,
@@ -1067,8 +1294,10 @@ impl View for ProjectSearchBar {
))
.contained()
.with_style(theme.search.option_button_group)
.aligned(),
)
.aligned();
row
})
.contained()
.with_margin_bottom(row_spacing),
)
+4
View File
@@ -53,6 +53,10 @@ impl SearchOptions {
}
}
pub fn none() -> SearchOptions {
SearchOptions::NONE
}
pub fn from_query(query: &SearchQuery) -> SearchOptions {
let mut options = SearchOptions::NONE;
options.set(SearchOptions::WHOLE_WORD, query.whole_word());
@@ -1,11 +1,11 @@
[package]
name = "vector_store"
name = "semantic_index"
version = "0.1.0"
edition = "2021"
publish = false
[lib]
path = "src/vector_store.rs"
path = "src/semantic_index.rs"
doctest = false
[dependencies]
@@ -20,6 +20,7 @@ editor = { path = "../editor" }
rpc = { path = "../rpc" }
settings = { path = "../settings" }
anyhow.workspace = true
postage.workspace = true
futures.workspace = true
smol.workspace = true
rusqlite = { version = "0.27.0", features = ["blob", "array", "modern_sqlite"] }
@@ -33,8 +34,10 @@ async-trait.workspace = true
bincode = "1.3.3"
matrixmultiply = "0.3.7"
tiktoken-rs = "0.5.0"
parking_lot.workspace = true
rand.workspace = true
schemars.workspace = true
globset.workspace = true
[dev-dependencies]
gpui = { path = "../gpui", features = ["test-support"] }
@@ -43,7 +46,17 @@ project = { path = "../project", features = ["test-support"] }
rpc = { path = "../rpc", features = ["test-support"] }
workspace = { path = "../workspace", features = ["test-support"] }
settings = { path = "../settings", features = ["test-support"]}
tree-sitter-rust = "*"
pretty_assertions.workspace = true
rand.workspace = true
unindent.workspace = true
tempdir.workspace = true
ctor.workspace = true
env_logger.workspace = true
tree-sitter-typescript = "*"
tree-sitter-json = "*"
tree-sitter-rust = "*"
tree-sitter-toml = "*"
tree-sitter-cpp = "*"
tree-sitter-elixir = "*"
@@ -1,20 +1,21 @@
use std::{
cmp::Ordering,
collections::HashMap,
path::{Path, PathBuf},
rc::Rc,
time::SystemTime,
};
use anyhow::{anyhow, Result};
use crate::parsing::ParsedFile;
use crate::VECTOR_STORE_VERSION;
use crate::{parsing::Document, SEMANTIC_INDEX_VERSION};
use anyhow::{anyhow, Context, Result};
use globset::GlobMatcher;
use project::Fs;
use rpc::proto::Timestamp;
use rusqlite::{
params,
types::{FromSql, FromSqlResult, ValueRef},
};
use std::{
cmp::Ordering,
collections::HashMap,
ops::Range,
path::{Path, PathBuf},
rc::Rc,
sync::Arc,
time::SystemTime,
};
#[derive(Debug)]
pub struct FileRecord {
@@ -42,48 +43,94 @@ pub struct VectorDatabase {
}
impl VectorDatabase {
pub fn new(path: String) -> Result<Self> {
pub async fn new(fs: Arc<dyn Fs>, path: Arc<PathBuf>) -> Result<Self> {
if let Some(db_directory) = path.parent() {
fs.create_dir(db_directory).await?;
}
let this = Self {
db: rusqlite::Connection::open(path)?,
db: rusqlite::Connection::open(path.as_path())?,
};
this.initialize_database()?;
Ok(this)
}
fn get_existing_version(&self) -> Result<i64> {
let mut version_query = self
.db
.prepare("SELECT version from semantic_index_config")?;
version_query
.query_row([], |row| Ok(row.get::<_, i64>(0)?))
.map_err(|err| anyhow!("version query failed: {err}"))
}
fn initialize_database(&self) -> Result<()> {
rusqlite::vtab::array::load_module(&self.db)?;
// This will create the database if it doesnt exist
// Delete existing tables, if SEMANTIC_INDEX_VERSION is bumped
if self
.get_existing_version()
.map_or(false, |version| version == SEMANTIC_INDEX_VERSION as i64)
{
log::trace!("vector database schema up to date");
return Ok(());
}
log::trace!("vector database schema out of date. updating...");
self.db
.execute("DROP TABLE IF EXISTS documents", [])
.context("failed to drop 'documents' table")?;
self.db
.execute("DROP TABLE IF EXISTS files", [])
.context("failed to drop 'files' table")?;
self.db
.execute("DROP TABLE IF EXISTS worktrees", [])
.context("failed to drop 'worktrees' table")?;
self.db
.execute("DROP TABLE IF EXISTS semantic_index_config", [])
.context("failed to drop 'semantic_index_config' table")?;
// Initialize Vector Databasing Tables
self.db.execute(
"CREATE TABLE IF NOT EXISTS worktrees (
"CREATE TABLE semantic_index_config (
version INTEGER NOT NULL
)",
[],
)?;
self.db.execute(
"INSERT INTO semantic_index_config (version) VALUES (?1)",
params![SEMANTIC_INDEX_VERSION],
)?;
self.db.execute(
"CREATE TABLE worktrees (
id INTEGER PRIMARY KEY AUTOINCREMENT,
absolute_path VARCHAR NOT NULL
);
CREATE UNIQUE INDEX IF NOT EXISTS worktrees_absolute_path ON worktrees (absolute_path);
CREATE UNIQUE INDEX worktrees_absolute_path ON worktrees (absolute_path);
",
[],
)?;
self.db.execute(
"CREATE TABLE IF NOT EXISTS files (
"CREATE TABLE files (
id INTEGER PRIMARY KEY AUTOINCREMENT,
worktree_id INTEGER NOT NULL,
relative_path VARCHAR NOT NULL,
mtime_seconds INTEGER NOT NULL,
mtime_nanos INTEGER NOT NULL,
vector_store_version INTEGER NOT NULL,
FOREIGN KEY(worktree_id) REFERENCES worktrees(id) ON DELETE CASCADE
)",
[],
)?;
self.db.execute(
"CREATE TABLE IF NOT EXISTS documents (
"CREATE TABLE documents (
id INTEGER PRIMARY KEY AUTOINCREMENT,
file_id INTEGER NOT NULL,
offset INTEGER NOT NULL,
start_byte INTEGER NOT NULL,
end_byte INTEGER NOT NULL,
name VARCHAR NOT NULL,
embedding BLOB NOT NULL,
FOREIGN KEY(file_id) REFERENCES files(id) ON DELETE CASCADE
@@ -91,6 +138,7 @@ impl VectorDatabase {
[],
)?;
log::trace!("vector database initialized with updated schema.");
Ok(())
}
@@ -102,43 +150,44 @@ impl VectorDatabase {
Ok(())
}
pub fn insert_file(&self, worktree_id: i64, indexed_file: ParsedFile) -> Result<()> {
pub fn insert_file(
&self,
worktree_id: i64,
path: PathBuf,
mtime: SystemTime,
documents: Vec<Document>,
) -> Result<()> {
// Write to files table, and return generated id.
self.db.execute(
"
DELETE FROM files WHERE worktree_id = ?1 AND relative_path = ?2;
",
params![worktree_id, indexed_file.path.to_str()],
params![worktree_id, path.to_str()],
)?;
let mtime = Timestamp::from(indexed_file.mtime);
let mtime = Timestamp::from(mtime);
self.db.execute(
"
INSERT INTO files
(worktree_id, relative_path, mtime_seconds, mtime_nanos, vector_store_version)
(worktree_id, relative_path, mtime_seconds, mtime_nanos)
VALUES
(?1, ?2, $3, $4, $5);
(?1, ?2, $3, $4);
",
params![
worktree_id,
indexed_file.path.to_str(),
mtime.seconds,
mtime.nanos,
VECTOR_STORE_VERSION
],
params![worktree_id, path.to_str(), mtime.seconds, mtime.nanos],
)?;
let file_id = self.db.last_insert_rowid();
// Currently inserting at approximately 3400 documents a second
// I imagine we can speed this up with a bulk insert of some kind.
for document in indexed_file.documents {
for document in documents {
let embedding_blob = bincode::serialize(&document.embedding)?;
self.db.execute(
"INSERT INTO documents (file_id, offset, name, embedding) VALUES (?1, ?2, ?3, ?4)",
"INSERT INTO documents (file_id, start_byte, end_byte, name, embedding) VALUES (?1, ?2, ?3, ?4, $5)",
params![
file_id,
document.offset.to_string(),
document.range.start.to_string(),
document.range.end.to_string(),
document.name,
embedding_blob
],
@@ -148,6 +197,23 @@ impl VectorDatabase {
Ok(())
}
pub fn worktree_previously_indexed(&self, worktree_root_path: &Path) -> Result<bool> {
let mut worktree_query = self
.db
.prepare("SELECT id FROM worktrees WHERE absolute_path = ?1")?;
let worktree_id = worktree_query
.query_row(params![worktree_root_path.to_string_lossy()], |row| {
Ok(row.get::<_, i64>(0)?)
})
.map_err(|err| anyhow!(err));
if worktree_id.is_ok() {
return Ok(true);
} else {
return Ok(false);
}
}
pub fn find_or_create_worktree(&self, worktree_root_path: &Path) -> Result<i64> {
// Check that the absolute path doesnt exist
let mut worktree_query = self
@@ -204,19 +270,26 @@ impl VectorDatabase {
worktree_ids: &[i64],
query_embedding: &Vec<f32>,
limit: usize,
) -> Result<Vec<(i64, PathBuf, usize, String)>> {
include_globs: Vec<GlobMatcher>,
exclude_globs: Vec<GlobMatcher>,
) -> Result<Vec<(i64, PathBuf, Range<usize>)>> {
let mut results = Vec::<(i64, f32)>::with_capacity(limit + 1);
self.for_each_document(&worktree_ids, |id, embedding| {
let similarity = dot(&embedding, &query_embedding);
let ix = match results
.binary_search_by(|(_, s)| similarity.partial_cmp(&s).unwrap_or(Ordering::Equal))
{
Ok(ix) => ix,
Err(ix) => ix,
};
results.insert(ix, (id, similarity));
results.truncate(limit);
})?;
self.for_each_document(
&worktree_ids,
include_globs,
exclude_globs,
|id, embedding| {
let similarity = dot(&embedding, &query_embedding);
let ix = match results.binary_search_by(|(_, s)| {
similarity.partial_cmp(&s).unwrap_or(Ordering::Equal)
}) {
Ok(ix) => ix,
Err(ix) => ix,
};
results.insert(ix, (id, similarity));
results.truncate(limit);
},
)?;
let ids = results.into_iter().map(|(id, _)| id).collect::<Vec<_>>();
self.get_documents_by_ids(&ids)
@@ -225,22 +298,51 @@ impl VectorDatabase {
fn for_each_document(
&self,
worktree_ids: &[i64],
include_globs: Vec<GlobMatcher>,
exclude_globs: Vec<GlobMatcher>,
mut f: impl FnMut(i64, Vec<f32>),
) -> Result<()> {
let mut file_query = self.db.prepare(
"
SELECT
id, relative_path
FROM
files
WHERE
worktree_id IN rarray(?)
