fix(ollama): honor memory embedding output dimensionality (#94811)

extensions/ollama/src/embedding-provider.test.ts

@@ -147,6 +147,25 @@ describe("ollama embedding provider", () => {
     expect(vector[1]).toBeCloseTo(0.8, 5);
   });
 
+  it("applies outputDimensionality before normalizing vectors", async () => {
+    mockEmbeddingFetch([3, 4, 12]);
+
+    const { provider } = await createOllamaEmbeddingProvider({
+      config: {} as OpenClawConfig,
+      provider: "ollama",
+      model: "unknown-embedder",
+      fallback: "none",
+      remote: { baseUrl: "http://127.0.0.1:11434" },
+      outputDimensionality: 2,
+    });
+
+    const vector = await provider.embedQuery("hi");
+
+    expect(vector).toHaveLength(2);
+    expect(vector[0]).toBeCloseTo(0.6, 5);
+    expect(vector[1]).toBeCloseTo(0.8, 5);
+  });
+
   it("marks the configured Ollama origin for managed-proxy direct routing", async () => {
     const fetchMock = mockEmbeddingFetch([1, 0]);
 
@@ -664,6 +683,23 @@ describe("ollama embedding provider", () => {
     expect(headers?.Authorization).toBeUndefined();
   });
 
+  it("includes outputDimensionality in the memory embedding cache identity", async () => {
+    const result = await ollamaMemoryEmbeddingProviderAdapter.create({
+      config: {} as OpenClawConfig,
+      provider: "ollama",
+      model: "nomic-embed-text",
+      fallback: "none",
+      remote: { baseUrl: "http://127.0.0.1:11434" },
+      outputDimensionality: 2,
+    });
+
+    expect(result.runtime?.cacheKeyData).toMatchObject({
+      provider: "ollama",
+      model: "nomic-embed-text",
+      outputDimensionality: 2,
+    });
+  });
+
   it("marks inline memory batches as local-server timeout work", async () => {
     const result = await ollamaMemoryEmbeddingProviderAdapter.create({
       config: {} as OpenClawConfig,

extensions/ollama/src/embedding-provider.ts

@@ -52,6 +52,7 @@ export type OllamaEmbeddingClient = {
   headers: Record<string, string>;
   ssrfPolicy?: SsrFPolicy;
   model: string;
+  outputDimensionality?: number;
   embedBatch: (texts: string[]) => Promise<number[][]>;
 };
 
@@ -76,8 +77,10 @@ const QUERY_INSTRUCTION_TEMPLATES = [
   },
 ] as const;
 
-function sanitizeAndNormalizeEmbedding(vec: unknown[]): number[] {
-  const sanitized = vec.map((value) => {
+function sanitizeAndNormalizeEmbedding(vec: unknown[], outputDimensionality?: number): number[] {
+  const selected =
+    typeof outputDimensionality === "number" ? vec.slice(0, outputDimensionality) : vec;
+  const sanitized = selected.map((value) => {
     if (typeof value !== "number") {
       throw new Error("Ollama embed response contains a non-number embedding value");
     }
@@ -320,6 +323,7 @@ function resolveOllamaEmbeddingClient(
     headers,
     ssrfPolicy: ssrfPolicyFromHttpBaseUrlAllowedOrigin(baseUrl),
     model,
+    outputDimensionality: options.outputDimensionality,
   };
 }
 
@@ -364,7 +368,7 @@ export async function createOllamaEmbeddingProvider(
       if (!Array.isArray(embedding)) {
         throw new Error("Ollama embed response contains a non-array embedding");
       }
-      return sanitizeAndNormalizeEmbedding(embedding);
+      return sanitizeAndNormalizeEmbedding(embedding, client.outputDimensionality);
     });
   };
 

extensions/ollama/src/memory-embedding-adapter.ts

@@ -24,6 +24,7 @@ export const ollamaMemoryEmbeddingProviderAdapter: MemoryEmbeddingProviderAdapte
         cacheKeyData: {
           provider: "ollama",
           model: client.model,
+          outputDimensionality: client.outputDimensionality,
         },
       },
     };