ZIm/crates/semantic_index/src/semantic_index.rs
Antonio Scandurra 59662fbeb6
Introduce /search command to assistant (#12372)
This pull request introduces semantic search to the assistant using a
slash command:


https://github.com/zed-industries/zed/assets/482957/62f39eae-d7d5-46bf-a356-dd081ff88312

Moreover, this also adds a status to pending slash commands, so that we
can show when a query is running or whether it failed:

<img width="1588" alt="image"
src="https://github.com/zed-industries/zed/assets/482957/e8d85960-6275-4552-a068-85efb74cfde1">

I think this could be better design-wise, but seems like a pretty good
start.

Release Notes:

- N/A
2024-05-28 16:06:09 +02:00

1263 lines
44 KiB
Rust

mod chunking;
mod embedding;
mod project_index_debug_view;
use anyhow::{anyhow, Context as _, Result};
use chunking::{chunk_text, Chunk};
use collections::{Bound, HashMap, HashSet};
pub use embedding::*;
use fs::Fs;
use futures::{future::Shared, stream::StreamExt, FutureExt};
use futures_batch::ChunksTimeoutStreamExt;
use gpui::{
AppContext, AsyncAppContext, BorrowAppContext, Context, Entity, EntityId, EventEmitter, Global,
Model, ModelContext, Subscription, Task, WeakModel,
};
use heed::types::{SerdeBincode, Str};
use language::LanguageRegistry;
use parking_lot::Mutex;
use project::{Entry, Project, ProjectEntryId, UpdatedEntriesSet, Worktree, WorktreeId};
use serde::{Deserialize, Serialize};
use smol::channel;
use std::{
cmp::Ordering,
future::Future,
iter,
num::NonZeroUsize,
ops::Range,
path::{Path, PathBuf},
sync::{Arc, Weak},
time::{Duration, SystemTime},
};
use util::ResultExt;
use worktree::LocalSnapshot;
pub use project_index_debug_view::ProjectIndexDebugView;
pub struct SemanticIndex {
embedding_provider: Arc<dyn EmbeddingProvider>,
db_connection: heed::Env,
project_indices: HashMap<WeakModel<Project>, Model<ProjectIndex>>,
}
impl Global for SemanticIndex {}
impl SemanticIndex {
pub async fn new(
db_path: PathBuf,
embedding_provider: Arc<dyn EmbeddingProvider>,
cx: &mut AsyncAppContext,
) -> Result<Self> {
let db_connection = cx
.background_executor()
.spawn(async move {
std::fs::create_dir_all(&db_path)?;
unsafe {
heed::EnvOpenOptions::new()
.map_size(1024 * 1024 * 1024)
.max_dbs(3000)
.open(db_path)
}
})
.await
.context("opening database connection")?;
Ok(SemanticIndex {
db_connection,
embedding_provider,
project_indices: HashMap::default(),
})
}
pub fn project_index(
&mut self,
project: Model<Project>,
cx: &mut AppContext,
) -> Model<ProjectIndex> {
let project_weak = project.downgrade();
project.update(cx, move |_, cx| {
cx.on_release(move |_, cx| {
if cx.has_global::<SemanticIndex>() {
cx.update_global::<SemanticIndex, _>(|this, _| {
this.project_indices.remove(&project_weak);
})
}
})
.detach();
});
self.project_indices
.entry(project.downgrade())
.or_insert_with(|| {
cx.new_model(|cx| {
ProjectIndex::new(
project,
self.db_connection.clone(),
self.embedding_provider.clone(),
cx,
)
})
})
.clone()
}
}
pub struct ProjectIndex {
db_connection: heed::Env,
project: WeakModel<Project>,
worktree_indices: HashMap<EntityId, WorktreeIndexHandle>,
language_registry: Arc<LanguageRegistry>,
fs: Arc<dyn Fs>,
last_status: Status,
status_tx: channel::Sender<()>,
embedding_provider: Arc<dyn EmbeddingProvider>,
_maintain_status: Task<()>,
_subscription: Subscription,
}
#[derive(Clone)]
enum WorktreeIndexHandle {
Loading {
index: Shared<Task<Result<Model<WorktreeIndex>, Arc<anyhow::Error>>>>,
},
Loaded {
index: Model<WorktreeIndex>,
},
}
impl ProjectIndex {
fn new(
project: Model<Project>,
db_connection: heed::Env,
embedding_provider: Arc<dyn EmbeddingProvider>,
cx: &mut ModelContext<Self>,
) -> Self {
let language_registry = project.read(cx).languages().clone();
let fs = project.read(cx).fs().clone();
let (status_tx, mut status_rx) = channel::unbounded();
let mut this = ProjectIndex {
db_connection,
project: project.downgrade(),
