[codex] Generate embeddings for semantic retrieval

crates/tempyr-cli/src/commands/ask.rs

@@ -1,23 +1,22 @@
+use crate::commands::semantic::SemanticSearchRuntime;
 use crate::config::ProjectContext;
 use tempyr_core::graph::Graph;
-use tempyr_index::hybrid::{RetrievalConfig, hybrid_retrieve};
-use tempyr_index::indexer::Index;
+use tempyr_index::hybrid::RetrievalConfig;
 
 pub fn run(
     ctx: &ProjectContext,
     question: &str,
     root: Option<&str>,
     json: bool,
 ) -> anyhow::Result<()> {
-    let index_path = ctx.queryable_index_path()?;
     let graph = Graph::load_from_directory(&ctx.graph_dir, ctx.schema.clone())?;
-    let index = Index::open(&index_path)?;
     let config = RetrievalConfig {
         token_budget: 8000,
         ..RetrievalConfig::standard()
     };
 
-    let results = hybrid_retrieve(&index, &graph, question, root, &config, None)?;
+    let mut semantic_search = SemanticSearchRuntime::new(ctx)?;
+    let results = semantic_search.hybrid_retrieve(&graph, question, root, config)?;
 
     if results.is_empty() {
         println!("No relevant context found for: {question}");

crates/tempyr-cli/src/commands/context.rs

@@ -1,7 +1,7 @@
+use crate::commands::semantic::SemanticSearchRuntime;
 use crate::config::ProjectContext;
 use tempyr_core::graph::Graph;
-use tempyr_index::hybrid::{RetrievalConfig, hybrid_retrieve};
-use tempyr_index::indexer::Index;
+use tempyr_index::hybrid::RetrievalConfig;
 
 pub fn run(
     ctx: &ProjectContext,
@@ -10,15 +10,14 @@ pub fn run(
     budget: usize,
     json: bool,
 ) -> anyhow::Result<()> {
-    let index_path = ctx.queryable_index_path()?;
     let graph = Graph::load_from_directory(&ctx.graph_dir, ctx.schema.clone())?;
-    let index = Index::open(&index_path)?;
     let config = RetrievalConfig {
         token_budget: budget,
         ..RetrievalConfig::standard()
     };
 
-    let results = hybrid_retrieve(&index, &graph, query, root, &config, None)?;
+    let mut semantic_search = SemanticSearchRuntime::new(ctx)?;
+    let results = semantic_search.hybrid_retrieve(&graph, query, root, config)?;
 
     if json {
         let json_results: Vec<_> = results
@@ -29,6 +28,7 @@ pub fn run(
                     "combined_score": r.combined_score,
                     "structural_score": r.structural_score,
                     "bm25_score": r.bm25_score,
+                    "vector_score": r.vector_score,
                 })
             })
             .collect();
@@ -50,8 +50,12 @@ pub fn run(
             .bm25_score
             .map(|s| format!(" bm25={s:.2}"))
             .unwrap_or_default();
+        let vector = result
+            .vector_score
+            .map(|s| format!(" vec={s:.2}"))
+            .unwrap_or_default();
         println!(
-            "{} (score={:.3}{structural}{bm25})",
+            "{} (score={:.3}{structural}{bm25}{vector})",
             result.node_id, result.combined_score
         );
     }

crates/tempyr-cli/src/commands/mod.rs

@@ -23,6 +23,7 @@ pub(crate) mod process_utils;
 pub mod rename;
 pub mod render_cmd;
 pub mod search;
+pub mod semantic;
 pub mod status_cmd;
 pub mod traverse;
 pub mod update;

crates/tempyr-cli/src/commands/render_cmd.rs

@@ -2,6 +2,7 @@ use std::path::Path;
 
 use chrono::NaiveDate;
 
+use crate::commands::semantic::SemanticSearchRuntime;
 use crate::config::ProjectContext;
 use tempyr_core::graph::Graph;
 use tempyr_core::temporal::TemporalFilter;
@@ -10,6 +11,61 @@ const BUILTIN_PRD: &str = include_str!("../../../../templates/prd.toml");
 const BUILTIN_TDD: &str = include_str!("../../../../templates/tdd.toml");
 const BUILTIN_TASK_PROMPT: &str = include_str!("../../../../templates/task-prompt.toml");
 