",
)?;
let mut file_ids = Vec::<i64>::new();
let mut rows = file_query.query([ids_to_sql(worktree_ids)])?;
while let Some(row) = rows.next()? {
let file_id = row.get(0)?;
let relative_path = row.get_ref(1)?.as_str()?;
let included = include_globs.is_empty()
|| include_globs
.iter()
.any(|glob| glob.is_match(relative_path));
let excluded = exclude_globs
.iter()
.any(|glob| glob.is_match(relative_path));
if included && !excluded {
file_ids.push(file_id);
}
}
let mut query_statement = self.db.prepare(
"
SELECT
documents.id, documents.embedding
id, embedding
FROM
documents, files
documents
WHERE
documents.file_id = files.id AND
files.worktree_id IN rarray(?)
file_id IN rarray(?)
",
)?;
query_statement
.query_map(params![ids_to_sql(worktree_ids)], |row| {
.query_map(params![ids_to_sql(&file_ids)], |row| {
Ok((row.get(0)?, row.get::<_, Embedding>(1)?))
})?
.filter_map(|row| row.ok())
@@ -248,11 +350,15 @@ impl VectorDatabase {
Ok(())
}
fn get_documents_by_ids(&self, ids: &[i64]) -> Result<Vec<(i64, PathBuf, usize, String)>> {
fn get_documents_by_ids(&self, ids: &[i64]) -> Result<Vec<(i64, PathBuf, Range<usize>)>> {
let mut statement = self.db.prepare(
"
SELECT
documents.id, files.worktree_id, files.relative_path, documents.offset, documents.name
documents.id,
files.worktree_id,
files.relative_path,
documents.start_byte,
documents.end_byte
FROM
documents, files
WHERE
@@ -266,15 +372,14 @@ impl VectorDatabase {
row.get::<_, i64>(0)?,
row.get::<_, i64>(1)?,
row.get::<_, String>(2)?.into(),
row.get(3)?,
row.get(4)?,
row.get(3)?..row.get(4)?,
))
})?;
let mut values_by_id = HashMap::<i64, (i64, PathBuf, usize, String)>::default();
let mut values_by_id = HashMap::<i64, (i64, PathBuf, Range<usize>)>::default();
for row in result_iter {
let (id, worktree_id, path, offset, name) = row?;
values_by_id.insert(id, (worktree_id, path, offset, name));
let (id, worktree_id, path, range) = row?;
values_by_id.insert(id, (worktree_id, path, range));
}
let mut results = Vec::with_capacity(ids.len());
@@ -67,17 +67,16 @@ impl EmbeddingProvider for DummyEmbeddings {
}
}
const INPUT_LIMIT: usize = 8190;
const OPENAI_INPUT_LIMIT: usize = 8190;
impl OpenAIEmbeddings {
fn truncate(span: String) -> String {
let mut tokens = OPENAI_BPE_TOKENIZER.encode_with_special_tokens(span.as_ref());
if tokens.len() > INPUT_LIMIT {
tokens.truncate(INPUT_LIMIT);
if tokens.len() > OPENAI_INPUT_LIMIT {
tokens.truncate(OPENAI_INPUT_LIMIT);
let result = OPENAI_BPE_TOKENIZER.decode(tokens.clone());
if result.is_ok() {
let transformed = result.unwrap();
// assert_ne!(transformed, span);
return transformed;
}
}
@@ -88,6 +87,7 @@ impl OpenAIEmbeddings {
async fn send_request(&self, api_key: &str, spans: Vec<&str>) -> Result<Response<AsyncBody>> {
let request = Request::post("https://api.openai.com/v1/embeddings")
.redirect_policy(isahc::config::RedirectPolicy::Follow)
.timeout(Duration::from_secs(4))
.header("Content-Type", "application/json")
.header("Authorization", format!("Bearer {}", api_key))
.body(
@@ -106,7 +106,7 @@ impl OpenAIEmbeddings {
#[async_trait]
impl EmbeddingProvider for OpenAIEmbeddings {
async fn embed_batch(&self, spans: Vec<&str>) -> Result<Vec<Vec<f32>>> {
const BACKOFF_SECONDS: [usize; 3] = [65, 180, 360];
const BACKOFF_SECONDS: [usize; 3] = [45, 75, 125];
const MAX_RETRIES: usize = 3;
let api_key = OPENAI_API_KEY
@@ -114,6 +114,7 @@ impl EmbeddingProvider for OpenAIEmbeddings {
.ok_or_else(|| anyhow!("no api key"))?;
let mut request_number = 0;
let mut truncated = false;
let mut response: Response<AsyncBody>;
let mut spans: Vec<String> = spans.iter().map(|x| x.to_string()).collect();
while request_number < MAX_RETRIES {
@@ -132,14 +133,25 @@ impl EmbeddingProvider for OpenAIEmbeddings {
match response.status() {
StatusCode::TOO_MANY_REQUESTS => {
let delay = Duration::from_secs(BACKOFF_SECONDS[request_number - 1] as u64);
log::trace!(
"open ai rate limiting, delaying request by {:?} seconds",
delay.as_secs()
);
self.executor.timer(delay).await;
}
StatusCode::BAD_REQUEST => {
log::info!("BAD REQUEST: {:?}", &response.status());
// Don't worry about delaying bad request, as we can assume
// we haven't been rate limited yet.
for span in spans.iter_mut() {
*span = Self::truncate(span.to_string());
// Only truncate if it hasnt been truncated before
if !truncated {
for span in spans.iter_mut() {
*span = Self::truncate(span.clone());
}
truncated = true;
} else {
// If failing once already truncated, log the error and break the loop
let mut body = String::new();
response.body_mut().read_to_string(&mut body).await?;
log::trace!("open ai bad request: {:?} {:?}", &response.status(), body);
break;
}
}
StatusCode::OK => {
@@ -147,7 +159,7 @@ impl EmbeddingProvider for OpenAIEmbeddings {
response.body_mut().read_to_string(&mut body).await?;
let response: OpenAIEmbeddingResponse = serde_json::from_str(&body)?;
log::info!(
log::trace!(
"openai embedding completed. tokens: {:?}",
response.usage.total_tokens
);
+299
View File
@@ -0,0 +1,299 @@
use anyhow::{anyhow, Ok, Result};
use language::{Grammar, Language};
use std::{
cmp::{self, Reverse},
collections::HashSet,
ops::Range,
path::Path,
sync::Arc,
};
use tree_sitter::{Parser, QueryCursor};
#[derive(Debug, PartialEq, Clone)]
pub struct Document {
pub name: String,
pub range: Range<usize>,
pub content: String,
pub embedding: Vec<f32>,
}
const CODE_CONTEXT_TEMPLATE: &str =
"The below code snippet is from file '<path>'\n\n```<language>\n<item>\n```";
const ENTIRE_FILE_TEMPLATE: &str =
"The below snippet is from file '<path>'\n\n```<language>\n<item>\n```";
pub const PARSEABLE_ENTIRE_FILE_TYPES: &[&str] = &["TOML", "YAML", "CSS"];
pub struct CodeContextRetriever {
pub parser: Parser,
pub cursor: QueryCursor,
}
// Every match has an item, this represents the fundamental treesitter symbol and anchors the search
// Every match has one or more 'name' captures. These indicate the display range of the item for deduplication.
// If there are preceeding comments, we track this with a context capture
// If there is a piece that should be collapsed in hierarchical queries, we capture it with a collapse capture
// If there is a piece that should be kept inside a collapsed node, we capture it with a keep capture
#[derive(Debug, Clone)]
pub struct CodeContextMatch {
pub start_col: usize,
pub item_range: Option<Range<usize>>,
pub name_range: Option<Range<usize>>,
pub context_ranges: Vec<Range<usize>>,
pub collapse_ranges: Vec<Range<usize>>,
}
impl CodeContextRetriever {
pub fn new() -> Self {
Self {
parser: Parser::new(),
cursor: QueryCursor::new(),
}
}
fn parse_entire_file(
&self,
relative_path: &Path,
language_name: Arc<str>,
content: &str,
) -> Result<Vec<Document>> {
let document_span = ENTIRE_FILE_TEMPLATE
.replace("<path>", relative_path.to_string_lossy().as_ref())
.replace("<language>", language_name.as_ref())
.replace("item", &content);
Ok(vec![Document {
range: 0..content.len(),
content: document_span,
embedding: Vec::new(),
name: language_name.to_string(),
}])
}
fn get_matches_in_file(
&mut self,
content: &str,
grammar: &Arc<Grammar>,
) -> Result<Vec<CodeContextMatch>> {
let embedding_config = grammar
.embedding_config
.as_ref()
.ok_or_else(|| anyhow!("no embedding queries"))?;
self.parser.set_language(grammar.ts_language).unwrap();
let tree = self
.parser
.parse(&content, None)
.ok_or_else(|| anyhow!("parsing failed"))?;
let mut captures: Vec<CodeContextMatch> = Vec::new();
let mut collapse_ranges: Vec<Range<usize>> = Vec::new();
let mut keep_ranges: Vec<Range<usize>> = Vec::new();
for mat in self.cursor.matches(
&embedding_config.query,
tree.root_node(),
content.as_bytes(),
) {
let mut start_col = 0;
let mut item_range: Option<Range<usize>> = None;
let mut name_range: Option<Range<usize>> = None;
let mut context_ranges: Vec<Range<usize>> = Vec::new();
collapse_ranges.clear();
keep_ranges.clear();
for capture in mat.captures {
if capture.index == embedding_config.item_capture_ix {
item_range = Some(capture.node.byte_range());
start_col = capture.node.start_position().column;
} else if Some(capture.index) == embedding_config.name_capture_ix {
name_range = Some(capture.node.byte_range());
} else if Some(capture.index) == embedding_config.context_capture_ix {
context_ranges.push(capture.node.byte_range());
} else if Some(capture.index) == embedding_config.collapse_capture_ix {
collapse_ranges.push(capture.node.byte_range());
} else if Some(capture.index) == embedding_config.keep_capture_ix {
keep_ranges.push(capture.node.byte_range());
}
}
captures.push(CodeContextMatch {
start_col,
item_range,
name_range,
context_ranges,
collapse_ranges: subtract_ranges(&collapse_ranges, &keep_ranges),
});
}
Ok(captures)
}
pub fn parse_file_with_template(
&mut self,
relative_path: &Path,
content: &str,
language: Arc<Language>,
) -> Result<Vec<Document>> {
let language_name = language.name();
if PARSEABLE_ENTIRE_FILE_TYPES.contains(&language_name.as_ref()) {
return self.parse_entire_file(relative_path, language_name, &content);
}
let mut documents = self.parse_file(content, language)?;
for document in &mut documents {
document.content = CODE_CONTEXT_TEMPLATE
.replace("<path>", relative_path.to_string_lossy().as_ref())
.replace("<language>", language_name.as_ref())
.replace("item", &document.content);
