Files
coyote/src/rag/providers/duckdb.rs
T

933 lines
39 KiB
Rust

use crate::rag::provider::RagProvider;
use crate::rag::{DocumentId, RagData};
use std::collections::HashMap;
use anyhow::{Context, Result, anyhow, bail};
use async_trait::async_trait;
use duckdb::Connection;
use duckdb::types::Value;
use indexmap::IndexMap;
use log::warn;
use std::path::{Path, PathBuf};
use std::sync::atomic::{AtomicBool, Ordering};
use std::sync::{Arc, Mutex, MutexGuard};
/// Serializes `INSTALL` across every thread in this process. DuckDB installs an
/// extension by downloading it to a temp file and then MOVING that file into
/// `~/.duckdb/extensions/...`. Two threads installing the same extension at once
/// both perform that move; on Windows the loser's move targets a file the winner
/// already holds open and fails with "Access is denied", where POSIX would let the
/// replacement through. Guards nothing but the install step, so it is never held
/// across a `DuckDbProvider::conn` guard and cannot invert lock order.
static INSTALL_LOCK: Mutex<()> = Mutex::new(());
/// Derive the DuckDB sidecar path from a RAG's YAML path: `docs.yaml` -> `docs.duckdb`.
pub(crate) fn duckdb_path_from_yaml(yaml_path: &Path) -> PathBuf {
yaml_path.with_extension("duckdb")
}
pub struct DuckDbProvider {
path: PathBuf,
conn: Arc<Mutex<Connection>>,
/// Embedding dimension; fixed at open time because the `FLOAT[N]` column depends on it.
dim: usize,
/// True once an FTS index has been built on `documents`. Until then
/// `fts_main_documents.match_bm25` does not exist and any keyword query would
/// fail with a DuckDB catalog error. Backs `has_native_keyword_search`.
fts_ready: AtomicBool,
}
impl DuckDbProvider {
/// Open (or create) the DuckDB file. `dim` is the embedding vector dimension,
/// supplied by the caller who knows the model.
pub fn open(db_path: &Path, dim: usize) -> Result<Self> {
let conn = Connection::open(db_path).with_context(|| {
format!(
"Failed to open the DuckDB store at '{}'. If another Coyote process (or \
another window) has this RAG open, close it and retry — a duckdb RAG can \
only be open in ONE process at a time. Unlike the yaml driver, its data \
lives in a single file with an exclusive lock.",
db_path.display()
)
})?;
// Statement order is load-bearing. `hnsw_enable_experimental_persistence` is
// registered BY the vss extension, so setting it before `LOAD vss` fails with
// "Setting with name ... is not in the catalog, but it exists in the vss
// extension". Omitting it entirely makes CREATE INDEX ... USING HNSW on a
// file-backed database fail with "HNSW index persistence is not yet supported
// by default". ensure vss (installing it if missing) -> ensure fts -> SET ->
// CREATE INDEX.
Self::ensure_extension(&conn, "vss")?;
Self::ensure_extension(&conn, "fts")?;
conn.execute_batch(&format!(
"SET hnsw_enable_experimental_persistence = true;
CREATE TABLE IF NOT EXISTS vectors (
doc_id UBIGINT PRIMARY KEY,
embedding FLOAT[{dim}]
);
CREATE INDEX IF NOT EXISTS hnsw_idx
ON vectors USING HNSW (embedding)
WITH (metric = 'cosine');
CREATE TABLE IF NOT EXISTS documents (
doc_id UBIGINT PRIMARY KEY,
page_content TEXT NOT NULL
);"
))
.context("Failed to initialize DuckDB schema")?;
// A reopened file may already carry a live FTS index from a previous session,
// in which case keyword search works immediately.
let fts_exists = Self::probe_fts_index(&conn);
Ok(Self {
path: db_path.to_path_buf(),
conn: Arc::new(Mutex::new(conn)),
dim,
fts_ready: AtomicBool::new(fts_exists),
})
}
/// Make a DuckDB extension available on `conn`, installing it if this machine does
/// not have it yet. `LOAD` is attempted first so an extension that is already
/// installed costs nothing and never touches the network; `INSTALL` is only reached
/// once, on a machine seeing the extension for the first time.
