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feat(status): report indexed embedding metadata #48

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32 changes: 31 additions & 1 deletion src/indexer.rs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -12,7 +12,7 @@ use crate::chunker::{chunk_markdown, split_oversized_chunks};
use crate::config::Config;
use crate::docid::generate_docid;
use crate::graph::extract_wikilink_targets;
use crate::llm::EmbedModel;
use crate::llm::{EmbedModel, ModelDefaults};
use crate::profile::VaultProfile;
use crate::store::{FileRecord, Store};

Expand DownExpand Up@@ -545,6 +545,15 @@ fn run_index_inner(
) -> Result<IndexResult> {
let start = Instant::now();

let defaults = ModelDefaults::default();
let embedding_uri = config
.models
.embed
.as_deref()
.unwrap_or(&defaults.embed_uri);
store.set_meta("embedding_model_uri", embedding_uri)?;

@chatgpt-codex-connectorchatgpt-codex-connectorBotJul 11, 2026

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P1 Badge Rebuild when the embedding URI changes

When a user changes models.embed to another model with the same output dimension, engraph index can take the non-rebuild path and diff_vault will skip unchanged files, but this line still overwrites embedding_model_uri. engraph status then reports the new model even though existing vectors were produced by the old model, and searches embed queries with the new model against stale embeddings; the CLI also tells users the next index will re-embed the vault at src/main.rs:700. Compare the stored URI before writing it and force a rebuild/reset when it changes.

Useful? React with 👍 / 👎.

store.set_meta("embedding_dim", &embedder.dim().to_string())?;

let cleaned = crate::writer::cleanup_temp_files(vault_path)?;
if cleaned > 0 {
info!(cleaned, "cleaned up incomplete writes from previous run");
Expand DownExpand Up@@ -1159,4 +1168,25 @@ mod tests {
assert_eq!(mentions.len(), 1);
assert_eq!(mentions[0].0, person);
}

#[test]
fn test_index_records_embedding_metadata() {
let vault = TempDir::new().unwrap();
write_file(vault.path(), "note.md", "# Metadata fixture\n");

let store = Store::open_memory().unwrap();
let mut embedder = crate::llm::MockLlm::new(256);
let config = Config::default();

run_index_shared(vault.path(), &config, &store, &mut embedder, false, None).unwrap();

assert_eq!(
store.get_meta("embedding_model_uri").unwrap(),
Some(ModelDefaults::default().embed_uri)
);
assert_eq!(
store.get_meta("embedding_dim").unwrap().as_deref(),
Some("256")
);
}
}
10 changes: 8 additions & 2 deletions src/search.rs
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Original file line numberDiff line numberDiff line change
Expand Up@@ -497,7 +497,13 @@ pub fn run_status(json: bool, data_dir: &Path) -> Result<()> {
// Compute index size on disk (sqlite db file).
let index_size = std::fs::metadata(&db_path).map(|m| m.len()).unwrap_or(0);

let model_name = "all-MiniLM-L6-v2";
let model_uri = store
.get_meta("embedding_model_uri")?
.unwrap_or_else(|| "<unknown>".to_string());
let model_dim = store
.get_meta("embedding_dim")?
.unwrap_or_else(|| "unknown".to_string());
let model_name = format!("{model_uri} (dim {model_dim})");

let config = crate::config::Config::load().unwrap_or_default();
let intelligence = if config.intelligence_enabled() {
Expand All@@ -509,7 +515,7 @@ pub fn run_status(json: bool, data_dir: &Path) -> Result<()> {
let output = format_status(
&stats,
index_size,
model_name,
&model_name,
intelligence,
date_count,
json,
Expand Down