feat: semantic (embedding-based) response cache

- cache.rs: cosine-similarity store (threshold, TTL, ring buffer), partitioned by
  routing signature; tracks hit rate and model cost saved
- pipeline: embed routing text, look up before the model call (route_source=cache on
  hit), insert successful responses; stats record cache hits
- config [cache] + admin settings card; dashboard shows hit-rate and savings
- embedding model resolved from the pool (or first kind="embedding")

CHANGELOG.md

@@ -19,6 +19,10 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/).
   SSE), so Claude-native clients can target the gateway.
 - **Embeddings**: `POST /v1/embeddings` inbound + provider `embed()`; embedding models
   are now resolvable from the pool.
+- **Semantic cache**: embedding-based cache that returns a stored answer for prompts
+  semantically near a previous one (cosine threshold, TTL, ring buffer), skipping the
+  model call. Partitioned by routing signature; hit-rate and cost saved are tracked and
+  shown on the dashboard; configurable from Settings (`[cache]`).
 
 ## [0.1.0] - 2026-06-30
 

config/gateway.example.toml

@@ -150,3 +150,15 @@ enabled   = true
 file      = "config/stats.jsonl"   # empty = in-memory only
 ring_size = 500                     # how many recent requests to keep in the feed
 retention = "7d"                    # aggregate/series depth (replayed on startup)
+
+# ============================================================================
+# Semantic cache — returns a cached answer for prompts semantically near a
+# previous one, skipping the model call. Requires an embedding model in the pool.
+# Disabled by default. (Cache settings take effect on restart.)
+# ============================================================================
+[cache]
+enabled     = false
+threshold   = 0.92                  # cosine similarity for a hit (0..1)
+ttl         = "1h"
+max_entries = 1000
+# embed_model = "local-embed"       # defaults to the first kind = "embedding" model

src/admin/mod.rs

@@ -8,8 +8,8 @@
 pub mod assets;
 
 use crate::config::{
-    AdminCfg, ApiKeyCfg, BreakerCfg, Config, CortiqCfg, LogCfg, ModelCfg, ProtocolsCfg, RouteCfg,
-    RouterCfg, RoutingCfg, RoutingPolicy, StatsCfg, TelemetryCfg, TierTargets,
+    AdminCfg, ApiKeyCfg, BreakerCfg, CacheCfg, Config, CortiqCfg, LogCfg, ModelCfg, ProtocolsCfg,
+    RouteCfg, RouterCfg, RoutingCfg, RoutingPolicy, StatsCfg, TelemetryCfg, TierTargets,
 };
 use crate::model::{ChatRequest, GenParams, Message, RequestMeta, RoutingDirective};
 use crate::state::SharedState;
@@ -477,6 +477,7 @@ async fn get_settings(State(state): State<SharedState>) -> ApiResult {
         "cortiq": c.cortiq,
         "stats": c.stats,
         "admin": c.admin,
+        "cache": c.cache,
     }))
 }
 
@@ -491,6 +492,7 @@ struct SettingsBody {
     cortiq: Option<CortiqCfg>,
     stats: Option<StatsCfg>,
     admin: Option<AdminCfg>,
+    cache: Option<CacheCfg>,
 }
 
 async fn put_settings(State(state): State<SharedState>, Json(b): Json<SettingsBody>) -> ApiResult {
@@ -529,6 +531,11 @@ async fn put_settings(State(state): State<SharedState>, Json(b): Json<SettingsBo
         }
         cfg.admin = v;
     }
+    if let Some(v) = b.cache {
+        // the cache is built at startup; persist now, apply on restart
+        needs_restart = true;
+        cfg.cache = v;
+    }
     state.reload(cfg)?;
     ok(json!({ "ok": true, "needs_restart": needs_restart }))
 }
@@ -666,7 +673,9 @@ async fn get_stats(State(state): State<SharedState>, Query(q): Query<StatsQuery>
         .and_then(parse_duration_secs)
         .unwrap_or(24 * 3600);
     let groupby = q.groupby.as_deref().unwrap_or("model");
-    ok(state.stats.snapshot(range_secs, groupby))
+    let mut snap = state.stats.snapshot(range_secs, groupby);
+    snap["cache"] = state.cache.snapshot();
+    ok(snap)
 }
 
