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WIP: work towards wiring up a embeddings_for_digest hashmap that is stored for all indexed files

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This commit is contained in:
KCaverly 2023-08-31 16:42:39 -04:00
parent 50cfb067e7
commit afa59abbcd
2 changed files with 104 additions and 23 deletions
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36
crates/semantic_index/src/db.rs
View file

@ -9,6 +9,7 @@ use gpui::executor;
use project::{search::PathMatcher, Fs};
use rpc::proto::Timestamp;
use rusqlite::params;
use rusqlite::types::Value;
use std::{
cmp::Ordering,
collections::HashMap,
@ -283,6 +284,41 @@ impl VectorDatabase {
})
}
pub fn embeddings_for_files(
&self,
worktree_id_file_paths: Vec<(i64, PathBuf)>,
) -> impl Future<Output = Result<HashMap<DocumentDigest, Embedding>>> {
todo!();
// The remainder of the code is wired up.
// I'm having a bit of trouble figuring out the rusqlite syntax for a WHERE (files.worktree_id, files.relative_path) IN (VALUES (?, ?), (?, ?)) query
async { Ok(HashMap::new()) }
// let mut embeddings_by_digest = HashMap::new();
// self.transact(move |db| {
// let worktree_ids: Rc<Vec<Value>> = Rc::new(
// worktree_id_file_paths
// .iter()
// .map(|(id, _)| Value::from(*id))
// .collect(),
// );
// let file_paths: Rc<Vec<Value>> = Rc::new(worktree_id_file_paths
// .iter()
// .map(|(_, path)| Value::from(path.to_string_lossy().to_string()))
// .collect());
// let mut query = db.prepare("SELECT digest, embedding FROM documents LEFT JOIN files ON files.id = documents.file_id WHERE (files.worktree_id, files.relative_path) IN (VALUES (rarray = (?1), rarray = (?2))")?;
// for row in query.query_map(params![worktree_ids, file_paths], |row| {
// Ok((row.get::<_, DocumentDigest>(0)?, row.get::<_, Embedding>(1)?))
// })? {
// if let Ok(row) = row {
// embeddings_by_digest.insert(row.0, row.1);
// }
// }
// Ok(embeddings_by_digest)
// })
}
pub fn find_or_create_worktree(
&self,
worktree_root_path: PathBuf,