}
Ok(documents)
}
pub fn parse_file(&mut self, content: &str, language: Arc<Language>) -> Result<Vec<Document>> {
let grammar = language
.grammar()
.ok_or_else(|| anyhow!("no grammar for language"))?;
// Iterate through query matches
let matches = self.get_matches_in_file(content, grammar)?;
let language_scope = language.default_scope();
let placeholder = language_scope.collapsed_placeholder();
let mut documents = Vec::new();
let mut collapsed_ranges_within = Vec::new();
let mut parsed_name_ranges = HashSet::new();
for (i, context_match) in matches.iter().enumerate() {
// Items which are collapsible but not embeddable have no item range
let item_range = if let Some(item_range) = context_match.item_range.clone() {
item_range
} else {
continue;
};
// Checks for deduplication
let name;
if let Some(name_range) = context_match.name_range.clone() {
name = content
.get(name_range.clone())
.map_or(String::new(), |s| s.to_string());
if parsed_name_ranges.contains(&name_range) {
continue;
}
parsed_name_ranges.insert(name_range);
} else {
name = String::new();
}
collapsed_ranges_within.clear();
'outer: for remaining_match in &matches[(i + 1)..] {
for collapsed_range in &remaining_match.collapse_ranges {
if item_range.start <= collapsed_range.start
&& item_range.end >= collapsed_range.end
{
collapsed_ranges_within.push(collapsed_range.clone());
} else {
break 'outer;
}
}
}
collapsed_ranges_within.sort_by_key(|r| (r.start, Reverse(r.end)));
let mut document_content = String::new();
for context_range in &context_match.context_ranges {
document_content.push_str(&content[context_range.clone()]);
document_content.push_str("\n");
}
let mut offset = item_range.start;
for collapsed_range in &collapsed_ranges_within {
if collapsed_range.start > offset {
add_content_from_range(
&mut document_content,
content,
offset..collapsed_range.start,
context_match.start_col,
);
offset = collapsed_range.start;
}
if collapsed_range.end > offset {
document_content.push_str(placeholder);
offset = collapsed_range.end;
}
}
if offset < item_range.end {
add_content_from_range(
&mut document_content,
content,
offset..item_range.end,
context_match.start_col,
);
}
documents.push(Document {
name,
content: document_content,
range: item_range.clone(),
embedding: vec![],
})
}
return Ok(documents);
}
}
pub(crate) fn subtract_ranges(
ranges: &[Range<usize>],
ranges_to_subtract: &[Range<usize>],
) -> Vec<Range<usize>> {
let mut result = Vec::new();
let mut ranges_to_subtract = ranges_to_subtract.iter().peekable();
for range in ranges {
let mut offset = range.start;
while offset < range.end {
if let Some(range_to_subtract) = ranges_to_subtract.peek() {
if offset < range_to_subtract.start {
let next_offset = cmp::min(range_to_subtract.start, range.end);
result.push(offset..next_offset);
offset = next_offset;
} else {
let next_offset = cmp::min(range_to_subtract.end, range.end);
offset = next_offset;
}
if offset >= range_to_subtract.end {
ranges_to_subtract.next();
}
} else {
result.push(offset..range.end);
offset = range.end;
}
}
}
result
}
fn add_content_from_range(
output: &mut String,
content: &str,
range: Range<usize>,
start_col: usize,
) {
for mut line in content.get(range.clone()).unwrap_or("").lines() {
for _ in 0..start_col {
if line.starts_with(' ') {
line = &line[1..];
} else {
break;
}
}
output.push_str(line);
output.push('\n');
}
output.pop();
}
+777
View File
@@ -0,0 +1,777 @@
mod db;
mod embedding;
mod parsing;
pub mod semantic_index_settings;
#[cfg(test)]
mod semantic_index_tests;
use crate::semantic_index_settings::SemanticIndexSettings;
use anyhow::{anyhow, Result};
use db::VectorDatabase;
use embedding::{EmbeddingProvider, OpenAIEmbeddings};
use futures::{channel::oneshot, Future};
use globset::GlobMatcher;
use gpui::{AppContext, AsyncAppContext, Entity, ModelContext, ModelHandle, Task, WeakModelHandle};
use language::{Anchor, Buffer, Language, LanguageRegistry};
use parking_lot::Mutex;
use parsing::{CodeContextRetriever, Document, PARSEABLE_ENTIRE_FILE_TYPES};
use postage::watch;
use project::{Fs, Project, WorktreeId};
use smol::channel;
use std::{
collections::HashMap,
mem,
ops::Range,
path::{Path, PathBuf},
sync::{Arc, Weak},
time::{Instant, SystemTime},
};
use util::{
channel::{ReleaseChannel, RELEASE_CHANNEL, RELEASE_CHANNEL_NAME},
http::HttpClient,
paths::EMBEDDINGS_DIR,
ResultExt,
};
const SEMANTIC_INDEX_VERSION: usize = 6;
const EMBEDDINGS_BATCH_SIZE: usize = 80;
pub fn init(
fs: Arc<dyn Fs>,
http_client: Arc<dyn HttpClient>,
language_registry: Arc<LanguageRegistry>,
cx: &mut AppContext,
) {
settings::register::<SemanticIndexSettings>(cx);
let db_file_path = EMBEDDINGS_DIR
.join(Path::new(RELEASE_CHANNEL_NAME.as_str()))
.join("embeddings_db");
if *RELEASE_CHANNEL == ReleaseChannel::Stable
|| !settings::get::<SemanticIndexSettings>(cx).enabled
{
return;
}
cx.spawn(move |mut cx| async move {
let semantic_index = SemanticIndex::new(
fs,
db_file_path,
Arc::new(OpenAIEmbeddings {
client: http_client,
executor: cx.background(),
}),
language_registry,
cx.clone(),
)
.await?;
cx.update(|cx| {
cx.set_global(semantic_index.clone());
});
anyhow::Ok(())
})
.detach();
}
pub struct SemanticIndex {
fs: Arc<dyn Fs>,
database_url: Arc<PathBuf>,
embedding_provider: Arc<dyn EmbeddingProvider>,
language_registry: Arc<LanguageRegistry>,
db_update_tx: channel::Sender<DbOperation>,
parsing_files_tx: channel::Sender<PendingFile>,
_db_update_task: Task<()>,
_embed_batch_tasks: Vec<Task<()>>,
_batch_files_task: Task<()>,
_parsing_files_tasks: Vec<Task<()>>,
projects: HashMap<WeakModelHandle<Project>, ProjectState>,
}
struct ProjectState {
worktree_db_ids: Vec<(WorktreeId, i64)>,
outstanding_job_count_rx: watch::Receiver<usize>,
_outstanding_job_count_tx: Arc<Mutex<watch::Sender<usize>>>,
}
struct JobHandle {
tx: Weak<Mutex<watch::Sender<usize>>>,
}
impl ProjectState {
fn db_id_for_worktree_id(&self, id: WorktreeId) -> Option<i64> {
self.worktree_db_ids
.iter()
.find_map(|(worktree_id, db_id)| {
if *worktree_id == id {
Some(*db_id)
} else {
None
}
})
}
fn worktree_id_for_db_id(&self, id: i64) -> Option<WorktreeId> {
self.worktree_db_ids
.iter()
.find_map(|(worktree_id, db_id)| {
if *db_id == id {
Some(*worktree_id)
} else {
None
}
})
}
}
pub struct PendingFile {
worktree_db_id: i64,
relative_path: PathBuf,
absolute_path: PathBuf,
language: Arc<Language>,
modified_time: SystemTime,
job_handle: JobHandle,
}
pub struct SearchResult {
pub buffer: ModelHandle<Buffer>,
pub range: Range<Anchor>,
}
enum DbOperation {
InsertFile {
worktree_id: i64,
documents: Vec<Document>,
path: PathBuf,
mtime: SystemTime,
job_handle: JobHandle,
},
Delete {
worktree_id: i64,
path: PathBuf,
},
FindOrCreateWorktree {
path: PathBuf,
sender: oneshot::Sender<Result<i64>>,
},
FileMTimes {
worktree_id: i64,
sender: oneshot::Sender<Result<HashMap<PathBuf, SystemTime>>>,
},
WorktreePreviouslyIndexed {
path: Arc<Path>,
sender: oneshot::Sender<Result<bool>>,
},
}
enum EmbeddingJob {
Enqueue {
worktree_id: i64,
path: PathBuf,
mtime: SystemTime,
documents: Vec<Document>,
job_handle: JobHandle,
},
Flush,
}
impl SemanticIndex {
pub fn global(cx: &AppContext) -> Option<ModelHandle<SemanticIndex>> {
if cx.has_global::<ModelHandle<Self>>() {
Some(cx.global::<ModelHandle<SemanticIndex>>().clone())
} else {
None
}
}
pub fn enabled(cx: &AppContext) -> bool {
settings::get::<SemanticIndexSettings>(cx).enabled
&& *RELEASE_CHANNEL != ReleaseChannel::Stable
}
async fn new(
fs: Arc<dyn Fs>,
database_url: PathBuf,
embedding_provider: Arc<dyn EmbeddingProvider>,
language_registry: Arc<LanguageRegistry>,
mut cx: AsyncAppContext,
) -> Result<ModelHandle<Self>> {
let t0 = Instant::now();
let database_url = Arc::new(database_url);
let db = cx
.background()
.spawn(VectorDatabase::new(fs.clone(), database_url.clone()))
.await?;
log::trace!(
"db initialization took {:?} milliseconds",
t0.elapsed().as_millis()
);
Ok(cx.add_model(|cx| {
let t0 = Instant::now();
// Perform database operations
let (db_update_tx, db_update_rx) = channel::unbounded();
let _db_update_task = cx.background().spawn({
async move {
while let Ok(job) = db_update_rx.recv().await {
Self::run_db_operation(&db, job)
}
}
});
// Group documents into batches and send them to the embedding provider.
let (embed_batch_tx, embed_batch_rx) =
channel::unbounded::<Vec<(i64, Vec<Document>, PathBuf, SystemTime, JobHandle)>>();
let mut _embed_batch_tasks = Vec::new();
for _ in 0..cx.background().num_cpus() {
let embed_batch_rx = embed_batch_rx.clone();
_embed_batch_tasks.push(cx.background().spawn({
let db_update_tx = db_update_tx.clone();
let embedding_provider = embedding_provider.clone();
async move {
while let Ok(embeddings_queue) = embed_batch_rx.recv().await {
Self::compute_embeddings_for_batch(
embeddings_queue,
&embedding_provider,
&db_update_tx,
)
.await;
}
}
}));
}
// Group documents into batches and send them to the embedding provider.
let (batch_files_tx, batch_files_rx) = channel::unbounded::<EmbeddingJob>();
let _batch_files_task = cx.background().spawn(async move {
let mut queue_len = 0;
let mut embeddings_queue = vec![];
while let Ok(job) = batch_files_rx.recv().await {
Self::enqueue_documents_to_embed(
job,
&mut queue_len,
&mut embeddings_queue,
&embed_batch_tx,
);
}
});
// Parse files into embeddable documents.
