Files
optimclaw/src/db/libsql/workspace.rs
T
ffb1cc9be8 refactor: architecture improvements for contributor velocity (#198)
* refactor: split large files and consolidate test stubs for contributor velocity

- Extract 7 Database sub-traits (ConversationStore, JobStore, SandboxStore,
  RoutineStore, ToolFailureStore, SettingsStore, WorkspaceStore) with Database
  as a supertrait combining them all
- Split libsql_backend.rs (2769 lines) into src/db/libsql/ directory with
  one file per sub-trait implementation
- Split config.rs (1753 lines) into src/config/ directory with 16 domain files
- Consolidate 3 duplicate test LLM stubs into shared StubLlm in src/testing.rs
- Split server.rs handlers into src/channels/web/handlers/ directory
- Extract main.rs init phases into AppBuilder (src/app.rs)
- Add developer setup script (scripts/dev-setup.sh)

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* refactor: move heartbeat test from examples/ to tests/

Convert standalone example binary into a proper #[ignore] integration
test, matching the convention of the other integration tests.

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* style: fix rustfmt formatting for CI

Co-Authored-By: Claude Opus 4.6 <[email protected]>

* fix: address PR review comments from Copilot

- tunnel.rs: replace .ok().flatten() with ? to propagate env var errors
- secrets.rs: remove misleading "process-wide cache" comment
- database.rs: use uppercase "DATABASE_URL" in error key
- testing.rs: gate harness tests with #[cfg(feature = "libsql")]

Co-Authored-By: Claude Opus 4.6 <[email protected]>

---------

Co-authored-by: Illia Polosukhin <[email protected]>
Co-authored-by: Claude Opus 4.6 <[email protected]>
2026-02-18 23:05:47 +00:00