+struct RenderSemanticSearch<'a> {
+    ctx: &'a ProjectContext,
+    graph: &'a Graph,
+    runtime: Option<SemanticSearchRuntime>,
+}
+
+impl<'a> RenderSemanticSearch<'a> {
+    fn new(ctx: &'a ProjectContext, graph: &'a Graph) -> Self {
+        Self {
+            ctx,
+            graph,
+            runtime: None,
+        }
+    }
+
+    fn runtime(&mut self) -> tempyr_render::Result<&mut SemanticSearchRuntime> {
+        if self.runtime.is_none() {
+            let runtime = SemanticSearchRuntime::new(self.ctx).map_err(render_error)?;
+            self.runtime = Some(runtime);
+        }
+        Ok(self.runtime.as_mut().expect("semantic runtime initialized"))
+    }
+}
+
+impl tempyr_render::SemanticSearchProvider for RenderSemanticSearch<'_> {
+    fn search(
+        &mut self,
+        request: &tempyr_render::SemanticSearchRequest,
+    ) -> tempyr_render::Result<Vec<tempyr_render::SemanticSearchHit>> {
+        let graph = self.graph;
+        let results = self
+            .runtime()?
+            .vector_search(
+                graph,
+                &request.query,
+                request.max_results,
+                request.target_type.as_deref(),
+                request.min_similarity,
+            )
+            .map_err(render_error)?;
+
+        Ok(results
+            .into_iter()
+            .map(|result| tempyr_render::SemanticSearchHit {
+                node_id: result.node_id,
+                score: result.similarity,
+            })
+            .collect())
+    }
+}
+
+fn render_error(err: anyhow::Error) -> tempyr_render::RenderError {
+    tempyr_render::RenderError::General(err.to_string())
+}
+
 pub fn run(
     ctx: &ProjectContext,
     template_name: &str,
@@ -35,8 +91,17 @@ pub fn run(
         .tempyr_dir
         .join("render")
         .join(format!("{template_name}.toml"));
+    let mut semantic_search = RenderSemanticSearch::new(ctx, &graph);
     let result = if local_path.exists() {
-        tempyr_render::render(&graph, &local_path, root_id, &temporal_filter)?
+        tempyr_render::render_with_options(
+            &graph,
+            &local_path,
+            root_id,
+            &temporal_filter,
+            tempyr_render::RenderOptions {
+                semantic_search: Some(&mut semantic_search),
+            },
+        )?
     } else {
         // Use built-in template
         let template_toml = match template_name {
@@ -47,7 +112,15 @@ pub fn run(
                 "Unknown template: '{template_name}'. Available: prd, tdd, task-prompt (or place a custom template in .tempyr/render/)"
             ),
         };
-        tempyr_render::render_from_str(&graph, template_toml, root_id, &temporal_filter)?
+        tempyr_render::render_from_str_with_options(
+            &graph,
+            template_toml,
+            root_id,
+            &temporal_filter,
+            tempyr_render::RenderOptions {
+                semantic_search: Some(&mut semantic_search),
+            },
+        )?
     };
 
     if let Some(output_path) = output {

crates/tempyr-cli/src/commands/semantic.rs

@@ -0,0 +1,62 @@
+use crate::config::ProjectContext;
+
+use tempyr_core::graph::Graph;
+use tempyr_index::embeddings::{self, EmbeddingStore};
+use tempyr_index::hybrid::{HybridResult, RetrievalConfig};
+use tempyr_index::indexer::Index;
+use tempyr_index::semantic::SemanticSearchEngine;
+use tempyr_index::vector::VectorSearchResult;
+
+/// Runtime state for commands that need semantic search over the graph.
+pub struct SemanticSearchRuntime {
+    engine: SemanticSearchEngine,
+    runtime: tokio::runtime::Runtime,
+}
+
+impl SemanticSearchRuntime {
+    pub fn new(ctx: &ProjectContext) -> anyhow::Result<Self> {
+        let index_path = ctx.queryable_index_path()?;
+        let index = Index::open(&index_path)?;
+        let resolved = ctx.resolved_embedding_config()?;
+        let store_path = ctx.embedding_store_path(
+            &resolved.provider,
+            resolved.model.as_deref(),
+            Some(resolved.dimensions),
+        );
+        let store = EmbeddingStore::open_or_create(&store_path)?;
+        let provider = embeddings::create_provider_from_resolved(&resolved)?;
+        let runtime = tokio::runtime::Runtime::new()?;
+        let engine = SemanticSearchEngine::new(index, store, provider);
+
+        Ok(Self { engine, runtime })
+    }
+
+    pub fn vector_search(
+        &mut self,
+        graph: &Graph,
+        query: &str,
+        max_results: usize,
+        node_type: Option<&str>,
+        min_similarity: Option<f64>,
+    ) -> anyhow::Result<Vec<VectorSearchResult>> {
+        Ok(self.runtime.block_on(self.engine.vector_search(
+            graph,
+            query,
+            max_results,
+            node_type,
+            min_similarity,
+        ))?)
+    }
+
+    pub fn hybrid_retrieve(
+        &mut self,
+        graph: &Graph,
+        query: &str,
+        root: Option<&str>,
+        config: RetrievalConfig,
+    ) -> anyhow::Result<Vec<HybridResult>> {
+        Ok(self
+            .runtime
+            .block_on(self.engine.hybrid_retrieve(graph, query, root, config))?)
+    }
+}

