tawasuyu/brahman

Backend sin modelo real: FNV-1a del texto siembra un LCG que genera el
vector. Mismo texto → mismo vector siempre; textos distintos → vectores
distintos. Dimensión configurable (default 384d, típica de modelos
ligeros).

Desbloquea desarrollar y testear los consumidores de verbo
(fana-semantic, badu, chasqui) sin descargar modelos ONNX ni pegarle a
Cohere. Los backends reales (cohere/bge/fastembed) son swaps de config.

4 tests verdes (determinismo, distinción, dimensión, batch).
cargo check --workspace verde.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

diff --git a/Cargo.lock b/Cargo.lock
index 71d953a..9910d8d 100644
--- a/Cargo.lock
+++ b/Cargo.lock
@@ -13207,6 +13207,15 @@ dependencies = [
  "thiserror 2.0.18",
 ]
 
+[[package]]
+name = "verbo-mock"
+version = "0.1.0"
+dependencies = [
+ "async-trait",
+ "tokio",
+ "verbo-core",
+]
+
 [[package]]
 name = "version_check"
 version = "0.9.5"
diff --git a/Cargo.toml b/Cargo.toml
index 0aa2af7..186a6c9 100644
--- a/Cargo.toml
+++ b/Cargo.toml
@@ -116,6 +116,7 @@ members = [
     # modules/verbo/ — Provider de embeddings model-agnostic
     # ============================================================
     "crates/modules/verbo/verbo-core",
+    "crates/modules/verbo/verbo-mock",
 
     # ============================================================
     # modules/nakui/ — ERP matemático (categórico)
diff --git a/crates/modules/verbo/verbo-mock/Cargo.toml b/crates/modules/verbo/verbo-mock/Cargo.toml
new file mode 100644
index 0000000..d9d0335
--- /dev/null
+++ b/crates/modules/verbo/verbo-mock/Cargo.toml
@@ -0,0 +1,15 @@
+[package]
+name = "verbo-mock"
+version.workspace = true
+edition.workspace = true
+license.workspace = true
+authors.workspace = true
+publish.workspace = true
+description = "verbo — backend de embeddings determinista (sin modelo real). Mismo texto → mismo vector. Para desarrollar y testear consumidores sin descargar modelos."
+
+[dependencies]
+verbo-core = { path = "../verbo-core" }
+async-trait = { workspace = true }
+
+[dev-dependencies]
+tokio = { workspace = true }
diff --git a/crates/modules/verbo/verbo-mock/src/lib.rs b/crates/modules/verbo/verbo-mock/src/lib.rs
new file mode 100644
index 0000000..9754ffc
--- /dev/null
+++ b/crates/modules/verbo/verbo-mock/src/lib.rs
@@ -0,0 +1,113 @@
+//! `verbo-mock` — backend de embeddings determinista.
+//!
+//! No carga ningún modelo: hashea el texto y genera el vector con un LCG
+//! sembrado por ese hash. Mismo texto → mismo vector, siempre. Textos
+//! distintos → vectores distintos. Sirve para desarrollar y testear los
+//! consumidores de `verbo` (fana-semantic, badu, chasqui) sin descargar
+//! modelos ONNX ni pegarle a la API de Cohere.
+
+#![forbid(unsafe_code)]
+
+use async_trait::async_trait;
+use verbo_core::{EmbedError, EmbeddingVector, ModelId, Provider};
+
+/// Proveedor determinista. La dimensión es configurable.
+pub struct MockProvider {
+    model: ModelId,
+}
+
+impl MockProvider {
+    /// Crea un proveedor mock de la dimensión dada.
+    pub fn new(dimension: usize) -> Self {
+        Self {
+            model: ModelId::new(format!("verbo-mock-{dimension}d"), dimension),
+        }
+    }
+}
+
+impl Default for MockProvider {
+    /// Mock de 384d — la dimensión típica de los modelos ligeros (MiniLM).
+    fn default() -> Self {
+        Self::new(384)
+    }
+}
+
+/// FNV-1a de 64 bits sobre los bytes del texto.
+fn fnv1a(text: &str) -> u64 {
+    let mut h: u64 = 0xcbf2_9ce4_8422_2325;
+    for b in text.bytes() {
+        h ^= b as u64;
+        h = h.wrapping_mul(0x100_0000_01b3);
+    }
+    h
+}
+
+/// Genera `dim` valores en `[-1, 1)` con un LCG sembrado por `seed`.
+fn lcg_vector(seed: u64, dim: usize) -> Vec<f32> {
+    let mut state = seed;
+    let mut out = Vec::with_capacity(dim);
+    for _ in 0..dim {
+        state = state
+            .wrapping_mul(6364136223846793005)
+            .wrapping_add(1442695040888963407);
+        // bits altos → f32 en [0,1) → reescalado a [-1,1).
+        let unit = (state >> 40) as f32 / (1u64 << 24) as f32;
+        out.push(unit * 2.0 - 1.0);
+    }
+    out
+}
+
+#[async_trait]
+impl Provider for MockProvider {
+    fn model_id(&self) -> &ModelId {
+        &self.model
+    }
+
+    async fn embed(&self, text: &str) -> Result<EmbeddingVector, EmbedError> {
+        let values = lcg_vector(fnv1a(text), self.model.dimension);
+        EmbeddingVector::new(self.model.clone(), values)
+    }
+}
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[tokio::test]
+    async fn same_text_yields_same_vector() {
+        let p = MockProvider::new(16);
+        let a = p.embed("hola mundo").await.unwrap();
+        let b = p.embed("hola mundo").await.unwrap();
+        assert_eq!(a.values, b.values);
+    }
+
+    #[tokio::test]
+    async fn different_text_yields_different_vector() {
+        let p = MockProvider::new(64);
+        let a = p.embed("alpha").await.unwrap();
+        let b = p.embed("beta").await.unwrap();
+        assert_ne!(a.values, b.values);
+        // Y son comparables (mismo modelo).
+        assert!(a.cosine(&b).is_ok());
+    }
+
+    #[tokio::test]
+    async fn vector_has_configured_dimension() {
+        let p = MockProvider::new(384);
+        let v = p.embed("x").await.unwrap();
+        assert_eq!(v.values.len(), 384);
+        assert_eq!(v.model.dimension, 384);
+    }
+
+    #[tokio::test]
+    async fn batch_matches_individual() {
+        let p = MockProvider::new(32);
+        let batch = p
+            .embed_batch(&["uno".into(), "dos".into()])
+            .await
+            .unwrap();
+        let single = p.embed("uno").await.unwrap();
+        assert_eq!(batch[0].values, single.values);
+        assert_eq!(batch.len(), 2);
+    }
+}