worktree_indices: HashMap::default(),
language_registry,
fs,
status_tx,
last_status: Status::Idle,
embedding_provider,
_subscription: cx.subscribe(&project, Self::handle_project_event),
_maintain_status: cx.spawn(|this, mut cx| async move {
while status_rx.next().await.is_some() {
if this
.update(&mut cx, |this, cx| this.update_status(cx))
.is_err()
{
break;
}
}
}),
};
this.update_worktree_indices(cx);
this
}
pub fn status(&self) -> Status {
self.last_status
}
pub fn project(&self) -> WeakModel<Project> {
self.project.clone()
}
pub fn fs(&self) -> Arc<dyn Fs> {
self.fs.clone()
}
fn handle_project_event(
&mut self,
_: Model<Project>,
event: &project::Event,
cx: &mut ModelContext<Self>,
) {
match event {
project::Event::WorktreeAdded | project::Event::WorktreeRemoved(_) => {
self.update_worktree_indices(cx);
}
_ => {}
}
}
fn update_worktree_indices(&mut self, cx: &mut ModelContext<Self>) {
let Some(project) = self.project.upgrade() else {
return;
};
let worktrees = project
.read(cx)
.visible_worktrees(cx)
.filter_map(|worktree| {
if worktree.read(cx).is_local() {
Some((worktree.entity_id(), worktree))
} else {
None
}
})
.collect::<HashMap<_, _>>();
self.worktree_indices
.retain(|worktree_id, _| worktrees.contains_key(worktree_id));
for (worktree_id, worktree) in worktrees {
self.worktree_indices.entry(worktree_id).or_insert_with(|| {
let worktree_index = WorktreeIndex::load(
worktree.clone(),
self.db_connection.clone(),
self.language_registry.clone(),
self.fs.clone(),
self.status_tx.clone(),
self.embedding_provider.clone(),
cx,
);
let load_worktree = cx.spawn(|this, mut cx| async move {
let result = match worktree_index.await {
Ok(worktree_index) => {
this.update(&mut cx, |this, _| {
this.worktree_indices.insert(
worktree_id,
WorktreeIndexHandle::Loaded {
index: worktree_index.clone(),
},
);
})?;
Ok(worktree_index)
}
Err(error) => {
this.update(&mut cx, |this, _cx| {
this.worktree_indices.remove(&worktree_id)
})?;
Err(Arc::new(error))
}
};
this.update(&mut cx, |this, cx| this.update_status(cx))?;
result
});
WorktreeIndexHandle::Loading {
index: load_worktree.shared(),
}
});
}
self.update_status(cx);
}
fn update_status(&mut self, cx: &mut ModelContext<Self>) {
let mut indexing_count = 0;
let mut any_loading = false;
for index in self.worktree_indices.values_mut() {
match index {
WorktreeIndexHandle::Loading { .. } => {
any_loading = true;
break;
}
WorktreeIndexHandle::Loaded { index, .. } => {
indexing_count += index.read(cx).entry_ids_being_indexed.len();
}
}
}
let status = if any_loading {
Status::Loading
} else if let Some(remaining_count) = NonZeroUsize::new(indexing_count) {
Status::Scanning { remaining_count }
} else {
Status::Idle
};
if status != self.last_status {
self.last_status = status;
cx.emit(status);
}
}
pub fn search(
&self,
query: String,
limit: usize,
cx: &AppContext,
) -> Task<Result<Vec<SearchResult>>> {
let (chunks_tx, chunks_rx) = channel::bounded(1024);
let mut worktree_scan_tasks = Vec::new();
for worktree_index in self.worktree_indices.values() {
let worktree_index = worktree_index.clone();
let chunks_tx = chunks_tx.clone();
worktree_scan_tasks.push(cx.spawn(|cx| async move {
let index = match worktree_index {
WorktreeIndexHandle::Loading { index } => {
index.clone().await.map_err(|error| anyhow!(error))?
}
WorktreeIndexHandle::Loaded { index } => index.clone(),
};
index
.read_with(&cx, |index, cx| {
let worktree_id = index.worktree.read(cx).id();
let db_connection = index.db_connection.clone();
let db = index.db;
cx.background_executor().spawn(async move {
let txn = db_connection
.read_txn()
.context("failed to create read transaction")?;
let db_entries = db.iter(&txn).context("failed to iterate database")?;
for db_entry in db_entries {
let (_key, db_embedded_file) = db_entry?;
for chunk in db_embedded_file.chunks {
chunks_tx
.send((worktree_id, db_embedded_file.path.clone(), chunk))
.await?;
}
}
anyhow::Ok(())
})
})?