let (parsing_files_tx, parsing_files_rx) = channel::unbounded::<PendingFile>();
let mut _parsing_files_tasks = Vec::new();
for _ in 0..cx.background().num_cpus() {
let fs = fs.clone();
let parsing_files_rx = parsing_files_rx.clone();
let batch_files_tx = batch_files_tx.clone();
let db_update_tx = db_update_tx.clone();
_parsing_files_tasks.push(cx.background().spawn(async move {
let mut retriever = CodeContextRetriever::new();
while let Ok(pending_file) = parsing_files_rx.recv().await {
Self::parse_file(
&fs,
pending_file,
&mut retriever,
&batch_files_tx,
&parsing_files_rx,
&db_update_tx,
)
.await;
}
}));
}
log::trace!(
"semantic index task initialization took {:?} milliseconds",
t0.elapsed().as_millis()
);
Self {
fs,
database_url,
embedding_provider,
language_registry,
db_update_tx,
parsing_files_tx,
_db_update_task,
_embed_batch_tasks,
_batch_files_task,
_parsing_files_tasks,
projects: HashMap::new(),
}
}))
}
fn run_db_operation(db: &VectorDatabase, job: DbOperation) {
match job {
DbOperation::InsertFile {
worktree_id,
documents,
path,
mtime,
job_handle,
} => {
db.insert_file(worktree_id, path, mtime, documents)
.log_err();
drop(job_handle)
}
DbOperation::Delete { worktree_id, path } => {
db.delete_file(worktree_id, path).log_err();
}
DbOperation::FindOrCreateWorktree { path, sender } => {
let id = db.find_or_create_worktree(&path);
sender.send(id).ok();
}
DbOperation::FileMTimes {
worktree_id: worktree_db_id,
sender,
} => {
let file_mtimes = db.get_file_mtimes(worktree_db_id);
sender.send(file_mtimes).ok();
}
DbOperation::WorktreePreviouslyIndexed { path, sender } => {
let worktree_indexed = db.worktree_previously_indexed(path.as_ref());
sender.send(worktree_indexed).ok();
}
}
}
async fn compute_embeddings_for_batch(
mut embeddings_queue: Vec<(i64, Vec<Document>, PathBuf, SystemTime, JobHandle)>,
embedding_provider: &Arc<dyn EmbeddingProvider>,
db_update_tx: &channel::Sender<DbOperation>,
) {
let mut batch_documents = vec![];
for (_, documents, _, _, _) in embeddings_queue.iter() {
batch_documents.extend(documents.iter().map(|document| document.content.as_str()));
}
if let Ok(embeddings) = embedding_provider.embed_batch(batch_documents).await {
log::trace!(
"created {} embeddings for {} files",
embeddings.len(),
embeddings_queue.len(),
);
let mut i = 0;
let mut j = 0;
for embedding in embeddings.iter() {
while embeddings_queue[i].1.len() == j {
i += 1;
j = 0;
}
embeddings_queue[i].1[j].embedding = embedding.to_owned();
j += 1;
}
for (worktree_id, documents, path, mtime, job_handle) in embeddings_queue.into_iter() {
db_update_tx
.send(DbOperation::InsertFile {
worktree_id,
documents,
path,
mtime,
job_handle,
})
.await
.unwrap();
}
}
}
fn enqueue_documents_to_embed(
job: EmbeddingJob,
queue_len: &mut usize,
embeddings_queue: &mut Vec<(i64, Vec<Document>, PathBuf, SystemTime, JobHandle)>,
embed_batch_tx: &channel::Sender<Vec<(i64, Vec<Document>, PathBuf, SystemTime, JobHandle)>>,
) {
let should_flush = match job {
EmbeddingJob::Enqueue {
documents,
worktree_id,
path,
mtime,
job_handle,
} => {
*queue_len += &documents.len();
embeddings_queue.push((worktree_id, documents, path, mtime, job_handle));
*queue_len >= EMBEDDINGS_BATCH_SIZE
}
EmbeddingJob::Flush => true,
};
if should_flush {
embed_batch_tx
.try_send(mem::take(embeddings_queue))
.unwrap();
*queue_len = 0;
}
}
async fn parse_file(
fs: &Arc<dyn Fs>,
pending_file: PendingFile,
retriever: &mut CodeContextRetriever,
batch_files_tx: &channel::Sender<EmbeddingJob>,
parsing_files_rx: &channel::Receiver<PendingFile>,
db_update_tx: &channel::Sender<DbOperation>,
) {
if let Some(content) = fs.load(&pending_file.absolute_path).await.log_err() {
if let Some(documents) = retriever
.parse_file_with_template(
&pending_file.relative_path,
&content,
pending_file.language,
)
.log_err()
{
log::trace!(
"parsed path {:?}: {} documents",
pending_file.relative_path,
documents.len()
);
if documents.len() == 0 {
db_update_tx
.send(DbOperation::InsertFile {
worktree_id: pending_file.worktree_db_id,
documents,
path: pending_file.relative_path,
mtime: pending_file.modified_time,
job_handle: pending_file.job_handle,
})
.await
.unwrap();
} else {
batch_files_tx
.try_send(EmbeddingJob::Enqueue {
worktree_id: pending_file.worktree_db_id,
path: pending_file.relative_path,
mtime: pending_file.modified_time,
job_handle: pending_file.job_handle,
documents,
})
.unwrap();
}
}
}
if parsing_files_rx.len() == 0 {
batch_files_tx.try_send(EmbeddingJob::Flush).unwrap();
}
}
fn find_or_create_worktree(&self, path: PathBuf) -> impl Future<Output = Result<i64>> {
let (tx, rx) = oneshot::channel();
self.db_update_tx
.try_send(DbOperation::FindOrCreateWorktree { path, sender: tx })
.unwrap();
async move { rx.await? }
}
fn get_file_mtimes(
&self,
worktree_id: i64,
) -> impl Future<Output = Result<HashMap<PathBuf, SystemTime>>> {
let (tx, rx) = oneshot::channel();
self.db_update_tx
.try_send(DbOperation::FileMTimes {
worktree_id,
sender: tx,
})
.unwrap();
async move { rx.await? }
}
fn worktree_previously_indexed(&self, path: Arc<Path>) -> impl Future<Output = Result<bool>> {
let (tx, rx) = oneshot::channel();
self.db_update_tx
.try_send(DbOperation::WorktreePreviouslyIndexed { path, sender: tx })
.unwrap();
async move { rx.await? }
}
pub fn project_previously_indexed(
&mut self,
project: ModelHandle<Project>,
cx: &mut ModelContext<Self>,
) -> Task<Result<bool>> {
let worktree_scans_complete = project
.read(cx)
.worktrees(cx)
.map(|worktree| {
let scan_complete = worktree.read(cx).as_local().unwrap().scan_complete();
async move {
scan_complete.await;
}
})
.collect::<Vec<_>>();
let worktrees_indexed_previously = project
.read(cx)
.worktrees(cx)
.map(|worktree| self.worktree_previously_indexed(worktree.read(cx).abs_path()))
.collect::<Vec<_>>();
cx.spawn(|_, _cx| async move {
futures::future::join_all(worktree_scans_complete).await;
let worktree_indexed_previously =
futures::future::join_all(worktrees_indexed_previously).await;
Ok(worktree_indexed_previously
.iter()
.filter(|worktree| worktree.is_ok())
.all(|v| v.as_ref().log_err().is_some_and(|v| v.to_owned())))
})
}
pub fn index_project(
&mut self,
project: ModelHandle<Project>,
cx: &mut ModelContext<Self>,
) -> Task<Result<(usize, watch::Receiver<usize>)>> {
let t0 = Instant::now();
let worktree_scans_complete = project
.read(cx)
.worktrees(cx)
.map(|worktree| {
let scan_complete = worktree.read(cx).as_local().unwrap().scan_complete();
async move {
scan_complete.await;
}
})
.collect::<Vec<_>>();
let worktree_db_ids = project
.read(cx)
.worktrees(cx)
.map(|worktree| {
self.find_or_create_worktree(worktree.read(cx).abs_path().to_path_buf())
})
.collect::<Vec<_>>();
let language_registry = self.language_registry.clone();
let db_update_tx = self.db_update_tx.clone();
let parsing_files_tx = self.parsing_files_tx.clone();
cx.spawn(|this, mut cx| async move {
futures::future::join_all(worktree_scans_complete).await;
let worktree_db_ids = futures::future::join_all(worktree_db_ids).await;
let worktrees = project.read_with(&cx, |project, cx| {
project
.worktrees(cx)
.map(|worktree| worktree.read(cx).snapshot())
.collect::<Vec<_>>()
});
let mut worktree_file_mtimes = HashMap::new();
let mut db_ids_by_worktree_id = HashMap::new();
for (worktree, db_id) in worktrees.iter().zip(worktree_db_ids) {
let db_id = db_id?;
db_ids_by_worktree_id.insert(worktree.id(), db_id);
worktree_file_mtimes.insert(
worktree.id(),
this.read_with(&cx, |this, _| this.get_file_mtimes(db_id))
.await?,
);
}
let (job_count_tx, job_count_rx) = watch::channel_with(0);
let job_count_tx = Arc::new(Mutex::new(job_count_tx));
this.update(&mut cx, |this, _| {
this.projects.insert(
project.downgrade(),
ProjectState {
worktree_db_ids: db_ids_by_worktree_id
.iter()
.map(|(a, b)| (*a, *b))
.collect(),
outstanding_job_count_rx: job_count_rx.clone(),
_outstanding_job_count_tx: job_count_tx.clone(),
},
);
});
cx.background()
.spawn(async move {
let mut count = 0;
for worktree in worktrees.into_iter() {
let mut file_mtimes = worktree_file_mtimes.remove(&worktree.id()).unwrap();
for file in worktree.files(false, 0) {
let absolute_path = worktree.absolutize(&file.path);
if let Ok(language) = language_registry
.language_for_file(&absolute_path, None)
.await
{
if !PARSEABLE_ENTIRE_FILE_TYPES.contains(&language.name().as_ref())
&& language
.grammar()
.and_then(|grammar| grammar.embedding_config.as_ref())
.is_none()
{
continue;
}
let path_buf = file.path.to_path_buf();
let stored_mtime = file_mtimes.remove(&file.path.to_path_buf());
let already_stored = stored_mtime
.map_or(false, |existing_mtime| existing_mtime == file.mtime);
if !already_stored {
count += 1;
*job_count_tx.lock().borrow_mut() += 1;
let job_handle = JobHandle {
tx: Arc::downgrade(&job_count_tx),
};
parsing_files_tx
.try_send(PendingFile {
worktree_db_id: db_ids_by_worktree_id[&worktree.id()],
relative_path: path_buf,
absolute_path,
language,
job_handle,
modified_time: file.mtime,
})
.unwrap();
}
}
}
for file in file_mtimes.keys() {
db_update_tx
.try_send(DbOperation::Delete {
worktree_id: db_ids_by_worktree_id[&worktree.id()],
path: file.to_owned(),
})
.unwrap();
}
}
log::trace!(
"walking worktree took {:?} milliseconds",
t0.elapsed().as_millis()
);
anyhow::Ok((count, job_count_rx))
})
.await
})
}
pub fn outstanding_job_count_rx(
&self,
project: &ModelHandle<Project>,
) -> Option<watch::Receiver<usize>> {
Some(
self.projects
.get(&project.downgrade())?
.outstanding_job_count_rx
.clone(),
)
}
pub fn search_project(
&mut self,
project: ModelHandle<Project>,
phrase: String,
limit: usize,
include_globs: Vec<GlobMatcher>,
exclude_globs: Vec<GlobMatcher>,
cx: &mut ModelContext<Self>,
) -> Task<Result<Vec<SearchResult>>> {
let project_state = if let Some(state) = self.projects.get(&project.downgrade()) {
state
} else {
return Task::ready(Err(anyhow!("project not added")));
};
let worktree_db_ids = project
.read(cx)
.worktrees(cx)
.filter_map(|worktree| {
let worktree_id = worktree.read(cx).id();
project_state.db_id_for_worktree_id(worktree_id)
})
.collect::<Vec<_>>();
let embedding_provider = self.embedding_provider.clone();
let database_url = self.database_url.clone();
let fs = self.fs.clone();
cx.spawn(|this, mut cx| async move {
let documents = cx
.background()
.spawn(async move {
let database = VectorDatabase::new(fs, database_url).await?;
let phrase_embedding = embedding_provider
.embed_batch(vec![&phrase])
.await?