///
/// `LOAD` is per-connection and so runs on every connection; only `INSTALL` is
/// serialized, and the second `LOAD` under the lock is what keeps it to one
/// install. Without that re-check, every thread that queued behind the winner
/// would still run a redundant `INSTALL` and re-trigger the same file move.
fn ensure_extension(conn: &Connection, name: &str) -> Result<()> {
if conn.execute_batch(&format!("LOAD {name};")).is_ok() {
return Ok(());
}
// A poisoned lock means some other thread panicked mid-install; the lock owns
// no state to corrupt, so recover rather than failing every later open.
let _install_guard = INSTALL_LOCK.lock().unwrap_or_else(|e| e.into_inner());
// Re-check now that we hold the lock: whoever held it before us may already
// have installed the extension, in which case this `LOAD` finds it on disk.
if conn.execute_batch(&format!("LOAD {name};")).is_ok() {
return Ok(());
}
conn.execute_batch(&format!("INSTALL {name};"))
.with_context(|| {
format!(
"Failed to install the DuckDB `{name}` extension. The duckdb RAG driver \
needs it, and downloading it needs network access the first time. If this \
machine is offline, connect once and retry, or run `INSTALL {name};` \
yourself from a DuckDB shell."
)
})?;
conn.execute_batch(&format!("LOAD {name};"))
.with_context(|| {
format!("Failed to load the DuckDB `{name}` extension after installing it.")
})
}
/// Read all `(doc_id, embedding)` pairs so `create()` can hydrate `data.vectors`
/// from disk. This is what makes the next incremental sync non-destructive, and is
/// mandatory rather than an optimization.
///
/// 🔴 THIS PATTERN IS DUCKDB-ONLY. NEVER write the qdrant equivalent. Qdrant Cosine
/// collections L2-normalize stored vectors on write, so hydrating `data.vectors`
/// from a Qdrant read fills it with NORMALIZED vectors and the next save() destroys
/// the originals permanently. The symmetry with this function is exactly why that
/// bug is easy to introduce.
///
/// ALL-OR-NOTHING. An empty `vectors` table is `Ok(empty)`; ANY decode failure or
/// non-finite embedding is an `Err`. A partially-hydrated map is worse than no map:
/// `rebuild_indexes` does `CREATE OR REPLACE TABLE` and writes exactly what it is
/// given, so a thinned map is committed as the new truth on the next sync.
pub(crate) fn read_all_vectors(&self) -> Result<IndexMap<DocumentId, Vec<f32>>> {
let conn = self.lock_conn()?;
let mut stmt = conn.prepare("SELECT doc_id, embedding FROM vectors")?;
let raw: Vec<(u64, Vec<f32>)> = stmt
.query_map([], |row| {
let id: u64 = row.get(0)?;
// The duckdb crate does not implement `FromSql` for `Vec<f32>`, so the
// column is read as a `Value` and destructured. A FLOAT[N] column yields
// `Value::Array`, a FLOAT[] column yields `Value::List`; match both so
// the reader survives a file written under either schema.
let embedding: Vec<f32> = match row.get::<_, Value>(1)? {
Value::Array(vals) | Value::List(vals) => vals
.into_iter()
.map(|v| match v {
Value::Float(f) => f,
Value::Double(d) => d as f32,
_ => f32::NAN,
})
.collect(),
_ => Vec::new(),
};
Ok((id, embedding))
})?
.collect::<duckdb::Result<Vec<_>>>()
.with_context(|| {
format!(
"Failed to decode the `vectors` table in '{}'. The DuckDB sidecar is \
unreadable; delete it and run `.rebuild rag` to re-ingest from source.",
self.path.display()
)
})?;
// Validate OUTSIDE the closure so the error can name the offending row. A
// non-finite embedding is NOT droppable: dropping it thins the map, and the
// thinned map is what the next CREATE OR REPLACE commits.
let mut out = IndexMap::with_capacity(raw.len());
for (id, embedding) in raw {
if embedding.is_empty() || embedding.iter().any(|f| !f.is_finite()) {
bail!(
"Vector for doc_id {id} in '{}' is empty or contains a non-finite \
value. Refusing to hydrate a partial vector map — that would erase \
the remaining vectors on the next sync. Delete the sidecar and run \
`.rebuild rag` to re-ingest from source.",
self.path.display()
);
}
out.insert(DocumentId(id as usize), embedding);
}
Ok(out)
}
/// Does a LIVE FTS index exist on `documents`? Probed at open time so a reopened
/// database reports native keyword search accurately.
///
/// A schema-existence check alone is NOT sufficient. After
/// `CREATE OR REPLACE TABLE documents`, the `fts_main_documents` schema still
/// exists and `match_bm25` still SUCCEEDS, but returns zero rows for every term.