.await
}));
}
drop(chunks_tx);
let project = self.project.clone();
let embedding_provider = self.embedding_provider.clone();
cx.spawn(|cx| async move {
#[cfg(debug_assertions)]
let embedding_query_start = std::time::Instant::now();
log::info!("Searching for {query}");
let query_embeddings = embedding_provider
.embed(&[TextToEmbed::new(&query)])
.await?;
let query_embedding = query_embeddings
.into_iter()
.next()
.ok_or_else(|| anyhow!("no embedding for query"))?;
let mut results_by_worker = Vec::new();
for _ in 0..cx.background_executor().num_cpus() {
results_by_worker.push(Vec::<WorktreeSearchResult>::new());
}
#[cfg(debug_assertions)]
let search_start = std::time::Instant::now();
cx.background_executor()
.scoped(|cx| {
for results in results_by_worker.iter_mut() {
cx.spawn(async {
while let Ok((worktree_id, path, chunk)) = chunks_rx.recv().await {
let score = chunk.embedding.similarity(&query_embedding);
let ix = match results.binary_search_by(|probe| {
score.partial_cmp(&probe.score).unwrap_or(Ordering::Equal)
}) {
Ok(ix) | Err(ix) => ix,
};
results.insert(
ix,
WorktreeSearchResult {
worktree_id,
path: path.clone(),
range: chunk.chunk.range.clone(),
score,
},
);
results.truncate(limit);
}
});
}
})
.await;
for scan_task in futures::future::join_all(worktree_scan_tasks).await {
scan_task.log_err();
}
project.read_with(&cx, |project, cx| {
let mut search_results = Vec::with_capacity(results_by_worker.len() * limit);
for worker_results in results_by_worker {
search_results.extend(worker_results.into_iter().filter_map(|result| {
Some(SearchResult {
worktree: project.worktree_for_id(result.worktree_id, cx)?,
path: result.path,
range: result.range,
score: result.score,
})
}));
}
search_results.sort_unstable_by(|a, b| {
b.score.partial_cmp(&a.score).unwrap_or(Ordering::Equal)
});
search_results.truncate(limit);
#[cfg(debug_assertions)]
{
let search_elapsed = search_start.elapsed();
log::debug!(
"searched {} entries in {:?}",
search_results.len(),
search_elapsed
);
let embedding_query_elapsed = embedding_query_start.elapsed();
log::debug!("embedding query took {:?}", embedding_query_elapsed);
}
search_results
})
})
}
#[cfg(test)]
pub fn path_count(&self, cx: &AppContext) -> Result<u64> {
let mut result = 0;
for worktree_index in self.worktree_indices.values() {
if let WorktreeIndexHandle::Loaded { index, .. } = worktree_index {
result += index.read(cx).path_count()?;
}
}
Ok(result)
}
pub(crate) fn worktree_index(
&self,
worktree_id: WorktreeId,
cx: &AppContext,
) -> Option<Model<WorktreeIndex>> {
for index in self.worktree_indices.values() {
if let WorktreeIndexHandle::Loaded { index, .. } = index {
if index.read(cx).worktree.read(cx).id() == worktree_id {
return Some(index.clone());
}
}
}
None
}
pub(crate) fn worktree_indices(&self, cx: &AppContext) -> Vec<Model<WorktreeIndex>> {
let mut result = self
.worktree_indices
.values()
.filter_map(|index| {
if let WorktreeIndexHandle::Loaded { index, .. } = index {
Some(index.clone())
} else {
None
}
})
.collect::<Vec<_>>();
result.sort_by_key(|index| index.read(cx).worktree.read(cx).id());
result
}
}
pub struct SearchResult {
pub worktree: Model<Worktree>,
pub path: Arc<Path>,
pub range: Range<usize>,
pub score: f32,
}
pub struct WorktreeSearchResult {
pub worktree_id: WorktreeId,
pub path: Arc<Path>,
pub range: Range<usize>,
pub score: f32,
}
#[derive(Copy, Clone, Debug, Eq, PartialEq, Serialize, Deserialize)]
pub enum Status {
Idle,
Loading,
Scanning { remaining_count: NonZeroUsize },
}
impl EventEmitter<Status> for ProjectIndex {}
struct WorktreeIndex {
worktree: Model<Worktree>,
db_connection: heed::Env,
db: heed::Database<Str, SerdeBincode<EmbeddedFile>>,
language_registry: Arc<LanguageRegistry>,
fs: Arc<dyn Fs>,
embedding_provider: Arc<dyn EmbeddingProvider>,
entry_ids_being_indexed: Arc<IndexingEntrySet>,
_index_entries: Task<Result<()>>,
_subscription: Subscription,
}
impl WorktreeIndex {