.into_iter()
.next()
.unwrap();
database.top_k_search(
&worktree_db_ids,
&phrase_embedding,
limit,
include_globs,
exclude_globs,
)
})
.await?;
let mut tasks = Vec::new();
let mut ranges = Vec::new();
let weak_project = project.downgrade();
project.update(&mut cx, |project, cx| {
for (worktree_db_id, file_path, byte_range) in documents {
let project_state =
if let Some(state) = this.read(cx).projects.get(&weak_project) {
state
} else {
return Err(anyhow!("project not added"));
};
if let Some(worktree_id) = project_state.worktree_id_for_db_id(worktree_db_id) {
tasks.push(project.open_buffer((worktree_id, file_path), cx));
ranges.push(byte_range);
}
}
Ok(())
})?;
let buffers = futures::future::join_all(tasks).await;
Ok(buffers
.into_iter()
.zip(ranges)
.filter_map(|(buffer, range)| {
let buffer = buffer.log_err()?;
let range = buffer.read_with(&cx, |buffer, _| {
buffer.anchor_before(range.start)..buffer.anchor_after(range.end)
});
Some(SearchResult { buffer, range })
})
.collect::<Vec<_>>())
})
}
}
impl Entity for SemanticIndex {
type Event = ();
}
impl Drop for JobHandle {
fn drop(&mut self) {
if let Some(tx) = self.tx.upgrade() {
let mut tx = tx.lock();
*tx.borrow_mut() -= 1;
}
}
}
@@ -4,21 +4,21 @@ use serde::{Deserialize, Serialize};
use settings::Setting;
#[derive(Deserialize, Debug)]
pub struct VectorStoreSettings {
pub struct SemanticIndexSettings {
pub enabled: bool,
pub reindexing_delay_seconds: usize,
}
#[derive(Clone, Default, Serialize, Deserialize, JsonSchema, Debug)]
pub struct VectorStoreSettingsContent {
pub struct SemanticIndexSettingsContent {
pub enabled: Option<bool>,
pub reindexing_delay_seconds: Option<usize>,
}
impl Setting for VectorStoreSettings {
const KEY: Option<&'static str> = Some("vector_store");
impl Setting for SemanticIndexSettings {
const KEY: Option<&'static str> = Some("semantic_index");
type FileContent = VectorStoreSettingsContent;
type FileContent = SemanticIndexSettingsContent;
fn load(
default_value: &Self::FileContent,
File diff suppressed because it is too large Load Diff
-172
View File
@@ -1,172 +0,0 @@
use crate::{SearchResult, VectorStore};
use editor::{scroll::autoscroll::Autoscroll, Editor};
use gpui::{
actions, elements::*, AnyElement, AppContext, ModelHandle, MouseState, Task, ViewContext,
WeakViewHandle,
};
use picker::{Picker, PickerDelegate, PickerEvent};
use project::{Project, ProjectPath};
use std::{collections::HashMap, sync::Arc, time::Duration};
use util::ResultExt;
use workspace::Workspace;
const MIN_QUERY_LEN: usize = 5;
const EMBEDDING_DEBOUNCE_INTERVAL: Duration = Duration::from_millis(500);
actions!(semantic_search, [Toggle]);
pub type SemanticSearch = Picker<SemanticSearchDelegate>;
pub struct SemanticSearchDelegate {
workspace: WeakViewHandle<Workspace>,
project: ModelHandle<Project>,
vector_store: ModelHandle<VectorStore>,
selected_match_index: usize,
matches: Vec<SearchResult>,
history: HashMap<String, Vec<SearchResult>>,
}
impl SemanticSearchDelegate {
// This is currently searching on every keystroke,
// This is wildly overkill, and has the potential to get expensive
// We will need to update this to throttle searching
pub fn new(
workspace: WeakViewHandle<Workspace>,
project: ModelHandle<Project>,
vector_store: ModelHandle<VectorStore>,
) -> Self {
Self {
workspace,
project,
vector_store,
selected_match_index: 0,
matches: vec![],
history: HashMap::new(),
}
}
}
impl PickerDelegate for SemanticSearchDelegate {
fn placeholder_text(&self) -> Arc<str> {
"Search repository in natural language...".into()
}
fn confirm(&mut self, _: bool, cx: &mut ViewContext<SemanticSearch>) {
if let Some(search_result) = self.matches.get(self.selected_match_index) {
// Open Buffer
let search_result = search_result.clone();
let buffer = self.project.update(cx, |project, cx| {
project.open_buffer(
ProjectPath {
worktree_id: search_result.worktree_id,
path: search_result.file_path.clone().into(),
},
cx,
)
});
let workspace = self.workspace.clone();
let position = search_result.clone().offset;
cx.spawn(|_, mut cx| async move {
let buffer = buffer.await?;
workspace.update(&mut cx, |workspace, cx| {
let editor = workspace.open_project_item::<Editor>(buffer, cx);
editor.update(cx, |editor, cx| {
editor.change_selections(Some(Autoscroll::center()), cx, |s| {
s.select_ranges([position..position])
});
});
})?;
Ok::<_, anyhow::Error>(())
})
.detach_and_log_err(cx);
cx.emit(PickerEvent::Dismiss);
}
}
fn dismissed(&mut self, _cx: &mut ViewContext<SemanticSearch>) {}
fn match_count(&self) -> usize {
self.matches.len()
}
fn selected_index(&self) -> usize {
self.selected_match_index
}
fn set_selected_index(&mut self, ix: usize, _cx: &mut ViewContext<SemanticSearch>) {
self.selected_match_index = ix;
}
fn update_matches(&mut self, query: String, cx: &mut ViewContext<SemanticSearch>) -> Task<()> {
log::info!("Searching for {:?}...", query);
if query.len() < MIN_QUERY_LEN {
log::info!("Query below minimum length");
return Task::ready(());
}
let vector_store = self.vector_store.clone();
let project = self.project.clone();
cx.spawn(|this, mut cx| async move {
cx.background().timer(EMBEDDING_DEBOUNCE_INTERVAL).await;
let retrieved_cached = this.update(&mut cx, |this, _| {
let delegate = this.delegate_mut();
if delegate.history.contains_key(&query) {
let historic_results = delegate.history.get(&query).unwrap().to_owned();
delegate.matches = historic_results.clone();
true
} else {
false
}
});
if let Some(retrieved) = retrieved_cached.log_err() {
if !retrieved {
let task = vector_store.update(&mut cx, |store, cx| {
store.search(project.clone(), query.to_string(), 10, cx)
});
if let Some(results) = task.await.log_err() {
log::info!("Not queried previously, searching...");
this.update(&mut cx, |this, _| {
let delegate = this.delegate_mut();
delegate.matches = results.clone();
delegate.history.insert(query, results);
})
.ok();
}
} else {
log::info!("Already queried, retrieved directly from cached history");
}
}
})
}
fn render_match(
&self,
ix: usize,
mouse_state: &mut MouseState,
selected: bool,
cx: &AppContext,
) -> AnyElement<Picker<Self>> {
let theme = theme::current(cx);
let style = &theme.picker.item;
let current_style = style.in_state(selected).style_for(mouse_state);
let search_result = &self.matches[ix];
let path = search_result.file_path.to_string_lossy();
let name = search_result.name.clone();
Flex::column()
.with_child(Text::new(name, current_style.label.text.clone()).with_soft_wrap(false))
.with_child(Label::new(
path.to_string(),
style.inactive_state().default.label.clone(),
))
.contained()
.with_style(current_style.container)
.into_any()
}
}
-115
View File
@@ -1,115 +0,0 @@
use std::{path::PathBuf, sync::Arc, time::SystemTime};
use anyhow::{anyhow, Ok, Result};
use project::Fs;
use tree_sitter::{Parser, QueryCursor};
use crate::PendingFile;
#[derive(Debug, PartialEq, Clone)]
pub struct Document {
pub offset: usize,
pub name: String,
pub embedding: Vec<f32>,
}
#[derive(Debug, PartialEq, Clone)]
pub struct ParsedFile {
pub path: PathBuf,
pub mtime: SystemTime,
pub documents: Vec<Document>,
}
const CODE_CONTEXT_TEMPLATE: &str =
"The below code snippet is from file '<path>'\n\n```<language>\n<item>\n```";
pub struct CodeContextRetriever {
pub parser: Parser,
pub cursor: QueryCursor,
pub fs: Arc<dyn Fs>,
}
impl CodeContextRetriever {
pub async fn parse_file(
&mut self,
pending_file: PendingFile,
) -> Result<(ParsedFile, Vec<String>)> {
let grammar = pending_file
.language
.grammar()
.ok_or_else(|| anyhow!("no grammar for language"))?;
let embedding_config = grammar
.embedding_config
.as_ref()
.ok_or_else(|| anyhow!("no embedding queries"))?;
let content = self.fs.load(&pending_file.absolute_path).await?;
self.parser.set_language(grammar.ts_language).unwrap();
let tree = self
.parser
.parse(&content, None)
.ok_or_else(|| anyhow!("parsing failed"))?;
let mut documents = Vec::new();
let mut context_spans = Vec::new();
// Iterate through query matches
for mat in self.cursor.matches(
&embedding_config.query,
tree.root_node(),
content.as_bytes(),
) {
// log::info!("-----MATCH-----");
let mut name = Vec::new();
let mut item: Option<&str> = None;
let mut offset: Option<usize> = None;
for capture in mat.captures {
if capture.index == embedding_config.item_capture_ix {
offset = Some(capture.node.byte_range().start);
item = content.get(capture.node.byte_range());
} else if capture.index == embedding_config.name_capture_ix {
if let Some(name_content) = content.get(capture.node.byte_range()) {
name.push(name_content);
}
}
if let Some(context_capture_ix) = embedding_config.context_capture_ix {
if capture.index == context_capture_ix {
if let Some(context) = content.get(capture.node.byte_range()) {
name.push(context);
}
}
}
}
if item.is_some() && offset.is_some() && name.len() > 0 {
let context_span = CODE_CONTEXT_TEMPLATE
.replace("<path>", pending_file.relative_path.to_str().unwrap())
.replace("<language>", &pending_file.language.name().to_lowercase())
.replace("<item>", item.unwrap());
// log::info!("Name: {:?}", name);
// log::info!("Span: {:?}", util::truncate(&context_span, 100));
context_spans.push(context_span);
documents.push(Document {
name: name.join(" "),
offset: offset.unwrap(),
embedding: Vec::new(),
})
}
}
return Ok((
ParsedFile {
path: pending_file.relative_path,
mtime: pending_file.modified_time,
documents,
},
context_spans,
));
}
}
-770
View File
@@ -1,770 +0,0 @@
mod db;
mod embedding;
mod modal;
mod parsing;
mod vector_store_settings;
#[cfg(test)]
mod vector_store_tests;
use crate::vector_store_settings::VectorStoreSettings;
use anyhow::{anyhow, Result};
use db::VectorDatabase;
use embedding::{EmbeddingProvider, OpenAIEmbeddings};
use futures::{channel::oneshot, Future};
use gpui::{
AppContext, AsyncAppContext, Entity, ModelContext, ModelHandle, Task, ViewContext,
WeakModelHandle,
};
use language::{Language, LanguageRegistry};
use modal::{SemanticSearch, SemanticSearchDelegate, Toggle};
use parsing::{CodeContextRetriever, ParsedFile};
use project::{Fs, PathChange, Project, ProjectEntryId, WorktreeId};
use smol::channel;
use std::{
collections::HashMap,
path::{Path, PathBuf},
sync::Arc,
time::{Duration, Instant, SystemTime},
};
use tree_sitter::{Parser, QueryCursor};
use util::{
channel::{ReleaseChannel, RELEASE_CHANNEL, RELEASE_CHANNEL_NAME},