/// The index is silently dead. The probe therefore asserts that a KNOWN row comes
/// back rather than merely that the call did not error.
fn probe_fts_index(conn: &Connection) -> bool {
let schema_exists = conn
.query_row(
"SELECT COUNT(*) FROM duckdb_schemas() WHERE schema_name = 'fts_main_documents'",
[],
|row| row.get::<_, i64>(0),
)
.map(|n| n > 0)
.unwrap_or(false);
if !schema_exists {
return false;
}
conn.query_row(
"SELECT COUNT(*) FROM documents d
WHERE fts_main_documents.match_bm25(
d.doc_id,
(SELECT string_split(trim(page_content), ' ')[1]
FROM documents WHERE length(trim(page_content)) > 0 LIMIT 1)
) IS NOT NULL",
[],
|row| row.get::<_, i64>(0),
)
.map(|n| n > 0)
.unwrap_or(false)
}
/// Lock the shared connection, converting mutex poisoning into an `anyhow` error.
///
/// Never `.lock().unwrap()` here: a panic anywhere inside a locked scope poisons the
/// mutex permanently, and an unwrap would then turn every subsequent RAG query into
/// a panic for the remaining life of the process.
fn lock_conn(&self) -> Result<MutexGuard<'_, Connection>> {
self.conn
.lock()
.map_err(|e| anyhow!("DuckDB connection mutex was poisoned: {e}"))
}
}
#[async_trait]
impl RagProvider for DuckDbProvider {
// NOTE: the MutexGuard is held across the body of these `async fn`s. That is sound
// ONLY because no `.await` appears inside a locked scope. Adding one would make the
// generated future non-`Send` and break the `RagProvider: Send + Sync` bound.
async fn vector_search(
&self,
embedding: &[f32],
top_k: usize,
min_score: f32,
) -> Result<Vec<(DocumentId, f32)>> {
if embedding.iter().any(|f| !f.is_finite()) {
bail!("Query embedding contains a non-finite value (NaN or infinity)");
}
let vals: String = embedding
.iter()
.map(|f| f.to_string())
.collect::<Vec<_>>()
.join(", ");
let dim = self.dim;
let conn = self.lock_conn()?;
// array_cosine_distance requires a FLOAT[N] ARRAY, not the LIST type FLOAT[].
// ORDER BY distance ASC is required for the planner to use hnsw_idx; the
// similarity form (DESC) does NOT trigger the ANN index. Distance is converted
// back to a similarity score on return.
let sql = format!(
"SELECT doc_id, \
array_cosine_distance(embedding, [{vals}]::FLOAT[{dim}]) AS distance \
FROM vectors ORDER BY distance ASC LIMIT {top_k}"
);
let mut stmt = conn.prepare(&sql)?;
let results = stmt
.query_map([], |row| {
let id: u64 = row.get(0)?;
// `array_cosine_distance` on a FLOAT[N] column returns FLOAT (f32), NOT
// DOUBLE. Reading it as f64 raises InvalidColumnType INSIDE the closure,
// which a bare `.filter_map(|r| r.ok())` would silently discard,
// yielding ZERO results with no error and no log line.
let distance: f32 = match row.get::<_, Value>(1)? {
Value::Float(f) => f,
Value::Double(d) => d as f32,
other => {
warn!("unexpected distance type from DuckDB: {other:?}");
return Err(duckdb::Error::InvalidQuery);
}
};
Ok((DocumentId(id as usize), 1.0_f32 - distance))
})?
// Log-and-drop rather than a bare `.ok()`: a systematic decode failure here
// is otherwise indistinguishable from "no matches".
.filter_map(|r| match r {
Ok(v) => Some(v),
Err(e) => {
warn!("vector_search row decode failed: {e}");
None
}
})
.filter(|(_, score)| *score > min_score)
.collect();
Ok(results)
}
async fn fetch_content(&self, ids: &[DocumentId]) -> Result<Vec<(DocumentId, String)>> {
if ids.is_empty() {
return Ok(vec![]);
}
let conn = self.lock_conn()?;
let placeholders = ids.iter().map(|_| "?").collect::<Vec<_>>().join(", ");
let sql =
format!("SELECT doc_id, page_content FROM documents WHERE doc_id IN ({placeholders})");
let params: Vec<Value> = ids.iter().map(|id| Value::UBigInt(id.0 as u64)).collect();
let mut stmt = conn.prepare(&sql)?;
let mut rows: Vec<(DocumentId, String)> = stmt
.query_map(duckdb::params_from_iter(params.iter()), |row| {
let id: u64 = row.get(0)?;
let text: String = row.get(1)?;
Ok((DocumentId(id as usize), text))
})?