pub fn load(
worktree: Model<Worktree>,
db_connection: heed::Env,
language_registry: Arc<LanguageRegistry>,
fs: Arc<dyn Fs>,
status_tx: channel::Sender<()>,
embedding_provider: Arc<dyn EmbeddingProvider>,
cx: &mut AppContext,
) -> Task<Result<Model<Self>>> {
let worktree_abs_path = worktree.read(cx).abs_path();
cx.spawn(|mut cx| async move {
let db = cx
.background_executor()
.spawn({
let db_connection = db_connection.clone();
async move {
let mut txn = db_connection.write_txn()?;
let db_name = worktree_abs_path.to_string_lossy();
let db = db_connection.create_database(&mut txn, Some(&db_name))?;
txn.commit()?;
anyhow::Ok(db)
}
})
.await?;
cx.new_model(|cx| {
Self::new(
worktree,
db_connection,
db,
status_tx,
language_registry,
fs,
embedding_provider,
cx,
)
})
})
}
#[allow(clippy::too_many_arguments)]
fn new(
worktree: Model<Worktree>,
db_connection: heed::Env,
db: heed::Database<Str, SerdeBincode<EmbeddedFile>>,
status: channel::Sender<()>,
language_registry: Arc<LanguageRegistry>,
fs: Arc<dyn Fs>,
embedding_provider: Arc<dyn EmbeddingProvider>,
cx: &mut ModelContext<Self>,
) -> Self {
let (updated_entries_tx, updated_entries_rx) = channel::unbounded();
let _subscription = cx.subscribe(&worktree, move |_this, _worktree, event, _cx| {
if let worktree::Event::UpdatedEntries(update) = event {
_ = updated_entries_tx.try_send(update.clone());
}
});
Self {
db_connection,
db,
worktree,
language_registry,
fs,
embedding_provider,
entry_ids_being_indexed: Arc::new(IndexingEntrySet::new(status)),
_index_entries: cx.spawn(|this, cx| Self::index_entries(this, updated_entries_rx, cx)),
_subscription,
}
}
async fn index_entries(
this: WeakModel<Self>,
updated_entries: channel::Receiver<UpdatedEntriesSet>,
mut cx: AsyncAppContext,
) -> Result<()> {
let index = this.update(&mut cx, |this, cx| this.index_entries_changed_on_disk(cx))?;
index.await.log_err();
while let Ok(updated_entries) = updated_entries.recv().await {
let index = this.update(&mut cx, |this, cx| {
this.index_updated_entries(updated_entries, cx)
})?;
index.await.log_err();
}
Ok(())
}
fn index_entries_changed_on_disk(&self, cx: &AppContext) -> impl Future<Output = Result<()>> {
let worktree = self.worktree.read(cx).as_local().unwrap().snapshot();
let worktree_abs_path = worktree.abs_path().clone();
let scan = self.scan_entries(worktree.clone(), cx);
let chunk = self.chunk_files(worktree_abs_path, scan.updated_entries, cx);
let embed = Self::embed_files(self.embedding_provider.clone(), chunk.files, cx);
let persist = self.persist_embeddings(scan.deleted_entry_ranges, embed.files, cx);
async move {
futures::try_join!(scan.task, chunk.task, embed.task, persist)?;
Ok(())
}
}
fn index_updated_entries(
&self,
updated_entries: UpdatedEntriesSet,
cx: &AppContext,
) -> impl Future<Output = Result<()>> {
let worktree = self.worktree.read(cx).as_local().unwrap().snapshot();
let worktree_abs_path = worktree.abs_path().clone();
let scan = self.scan_updated_entries(worktree, updated_entries.clone(), cx);
let chunk = self.chunk_files(worktree_abs_path, scan.updated_entries, cx);
let embed = Self::embed_files(self.embedding_provider.clone(), chunk.files, cx);
let persist = self.persist_embeddings(scan.deleted_entry_ranges, embed.files, cx);
async move {
futures::try_join!(scan.task, chunk.task, embed.task, persist)?;
Ok(())
}
}
fn scan_entries(&self, worktree: LocalSnapshot, cx: &AppContext) -> ScanEntries {
let (updated_entries_tx, updated_entries_rx) = channel::bounded(512);
let (deleted_entry_ranges_tx, deleted_entry_ranges_rx) = channel::bounded(128);
let db_connection = self.db_connection.clone();
let db = self.db;
let entries_being_indexed = self.entry_ids_being_indexed.clone();
let task = cx.background_executor().spawn(async move {
let txn = db_connection
.read_txn()
.context("failed to create read transaction")?;
let mut db_entries = db
.iter(&txn)
.context("failed to create iterator")?