 #[derive(Deserialize)]

src/cache.rs

@@ -0,0 +1,171 @@
+//! Semantic (embedding-based) response cache.
+//!
+//! Each entry stores an L2-normalized embedding of the request plus the response.
+//! A lookup returns a cached answer when the cosine similarity to a previous request
+//! (with the same routing signature, within TTL) meets the configured threshold —
+//! skipping the expensive model call. In-memory ring buffer; counters track hit
+//! rate and the model cost saved.
+
+use crate::config::CacheCfg;
+use crate::stats::parse_duration_secs;
+use std::collections::VecDeque;
+use std::sync::atomic::{AtomicU64, Ordering};
+use std::sync::{Arc, Mutex};
+use std::time::{SystemTime, UNIX_EPOCH};
+
+fn now_secs() -> u64 {
+    SystemTime::now()
+        .duration_since(UNIX_EPOCH)
+        .unwrap_or_default()
+        .as_secs()
+}
+
+struct Entry {
+    sig: String,
+    vec: Vec<f32>, // L2-normalized
+    ts: u64,
+    model_used: String,
+    content: String,
+    prompt_tokens: u32,
+    completion_tokens: u32,
+    cost: f64,
+}
+
+pub struct CacheHit {
+    pub model_used: String,
+    pub content: String,
+    pub prompt_tokens: u32,
+    pub completion_tokens: u32,
+    pub similarity: f32,
+}
+
+pub struct SemanticCache {
+    enabled: bool,
+    threshold: f32,
+    ttl_secs: u64,
+    max_entries: usize,
+    embed_model: Option<String>,
+    entries: Mutex<VecDeque<Entry>>,
+    hits: AtomicU64,
+    misses: AtomicU64,
+    saved_micro_usd: AtomicU64,
+}
+
+impl SemanticCache {
+    pub fn new(cfg: &CacheCfg) -> Arc<Self> {
+        Arc::new(Self {
+            enabled: cfg.enabled,
+            threshold: cfg.threshold,
+            ttl_secs: parse_duration_secs(&cfg.ttl).unwrap_or(3600),
+            max_entries: cfg.max_entries.max(1),
+            embed_model: cfg.embed_model.clone(),
+            entries: Mutex::new(VecDeque::new()),
+            hits: AtomicU64::new(0),
+            misses: AtomicU64::new(0),
+            saved_micro_usd: AtomicU64::new(0),
+        })
+    }
+
+    pub fn enabled(&self) -> bool {
+        self.enabled
+    }
+    pub fn embed_model(&self) -> Option<&str> {
+        self.embed_model.as_deref()
+    }
+
+    /// Look up a cached response by routing signature + query embedding.
+    pub fn lookup(&self, sig: &str, query: &[f32]) -> Option<CacheHit> {
+        if !self.enabled {
+            return None;
+        }
+        let q = normalized(query);
+        let cutoff = now_secs().saturating_sub(self.ttl_secs);
+        let inner = self.entries.lock().unwrap();
+        let mut best: Option<(f32, &Entry)> = None;
+        for e in inner.iter() {
+            if e.sig != sig || e.ts < cutoff {
+                continue;
+            }
+            let sim = dot(&e.vec, &q);
+            if sim >= self.threshold && best.map(|(b, _)| sim > b).unwrap_or(true) {
+                best = Some((sim, e));
+            }
+        }
+        match best {
+            Some((sim, e)) => {
+                self.hits.fetch_add(1, Ordering::Relaxed);
+                self.saved_micro_usd
+                    .fetch_add((e.cost * 1_000_000.0) as u64, Ordering::Relaxed);
+                Some(CacheHit {
+                    model_used: e.model_used.clone(),
+                    content: e.content.clone(),
+                    prompt_tokens: e.prompt_tokens,
+                    completion_tokens: e.completion_tokens,
+                    similarity: sim,
+                })
+            }
+            None => {
+                self.misses.fetch_add(1, Ordering::Relaxed);
+                None
+            }
+        }
+    }
+
+    /// Store a response under its routing signature + query embedding.
+    #[allow(clippy::too_many_arguments)]
+    pub fn insert(
+        &self,
+        sig: String,
+        query: Vec<f32>,
+        model_used: String,
+        content: String,
+        prompt_tokens: u32,
+        completion_tokens: u32,
+        cost: f64,
+    ) {
+        if !self.enabled || query.is_empty() {
+            return;
+        }
+        let vec = normalized(&query);
+        let mut inner = self.entries.lock().unwrap();
+        inner.push_back(Entry {
+            sig,
+            vec,
+            ts: now_secs(),
+            model_used,
+            content,
+            prompt_tokens,
+            completion_tokens,
+            cost,
+        });
+        while inner.len() > self.max_entries {
+            inner.pop_front();
+        }
+    }
+
+    pub fn snapshot(&self) -> serde_json::Value {
+        let h = self.hits.load(Ordering::Relaxed);
+        let m = self.misses.load(Ordering::Relaxed);
+        serde_json::json!({
+            "enabled": self.enabled,
+            "hits": h,
+            "misses": m,
+            "hit_rate": if h + m > 0 { h as f64 / (h + m) as f64 } else { 0.0 },
+            "entries": self.entries.lock().unwrap().len(),
+            "saved_usd": self.saved_micro_usd.load(Ordering::Relaxed) as f64 / 1_000_000.0,
+        })
+    }
+}
+
+fn dot(a: &[f32], b: &[f32]) -> f32 {
+    a.iter().zip(b.iter()).map(|(x, y)| x * y).sum()
+}
+
+fn normalized(v: &[f32]) -> Vec<f32> {
+    let n = v.iter().map(|x| x * x).sum::<f32>().sqrt();
+    if n > 0.0 {
+        v.iter().map(|x| x / n).collect()
+    } else {
+        v.to_vec()
+    }
+}