91
crates/semantic_index/src/semantic_index.rs
View file

@ -10,12 +10,12 @@ mod semantic_index_tests;
use crate::semantic_index_settings::SemanticIndexSettings;
use anyhow::{anyhow, Result};
use db::VectorDatabase;
use embedding::{EmbeddingProvider, OpenAIEmbeddings};
use embedding::{Embedding, EmbeddingProvider, OpenAIEmbeddings};
use embedding_queue::{EmbeddingQueue, FileToEmbed};
use gpui::{AppContext, AsyncAppContext, Entity, ModelContext, ModelHandle, Task, WeakModelHandle};
use language::{Anchor, Buffer, Language, LanguageRegistry};
use parking_lot::Mutex;
use parsing::{CodeContextRetriever, PARSEABLE_ENTIRE_FILE_TYPES};
use parsing::{CodeContextRetriever, DocumentDigest, PARSEABLE_ENTIRE_FILE_TYPES};
use postage::watch;
use project::{
search::PathMatcher, Fs, PathChange, Project, ProjectEntryId, ProjectPath, Worktree, WorktreeId,
@ -103,7 +103,7 @@ pub struct SemanticIndex {
db: VectorDatabase,
embedding_provider: Arc<dyn EmbeddingProvider>,
language_registry: Arc<LanguageRegistry>,
parsing_files_tx: channel::Sender<PendingFile>,
parsing_files_tx: channel::Sender<(Arc<HashMap<DocumentDigest, Embedding>>, PendingFile)>,
_embedding_task: Task<()>,
_parsing_files_tasks: Vec<Task<()>>,
projects: HashMap<WeakModelHandle<Project>, ProjectState>,
@ -247,7 +247,8 @@ impl SemanticIndex {
});
// Parse files into embeddable documents.
let (parsing_files_tx, parsing_files_rx) = channel::unbounded::<PendingFile>();
let (parsing_files_tx, parsing_files_rx) =
channel::unbounded::<(Arc<HashMap<DocumentDigest, Embedding>>, PendingFile)>();
let embedding_queue = Arc::new(Mutex::new(embedding_queue));
let mut _parsing_files_tasks = Vec::new();
for _ in 0..cx.background().num_cpus() {
@ -258,14 +259,16 @@ impl SemanticIndex {
let db = db.clone();
_parsing_files_tasks.push(cx.background().spawn(async move {
let mut retriever = CodeContextRetriever::new(embedding_provider.clone());
while let Ok(pending_file) = parsing_files_rx.recv().await {
while let Ok((embeddings_for_digest, pending_file)) =
parsing_files_rx.recv().await
{
Self::parse_file(
&fs,
pending_file,
&mut retriever,
&embedding_queue,
&parsing_files_rx,
&db,
&embeddings_for_digest,
)
.await;
}
@ -294,8 +297,11 @@ impl SemanticIndex {
pending_file: PendingFile,
retriever: &mut CodeContextRetriever,
embedding_queue: &Arc<Mutex<EmbeddingQueue>>,
parsing_files_rx: &channel::Receiver<PendingFile>,
db: &VectorDatabase,
parsing_files_rx: &channel::Receiver<(
Arc<HashMap<DocumentDigest, Embedding>>,
PendingFile,
)>,
embeddings_for_digest: &HashMap<DocumentDigest, Embedding>,
) {
let Some(language) = pending_file.language else {
return;
@ -312,18 +318,9 @@ impl SemanticIndex {
documents.len()
);
if let Some(sha_to_embeddings) = db
.embeddings_for_file(
pending_file.worktree_db_id,
pending_file.relative_path.clone(),
)
.await
.log_err()
{
for document in documents.iter_mut() {
if let Some(embedding) = sha_to_embeddings.get(&document.digest) {
document.embedding = Some(embedding.to_owned());
}
for document in documents.iter_mut() {
if let Some(embedding) = embeddings_for_digest.get(&document.digest) {
document.embedding = Some(embedding.to_owned());
}
}
@ -381,6 +378,17 @@ impl SemanticIndex {
return;
};
let embeddings_for_digest = {
let mut worktree_id_file_paths = Vec::new();
for (path, _) in &project_state.changed_paths {
if let Some(worktree_db_id) = project_state.db_id_for_worktree_id(path.worktree_id)
{
worktree_id_file_paths.push((worktree_db_id, path.path.to_path_buf()));
}
}
self.db.embeddings_for_files(worktree_id_file_paths)
};
let worktree = worktree.read(cx);
let change_time = Instant::now();
for (path, entry_id, change) in changes.iter() {
@ -405,9 +413,18 @@ impl SemanticIndex {
}
cx.spawn_weak(|this, mut cx| async move {
let embeddings_for_digest = embeddings_for_digest.await.log_err().unwrap_or_default();
cx.background().timer(BACKGROUND_INDEXING_DELAY).await;
if let Some((this, project)) = this.upgrade(&cx).zip(project.upgrade(&cx)) {
Self::reindex_changed_paths(this, project, Some(change_time), &mut cx).await;
Self::reindex_changed_paths(
this,
project,
Some(change_time),
&mut cx,
Arc::new(embeddings_for_digest),
)
.await;
}
})
.detach();
@ -561,7 +578,32 @@ impl SemanticIndex {
cx: &mut ModelContext<Self>,
) -> Task<Result<(usize, watch::Receiver<usize>)>> {
cx.spawn(|this, mut cx| async move {
Self::reindex_changed_paths(this.clone(), project.clone(), None, &mut cx).await;
let embeddings_for_digest = this.read_with(&cx, |this, cx| {
if let Some(state) = this.projects.get(&project.downgrade()) {
let mut worktree_id_file_paths = Vec::new();
for (path, _) in &state.changed_paths {
if let Some(worktree_db_id) = state.db_id_for_worktree_id(path.worktree_id)
{
worktree_id_file_paths.push((worktree_db_id, path.path.to_path_buf()));
}
}
Ok(this.db.embeddings_for_files(worktree_id_file_paths))
} else {
Err(anyhow!("Project not yet initialized"))
}
})?;
let embeddings_for_digest = Arc::new(embeddings_for_digest.await?);
Self::reindex_changed_paths(
this.clone(),
project.clone(),
None,
&mut cx,
embeddings_for_digest,
)
.await;
this.update(&mut cx, |this, _cx| {
let Some(state) = this.projects.get(&project.downgrade()) else {
@ -726,6 +768,7 @@ impl SemanticIndex {
project: ModelHandle<Project>,
last_changed_before: Option<Instant>,
cx: &mut AsyncAppContext,
embeddings_for_digest: Arc<HashMap<DocumentDigest, Embedding>>,
) {
let mut pending_files = Vec::new();
let mut files_to_delete = Vec::new();
@ -805,7 +848,9 @@ impl SemanticIndex {
}
pending_file.language = Some(language);
}
parsing_files_tx.try_send(pending_file).ok();
parsing_files_tx
.try_send((embeddings_for_digest.clone(), pending_file))
.ok();
}
}
}