http::HttpClient,
paths::EMBEDDINGS_DIR,
ResultExt,
};
use workspace::{Workspace, WorkspaceCreated};
const VECTOR_STORE_VERSION: usize = 0;
const EMBEDDINGS_BATCH_SIZE: usize = 150;
pub fn init(
fs: Arc<dyn Fs>,
http_client: Arc<dyn HttpClient>,
language_registry: Arc<LanguageRegistry>,
cx: &mut AppContext,
) {
settings::register::<VectorStoreSettings>(cx);
let db_file_path = EMBEDDINGS_DIR
.join(Path::new(RELEASE_CHANNEL_NAME.as_str()))
.join("embeddings_db");
SemanticSearch::init(cx);
cx.add_action(
|workspace: &mut Workspace, _: &Toggle, cx: &mut ViewContext<Workspace>| {
if cx.has_global::<ModelHandle<VectorStore>>() {
let vector_store = cx.global::<ModelHandle<VectorStore>>().clone();
workspace.toggle_modal(cx, |workspace, cx| {
let project = workspace.project().clone();
let workspace = cx.weak_handle();
cx.add_view(|cx| {
SemanticSearch::new(
SemanticSearchDelegate::new(workspace, project, vector_store),
cx,
)
})
});
}
},
);
if *RELEASE_CHANNEL == ReleaseChannel::Stable
|| !settings::get::<VectorStoreSettings>(cx).enabled
{
return;
}
cx.spawn(move |mut cx| async move {
let vector_store = VectorStore::new(
fs,
db_file_path,
// Arc::new(embedding::DummyEmbeddings {}),
Arc::new(OpenAIEmbeddings {
client: http_client,
executor: cx.background(),
}),
language_registry,
cx.clone(),
)
.await?;
cx.update(|cx| {
cx.set_global(vector_store.clone());
cx.subscribe_global::<WorkspaceCreated, _>({
let vector_store = vector_store.clone();
move |event, cx| {
let workspace = &event.0;
if let Some(workspace) = workspace.upgrade(cx) {
let project = workspace.read(cx).project().clone();
if project.read(cx).is_local() {
vector_store.update(cx, |store, cx| {
store.add_project(project, cx).detach();
});
}
}
}
})
.detach();
});
anyhow::Ok(())
})
.detach();
}
pub struct VectorStore {
fs: Arc<dyn Fs>,
database_url: Arc<PathBuf>,
embedding_provider: Arc<dyn EmbeddingProvider>,
language_registry: Arc<LanguageRegistry>,
db_update_tx: channel::Sender<DbOperation>,
parsing_files_tx: channel::Sender<PendingFile>,
_db_update_task: Task<()>,
_embed_batch_task: Task<()>,
_batch_files_task: Task<()>,
_parsing_files_tasks: Vec<Task<()>>,
projects: HashMap<WeakModelHandle<Project>, ProjectState>,
}
struct ProjectState {
worktree_db_ids: Vec<(WorktreeId, i64)>,
pending_files: HashMap<PathBuf, (PendingFile, SystemTime)>,
_subscription: gpui::Subscription,
}
impl ProjectState {
fn db_id_for_worktree_id(&self, id: WorktreeId) -> Option<i64> {
self.worktree_db_ids
.iter()
.find_map(|(worktree_id, db_id)| {
if *worktree_id == id {
Some(*db_id)
} else {
None
}
})
}
fn worktree_id_for_db_id(&self, id: i64) -> Option<WorktreeId> {
self.worktree_db_ids
.iter()
.find_map(|(worktree_id, db_id)| {
if *db_id == id {
Some(*worktree_id)
} else {
None
}
})
}
fn update_pending_files(&mut self, pending_file: PendingFile, indexing_time: SystemTime) {
// If Pending File Already Exists, Replace it with the new one
// but keep the old indexing time
if let Some(old_file) = self
.pending_files
.remove(&pending_file.relative_path.clone())
{
self.pending_files.insert(
pending_file.relative_path.clone(),
(pending_file, old_file.1),
);
} else {
self.pending_files.insert(
pending_file.relative_path.clone(),
(pending_file, indexing_time),
);
};
}
fn get_outstanding_files(&mut self) -> Vec<PendingFile> {
let mut outstanding_files = vec![];
let mut remove_keys = vec![];
for key in self.pending_files.keys().into_iter() {
if let Some(pending_details) = self.pending_files.get(key) {
let (pending_file, index_time) = pending_details;
if index_time <= &SystemTime::now() {
outstanding_files.push(pending_file.clone());
remove_keys.push(key.clone());
}
}
}
for key in remove_keys.iter() {
self.pending_files.remove(key);
}
return outstanding_files;
}
}
#[derive(Clone, Debug)]
pub struct PendingFile {
worktree_db_id: i64,
relative_path: PathBuf,
absolute_path: PathBuf,
language: Arc<Language>,
modified_time: SystemTime,
}
#[derive(Debug, Clone)]
pub struct SearchResult {
pub worktree_id: WorktreeId,
pub name: String,
pub offset: usize,
pub file_path: PathBuf,
}
enum DbOperation {
InsertFile {
worktree_id: i64,
indexed_file: ParsedFile,
},
Delete {
worktree_id: i64,
path: PathBuf,
},
FindOrCreateWorktree {
path: PathBuf,
sender: oneshot::Sender<Result<i64>>,
},
FileMTimes {
worktree_id: i64,
sender: oneshot::Sender<Result<HashMap<PathBuf, SystemTime>>>,
},
}
enum EmbeddingJob {
Enqueue {
worktree_id: i64,
parsed_file: ParsedFile,
document_spans: Vec<String>,
},
Flush,
}
impl VectorStore {
async fn new(
fs: Arc<dyn Fs>,
database_url: PathBuf,
embedding_provider: Arc<dyn EmbeddingProvider>,
language_registry: Arc<LanguageRegistry>,
mut cx: AsyncAppContext,
) -> Result<ModelHandle<Self>> {
let database_url = Arc::new(database_url);
let db = cx
.background()
.spawn({
let fs = fs.clone();
let database_url = database_url.clone();
async move {
if let Some(db_directory) = database_url.parent() {
fs.create_dir(db_directory).await.log_err();
}
let db = VectorDatabase::new(database_url.to_string_lossy().to_string())?;
anyhow::Ok(db)
}
})
.await?;
Ok(cx.add_model(|cx| {
// paths_tx -> embeddings_tx -> db_update_tx
//db_update_tx/rx: Updating Database
let (db_update_tx, db_update_rx) = channel::unbounded();
let _db_update_task = cx.background().spawn(async move {
while let Ok(job) = db_update_rx.recv().await {
match job {
DbOperation::InsertFile {
worktree_id,
indexed_file,
} => {
db.insert_file(worktree_id, indexed_file).log_err();
}
DbOperation::Delete { worktree_id, path } => {
db.delete_file(worktree_id, path).log_err();
}
DbOperation::FindOrCreateWorktree { path, sender } => {
let id = db.find_or_create_worktree(&path);
sender.send(id).ok();
}
DbOperation::FileMTimes {
worktree_id: worktree_db_id,
sender,
} => {
let file_mtimes = db.get_file_mtimes(worktree_db_id);
sender.send(file_mtimes).ok();
}
}
}
});
// embed_tx/rx: Embed Batch and Send to Database
let (embed_batch_tx, embed_batch_rx) =
channel::unbounded::<Vec<(i64, ParsedFile, Vec<String>)>>();
let _embed_batch_task = cx.background().spawn({
let db_update_tx = db_update_tx.clone();
let embedding_provider = embedding_provider.clone();
async move {
while let Ok(mut embeddings_queue) = embed_batch_rx.recv().await {
// Construct Batch
let mut document_spans = vec![];
for (_, _, document_span) in embeddings_queue.iter() {
document_spans.extend(document_span.iter().map(|s| s.as_str()));
}
if let Ok(embeddings) = embedding_provider.embed_batch(document_spans).await
{
let mut i = 0;
let mut j = 0;
for embedding in embeddings.iter() {
while embeddings_queue[i].1.documents.len() == j {
i += 1;
j = 0;
}
embeddings_queue[i].1.documents[j].embedding = embedding.to_owned();
j += 1;
}
for (worktree_id, indexed_file, _) in embeddings_queue.into_iter() {
for document in indexed_file.documents.iter() {
// TODO: Update this so it doesn't panic
assert!(
document.embedding.len() > 0,
"Document Embedding Not Complete"
);
}
db_update_tx
.send(DbOperation::InsertFile {
worktree_id,
indexed_file,
})
.await
.unwrap();
}
}
}
}
});
// batch_tx/rx: Batch Files to Send for Embeddings
let (batch_files_tx, batch_files_rx) = channel::unbounded::<EmbeddingJob>();
let _batch_files_task = cx.background().spawn(async move {
let mut queue_len = 0;
let mut embeddings_queue = vec![];
while let Ok(job) = batch_files_rx.recv().await {
let should_flush = match job {
EmbeddingJob::Enqueue {
document_spans,
worktree_id,
parsed_file,
} => {
queue_len += &document_spans.len();
embeddings_queue.push((worktree_id, parsed_file, document_spans));
queue_len >= EMBEDDINGS_BATCH_SIZE
}
EmbeddingJob::Flush => true,
};
if should_flush {
embed_batch_tx.try_send(embeddings_queue).unwrap();
embeddings_queue = vec![];
queue_len = 0;
}
}
});
// parsing_files_tx/rx: Parsing Files to Embeddable Documents
let (parsing_files_tx, parsing_files_rx) = channel::unbounded::<PendingFile>();
let mut _parsing_files_tasks = Vec::new();
// for _ in 0..cx.background().num_cpus() {
for _ in 0..1 {
let fs = fs.clone();
let parsing_files_rx = parsing_files_rx.clone();
let batch_files_tx = batch_files_tx.clone();
_parsing_files_tasks.push(cx.background().spawn(async move {
let parser = Parser::new();
let cursor = QueryCursor::new();
let mut retriever = CodeContextRetriever { parser, cursor, fs };
while let Ok(pending_file) = parsing_files_rx.recv().await {
if let Some((indexed_file, document_spans)) =
retriever.parse_file(pending_file.clone()).await.log_err()
{
batch_files_tx
.try_send(EmbeddingJob::Enqueue {
worktree_id: pending_file.worktree_db_id,
parsed_file: indexed_file,
document_spans,
})
.unwrap();
}
if parsing_files_rx.len() == 0 {
batch_files_tx.try_send(EmbeddingJob::Flush).unwrap();
}
}
}));
}
Self {
fs,
database_url,
embedding_provider,
language_registry,
db_update_tx,
parsing_files_tx,
_db_update_task,
_embed_batch_task,
_batch_files_task,
_parsing_files_tasks,
projects: HashMap::new(),
}
}))
}
fn find_or_create_worktree(&self, path: PathBuf) -> impl Future<Output = Result<i64>> {
let (tx, rx) = oneshot::channel();
self.db_update_tx
.try_send(DbOperation::FindOrCreateWorktree { path, sender: tx })
.unwrap();
async move { rx.await? }
}
fn get_file_mtimes(
&self,
worktree_id: i64,
) -> impl Future<Output = Result<HashMap<PathBuf, SystemTime>>> {
let (tx, rx) = oneshot::channel();
self.db_update_tx
.try_send(DbOperation::FileMTimes {
worktree_id,
sender: tx,
})
.unwrap();
async move { rx.await? }
}
fn add_project(
&mut self,
project: ModelHandle<Project>,
cx: &mut ModelContext<Self>,
) -> Task<Result<()>> {
let worktree_scans_complete = project
.read(cx)
.worktrees(cx)
.map(|worktree| {
let scan_complete = worktree.read(cx).as_local().unwrap().scan_complete();
async move {
scan_complete.await;
}
})
.collect::<Vec<_>>();
let worktree_db_ids = project
.read(cx)
.worktrees(cx)
.map(|worktree| {
self.find_or_create_worktree(worktree.read(cx).abs_path().to_path_buf())
})
.collect::<Vec<_>>();
let fs = self.fs.clone();
let language_registry = self.language_registry.clone();
let database_url = self.database_url.clone();
let db_update_tx = self.db_update_tx.clone();
let parsing_files_tx = self.parsing_files_tx.clone();
cx.spawn(|this, mut cx| async move {
futures::future::join_all(worktree_scans_complete).await;
let worktree_db_ids = futures::future::join_all(worktree_db_ids).await;