src/config.rs

@@ -31,6 +31,8 @@ pub struct Config {
     pub admin: AdminCfg,
     #[serde(default)]
     pub stats: StatsCfg,
+    #[serde(default)]
+    pub cache: CacheCfg,
 }
 
 #[derive(Clone, Debug, Serialize, Deserialize)]
@@ -320,6 +322,46 @@ fn default_stats_retention() -> String {
     "7d".into()
 }
 
+/// Semantic (embedding-based) response cache — returns a cached answer for prompts
+/// that are semantically near a previous one, skipping the (expensive) model call.
+#[derive(Clone, Debug, Serialize, Deserialize)]
+pub struct CacheCfg {
+    #[serde(default)]
+    pub enabled: bool,
+    /// Cosine-similarity threshold for a hit (0..1).
+    #[serde(default = "default_semcache_threshold")]
+    pub threshold: f32,
+    /// Entry time-to-live, e.g. `1h`.
+    #[serde(default = "default_semcache_ttl")]
+    pub ttl: String,
+    /// Maximum number of cached entries (ring buffer).
+    #[serde(default = "default_semcache_max")]
+    pub max_entries: usize,
+    /// Embedding model id (defaults to the first `kind = "embedding"` model).
+    #[serde(default, skip_serializing_if = "Option::is_none")]
+    pub embed_model: Option<String>,
+}
+impl Default for CacheCfg {
+    fn default() -> Self {
+        Self {
+            enabled: false,
+            threshold: default_semcache_threshold(),
+            ttl: default_semcache_ttl(),
+            max_entries: default_semcache_max(),
+            embed_model: None,
+        }
+    }
+}
+fn default_semcache_threshold() -> f32 {
+    0.92
+}
+fn default_semcache_ttl() -> String {
+    "1h".into()
+}
+fn default_semcache_max() -> usize {
+    1000
+}
+
 impl Config {
     /// Load and validate the config from a file.
     pub fn load(path: &str) -> anyhow::Result<Self> {

src/main.rs

@@ -9,6 +9,7 @@
 #![allow(dead_code)]
 