.filter_map(|r| match r {
Ok(v) => Some(v),
Err(e) => {
warn!("fetch_content row decode failed: {e}");
None
}
})
.collect();
let position: HashMap<DocumentId, usize> =
ids.iter().enumerate().map(|(i, id)| (*id, i)).collect();
rows.sort_by_key(|(id, _)| position.get(id).copied().unwrap_or(usize::MAX));
Ok(rows)
}
async fn rebuild_indexes(&mut self, data: &RagData, _full_rebuild: bool) -> Result<()> {
// Local on-disk state. A wholesale table reset plus re-INSERT is always
// correct, so the incremental/full distinction is ignored.
//
// 🔴 ANTI-WIPE GUARD. The CREATE OR REPLACE TABLE below writes exactly what
// `data.vectors` holds. An empty map on a RAG that HAS indexed files, against a
// store that ALREADY holds vectors, is always a bug; a failed/skipped
// hydration, or a caller that emptied the live map. Refuse rather than commit
// the loss. Every legitimate empty-vector rebuild also has an empty `files`
// (a fresh RAG; the zero-document tests), so this cannot fire on a correct call.
// The `existing > 0` conjunct is load-bearing, not belt-and-braces: a populated
// fixture rebuilt against a fresh temp database has count 0 and must proceed.
if data.vectors.is_empty() && !data.files.is_empty() {
let existing: i64 = {
// Scoped: the guard MUST be dropped before `lock_conn()` is taken again
// below. `Mutex` is not reentrant; holding both self-deadlocks at
// runtime, with no compile error.
let conn = self.lock_conn()?;
conn.query_row("SELECT count(*) FROM vectors", [], |r| r.get(0))
.context("Failed to count existing vectors before rebuild")?
};
if existing > 0 {
bail!(
"Refusing to rebuild the DuckDB store at '{}': the in-memory vector \
map is empty, but this RAG has {} indexed file(s) and the store \
already holds {existing} vector(s). Rebuilding would erase them. \
Vector hydration failed, or `data.vectors` was cleared on a live \
Rag. Nothing was written; the store is intact.",
self.path.display(),
data.files.len()
);
}
}
// Validate BEFORE opening the transaction so a bad embedding aborts before any
// write, not mid-write with the guard held.
for (doc_id, embedding) in &data.vectors {
if embedding.iter().any(|f| !f.is_finite()) {
bail!(
"Embedding for document {} contains a non-finite value",
doc_id.0
);
}
}
let dim = self.dim;
let mut conn = self.lock_conn()?;
let tx = conn
.transaction()
.context("Failed to begin DuckDB transaction")?;
// Use `CREATE OR REPLACE TABLE`, not `DELETE FROM`. Deleting rows and
// re-inserting the SAME primary keys inside ONE transaction violates DuckDB's PK
// constraint: the index holds deleted keys until commit, so the second rebuild
// fails with a duplicate-key error. `CREATE OR REPLACE` drops the table and its
// indexes atomically, leaving no stale keys. It also drops the HNSW index, which
// is recreated after commit.
tx.execute_batch(&format!(
"CREATE OR REPLACE TABLE vectors (
doc_id UBIGINT PRIMARY KEY,
embedding FLOAT[{dim}]
);
CREATE OR REPLACE TABLE documents (
doc_id UBIGINT PRIMARY KEY,
page_content TEXT NOT NULL
);"
))
.context("Failed to reset DuckDB tables")?;
{
// Plain INSERT: tables are empty after CREATE OR REPLACE, so no PK conflict.
// The embedding is bound as TEXT and cast in SQL. The duckdb crate's
// `bind_parameter` has no arm for List/Array, so binding a vector directly
// fails at runtime with "binding List parameters is not yet supported".
let mut vstmt = tx.prepare(&format!(
"INSERT INTO vectors (doc_id, embedding) VALUES (?, CAST(? AS FLOAT[{dim}]))"
))?;
let mut dstmt =
tx.prepare("INSERT INTO documents (doc_id, page_content) VALUES (?, ?)")?;
// 🔴 TWO INDEPENDENT LOOPS. `documents` is keyed on `files`, `vectors` on
// `vectors`. They are DIFFERENT key sets and neither is a subset of the
// other. Do not merge these into one loop over `&data.vectors` gated on a
// lookup into `files`: that produces keys(documents) ⊆ keys(vectors), and
// every id in `files \ vectors` (which `RagData::add`'s zip truncation
// really does produce) becomes a live, rankable id from BM25 and
// graph_search that resolves to nothing; no error, no log line.