608 lines
20 KiB
Rust

//! Workspace-related WorkspaceStore implementation for LibSqlBackend.
use std::collections::HashMap;
use async_trait::async_trait;
use libsql::params;
use uuid::Uuid;
use super::{
LibSqlBackend, fmt_ts, get_i64, get_opt_text, get_opt_ts, get_text, get_ts,
row_to_memory_document,
};
use crate::db::WorkspaceStore;
use crate::error::WorkspaceError;
use crate::workspace::{
MemoryChunk, MemoryDocument, RankedResult, SearchConfig, SearchResult, WorkspaceEntry,
reciprocal_rank_fusion,
};
use chrono::Utc;
#[async_trait]
impl WorkspaceStore for LibSqlBackend {
async fn get_document_by_path(
&self,
user_id: &str,
agent_id: Option<Uuid>,
path: &str,
) -> Result<MemoryDocument, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
let mut rows = conn
.query(
r#"
SELECT id, user_id, agent_id, path, content,
created_at, updated_at, metadata
FROM memory_documents
WHERE user_id = ?1 AND agent_id IS ?2 AND path = ?3
"#,
params![user_id, agent_id_str.as_deref(), path],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?;
match rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})? {
Some(row) => Ok(row_to_memory_document(&row)),
None => Err(WorkspaceError::DocumentNotFound {
doc_type: path.to_string(),
user_id: user_id.to_string(),
}),
}
}
async fn get_document_by_id(&self, id: Uuid) -> Result<MemoryDocument, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let mut rows = conn
.query(
r#"
SELECT id, user_id, agent_id, path, content,
created_at, updated_at, metadata
FROM memory_documents WHERE id = ?1
"#,
params![id.to_string()],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?;
match rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})? {
Some(row) => Ok(row_to_memory_document(&row)),
None => Err(WorkspaceError::DocumentNotFound {
doc_type: "unknown".to_string(),
user_id: "unknown".to_string(),
}),
}
}
async fn get_or_create_document_by_path(
&self,
user_id: &str,
agent_id: Option<Uuid>,
path: &str,
) -> Result<MemoryDocument, WorkspaceError> {
// Try get
match self.get_document_by_path(user_id, agent_id, path).await {
Ok(doc) => return Ok(doc),
Err(WorkspaceError::DocumentNotFound { .. }) => {}
Err(e) => return Err(e),
}
// Create
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let id = Uuid::new_v4();
let agent_id_str = agent_id.map(|id| id.to_string());
conn.execute(
r#"
INSERT INTO memory_documents (id, user_id, agent_id, path, content, metadata)
VALUES (?1, ?2, ?3, ?4, '', '{}')
ON CONFLICT (user_id, agent_id, path) DO NOTHING
"#,
params![id.to_string(), user_id, agent_id_str.as_deref(), path],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Insert failed: {}", e),
})?;
self.get_document_by_path(user_id, agent_id, path).await
}
async fn update_document(&self, id: Uuid, content: &str) -> Result<(), WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let now = fmt_ts(&Utc::now());
conn.execute(
"UPDATE memory_documents SET content = ?2, updated_at = ?3 WHERE id = ?1",
params![id.to_string(), content, now],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Update failed: {}", e),
})?;
Ok(())
}
async fn delete_document_by_path(
&self,
user_id: &str,
agent_id: Option<Uuid>,
path: &str,
) -> Result<(), WorkspaceError> {
let doc = self.get_document_by_path(user_id, agent_id, path).await?;
self.delete_chunks(doc.id).await?;
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
conn.execute(
"DELETE FROM memory_documents WHERE user_id = ?1 AND agent_id IS ?2 AND path = ?3",
params![user_id, agent_id_str.as_deref(), path],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Delete failed: {}", e),
})?;
Ok(())
}
async fn list_directory(
&self,
user_id: &str,
agent_id: Option<Uuid>,
directory: &str,
) -> Result<Vec<WorkspaceEntry>, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let dir = if !directory.is_empty() && !directory.ends_with('/') {
format!("{}/", directory)
} else {
directory.to_string()
};
let agent_id_str = agent_id.map(|id| id.to_string());
let pattern = if dir.is_empty() {
"%".to_string()
} else {
format!("{}%", dir)
};
let mut rows = conn
.query(
r#"
SELECT path, updated_at, substr(content, 1, 200) as content_preview
FROM memory_documents
WHERE user_id = ?1 AND agent_id IS ?2
AND (?3 = '%' OR path LIKE ?3)
ORDER BY path
"#,
params![user_id, agent_id_str.as_deref(), pattern],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("List directory failed: {}", e),
})?;
let mut entries_map: HashMap<String, WorkspaceEntry> = HashMap::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?
{
let full_path = get_text(&row, 0);
let updated_at = get_opt_ts(&row, 1);
let content_preview = get_opt_text(&row, 2);
let relative = if dir.is_empty() {
&full_path
} else if let Some(stripped) = full_path.strip_prefix(&dir) {
stripped
} else {
continue;
};
let child_name = if let Some(slash_pos) = relative.find('/') {
&relative[..slash_pos]
} else {
relative
};
if child_name.is_empty() {
continue;
}
let is_dir = relative.contains('/');
let entry_path = if dir.is_empty() {
child_name.to_string()
} else {
format!("{}{}", dir, child_name)
};
entries_map
.entry(child_name.to_string())
.and_modify(|e| {
if is_dir {
e.is_directory = true;
e.content_preview = None;
}
if let (Some(existing), Some(new)) = (&e.updated_at, &updated_at)
&& new > existing
{
e.updated_at = Some(*new);
}
})
.or_insert(WorkspaceEntry {
path: entry_path,
is_directory: is_dir,
updated_at,
content_preview: if is_dir { None } else { content_preview },
});
}
let mut entries: Vec<WorkspaceEntry> = entries_map.into_values().collect();
entries.sort_by(|a, b| a.path.cmp(&b.path));
Ok(entries)
}
async fn list_all_paths(
&self,
user_id: &str,
agent_id: Option<Uuid>,
) -> Result<Vec<String>, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
let mut rows = conn
.query(
"SELECT path FROM memory_documents WHERE user_id = ?1 AND agent_id IS ?2 ORDER BY path",