 mod admin;
+mod cache;
 mod config;
 mod error;
 mod model;

src/pipeline.rs

@@ -4,9 +4,9 @@
 
 use crate::error::{GatewayError, Result};
 use crate::model::{
-    ChatRequest, ChatResponse, Message, RouteDecision, RouteInfo, RoutingDirective,
+    ChatRequest, ChatResponse, Choice, Message, RouteDecision, RouteInfo, RoutingDirective, Usage,
 };
-use crate::state::SharedState;
+use crate::state::{Live, SharedState};
 use crate::stats::RequestRecord;
 use std::time::{Instant, SystemTime, UNIX_EPOCH};
 
@@ -28,6 +28,45 @@ impl Pipeline {
         }
         .to_string();
 
+        // --- semantic cache lookup (short-circuit before the model call) ---
+        let cache = &state.cache;
+        let mut cache_key: Option<(String, Vec<f32>)> = None;
+        if cache.enabled() {
+            let live = state.live();
+            let sig = cache_sig(&req);
+            let text = self.extract_text(&req.messages, "concat_all", live.cfg.route.max_chars);
+            let embed_model = cache
+                .embed_model()
+                .map(|s| s.to_string())
+                .or_else(|| first_embedding_model(&live));
+            if let Some(model_id) = embed_model {
+                if let Some(vec) = embed(&live, &model_id, &text).await {
+                    if let Some(hit) = cache.lookup(&sig, &vec) {
+                        state.stats.record(RequestRecord {
+                            ts: now_secs(),
+                            account,
+                            protocol,
+                            directive,
+                            task_label: "cache".into(),
+                            tier: "cache".into(),
+                            score: 0.0,
+                            model_id: hit.model_used.clone(),
+                            route_source: "cache".into(),
+                            prompt_tokens: hit.prompt_tokens,
+                            completion_tokens: hit.completion_tokens,
+                            cost_usd: 0.0,
+                            latency_ms: started.elapsed().as_millis() as u64,
+                            outcome: "ok".into(),
+                            failover: false,
+                            error: None,
+                        });
+                        return Ok(cached_response(&hit));
+                    }
+                    cache_key = Some((sig, vec));
+                }
+            }
+        }
+
         let result = self.run_inner(req, state).await;
 
         // record statistics (for both success and error)
@@ -76,6 +115,26 @@ impl Pipeline {
         };
         state.stats.record(rec);
 
+        // --- store a successful response in the semantic cache ---
+        if let (Ok(resp), Some((sig, vec))) = (&result, cache_key) {
+            let content = resp
+                .choices
+                .first()
+                .map(|c| c.message.content.clone())
+                .unwrap_or_default();
+            if !content.is_empty() {
+                state.cache.insert(
+                    sig,
+                    vec,
+                    resp.cortiq.selected_model.clone(),
+                    content,
+                    resp.usage.prompt_tokens,
+                    resp.usage.completion_tokens,
+                    resp.cortiq.cost_usd,
+                );
+            }
+        }
+
         result
     }
 