if let Some(db_directory) = database_url.parent() {
fs.create_dir(db_directory).await.log_err();
}
let worktrees = project.read_with(&cx, |project, cx| {
project
.worktrees(cx)
.map(|worktree| worktree.read(cx).snapshot())
.collect::<Vec<_>>()
});
let mut worktree_file_times = HashMap::new();
let mut db_ids_by_worktree_id = HashMap::new();
for (worktree, db_id) in worktrees.iter().zip(worktree_db_ids) {
let db_id = db_id?;
db_ids_by_worktree_id.insert(worktree.id(), db_id);
worktree_file_times.insert(
worktree.id(),
this.read_with(&cx, |this, _| this.get_file_mtimes(db_id))
.await?,
);
}
cx.background()
.spawn({
let db_ids_by_worktree_id = db_ids_by_worktree_id.clone();
let db_update_tx = db_update_tx.clone();
let language_registry = language_registry.clone();
let parsing_files_tx = parsing_files_tx.clone();
async move {
let t0 = Instant::now();
for worktree in worktrees.into_iter() {
let mut file_mtimes =
worktree_file_times.remove(&worktree.id()).unwrap();
for file in worktree.files(false, 0) {
let absolute_path = worktree.absolutize(&file.path);
if let Ok(language) = language_registry
.language_for_file(&absolute_path, None)
.await
{
if language
.grammar()
.and_then(|grammar| grammar.embedding_config.as_ref())
.is_none()
{
continue;
}
let path_buf = file.path.to_path_buf();
let stored_mtime = file_mtimes.remove(&file.path.to_path_buf());
let already_stored = stored_mtime
.map_or(false, |existing_mtime| {
existing_mtime == file.mtime
});
if !already_stored {
parsing_files_tx
.try_send(PendingFile {
worktree_db_id: db_ids_by_worktree_id
[&worktree.id()],
relative_path: path_buf,
absolute_path,
language,
modified_time: file.mtime,
})
.unwrap();
}
}
}
for file in file_mtimes.keys() {
db_update_tx
.try_send(DbOperation::Delete {
worktree_id: db_ids_by_worktree_id[&worktree.id()],
path: file.to_owned(),
})
.unwrap();
}
}
log::info!(
"Parsing Worktree Completed in {:?}",
t0.elapsed().as_millis()
);
}
})
.detach();
// let mut pending_files: Vec<(PathBuf, ((i64, PathBuf, Arc<Language>, SystemTime), SystemTime))> = vec![];
this.update(&mut cx, |this, cx| {
// The below is managing for updated on save
// Currently each time a file is saved, this code is run, and for all the files that were changed, if the current time is
// greater than the previous embedded time by the REINDEXING_DELAY variable, we will send the file off to be indexed.
let _subscription = cx.subscribe(&project, |this, project, event, cx| {
if let project::Event::WorktreeUpdatedEntries(worktree_id, changes) = event {
this.project_entries_changed(project, changes.clone(), cx, worktree_id);
}
});
this.projects.insert(
project.downgrade(),
ProjectState {
pending_files: HashMap::new(),
worktree_db_ids: db_ids_by_worktree_id.into_iter().collect(),
_subscription,
},
);
});
anyhow::Ok(())
})
}
pub fn search(
&mut self,
project: ModelHandle<Project>,
phrase: String,
limit: usize,
cx: &mut ModelContext<Self>,
) -> Task<Result<Vec<SearchResult>>> {
let project_state = if let Some(state) = self.projects.get(&project.downgrade()) {
state
} else {
return Task::ready(Err(anyhow!("project not added")));
};
let worktree_db_ids = project
.read(cx)
.worktrees(cx)
.filter_map(|worktree| {
let worktree_id = worktree.read(cx).id();
project_state.db_id_for_worktree_id(worktree_id)
})
.collect::<Vec<_>>();
let embedding_provider = self.embedding_provider.clone();
let database_url = self.database_url.clone();
cx.spawn(|this, cx| async move {
let documents = cx
.background()
.spawn(async move {
let database = VectorDatabase::new(database_url.to_string_lossy().into())?;
let phrase_embedding = embedding_provider
.embed_batch(vec![&phrase])
.await?
.into_iter()
.next()
.unwrap();
database.top_k_search(&worktree_db_ids, &phrase_embedding, limit)
})
.await?;
this.read_with(&cx, |this, _| {
let project_state = if let Some(state) = this.projects.get(&project.downgrade()) {
state
} else {
return Err(anyhow!("project not added"));
};
Ok(documents
.into_iter()
.filter_map(|(worktree_db_id, file_path, offset, name)| {
let worktree_id = project_state.worktree_id_for_db_id(worktree_db_id)?;
Some(SearchResult {
worktree_id,
name,
offset,
file_path,
})
})
.collect())
})
})
}
fn project_entries_changed(
&mut self,
project: ModelHandle<Project>,
changes: Arc<[(Arc<Path>, ProjectEntryId, PathChange)]>,
cx: &mut ModelContext<'_, VectorStore>,
worktree_id: &WorktreeId,
) -> Option<()> {
let reindexing_delay = settings::get::<VectorStoreSettings>(cx).reindexing_delay_seconds;
let worktree = project
.read(cx)
.worktree_for_id(worktree_id.clone(), cx)?
.read(cx)
.snapshot();
let worktree_db_id = self
.projects
.get(&project.downgrade())?
.db_id_for_worktree_id(worktree.id())?;
let file_mtimes = self.get_file_mtimes(worktree_db_id);
let language_registry = self.language_registry.clone();
cx.spawn(|this, mut cx| async move {
let file_mtimes = file_mtimes.await.log_err()?;
for change in changes.into_iter() {
let change_path = change.0.clone();
let absolute_path = worktree.absolutize(&change_path);
// Skip if git ignored or symlink
if let Some(entry) = worktree.entry_for_id(change.1) {
if entry.is_ignored || entry.is_symlink || entry.is_external {
continue;
}
}
match change.2 {
PathChange::Removed => this.update(&mut cx, |this, _| {
this.db_update_tx
.try_send(DbOperation::Delete {
worktree_id: worktree_db_id,
path: absolute_path,
})
.unwrap();
}),
_ => {
if let Ok(language) = language_registry
.language_for_file(&change_path.to_path_buf(), None)
.await
{
if language
.grammar()
.and_then(|grammar| grammar.embedding_config.as_ref())
.is_none()
{
continue;
}
let modified_time =
change_path.metadata().log_err()?.modified().log_err()?;
let existing_time = file_mtimes.get(&change_path.to_path_buf());
let already_stored = existing_time
.map_or(false, |existing_time| &modified_time != existing_time);
if !already_stored {
this.update(&mut cx, |this, _| {
let reindex_time = modified_time
+ Duration::from_secs(reindexing_delay as u64);
let project_state =
this.projects.get_mut(&project.downgrade())?;
project_state.update_pending_files(
PendingFile {
relative_path: change_path.to_path_buf(),
absolute_path,
modified_time,
worktree_db_id,
language: language.clone(),
},
reindex_time,
);
for file in project_state.get_outstanding_files() {
this.parsing_files_tx.try_send(file).unwrap();
}
Some(())
});
}
}
}
}
}
Some(())
})
.detach();
Some(())
}
}
impl Entity for VectorStore {
type Event = ();
}
@@ -1,161 +0,0 @@
use crate::{
db::dot, embedding::EmbeddingProvider, vector_store_settings::VectorStoreSettings, VectorStore,
};
use anyhow::Result;
use async_trait::async_trait;
use gpui::{Task, TestAppContext};
use language::{Language, LanguageConfig, LanguageRegistry};
use project::{project_settings::ProjectSettings, FakeFs, Project};
use rand::{rngs::StdRng, Rng};
use serde_json::json;
use settings::SettingsStore;
use std::sync::Arc;
use unindent::Unindent;
#[gpui::test]
async fn test_vector_store(cx: &mut TestAppContext) {
cx.update(|cx| {
cx.set_global(SettingsStore::test(cx));
settings::register::<VectorStoreSettings>(cx);
settings::register::<ProjectSettings>(cx);
});
let fs = FakeFs::new(cx.background());
fs.insert_tree(
"/the-root",
json!({
"src": {
"file1.rs": "
fn aaa() {
println!(\"aaaa!\");
}
fn zzzzzzzzz() {
println!(\"SLEEPING\");
}
".unindent(),
"file2.rs": "
fn bbb() {
println!(\"bbbb!\");
}
".unindent(),
}
}),
)
.await;
let languages = Arc::new(LanguageRegistry::new(Task::ready(())));
let rust_language = Arc::new(
Language::new(
LanguageConfig {
name: "Rust".into(),
path_suffixes: vec!["rs".into()],
..Default::default()
},
Some(tree_sitter_rust::language()),
)
.with_embedding_query(
r#"
(function_item
name: (identifier) @name
body: (block)) @item
"#,
)
.unwrap(),
);
languages.add(rust_language);
let db_dir = tempdir::TempDir::new("vector-store").unwrap();
let db_path = db_dir.path().join("db.sqlite");
let store = VectorStore::new(
fs.clone(),
db_path,
Arc::new(FakeEmbeddingProvider),
languages,
cx.to_async(),
)
.await
.unwrap();
let project = Project::test(fs, ["/the-root".as_ref()], cx).await;
let worktree_id = project.read_with(cx, |project, cx| {
project.worktrees(cx).next().unwrap().read(cx).id()
});
store
.update(cx, |store, cx| store.add_project(project.clone(), cx))
.await
.unwrap();
cx.foreground().run_until_parked();
let search_results = store
.update(cx, |store, cx| {
store.search(project.clone(), "aaaa".to_string(), 5, cx)
})
.await
.unwrap();
assert_eq!(search_results[0].offset, 0);
assert_eq!(search_results[0].name, "aaa");
assert_eq!(search_results[0].worktree_id, worktree_id);
}
#[gpui::test]
fn test_dot_product(mut rng: StdRng) {
assert_eq!(dot(&[1., 0., 0., 0., 0.], &[0., 1., 0., 0., 0.]), 0.);
assert_eq!(dot(&[2., 0., 0., 0., 0.], &[3., 1., 0., 0., 0.]), 6.);
for _ in 0..100 {
let size = 1536;
let mut a = vec![0.; size];
let mut b = vec![0.; size];
for (a, b) in a.iter_mut().zip(b.iter_mut()) {
*a = rng.gen();
*b = rng.gen();
}
assert_eq!(
round_to_decimals(dot(&a, &b), 1),
round_to_decimals(reference_dot(&a, &b), 1)
);
}
fn round_to_decimals(n: f32, decimal_places: i32) -> f32 {
let factor = (10.0 as f32).powi(decimal_places);
(n * factor).round() / factor
}
fn reference_dot(a: &[f32], b: &[f32]) -> f32 {
a.iter().zip(b.iter()).map(|(a, b)| a * b).sum()
}
}
struct FakeEmbeddingProvider;
#[async_trait]
impl EmbeddingProvider for FakeEmbeddingProvider {
async fn embed_batch(&self, spans: Vec<&str>) -> Result<Vec<Vec<f32>>> {
Ok(spans
.iter()
.map(|span| {
let mut result = vec![1.0; 26];
for letter in span.chars() {
let letter = letter.to_ascii_lowercase();
if letter as u32 >= 'a' as u32 {
let ix = (letter as u32) - ('a' as u32);
if ix < 26 {
result[ix as usize] += 1.0;
}
}
}
let norm = result.iter().map(|x| x * x).sum::<f32>().sqrt();
for x in &mut result {
*x /= norm;
}
result
})
.collect())
}
}
+1 -1
View File
@@ -64,7 +64,7 @@ terminal_view = { path = "../terminal_view" }
theme = { path = "../theme" }
theme_selector = { path = "../theme_selector" }
util = { path = "../util" }
vector_store = { path = "../vector_store" }
semantic_index = { path = "../semantic_index" }
vim = { path = "../vim" }
workspace = { path = "../workspace" }
welcome = { path = "../welcome" }
+43
View File
@@ -0,0 +1,43 @@
(
(comment)* @context
.
