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// Search Tools - Vector-based semantic search
use crate::{MemoryOperations, Result, types::*};
use cortex_mem_core::{ContextLayer, FilesystemOperations, SearchOptions};
impl MemoryOperations {
/// Semantic search using vector similarity
///
/// Uses directory recursive retrieval strategy:
/// 1. Intent Analysis - Analyze query intent
/// 2. Initial Positioning - Locate high-score directories via L0
/// 3. Refined Exploration - Search within directories
/// 4. Recursive Drill-down - Explore subdirectories
/// 5. Result Aggregation - Sort and deduplicate
pub async fn search(&self, args: SearchArgs) -> Result<SearchResponse> {
// Normalize scope before searching
let normalized_args = SearchArgs {
scope: args
.scope
.as_deref()
.map(|s| Self::normalize_scope(Some(s))),
..args
};
// Use vector search engine
let raw_results = self.vector_search(&normalized_args).await?;
// Enrich results with requested layers
let enriched_results = self
.enrich_results(
raw_results,
&normalized_args
.return_layers
.clone()
.unwrap_or(vec!["L0".to_string()]),
)
.await?;
let total = enriched_results.len();
Ok(SearchResponse {
query: normalized_args.query.clone(),
results: enriched_results,
total,
engine_used: "vector".to_string(),
})
}
/// Simple find - quick search returning only L0 abstracts
pub async fn find(&self, args: FindArgs) -> Result<FindResponse> {
let normalized_scope = Self::normalize_scope(args.scope.as_deref());
let search_args = SearchArgs {
query: args.query.clone(),
recursive: Some(true),
return_layers: Some(vec!["L0".to_string()]),
scope: Some(normalized_scope),
limit: args.limit,
};
let search_response = self.search(search_args).await?;
let results = search_response
.results
.into_iter()
.map(|r| FindResult {
uri: r.uri,
abstract_text: r.abstract_text.unwrap_or_default(),
})
.collect();
Ok(FindResponse {
query: args.query,
results,
total: search_response.total,
})
}
/// Normalize scope parameter to ensure it's a valid cortex URI
fn normalize_scope(scope: Option<&str>) -> String {
match scope {
None => "cortex://session".to_string(),
Some(s) => {
if s.starts_with("cortex://") {
let dimension = s
.strip_prefix("cortex://")
.and_then(|rest| rest.split('/').next())
.unwrap_or("");
match dimension {
"resources" | "user" | "agent" | "session" => s.to_string(),
// Legacy aliases - map to new structure
"threads" | "agents" | "users" | "global" => {
let rest = s
.strip_prefix("cortex://")
.and_then(|r| r.find('/').map(|pos| &r[pos..]))
.unwrap_or("");
format!("cortex://session{}", rest)
}
"system" | "assistant" | "bot" => "cortex://session".to_string(),
_ => "cortex://session".to_string(),
}
} else {
format!("cortex://session/{}", s.trim_start_matches('/'))
}
}
}
}
// ==================== Internal Methods ====================
/// Vector search using VectorSearchEngine
/// Uses layered semantic search (L0->L1->L2) for optimal retrieval
async fn vector_search(&self, args: &SearchArgs) -> Result<Vec<RawSearchResult>> {
let search_options = SearchOptions {
limit: args.limit.unwrap_or(10),
threshold: 0.5,
root_uri: args.scope.clone(),
recursive: args.recursive.unwrap_or(true),
};
// Use layered semantic search for L0/L1/L2 tiered retrieval
let results = self
.vector_engine
.layered_semantic_search(&args.query, &search_options)
.await?;
Ok(results
.into_iter()
.map(|r| RawSearchResult {
uri: r.uri,
score: r.score,
})
.collect())
}
/// Enrich raw results with requested layers
async fn enrich_results(
&self,
raw_results: Vec<RawSearchResult>,
return_layers: &[String],
) -> Result<Vec<SearchResult>> {
let mut enriched = Vec::new();
for raw in raw_results {
let mut result = SearchResult {
uri: raw.uri.clone(),
score: raw.score,
abstract_text: None,
overview_text: None,
content: None,
};
// Load layers as requested
if return_layers.contains(&"L0".to_string()) {
result.abstract_text = self
.layer_manager
.load(&raw.uri, ContextLayer::L0Abstract)
.await
.ok();
}
if return_layers.contains(&"L1".to_string()) {
result.overview_text = self
.layer_manager
.load(&raw.uri, ContextLayer::L1Overview)
.await
.ok();
}
if return_layers.contains(&"L2".to_string()) {
result.content = self.filesystem.read(&raw.uri).await.ok();
}
enriched.push(result);
}
Ok(enriched)
}
}