@@ -350,6 +409,69 @@ fn now_secs() -> u64 {
         .as_secs()
 }
 
+/// Routing signature used to partition cache entries (so a pinned model's cached
+/// answer is never returned for a different model/profile).
+fn cache_sig(req: &ChatRequest) -> String {
+    match &req.routing {
+        RoutingDirective::Auto { profile } => {
+            format!("auto:{}", profile.as_deref().unwrap_or(""))
+        }
+        RoutingDirective::Pinned { model_id } => format!("pinned:{model_id}"),
+    }
+}
+
+fn first_embedding_model(live: &Live) -> Option<String> {
+    live.cfg
+        .models
+        .iter()
+        .find(|m| m.kind == "embedding")
+        .map(|m| m.id.clone())
+}
+
+/// Embed `text` with the given model; returns the embedding vector (or None on error).
+async fn embed(live: &Live, model_id: &str, text: &str) -> Option<Vec<f32>> {
+    let provider = live.registry.get(model_id)?;
+    let body = provider.embed(serde_json::json!(text)).await.ok()?;
+    let arr = body["data"][0]["embedding"].as_array()?;
+    Some(
+        arr.iter()
+            .filter_map(|x| x.as_f64())
+            .map(|x| x as f32)
+            .collect(),
+    )
+}
+
+fn cached_response(hit: &crate::cache::CacheHit) -> ChatResponse {
+    ChatResponse {
+        id: "cache".to_string(),
+        model_used: hit.model_used.clone(),
+        choices: vec![Choice {
+            index: 0,
+            message: Message {
+                role: "assistant".into(),
+                content: hit.content.clone(),
+                tool_calls: vec![],
+            },
+            finish_reason: "stop".into(),
+        }],
+        usage: Usage {
+            prompt_tokens: hit.prompt_tokens,
+            completion_tokens: hit.completion_tokens,
+            total_tokens: hit.prompt_tokens + hit.completion_tokens,
+        },
+        cortiq: RouteInfo {
+            task_label: "cache".into(),
+            complexity_score: 0.0,
+            complexity_tier: "cache".into(),
+            selected_model: hit.model_used.clone(),
+            route_source: "cache".into(),
+            router_request_id: None,
+            cost_usd: 0.0,
+            failover: false,
+        },
+    }
+}
+
 fn record_error(
     state: &SharedState,
     account: &str,

src/state.rs

@@ -5,6 +5,7 @@
 //! a restart: the admin API validates the new config, builds a new `Live`,
 //! atomically writes the TOML, and swaps the pointer.
 
+use crate::cache::SemanticCache;
 use crate::config::Config;
 use crate::registry::Registry;
 use crate::router_client::RouterClient;
@@ -42,6 +43,7 @@ impl Live {
 pub struct AppState {
     pub live: ArcSwap<Live>,
     pub stats: Arc<Stats>,
+    pub cache: Arc<SemanticCache>,
     pub secrets: SecretStore,
     pub config_path: String,
     pub pipeline: crate::pipeline::Pipeline,
@@ -59,10 +61,12 @@ impl SharedState {
         let secrets_path = sibling(&config_path, "secrets.toml");
         let secrets = SecretStore::load(&secrets_path);
         let stats = Stats::new(&cfg.stats);
+        let cache = SemanticCache::new(&cfg.cache);
         let live = Live::build(cfg, &secrets)?;
         Ok(SharedState(Arc::new(AppState {
             live: ArcSwap::from_pointee(live),
             stats,
+            cache,
             secrets,
             config_path,
             pipeline: crate::pipeline::Pipeline::new(),

web/js/i18n/de.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "Gelöscht",
   "toast.probing": "Prüfe…",
   "toast.imported": "Konfiguration importiert",
+  "dash.cache": "Semantischer Cache",
+  "dash.cache.hitRate": "Trefferquote",
+  "dash.cache.hits": "Treffer",
+  "dash.cache.saved": "Gespart",
+  "dash.cache.disabled": "Semantischer Cache ist deaktiviert — in den Einstellungen aktivieren.",
+  "settings.cache": "Semantischer Cache",
+  "settings.cache.enabled": "Semantischen Cache aktivieren",
+  "settings.cache.threshold": "Ähnlichkeitsschwelle",
+  "settings.cache.ttl": "Eintrags-TTL",
+  "settings.cache.embed": "Embedding-Modell",
+  "settings.cache.note": "Cache-Einstellungen werden nach einem Neustart wirksam.",
 };

web/js/i18n/en.js

@@ -255,4 +255,15 @@ export default {
   "toast.deleted": "Deleted",
   "toast.probing": "Probing…",
   "toast.imported": "Config imported",
+  "dash.cache": "Semantic cache",
+  "dash.cache.hitRate": "Hit rate",
+  "dash.cache.hits": "Hits",
+  "dash.cache.saved": "Saved",
+  "dash.cache.disabled": "Semantic cache is disabled — enable it in Settings.",
+  "settings.cache": "Semantic cache",
+  "settings.cache.enabled": "Enable semantic cache",
+  "settings.cache.threshold": "Similarity threshold",
+  "settings.cache.ttl": "Entry TTL",
+  "settings.cache.embed": "Embedding model",
+  "settings.cache.note": "Cache settings take effect after a restart.",
 };