crates/tempyr-cli/src/commands/vsearch.rs

@@ -1,13 +1,6 @@
+use crate::commands::semantic::SemanticSearchRuntime;
 use crate::config::ProjectContext;
-use tempyr_index::embeddings::{self, EmbeddingStore, InputType};
-use tempyr_index::indexer::Index;
-
-fn should_use_legacy_embeddings(
-    store_embedding_count: usize,
-    legacy_embedding_count: usize,
-) -> bool {
-    legacy_embedding_count > 0 && legacy_embedding_count > store_embedding_count
-}
+use tempyr_core::graph::Graph;
 
 pub fn run(
     ctx: &ProjectContext,
@@ -16,44 +9,9 @@ pub fn run(
     node_type: Option<&str>,
     json: bool,
 ) -> anyhow::Result<()> {
-    let index_path = ctx.queryable_index_path()?;
-    let index = Index::open(&index_path)?;
-    let resolved = ctx.resolved_embedding_config()?;
-    let store_path = ctx.embedding_store_path(
-        &resolved.provider,
-        resolved.model.as_deref(),
-        Some(resolved.dimensions),
-    );
-    let store = EmbeddingStore::open_or_create(&store_path)?;
-
-    // Check if embeddings exist
-    let store_embedding_count = store.count_embeddings_for_index(&index, node_type)?;
-    let legacy_embedding_count = index.embedding_count_for_node_type(node_type)?;
-    let use_legacy_index_embeddings =
-        should_use_legacy_embeddings(store_embedding_count, legacy_embedding_count);
-    if store_embedding_count == 0 && legacy_embedding_count == 0 {
-        anyhow::bail!(
-            "No embeddings found. Run `tempyr index rebuild` with an embedding \
-             API key set in Tempyr's shared worktree env, `.env.local`, or \
-             your shell environment (VOYAGE_API_KEY or GEMINI_API_KEY)."
-        );
-    }
-
-    // Embed the query
-    let provider = embeddings::create_provider_from_resolved(&resolved)?;
-
-    let rt = tokio::runtime::Runtime::new()?;
-    let query_embeddings = rt.block_on(provider.embed(&[query.to_string()], InputType::Query))?;
-
-    if query_embeddings.is_empty() {
-        anyhow::bail!("Failed to embed query");
-    }
-
-    let results = if use_legacy_index_embeddings {
-        index.vector_search(&query_embeddings[0], max_results, node_type)?
-    } else {
-        store.vector_search(&index, &query_embeddings[0], max_results, node_type)?
-    };
+    let graph = Graph::load_from_directory(&ctx.graph_dir, ctx.schema.clone())?;
+    let mut semantic_search = SemanticSearchRuntime::new(ctx)?;
+    let results = semantic_search.vector_search(&graph, query, max_results, node_type, None)?;
 
     if json {
         let json_results: Vec<_> = results
@@ -78,23 +36,3 @@ pub fn run(
 
     Ok(())
 }
-
-#[cfg(test)]
-mod tests {
-    use super::should_use_legacy_embeddings;
-
-    #[test]
-    fn prefers_legacy_when_shared_store_is_empty() {
-        assert!(should_use_legacy_embeddings(0, 3));
-    }
-
-    #[test]
-    fn prefers_shared_store_when_coverage_is_equal() {
-        assert!(!should_use_legacy_embeddings(2, 2));
-    }
-
-    #[test]
-    fn prefers_shared_store_when_it_has_more_coverage() {
-        assert!(!should_use_legacy_embeddings(3, 2));
-    }
-}

crates/tempyr-index/src/health.rs

@@ -157,7 +157,7 @@ pub fn build_report(inputs: &HealthInputs<'_>) -> HealthReport {
     }
     if matches!(embedding.store_exists, Some(false)) && embedding.api_key_set != Some(false) {
         warnings.push(format!(
-            "Embedding store does not exist at {}. Run `tempyr index rebuild` to populate embeddings.",
+            "Embedding store does not exist at {}. Run a vector-backed command or `tempyr index rebuild` to populate embeddings.",
             embedding.store_path.as_ref().map(|p| p.display().to_string()).unwrap_or_default()
         ));
     }

crates/tempyr-index/src/hybrid.rs

@@ -50,7 +50,7 @@ type ScoreMap = std::collections::HashMap<String, ScoreTriplet>;
 /// Run the full hybrid retrieval pipeline.
 ///
 /// Combines structural traversal (if root_id provided), BM25 full-text search,
-/// and vector similarity (deferred — always None for now).
+/// and vector similarity when a query embedding is provided.
 pub fn hybrid_retrieve(
     index: &Index,
     graph: &Graph,

crates/tempyr-index/src/lib.rs

@@ -5,6 +5,7 @@ pub mod hybrid;
 pub mod incremental;
 pub mod indexer;
 pub mod refresh;
+pub mod semantic;
 pub mod vector;
 
 use thiserror::Error;