.move_between_keys()
.peekable();
let mut deletion_range: Option<(Bound<&str>, Bound<&str>)> = None;
for entry in worktree.files(false, 0) {
let entry_db_key = db_key_for_path(&entry.path);
let mut saved_mtime = None;
while let Some(db_entry) = db_entries.peek() {
match db_entry {
Ok((db_path, db_embedded_file)) => match (*db_path).cmp(&entry_db_key) {
Ordering::Less => {
if let Some(deletion_range) = deletion_range.as_mut() {
deletion_range.1 = Bound::Included(db_path);
} else {
deletion_range =
Some((Bound::Included(db_path), Bound::Included(db_path)));
}
db_entries.next();
}
Ordering::Equal => {
if let Some(deletion_range) = deletion_range.take() {
deleted_entry_ranges_tx
.send((
deletion_range.0.map(ToString::to_string),
deletion_range.1.map(ToString::to_string),
))
.await?;
}
saved_mtime = db_embedded_file.mtime;
db_entries.next();
break;
}
Ordering::Greater => {
break;
}
},
Err(_) => return Err(db_entries.next().unwrap().unwrap_err())?,
}
}
if entry.mtime != saved_mtime {
let handle = entries_being_indexed.insert(entry.id);
updated_entries_tx.send((entry.clone(), handle)).await?;
}
}
if let Some(db_entry) = db_entries.next() {
let (db_path, _) = db_entry?;
deleted_entry_ranges_tx
.send((Bound::Included(db_path.to_string()), Bound::Unbounded))
.await?;
}
Ok(())
});
ScanEntries {
updated_entries: updated_entries_rx,
deleted_entry_ranges: deleted_entry_ranges_rx,
task,
}
}
fn scan_updated_entries(
&self,
worktree: LocalSnapshot,
updated_entries: UpdatedEntriesSet,
cx: &AppContext,
) -> ScanEntries {
let (updated_entries_tx, updated_entries_rx) = channel::bounded(512);
let (deleted_entry_ranges_tx, deleted_entry_ranges_rx) = channel::bounded(128);
let entries_being_indexed = self.entry_ids_being_indexed.clone();
let task = cx.background_executor().spawn(async move {
for (path, entry_id, status) in updated_entries.iter() {
match status {
project::PathChange::Added
| project::PathChange::Updated
| project::PathChange::AddedOrUpdated => {
if let Some(entry) = worktree.entry_for_id(*entry_id) {
if entry.is_file() {
let handle = entries_being_indexed.insert(entry.id);
updated_entries_tx.send((entry.clone(), handle)).await?;
}
}
}
project::PathChange::Removed => {
let db_path = db_key_for_path(path);
deleted_entry_ranges_tx
.send((Bound::Included(db_path.clone()), Bound::Included(db_path)))
.await?;
}
project::PathChange::Loaded => {
// Do nothing.