for (id, doc) in data.iter_documents() {
dstmt.execute(duckdb::params![id.0 as u64, doc.page_content.as_str()])?;
}
for (doc_id, embedding) in &data.vectors {
// Serialize as a DuckDB array literal: "[0.1,0.2,...]". Finiteness was
// validated above, so `to_string()` cannot emit NaN/inf here.
let embedding_text = {
let mut s = String::with_capacity(embedding.len() * 12 + 2);
s.push('[');
for (i, f) in embedding.iter().enumerate() {
if i > 0 {
s.push(',');
}
s.push_str(&f.to_string());
}
s.push(']');
s
};
vstmt.execute(duckdb::params![doc_id.0 as u64, embedding_text.as_str()])?;
}
} // drop prepared statements before commit
tx.commit().context("Failed to commit DuckDB transaction")?;
// Recreate the HNSW index, dropped by CREATE OR REPLACE TABLE above. When
// CREATE INDEX USING HNSW fails, the preceding COMMIT still returns Ok, so the
// failure lands here; swallowing it would leave the database populated but
// UNINDEXED, with every vector_search silently falling back to a full scan.
conn.execute_batch(
"CREATE INDEX IF NOT EXISTS hnsw_idx \
ON vectors USING HNSW (embedding) WITH (metric = 'cosine');",
)
.context("Failed to recreate HNSW index")?;
// Rebuild the FTS index (must be outside the transaction). This rebuild is
// MANDATORY on every pass, not an optimization: CREATE OR REPLACE TABLE above
// leaves the old fts_main_documents schema in place but DEAD; match_bm25 keeps
// succeeding while returning zero rows for every term.
// GUARDED on a non-empty table: FTS cannot index an empty table, and
// rebuild_indexes is legitimately called with zero documents (a fresh RAG, and
// three of the tests below).
let doc_count: i64 = conn
.query_row("SELECT count(*) FROM documents", [], |r| r.get(0))
.context("Failed to count documents before FTS rebuild")?;
if doc_count > 0 {
conn.execute_batch(
"DROP FUNCTION IF EXISTS fts_main_documents_match_bm25;
PRAGMA create_fts_index('documents', 'doc_id', 'page_content', overwrite=1);",
)
.context("Failed to rebuild DuckDB FTS index")?;
}
// Live only if an index was actually built. With zero documents there is no FTS
// index, so `has_native_keyword_search()` must stay false and hybrid_search must
// fall back to local BM25, which is also empty, and therefore correct.
self.fts_ready.store(doc_count > 0, Ordering::Relaxed);
Ok(())
}
async fn keyword_search(&self, query: &str, top_k: usize) -> Result<Vec<(DocumentId, f32)>> {
let conn = self.lock_conn()?;
// match_bm25 returns NULL for non-matching rows; WHERE filters them out.
let mut stmt = conn.prepare(
"SELECT doc_id, fts_main_documents.match_bm25(doc_id, ?) AS score
FROM documents
WHERE score IS NOT NULL
ORDER BY score DESC
LIMIT ?",
)?;
let results = stmt
.query_map(duckdb::params![query, top_k as u64], |row| {
let id: u64 = row.get(0)?;
// Same hazard as vector_search's distance column: guessing the width
// wrong raises InvalidColumnType INSIDE the closure, which a bare
// `.filter_map(|r| r.ok())` silently discards, yielding ZERO keyword
// hits, indistinguishable from "the query matched nothing".
let score: f32 = match row.get::<_, Value>(1)? {
Value::Double(d) => d as f32,
Value::Float(f) => f,
other => {
warn!("unexpected match_bm25 score type from DuckDB: {other:?}");
return Err(duckdb::Error::InvalidQuery);
}
};
Ok((DocumentId(id as usize), score))
})?
.filter_map(|r| match r {
Ok(v) => Some(v),
Err(e) => {
warn!("keyword_search row decode failed: {e}");
None
}
})
.collect();
Ok(results)
}
fn has_native_keyword_search(&self) -> bool {
// NOT an unconditional `true`. The FTS schema only exists after
// rebuild_indexes has run the pragma (or after reopening a database where a
// previous session did). `create()` deliberately does NOT call rebuild_indexes,
// so a freshly created RAG reaches this point with no FTS index at all.