web/js/i18n/es.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "Eliminado",
   "toast.probing": "Sondeando…",
   "toast.imported": "Configuración importada",
+  "dash.cache": "Caché semántico",
+  "dash.cache.hitRate": "Aciertos",
+  "dash.cache.hits": "Aciertos",
+  "dash.cache.saved": "Ahorrado",
+  "dash.cache.disabled": "El caché semántico está desactivado — actívalo en Ajustes.",
+  "settings.cache": "Caché semántico",
+  "settings.cache.enabled": "Activar caché semántico",
+  "settings.cache.threshold": "Umbral de similitud",
+  "settings.cache.ttl": "TTL de entrada",
+  "settings.cache.embed": "Modelo de embeddings",
+  "settings.cache.note": "Los ajustes del caché se aplican tras reiniciar.",
 };

web/js/i18n/fr.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "Supprimé",
   "toast.probing": "Sondage…",
   "toast.imported": "Config importée",
+  "dash.cache": "Cache sémantique",
+  "dash.cache.hitRate": "Taux de succès",
+  "dash.cache.hits": "Succès",
+  "dash.cache.saved": "Économisé",
+  "dash.cache.disabled": "Le cache sémantique est désactivé — activez-le dans les Paramètres.",
+  "settings.cache": "Cache sémantique",
+  "settings.cache.enabled": "Activer le cache sémantique",
+  "settings.cache.threshold": "Seuil de similarité",
+  "settings.cache.ttl": "TTL d'entrée",
+  "settings.cache.embed": "Modèle d'embeddings",
+  "settings.cache.note": "Les paramètres du cache prennent effet après un redémarrage.",
 };

web/js/i18n/ru.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "Удалено",
   "toast.probing": "Проверка…",
   "toast.imported": "Конфигурация импортирована",
+  "dash.cache": "Семантический кэш",
+  "dash.cache.hitRate": "Попаданий",
+  "dash.cache.hits": "Попадания",
+  "dash.cache.saved": "Сэкономлено",
+  "dash.cache.disabled": "Семантический кэш выключен — включите в Настройках.",
+  "settings.cache": "Семантический кэш",
+  "settings.cache.enabled": "Включить семантический кэш",
+  "settings.cache.threshold": "Порог сходства",
+  "settings.cache.ttl": "TTL записи",
+  "settings.cache.embed": "Модель эмбеддингов",
+  "settings.cache.note": "Настройки кэша применяются после перезапуска.",
 };

web/js/i18n/tr.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "Silindi",
   "toast.probing": "Sınanıyor…",
   "toast.imported": "Yapılandırma içe aktarıldı",
+  "dash.cache": "Anlamsal önbellek",
+  "dash.cache.hitRate": "İsabet oranı",
+  "dash.cache.hits": "İsabet",
+  "dash.cache.saved": "Tasarruf",
+  "dash.cache.disabled": "Anlamsal önbellek kapalı — Ayarlar'dan etkinleştirin.",
+  "settings.cache": "Anlamsal önbellek",
+  "settings.cache.enabled": "Anlamsal önbelleği etkinleştir",
+  "settings.cache.threshold": "Benzerlik eşiği",
+  "settings.cache.ttl": "Giriş TTL",
+  "settings.cache.embed": "Gömme modeli",
+  "settings.cache.note": "Anlamsal önbellek ayarları yeniden başlatmadan sonra geçerli olur.",
 };

web/js/i18n/zh.js

@@ -254,4 +254,15 @@ export default {
   "toast.deleted": "已删除",
   "toast.probing": "探测中…",
   "toast.imported": "配置已导入",
+  "dash.cache": "语义缓存",
+  "dash.cache.hitRate": "命中率",
+  "dash.cache.hits": "命中",
+  "dash.cache.saved": "已节省",
+  "dash.cache.disabled": "语义缓存已禁用 — 在设置中启用。",
+  "settings.cache": "语义缓存",
+  "settings.cache.enabled": "启用语义缓存",
+  "settings.cache.threshold": "相似度阈值",
+  "settings.cache.ttl": "条目 TTL",
+  "settings.cache.embed": "嵌入模型",
+  "settings.cache.note": "缓存设置将在重启后生效。",
 };

web/js/views/dashboard.js

@@ -108,6 +108,22 @@ export async function renderDashboard() {
         barList(breakdown, num)
       ),
 