}
}
}
Ok(())
});
ScanEntries {
updated_entries: updated_entries_rx,
deleted_entry_ranges: deleted_entry_ranges_rx,
task,
}
}
fn chunk_files(
&self,
worktree_abs_path: Arc<Path>,
entries: channel::Receiver<(Entry, IndexingEntryHandle)>,
cx: &AppContext,
) -> ChunkFiles {
let language_registry = self.language_registry.clone();
let fs = self.fs.clone();
let (chunked_files_tx, chunked_files_rx) = channel::bounded(2048);
let task = cx.spawn(|cx| async move {
cx.background_executor()
.scoped(|cx| {
for _ in 0..cx.num_cpus() {
cx.spawn(async {
while let Ok((entry, handle)) = entries.recv().await {
let entry_abs_path = worktree_abs_path.join(&entry.path);
let Some(text) = fs
.load(&entry_abs_path)
.await
.with_context(|| {
format!("failed to read path {entry_abs_path:?}")
})
.log_err()
else {
continue;
};
let language = language_registry
.language_for_file_path(&entry.path)
.await
.ok();
let chunked_file = ChunkedFile {
chunks: chunk_text(&text, language.as_ref(), &entry.path),
handle,
path: entry.path,
mtime: entry.mtime,
text,
};
if chunked_files_tx.send(chunked_file).await.is_err() {
return;
}
}
});
}
})
.await;
Ok(())
});
ChunkFiles {
files: chunked_files_rx,
task,
}
}
fn embed_files(
embedding_provider: Arc<dyn EmbeddingProvider>,
chunked_files: channel::Receiver<ChunkedFile>,
cx: &AppContext,
) -> EmbedFiles {
let embedding_provider = embedding_provider.clone();
let (embedded_files_tx, embedded_files_rx) = channel::bounded(512);
let task = cx.background_executor().spawn(async move {
let mut chunked_file_batches =
chunked_files.chunks_timeout(512, Duration::from_secs(2));
while let Some(chunked_files) = chunked_file_batches.next().await {
// View the batch of files as a vec of chunks
// Flatten out to a vec of chunks that we can subdivide into batch sized pieces
// Once those are done, reassemble them back into the files in which they belong
// If any embeddings fail for a file, the entire file is discarded
let chunks: Vec<TextToEmbed> = chunked_files
.iter()
.flat_map(|file| {
file.chunks.iter().map(|chunk| TextToEmbed {
text: &file.text[chunk.range.clone()],
digest: chunk.digest,
})
})
.collect::<Vec<_>>();
let mut embeddings: Vec<Option<Embedding>> = Vec::new();
for embedding_batch in chunks.chunks(embedding_provider.batch_size()) {
if let Some(batch_embeddings) =
embedding_provider.embed(embedding_batch).await.log_err()
{
if batch_embeddings.len() == embedding_batch.len() {
embeddings.extend(batch_embeddings.into_iter().map(Some));
continue;
}
log::error!(
"embedding provider returned unexpected embedding count {}, expected {}",
batch_embeddings.len(), embedding_batch.len()
);
}
embeddings.extend(iter::repeat(None).take(embedding_batch.len()));
}
let mut embeddings = embeddings.into_iter();
for chunked_file in chunked_files {
let mut embedded_file = EmbeddedFile {
path: chunked_file.path,
mtime: chunked_file.mtime,
chunks: Vec::new(),
};
let mut embedded_all_chunks = true;
for (chunk, embedding) in
chunked_file.chunks.into_iter().zip(embeddings.by_ref())
{
if let Some(embedding) = embedding {
embedded_file
.chunks
.push(EmbeddedChunk { chunk, embedding });
} else {
embedded_all_chunks = false;
}
}
if embedded_all_chunks {
embedded_files_tx
.send((embedded_file, chunked_file.handle))
.await?;
}
}
}
Ok(())
});
EmbedFiles {
files: embedded_files_rx,
task,
}
}
fn persist_embeddings(
&self,
mut deleted_entry_ranges: channel::Receiver<(Bound<String>, Bound<String>)>,
embedded_files: channel::Receiver<(EmbeddedFile, IndexingEntryHandle)>,
cx: &AppContext,
) -> Task<Result<()>> {
let db_connection = self.db_connection.clone();
let db = self.db;
cx.background_executor().spawn(async move {
while let Some(deletion_range) = deleted_entry_ranges.next().await {
let mut txn = db_connection.write_txn()?;
let start = deletion_range.0.as_ref().map(|start| start.as_str());
let end = deletion_range.1.as_ref().map(|end| end.as_str());
log::debug!("deleting embeddings in range {:?}", &(start, end));
db.delete_range(&mut txn, &(start, end))?;
txn.commit()?;
}
let mut embedded_files = embedded_files.chunks_timeout(4096, Duration::from_secs(2));
while let Some(embedded_files) = embedded_files.next().await {
let mut txn = db_connection.write_txn()?;
for (file, _) in &embedded_files {
log::debug!("saving embedding for file {:?}", file.path);
let key = db_key_for_path(&file.path);
db.put(&mut txn, &key, file)?;
}
txn.commit()?;
drop(embedded_files);
log::debug!("committed");
}
Ok(())
})
}
fn paths(&self, cx: &AppContext) -> Task<Result<Vec<Arc<Path>>>> {
let connection = self.db_connection.clone();
let db = self.db;
cx.background_executor().spawn(async move {
let tx = connection
.read_txn()
.context("failed to create read transaction")?;
let result = db
.iter(&tx)?
.map(|entry| Ok(entry?.1.path.clone()))
.collect::<Result<Vec<Arc<Path>>>>();
drop(tx);
result
})
}
fn chunks_for_path(
&self,
path: Arc<Path>,
cx: &AppContext,
) -> Task<Result<Vec<EmbeddedChunk>>> {
let connection = self.db_connection.clone();
let db = self.db;
cx.background_executor().spawn(async move {
let tx = connection
.read_txn()
.context("failed to create read transaction")?;
Ok(db
.get(&tx, &db_key_for_path(&path))?