// Returning true there would route every query into keyword_search, whose `?`
// would propagate a DuckDB catalog error and fail the WHOLE search.
self.fts_ready.load(Ordering::Relaxed)
}
fn duplicate(&self, _data: &RagData) -> Box<dyn RagProvider> {
// Do NOT call DuckDbProvider::open() here. `Connection::open()` instantiates a
// NEW DuckDB *database* handle on the same file; the first handle still holds
// the file lock, so the second open fails with a locking error. Cloning the Arc
// shares the already-open connection, serialized by the Mutex.
//
// This means DuckDbProvider clones are NOT independent snapshots: state lives on
// disk and a rebuild through one handle is immediately visible to the other.
// That is unavoidable for any on-disk store and is handled by the discipline
// documented on `Rag`'s Clone impl, the pre-clone instance must be discarded.
Box::new(DuckDbProvider {
path: self.path.clone(),
conn: Arc::clone(&self.conn),
dim: self.dim,
fts_ready: AtomicBool::new(self.fts_ready.load(Ordering::Relaxed)),
})
}
}
#[cfg(test)]
mod tests {
use super::*;
use crate::rag::provider::RagProvider;
use crate::rag::{RagDocument, RagFile};
use std::time::{SystemTime, UNIX_EPOCH};
use std::{env, fs};
struct TempDb {
path: PathBuf,
}
impl TempDb {
fn new(tag: &str) -> Self {
let unique = SystemTime::now()
.duration_since(UNIX_EPOCH)
.unwrap()
.as_nanos();
let path = env::temp_dir().join(format!("coyote-duckdb-{tag}-{unique}.duckdb"));
Self { path }
}
}
impl Drop for TempDb {
fn drop(&mut self) {
let _ = fs::remove_file(&self.path);
let _ = fs::remove_file(self.path.with_extension("duckdb.wal"));
}
}
/// ⚠️ NOTE THE EMPTY `files`. This fixture describes a RAG with ZERO documents.
/// Since `rebuild_indexes` populates the `documents` table from
/// `data.iter_documents()` (keyed on `files`), any test built on this helper alone
/// exercises the `vectors` table and NOTHING ELSE. No `documents` rows, no FTS
/// index. That is correct for the rebuild tests below, and is exactly why the
/// FTS-flag test and the `fetch_content` tests use `populated_rag_data()` instead.
/// Do not "simplify" them back onto this helper.
fn minimal_rag_data() -> RagData {
RagData {
embedding_model: "text-embedding-3-small".to_string(),
chunk_size: 1024,
chunk_overlap: 50,
top_k: 5,
driver: "duckdb".to_string(),
attached: false,
..Default::default()
}
}
/// Two files, one document each; the minimum fixture that produces `documents`
/// rows.
fn populated_rag_data() -> RagData {
let mut data = minimal_rag_data();
debug_assert_eq!(DocumentId::new(0, 0), DocumentId(0));
data.files.insert(
0,
RagFile {
hash: "h0".to_string(),
path: "/tmp/a.md".to_string(),
documents: vec![RagDocument {
page_content: "alpha keyword".to_string(),
metadata: Default::default(),
}],
},
);
data.files.insert(
1,
RagFile {
hash: "h1".to_string(),
path: "/tmp/b.md".to_string(),
documents: vec![RagDocument {
page_content: "beta keyword".to_string(),
metadata: Default::default(),
}],
},
);
data
}
#[tokio::test]
async fn open_creates_schema() {
let db = TempDb::new("schema");
let provider = DuckDbProvider::open(&db.path, 3).unwrap();
let conn = provider.conn.lock().unwrap();
let v: i64 = conn
.query_row("SELECT COUNT(*) FROM vectors", [], |r| r.get(0))
.unwrap();
let d: i64 = conn
.query_row("SELECT COUNT(*) FROM documents", [], |r| r.get(0))
.unwrap();
assert_eq!(v, 0);
assert_eq!(d, 0);
}
#[tokio::test]
async fn vector_search_returns_top_result() {
let db = TempDb::new("vsearch");
let provider = DuckDbProvider::open(&db.path, 3).unwrap();
{
let conn = provider.conn.lock().unwrap();
// The ::FLOAT[3] cast is REQUIRED: a bare [0.1, 0.2, 0.3] literal infers
// DOUBLE[], which does not match the FLOAT[N] ARRAY column type.