+      // semantic cache
+      stats.cache && stats.cache.enabled
+        ? h(
+            "div",
+            { class: "card" },
+            h("div", { class: "card-head" }, h("h3", {}, t("dash.cache"))),
+            h(
+              "div",
+              { class: "kpis" },
+              kpi(pct(stats.cache.hit_rate), t("dash.cache.hitRate")),
+              kpi(num(stats.cache.hits), t("dash.cache.hits")),
+              kpi(money(stats.cache.saved_usd), t("dash.cache.saved"))
+            )
+          )
+        : null,
+
       // recent
       h(
         "div",

web/js/views/settings.js

@@ -42,6 +42,18 @@ export async function renderSettings() {
   const statsEnabled = check(t("settings.stats.enabled"), s.stats?.enabled);
   const statsFile = h("input", { value: s.stats?.file || "" });
   const statsRet = h("input", { value: s.stats?.retention || "7d" });
+  // cache
+  const modelsData = await api.listModels();
+  const embedModels = (modelsData.models || []).filter((m) => m.kind === "embedding").map((m) => m.id);
+  const cacheEnabled = check(t("settings.cache.enabled"), s.cache?.enabled);
+  const cacheThresh = h("input", { type: "number", step: "0.01", value: s.cache?.threshold ?? 0.92 });
+  const cacheTtlIn = h("input", { value: s.cache?.ttl || "1h" });
+  const cacheEmbedSel = h(
+    "select",
+    {},
+    h("option", { value: "" }, "auto"),
+    ...embedModels.map((id) => h("option", { value: id, selected: id === s.cache?.embed_model }, id))
+  );
 
   const saveBtn = h("button", { class: "btn primary" }, t("common.save"));
   saveBtn.addEventListener("click", async () => {
@@ -71,11 +83,19 @@ export async function renderSettings() {
         retention: statsRet.value.trim() || "7d",
         ring_size: s.stats?.ring_size ?? 500,
       },
+      cache: {
+        enabled: cacheEnabled.cb.checked,
+        threshold: parseFloat(cacheThresh.value) || 0.92,
+        ttl: cacheTtlIn.value.trim() || "1h",
+        max_entries: s.cache?.max_entries ?? 1000,
+        embed_model: cacheEmbedSel.value || null,
+      },
     };
     // serde: drop null optionals
     if (!patch.router.api_key_env) delete patch.router.api_key_env;
     if (!patch.router.taxonomy_id) delete patch.router.taxonomy_id;
     if (!patch.telemetry.otlp_endpoint_env) delete patch.telemetry.otlp_endpoint_env;
+    if (!patch.cache.embed_model) delete patch.cache.embed_model;
     try {
       const r = await api.putSettings(patch);
       toast(r.needs_restart ? t("settings.needsRestart") : t("toast.saved"), r.needs_restart ? "warn" : "good");
@@ -170,6 +190,15 @@ export async function renderSettings() {
         statsEnabled.node,
         field(t("settings.stats.file"), statsFile),
         field(t("settings.stats.retention"), statsRet)
+      ),
+      h(
+        "div",
+        { class: "card" },
+        h("div", { class: "card-head" }, h("h3", {}, t("settings.cache"))),
+        cacheEnabled.node,
+        h("div", { class: "row" }, field(t("settings.cache.threshold"), cacheThresh), field(t("settings.cache.ttl"), cacheTtlIn)),
+        field(t("settings.cache.embed"), cacheEmbedSel),
+        h("div", { class: "hint" }, t("settings.cache.note"))
       )
     ),
     h(