.ok_or_else(|| anyhow!("no such path"))?
.chunks
.clone())
})
}
#[cfg(test)]
fn path_count(&self) -> Result<u64> {
let txn = self
.db_connection
.read_txn()
.context("failed to create read transaction")?;
Ok(self.db.len(&txn)?)
}
}
struct ScanEntries {
updated_entries: channel::Receiver<(Entry, IndexingEntryHandle)>,
deleted_entry_ranges: channel::Receiver<(Bound<String>, Bound<String>)>,
task: Task<Result<()>>,
}
struct ChunkFiles {
files: channel::Receiver<ChunkedFile>,
task: Task<Result<()>>,
}
struct ChunkedFile {
pub path: Arc<Path>,
pub mtime: Option<SystemTime>,
pub handle: IndexingEntryHandle,
pub text: String,
pub chunks: Vec<Chunk>,
}
struct EmbedFiles {
files: channel::Receiver<(EmbeddedFile, IndexingEntryHandle)>,
task: Task<Result<()>>,
}
#[derive(Debug, Serialize, Deserialize)]
struct EmbeddedFile {
path: Arc<Path>,
mtime: Option<SystemTime>,
chunks: Vec<EmbeddedChunk>,
}
#[derive(Clone, Debug, Serialize, Deserialize)]
struct EmbeddedChunk {
chunk: Chunk,
embedding: Embedding,
}
/// The set of entries that are currently being indexed.
struct IndexingEntrySet {
entry_ids: Mutex<HashSet<ProjectEntryId>>,
tx: channel::Sender<()>,
}
/// When dropped, removes the entry from the set of entries that are being indexed.
#[derive(Clone)]
struct IndexingEntryHandle {
entry_id: ProjectEntryId,
set: Weak<IndexingEntrySet>,
}
impl IndexingEntrySet {
fn new(tx: channel::Sender<()>) -> Self {
Self {
entry_ids: Default::default(),
tx,
}
}
fn insert(self: &Arc<Self>, entry_id: ProjectEntryId) -> IndexingEntryHandle {
self.entry_ids.lock().insert(entry_id);
self.tx.send_blocking(()).ok();
IndexingEntryHandle {
entry_id,
set: Arc::downgrade(self),
}
}
pub fn len(&self) -> usize {
self.entry_ids.lock().len()
}
}
impl Drop for IndexingEntryHandle {
fn drop(&mut self) {
if let Some(set) = self.set.upgrade() {
set.tx.send_blocking(()).ok();
set.entry_ids.lock().remove(&self.entry_id);
}
}
}
fn db_key_for_path(path: &Arc<Path>) -> String {
path.to_string_lossy().replace('/', "\0")
}
#[cfg(test)]
mod tests {
use super::*;
use futures::{future::BoxFuture, FutureExt};
use gpui::TestAppContext;
use language::language_settings::AllLanguageSettings;
use project::Project;
use settings::SettingsStore;
use std::{future, path::Path, sync::Arc};
fn init_test(cx: &mut TestAppContext) {
_ = cx.update(|cx| {
let store = SettingsStore::test(cx);
cx.set_global(store);
language::init(cx);
Project::init_settings(cx);
SettingsStore::update(cx, |store, cx| {
store.update_user_settings::<AllLanguageSettings>(cx, |_| {});
});
});
}
pub struct TestEmbeddingProvider {
batch_size: usize,
compute_embedding: Box<dyn Fn(&str) -> Result<Embedding> + Send + Sync>,
}
impl TestEmbeddingProvider {
pub fn new(
batch_size: usize,
compute_embedding: impl 'static + Fn(&str) -> Result<Embedding> + Send + Sync,
) -> Self {
return Self {
batch_size,
compute_embedding: Box::new(compute_embedding),
};
}
}
impl EmbeddingProvider for TestEmbeddingProvider {
fn embed<'a>(
&'a self,
texts: &'a [TextToEmbed<'a>],
) -> BoxFuture<'a, Result<Vec<Embedding>>> {
let embeddings = texts
.iter()
.map(|to_embed| (self.compute_embedding)(to_embed.text))
.collect();
future::ready(embeddings).boxed()
}
fn batch_size(&self) -> usize {
self.batch_size
}
}
#[gpui::test]
async fn test_search(cx: &mut TestAppContext) {
cx.executor().allow_parking();
init_test(cx);
let temp_dir = tempfile::tempdir().unwrap();
let mut semantic_index = SemanticIndex::new(
temp_dir.path().into(),
Arc::new(TestEmbeddingProvider::new(16, |text| {
let mut embedding = vec![0f32; 2];
// if the text contains garbage, give it a 1 in the first dimension
if text.contains("garbage in") {
embedding[0] = 0.9;
} else {
embedding[0] = -0.9;