conn.execute(
"INSERT INTO vectors (doc_id, embedding) VALUES (0, [0.1, 0.2, 0.3]::FLOAT[3])",
[],
)
.unwrap();
}
let results = provider
.vector_search(&[0.1, 0.2, 0.3], 5, 0.0)
.await
.unwrap();
assert_eq!(results.len(), 1);
assert_eq!(results[0].0.0, 0);
assert!(results[0].1 > 0.99);
}
#[tokio::test]
async fn fetch_content_returns_stored_text() {
let db = TempDb::new("fetch");
let provider = DuckDbProvider::open(&db.path, 3).unwrap();
{
let conn = provider.conn.lock().unwrap();
conn.execute(
"INSERT INTO documents (doc_id, page_content) VALUES (42, 'hello world')",
[],
)
.unwrap();
}
let results = provider.fetch_content(&[DocumentId(42)]).await.unwrap();
assert_eq!(results.len(), 1);
assert_eq!(results[0].1, "hello world");
}
#[tokio::test]
async fn rebuild_indexes_then_vector_search() {
let db = TempDb::new("rebuild");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let data = minimal_rag_data();
provider.rebuild_indexes(&data, true).await.unwrap();
let results = provider
.vector_search(&[0.1, 0.2, 0.3], 5, 0.0)
.await
.unwrap();
assert!(results.is_empty());
}
#[tokio::test]
async fn rebuild_indexes_is_idempotent_across_two_passes() {
let db = TempDb::new("idempotent");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let mut data = minimal_rag_data();
data.vectors.insert(DocumentId(0), vec![0.1, 0.2, 0.3]);
data.vectors.insert(DocumentId(1), vec![0.4, 0.5, 0.6]);
provider.rebuild_indexes(&data, true).await.unwrap();
provider
.rebuild_indexes(&data, true)
.await
.expect("second rebuild must not violate the primary key constraint");
let conn = provider.conn.lock().unwrap();
let count: i64 = conn
.query_row("SELECT COUNT(*) FROM vectors", [], |r| r.get(0))
.unwrap();
assert_eq!(count, 2, "rebuild must replace rows, not duplicate them");
}
#[tokio::test]
async fn rebuild_indexes_preserves_prior_vectors_on_incremental_pass() {
let db = TempDb::new("incremental");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let mut data = minimal_rag_data();
data.vectors.insert(DocumentId(0), vec![0.1, 0.2, 0.3]);
data.vectors.insert(DocumentId(1), vec![0.4, 0.5, 0.6]);
provider.rebuild_indexes(&data, true).await.unwrap();
let mut reloaded = minimal_rag_data();
assert!(
reloaded.vectors.is_empty(),
"YAML-loaded data starts with no vectors"
);
reloaded.vectors = provider.read_all_vectors().unwrap();
assert_eq!(
reloaded.vectors.len(),
2,
"hydration must restore both vectors"
);
reloaded.vectors.insert(DocumentId(2), vec![0.7, 0.8, 0.9]);
provider.rebuild_indexes(&reloaded, false).await.unwrap();
let conn = provider.conn.lock().unwrap();
let count: i64 = conn
.query_row("SELECT COUNT(*) FROM vectors", [], |r| r.get(0))
.unwrap();
// Without hydration this is 1 — the two originals silently vanish.
assert_eq!(
count, 3,
"an incremental pass must not destroy previously indexed vectors"
);
}
#[tokio::test]
async fn keyword_search_is_not_advertised_before_first_rebuild() {
let db = TempDb::new("ftsflag");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
assert!(
!provider.has_native_keyword_search(),
"a freshly opened DB has no FTS index yet"
);
let mut data = populated_rag_data();
data.vectors.insert(DocumentId(0), vec![0.1, 0.2, 0.3]);
provider.rebuild_indexes(&data, true).await.unwrap();
{
let conn = provider.conn.lock().unwrap();
let docs: i64 = conn
.query_row("SELECT COUNT(*) FROM documents", [], |r| r.get(0))
.unwrap();
assert_eq!(docs, 2, "the fixture must produce documents rows");
}
assert!(
provider.has_native_keyword_search(),
"rebuild_indexes creates the FTS index and must flip the flag"
);
}
#[tokio::test]
async fn fetch_content_resolves_documents_without_vectors() {
let db = TempDb::new("docsnovec");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let mut data = populated_rag_data();
let id_a = DocumentId::new(0, 0);
let id_b = DocumentId::new(1, 0);