(declaration
declarator: [
(function_declarator
declarator: (_) @name)
(pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name))
(pointer_declarator
"*" @name
declarator: (pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name)))
]
) @item
)
(
(comment)* @context
.
(function_definition
declarator: [
(function_declarator
declarator: (_) @name
)
(pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name
))
(pointer_declarator
"*" @name
declarator: (pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name)))
]
) @item
)
@@ -0,0 +1,61 @@
(
(comment)* @context
.
(function_definition
(type_qualifier)? @name
type: (_)? @name
declarator: [
(function_declarator
declarator: (_) @name)
(pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name))
(pointer_declarator
"*" @name
declarator: (pointer_declarator
"*" @name
declarator: (function_declarator
declarator: (_) @name)))
(reference_declarator
["&" "&&"] @name
(function_declarator
declarator: (_) @name))
]
(type_qualifier)? @name) @item
)
(
(comment)* @context
.
(template_declaration
(class_specifier
"class" @name
name: (_) @name)
) @item
)
(
(comment)* @context
.
(class_specifier
"class" @name
name: (_) @name) @item
)
(
(comment)* @context
.
(enum_specifier
"enum" @name
name: (_) @name) @item
)
(
(comment)* @context
.
(declaration
type: (struct_specifier
"struct" @name)
declarator: (_) @name) @item
)
@@ -0,0 +1,27 @@
(
(unary_operator
operator: "@"
operand: (call
target: (identifier) @unary
(#match? @unary "^(doc)$"))
) @context
.
(call
target: (identifier) @name
(arguments
[
(identifier) @name
(call
target: (identifier) @name)
(binary_operator
left: (call
target: (identifier) @name)
operator: "when")
])
(#match? @name "^(def|defp|defdelegate|defguard|defguardp|defmacro|defmacrop|defn|defnp)$")) @item
)
(call
target: (identifier) @name
(arguments (alias) @name)
(#match? @name "^(defmodule|defprotocol)$")) @item
+24
View File
@@ -0,0 +1,24 @@
(
(comment)* @context
.
(type_declaration
(type_spec
name: (_) @name)
) @item
)
(
(comment)* @context
.
(function_declaration
name: (_) @name
) @item
)
(
(comment)* @context
.
(method_declaration
name: (_) @name
) @item
)
@@ -1,56 +1,71 @@
; (internal_module
; "namespace" @context
; name: (_) @name) @item
(enum_declaration
"enum" @context
name: (_) @name) @item
(function_declaration
"async"? @context
"function" @context
name: (_) @name) @item
(interface_declaration
"interface" @context
name: (_) @name) @item
; (program
; (export_statement
; (lexical_declaration
; ["let" "const"] @context
; (variable_declarator
; name: (_) @name) @item)))
(program
(lexical_declaration
["let" "const"] @context
(variable_declarator
name: (_) @name) @item))
(class_declaration
"class" @context
name: (_) @name) @item
(method_definition
(
(comment)* @context
.
[
"get"
"set"
"async"
"*"
"readonly"
"static"
(override_modifier)
(accessibility_modifier)
]* @context
name: (_) @name) @item
(export_statement
(function_declaration
"async"? @name
"function" @name
name: (_) @name))
(function_declaration
"async"? @name
"function" @name
name: (_) @name)
] @item
)
; (public_field_definition
; [
; "declare"
; "readonly"
; "abstract"
; "static"
; (accessibility_modifier)
; ]* @context
; name: (_) @name) @item
(
(comment)* @context
.
[
(export_statement
(class_declaration
"class" @name
name: (_) @name))
(class_declaration
"class" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(interface_declaration
"interface" @name
name: (_) @name))
(interface_declaration
"interface" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(enum_declaration
"enum" @name
name: (_) @name))
(enum_declaration
"enum" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
(method_definition
[
"get"
"set"
"async"
"*"
"static"
]* @name
name: (_) @name) @item
)
@@ -0,0 +1,14 @@
; Only produce one embedding for the entire file.
(document) @item
; Collapse arrays, except for the first object.
(array
"[" @keep
.
(object)? @keep
"]" @keep) @collapse
; Collapse string values (but not keys).
(pair value: (string
"\"" @keep
"\"" @keep) @collapse)
@@ -10,3 +10,4 @@ brackets = [
{ start = "\"", end = "\"", close = true, newline = false, not_in = ["string"] },
{ start = "/*", end = " */", close = true, newline = false, not_in = ["string", "comment"] },
]
collapsed_placeholder = " /* ... */ "
+23 -31
View File
@@ -1,36 +1,28 @@
(struct_item
(visibility_modifier)? @context
"struct" @context
name: (_) @name) @item
(
[(line_comment) (attribute_item)]* @context
.
[
(struct_item
name: (_) @name)
(enum_item
(visibility_modifier)? @context
"enum" @context
name: (_) @name) @item
(enum_item
name: (_) @name)
(impl_item
"impl" @context
trait: (_)? @name
"for"? @context
type: (_) @name) @item
(impl_item
trait: (_)? @name
"for"? @name
type: (_) @name)
(trait_item
(visibility_modifier)? @context
"trait" @context
name: (_) @name) @item
(trait_item
name: (_) @name)
(function_item
(visibility_modifier)? @context
(function_modifiers)? @context
"fn" @context
name: (_) @name) @item
(function_item
name: (_) @name
body: (block
"{" @keep
"}" @keep) @collapse)
(function_signature_item
(visibility_modifier)? @context
(function_modifiers)? @context
"fn" @context
name: (_) @name) @item
(macro_definition
. "macro_rules!" @context
name: (_) @name) @item
(macro_definition
name: (_) @name)
] @item
)
+84 -34
View File
@@ -1,35 +1,85 @@
(enum_declaration
"enum" @context
name: (_) @name) @item
(function_declaration
"async"? @context
"function" @context
name: (_) @name) @item
(interface_declaration
"interface" @context
name: (_) @name) @item
(program
(lexical_declaration
["let" "const"] @context
(variable_declarator
name: (_) @name) @item))
(class_declaration
"class" @context
name: (_) @name) @item
(method_definition
(
(comment)* @context
.
[
"get"
"set"
"async"
"*"
"readonly"
"static"
(override_modifier)
(accessibility_modifier)
]* @context
name: (_) @name) @item
(export_statement
(function_declaration
"async"? @name
"function" @name
name: (_) @name))
(function_declaration
"async"? @name
"function" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(class_declaration
"class" @name
name: (_) @name))
(class_declaration
"class" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(interface_declaration
"interface" @name
name: (_) @name))
(interface_declaration
"interface" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(enum_declaration
"enum" @name
name: (_) @name))
(enum_declaration
"enum" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(type_alias_declaration
"type" @name
name: (_) @name))
(type_alias_declaration
"type" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
(method_definition
[
"get"
"set"
"async"
"*"
"static"
]* @name
name: (_) @name) @item
)
@@ -1,59 +1,85 @@
; (internal_module
; "namespace" @context
; name: (_) @name) @item
(enum_declaration
"enum" @context
name: (_) @name) @item
; (type_alias_declaration
; "type" @context
; name: (_) @name) @item
(function_declaration
"async"? @context
"function" @context
name: (_) @name) @item
(interface_declaration
"interface" @context
name: (_) @name) @item
; (export_statement
; (lexical_declaration
; ["let" "const"] @context
; (variable_declarator
; name: (_) @name) @item))
(program
(lexical_declaration
["let" "const"] @context
(variable_declarator
name: (_) @name) @item))
(class_declaration
"class" @context
name: (_) @name) @item
(method_definition
(
(comment)* @context
.
[
"get"
"set"
"async"
"*"
"readonly"
"static"
(override_modifier)
(accessibility_modifier)
]* @context
name: (_) @name) @item
(export_statement
(function_declaration
"async"? @name
"function" @name
name: (_) @name))
(function_declaration
"async"? @name
"function" @name
name: (_) @name)
] @item
)
; (public_field_definition
; [
; "declare"
; "readonly"
; "abstract"
; "static"
; (accessibility_modifier)
; ]* @context
; name: (_) @name) @item
(
(comment)* @context
.
[
(export_statement
(class_declaration
"class" @name
name: (_) @name))
(class_declaration
"class" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(interface_declaration
"interface" @name
name: (_) @name))
(interface_declaration
"interface" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(enum_declaration
"enum" @name
name: (_) @name))
(enum_declaration
"enum" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
[
(export_statement
(type_alias_declaration
"type" @name
name: (_) @name))
(type_alias_declaration
"type" @name
name: (_) @name)
] @item
)
(
(comment)* @context
.
(method_definition
[
"get"
"set"
"async"
"*"
"static"
]* @name
name: (_) @name) @item
)
+1 -1
View File
@@ -157,7 +157,7 @@ fn main() {
project_panel::init(Assets, cx);
diagnostics::init(cx);
search::init(cx);
vector_store::init(fs.clone(), http.clone(), languages.clone(), cx);
semantic_index::init(fs.clone(), http.clone(), languages.clone(), cx);
vim::init(cx);
terminal_view::init(cx);
copilot::init(http.clone(), node_runtime, cx);