}
if text.contains("garbage out") {
embedding[1] = 0.9;
} else {
embedding[1] = -0.9;
}
Ok(Embedding::new(embedding))
})),
&mut cx.to_async(),
)
.await
.unwrap();
let project_path = Path::new("./fixture");
let project = cx
.spawn(|mut cx| async move { Project::example([project_path], &mut cx).await })
.await;
cx.update(|cx| {
let language_registry = project.read(cx).languages().clone();
let node_runtime = project.read(cx).node_runtime().unwrap().clone();
languages::init(language_registry, node_runtime, cx);
});
let project_index = cx.update(|cx| semantic_index.project_index(project.clone(), cx));
while project_index
.read_with(cx, |index, cx| index.path_count(cx))
.unwrap()
== 0
{
project_index.next_event(cx).await;
}
let results = cx
.update(|cx| {
let project_index = project_index.read(cx);
let query = "garbage in, garbage out";
project_index.search(query.into(), 4, cx)
})
.await
.unwrap();
assert!(results.len() > 1, "should have found some results");
for result in &results {
println!("result: {:?}", result.path);
println!("score: {:?}", result.score);
}
// Find result that is greater than 0.5
let search_result = results.iter().find(|result| result.score > 0.9).unwrap();
assert_eq!(search_result.path.to_string_lossy(), "needle.md");
let content = cx
.update(|cx| {
let worktree = search_result.worktree.read(cx);
let entry_abs_path = worktree.abs_path().join(&search_result.path);
let fs = project.read(cx).fs().clone();
cx.background_executor()
.spawn(async move { fs.load(&entry_abs_path).await.unwrap() })
})
.await;
let range = search_result.range.clone();
let content = content[range.clone()].to_owned();
assert!(content.contains("garbage in, garbage out"));
}
#[gpui::test]
async fn test_embed_files(cx: &mut TestAppContext) {
cx.executor().allow_parking();
let provider = Arc::new(TestEmbeddingProvider::new(3, |text| {
if text.contains('g') {
Err(anyhow!("cannot embed text containing a 'g' character"))
} else {
Ok(Embedding::new(
('a'..'z')
.map(|char| text.chars().filter(|c| *c == char).count() as f32)
.collect(),
))
}
}));
let (indexing_progress_tx, _) = channel::unbounded();
let indexing_entries = Arc::new(IndexingEntrySet::new(indexing_progress_tx));
let (chunked_files_tx, chunked_files_rx) = channel::unbounded::<ChunkedFile>();
chunked_files_tx
.send_blocking(ChunkedFile {
path: Path::new("test1.md").into(),
mtime: None,
handle: indexing_entries.insert(ProjectEntryId::from_proto(0)),
text: "abcdefghijklmnop".to_string(),
chunks: [0..4, 4..8, 8..12, 12..16]
.into_iter()
.map(|range| Chunk {
range,
digest: Default::default(),
})
.collect(),
})
.unwrap();
chunked_files_tx
.send_blocking(ChunkedFile {
path: Path::new("test2.md").into(),
mtime: None,
handle: indexing_entries.insert(ProjectEntryId::from_proto(1)),
text: "qrstuvwxyz".to_string(),
chunks: [0..4, 4..8, 8..10]
.into_iter()
.map(|range| Chunk {
range,
digest: Default::default(),
})
.collect(),
})
.unwrap();
chunked_files_tx.close();
let embed_files_task =
cx.update(|cx| WorktreeIndex::embed_files(provider.clone(), chunked_files_rx, cx));
embed_files_task.task.await.unwrap();
let mut embedded_files_rx = embed_files_task.files;
let mut embedded_files = Vec::new();
while let Some((embedded_file, _)) = embedded_files_rx.next().await {
embedded_files.push(embedded_file);
}
assert_eq!(embedded_files.len(), 1);
assert_eq!(embedded_files[0].path.as_ref(), Path::new("test2.md"));
assert_eq!(
embedded_files[0]
.chunks
.iter()
.map(|embedded_chunk| { embedded_chunk.embedding.clone() })
.collect::<Vec<Embedding>>(),
vec![
(provider.compute_embedding)("qrst").unwrap(),
(provider.compute_embedding)("uvwx").unwrap(),
(provider.compute_embedding)("yz").unwrap(),
],
);
}
}