data.vectors.insert(id_a, vec![0.1, 0.2, 0.3]);
assert!(
!data.vectors.contains_key(&id_b),
"precondition: b has no vector"
);
provider.rebuild_indexes(&data, true).await.unwrap();
let got = provider.fetch_content(&[id_a, id_b]).await.unwrap();
assert_eq!(
got.len(),
2,
"fetch_content must resolve BOTH documents; the one without a vector is \
still reachable by keyword and graph search"
);
assert_eq!(got[0].1, "alpha keyword");
assert_eq!(got[1].1, "beta keyword");
}
#[tokio::test]
async fn duckdb_fetch_content_preserves_input_order() {
let db = TempDb::new("order");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let data = populated_rag_data();
provider.rebuild_indexes(&data, true).await.unwrap();
let id_a = DocumentId::new(0, 0);
let id_b = DocumentId::new(1, 0);
let got = provider.fetch_content(&[id_b, id_a]).await.unwrap();
assert_eq!(got.len(), 2);
assert_eq!(got[0].0, id_b, "input order must win over storage order");
assert_eq!(got[0].1, "beta keyword");
assert_eq!(got[1].0, id_a);
assert_eq!(got[1].1, "alpha keyword");
}
#[tokio::test]
async fn rebuild_indexes_refuses_to_wipe_when_vectors_are_empty_but_files_are_not() {
let db = TempDb::new("nowipe");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let mut data = populated_rag_data();
data.vectors
.insert(DocumentId::new(0, 0), vec![0.1, 0.2, 0.3]);
data.vectors
.insert(DocumentId::new(1, 0), vec![0.4, 0.5, 0.6]);
provider.rebuild_indexes(&data, true).await.unwrap();
let broken = populated_rag_data();
assert!(
broken.vectors.is_empty() && !broken.files.is_empty(),
"precondition"
);
let err = provider.rebuild_indexes(&broken, true).await.unwrap_err();
assert!(
err.to_string().contains("Refusing to rebuild"),
"got: {err}"
);
let conn = provider.conn.lock().unwrap();
let count: i64 = conn
.query_row("SELECT COUNT(*) FROM vectors", [], |r| r.get(0))
.unwrap();
assert_eq!(
count, 2,
"the guard must abort BEFORE the CREATE OR REPLACE"
);
}
#[tokio::test]
async fn rebuild_indexes_allows_empty_vectors_when_files_are_also_empty() {
let db = TempDb::new("emptyok");
let mut provider = DuckDbProvider::open(&db.path, 3).unwrap();
let data = minimal_rag_data();
provider
.rebuild_indexes(&data, true)
.await
.expect("a fresh RAG with nothing indexed must rebuild cleanly");
}
#[tokio::test]
async fn duplicate_shares_the_same_connection() {
let db = TempDb::new("dup");
let provider = DuckDbProvider::open(&db.path, 3).unwrap();
let dup = provider.duplicate(&minimal_rag_data());
{
let conn = provider.conn.lock().unwrap();
conn.execute(
"INSERT INTO documents (doc_id, page_content) VALUES (7, 'shared row')",
[],
)
.unwrap();
}
let via_dup = dup.fetch_content(&[DocumentId(7)]).await.unwrap();
assert_eq!(
via_dup.len(),
1,
"duplicate() must see writes made via the original"
);
assert_eq!(via_dup[0].1, "shared row");
}
#[tokio::test]
async fn read_all_vectors_rejects_non_finite_embeddings() {
let db = TempDb::new("nonfinite");
let provider = DuckDbProvider::open(&db.path, 3).unwrap();
{
let conn = provider.conn.lock().unwrap();
conn.execute(
"INSERT INTO vectors (doc_id, embedding) VALUES (0, [0.1, 0.2, 0.3]::FLOAT[3])",
[],
)
.unwrap();
conn.execute(
// Each element is cast individually: a bare ['nan', 0.2, 0.3] literal
// mixes text and numerics, so DuckDB infers DECIMAL and the conversion
// fails before the row is ever stored.
"INSERT INTO vectors (doc_id, embedding) VALUES \
(1, [CAST('nan' AS FLOAT), CAST(0.2 AS FLOAT), CAST(0.3 AS FLOAT)]::FLOAT[3])",
[],
)
.unwrap();
}
let err = provider.read_all_vectors().unwrap_err();
assert!(
err.to_string().contains("non-finite"),
"hydration must abort rather than silently drop the row; got: {err}"
);
}
#[test]
fn duckdb_path_from_yaml_swaps_extension() {
let p = duckdb_path_from_yaml(Path::new("/tmp/rags/docs.yaml"));
assert_eq!(p, PathBuf::from("/tmp/rags/docs.duckdb"));
}
}