params![user_id, agent_id_str.as_deref()],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("List paths failed: {}", e),
})?;
let mut paths = Vec::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?
{
paths.push(get_text(&row, 0));
}
Ok(paths)
}
async fn list_documents(
&self,
user_id: &str,
agent_id: Option<Uuid>,
) -> Result<Vec<MemoryDocument>, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
let mut rows = conn
.query(
r#"
SELECT id, user_id, agent_id, path, content,
created_at, updated_at, metadata
FROM memory_documents
WHERE user_id = ?1 AND agent_id IS ?2
ORDER BY updated_at DESC
"#,
params![user_id, agent_id_str.as_deref()],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?;
let mut docs = Vec::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?
{
docs.push(row_to_memory_document(&row));
}
Ok(docs)
}
async fn delete_chunks(&self, document_id: Uuid) -> Result<(), WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::ChunkingFailed {
reason: e.to_string(),
})?;
conn.execute(
"DELETE FROM memory_chunks WHERE document_id = ?1",
params![document_id.to_string()],
)
.await
.map_err(|e| WorkspaceError::ChunkingFailed {
reason: format!("Delete failed: {}", e),
})?;
Ok(())
}
async fn insert_chunk(
&self,
document_id: Uuid,
chunk_index: i32,
content: &str,
embedding: Option<&[f32]>,
) -> Result<Uuid, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::ChunkingFailed {
reason: e.to_string(),
})?;
let id = Uuid::new_v4();
let embedding_blob = embedding.map(|e| {
let bytes: Vec<u8> = e.iter().flat_map(|f| f.to_le_bytes()).collect();
bytes
});
conn.execute(
r#"
INSERT INTO memory_chunks (id, document_id, chunk_index, content, embedding)
VALUES (?1, ?2, ?3, ?4, ?5)
"#,
params![
id.to_string(),
document_id.to_string(),
chunk_index as i64,
content,
embedding_blob.map(libsql::Value::Blob),
],
)
.await
.map_err(|e| WorkspaceError::ChunkingFailed {
reason: format!("Insert failed: {}", e),
})?;
Ok(id)
}
async fn update_chunk_embedding(
&self,
chunk_id: Uuid,
embedding: &[f32],
) -> Result<(), WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::EmbeddingFailed {
reason: e.to_string(),
})?;
let bytes: Vec<u8> = embedding.iter().flat_map(|f| f.to_le_bytes()).collect();
conn.execute(
"UPDATE memory_chunks SET embedding = ?2 WHERE id = ?1",
params![chunk_id.to_string(), libsql::Value::Blob(bytes)],
)
.await
.map_err(|e| WorkspaceError::EmbeddingFailed {
reason: format!("Update failed: {}", e),
})?;
Ok(())
}
async fn get_chunks_without_embeddings(
&self,
user_id: &str,
agent_id: Option<Uuid>,
limit: usize,
) -> Result<Vec<MemoryChunk>, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
let mut rows = conn
.query(
r#"
SELECT c.id, c.document_id, c.chunk_index, c.content, c.created_at
FROM memory_chunks c
JOIN memory_documents d ON d.id = c.document_id
WHERE d.user_id = ?1 AND d.agent_id IS ?2
AND c.embedding IS NULL
LIMIT ?3
"#,
params![user_id, agent_id_str.as_deref(), limit as i64],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?;
let mut chunks = Vec::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Query failed: {}", e),
})?
{
chunks.push(MemoryChunk {
id: get_text(&row, 0).parse().unwrap_or_default(),
document_id: get_text(&row, 1).parse().unwrap_or_default(),
chunk_index: get_i64(&row, 2) as i32,
content: get_text(&row, 3),
embedding: None,
created_at: get_ts(&row, 4),
});
}
Ok(chunks)
}
async fn hybrid_search(
&self,
user_id: &str,
agent_id: Option<Uuid>,
query: &str,
embedding: Option<&[f32]>,
config: &SearchConfig,
) -> Result<Vec<SearchResult>, WorkspaceError> {
let conn = self
.connect()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: e.to_string(),
})?;
let agent_id_str = agent_id.map(|id| id.to_string());
let pre_limit = config.pre_fusion_limit as i64;
let fts_results = if config.use_fts {
let mut rows = conn
.query(
r#"
SELECT c.id, c.document_id, c.content
FROM memory_chunks_fts fts
JOIN memory_chunks c ON c._rowid = fts.rowid
JOIN memory_documents d ON d.id = c.document_id
WHERE d.user_id = ?1 AND d.agent_id IS ?2
AND memory_chunks_fts MATCH ?3
ORDER BY rank
LIMIT ?4
"#,
params![user_id, agent_id_str.as_deref(), query, pre_limit],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("FTS query failed: {}", e),
})?;
let mut results = Vec::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("FTS row fetch failed: {}", e),
})?
{
results.push(RankedResult {
chunk_id: get_text(&row, 0).parse().unwrap_or_default(),
document_id: get_text(&row, 1).parse().unwrap_or_default(),
content: get_text(&row, 2),
rank: results.len() as u32 + 1,
});
}
results
} else {
Vec::new()
};
let vector_results = if let (true, Some(emb)) = (config.use_vector, embedding) {
let vector_json = format!(
"[{}]",
emb.iter()
.map(|f| f.to_string())
.collect::<Vec<_>>()
.join(",")
);
let mut rows = conn
.query(
r#"
SELECT c.id, c.document_id, c.content
FROM vector_top_k('idx_memory_chunks_embedding', vector(?1), ?2) AS top_k
JOIN memory_chunks c ON c._rowid = top_k.id
JOIN memory_documents d ON d.id = c.document_id
WHERE d.user_id = ?3 AND d.agent_id IS ?4
"#,
params![vector_json, pre_limit, user_id, agent_id_str.as_deref()],
)
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Vector query failed: {}", e),
})?;
let mut results = Vec::new();
while let Some(row) = rows
.next()
.await
.map_err(|e| WorkspaceError::SearchFailed {
reason: format!("Vector row fetch failed: {}", e),
})?
{
results.push(RankedResult {
chunk_id: get_text(&row, 0).parse().unwrap_or_default(),
document_id: get_text(&row, 1).parse().unwrap_or_default(),
content: get_text(&row, 2),
rank: results.len() as u32 + 1,
});
}
results
} else {
Vec::new()
};
if embedding.is_some() && !config.use_vector {
tracing::warn!(
"Embedding provided but vector search is disabled in config; using FTS-only results"
);
}
Ok(reciprocal_rank_fusion(fts_results, vector_results, config))
}
}