diff --git a/src/search/embeddings.ts b/src/search/embeddings.ts
index daa2f03..4ca2139 100644
--- a/src/search/embeddings.ts
+++ b/src/search/embeddings.ts
@@ -17,6 +17,7 @@ export async function embed(
       body: JSON.stringify({
         model: provider.model,
         input: batch,
+        ...(provider.dimensions ? { dimensions: provider.dimensions } : {}),
       }),
     });
 
diff --git a/src/search/provider.ts b/src/search/provider.ts
index 16ee2b6..4ff382e 100644
--- a/src/search/provider.ts
+++ b/src/search/provider.ts
@@ -28,7 +28,44 @@ const vercel: EmbeddingProvider = {
   }),
 };
 
+const gemini: EmbeddingProvider = {
+  name: 'gemini',
+  apiBase: 'https://generativelanguage.googleapis.com/v1beta/openai',
+  model: 'gemini-embedding-001',
+  dimensions: 1536,
+  headers: (key) => ({
+    Authorization: `Bearer ${key}`,
+    'Content-Type': 'application/json',
+  }),
+};
+
+/**
+ * Build a custom provider from LAT_LLM_ENDPOINT + optional LAT_LLM_MODEL.
+ * The endpoint must be OpenAI-compatible (POST /embeddings).
+ */
+export function customProvider(
+  endpoint: string,
+  model?: string,
+): EmbeddingProvider {
+  return {
+    name: 'custom',
+    apiBase: endpoint.replace(/\/+$/, ''),
+    model: model || 'text-embedding-3-small',
+    dimensions: 1536,
+    headers: (key) => ({
+      Authorization: `Bearer ${key}`,
+      'Content-Type': 'application/json',
+    }),
+  };
+}
+
 export function detectProvider(key: string): EmbeddingProvider {
+  // Custom endpoint takes highest priority
+  const endpoint = process.env.LAT_LLM_ENDPOINT;
+  if (endpoint) {
+    return customProvider(endpoint, process.env.LAT_LLM_MODEL);
+  }
+
   if (key.startsWith('REPLAY_LAT_LLM_KEY::')) {
     const replayUrl = key.slice('REPLAY_LAT_LLM_KEY::'.length);
     return {
@@ -44,9 +81,11 @@ export function detectProvider(key: string): EmbeddingProvider {
       "Anthropic doesn't offer an embedding model. Set LAT_LLM_KEY to an OpenAI (sk-...) or Vercel AI Gateway (vck_...) key.",
     );
   }
+  if (key.startsWith('AIza')) return gemini;
   if (key.startsWith('vck_')) return vercel;
   if (key.startsWith('sk-')) return openai;
   throw new Error(
-    `Unrecognized LAT_LLM_KEY prefix. Supported: OpenAI (sk-...), Vercel AI Gateway (vck_...).`,
+    `Unrecognized LAT_LLM_KEY prefix. Supported: OpenAI (sk-...), Vercel AI Gateway (vck_...), Gemini (AIza...). ` +
+      `Or set LAT_LLM_ENDPOINT for any OpenAI-compatible server.`,
   );
 }
diff --git a/tests/search.test.ts b/tests/search.test.ts
index bc284dd..0b99b2c 100644
--- a/tests/search.test.ts
+++ b/tests/search.test.ts
@@ -4,6 +4,7 @@ import { join } from 'node:path';
 import { tmpdir } from 'node:os';
 import {
   detectProvider,
+  customProvider,
   type EmbeddingProvider,
 } from '../src/search/provider.js';
 import { openDb, ensureSchema, closeDb } from '../src/search/db.js';
@@ -34,6 +35,55 @@ describe('detectProvider', () => {
   it('rejects unknown key', () => {
     expect(() => detectProvider('xyz_abc123')).toThrow(/Unrecognized/);
   });
+
+  it('detects Gemini key', () => {
+    const p = detectProvider('AIzaSyExampleKey123');
+    expect(p.name).toBe('gemini');
+    expect(p.apiBase).toContain('generativelanguage.googleapis.com');
+  });
+
+  it('uses LAT_LLM_ENDPOINT when set', () => {
+    const prev = process.env.LAT_LLM_ENDPOINT;
+    const prevModel = process.env.LAT_LLM_MODEL;
+    try {
+      process.env.LAT_LLM_ENDPOINT = 'http://localhost:11434/v1';
+      process.env.LAT_LLM_MODEL = 'nomic-embed-text';
+      const p = detectProvider('sk-abc123'); // key prefix ignored when endpoint set
+      expect(p.name).toBe('custom');
+      expect(p.apiBase).toBe('http://localhost:11434/v1');
+      expect(p.model).toBe('nomic-embed-text');
+    } finally {
+      if (prev === undefined) delete process.env.LAT_LLM_ENDPOINT;
+      else process.env.LAT_LLM_ENDPOINT = prev;
+      if (prevModel === undefined) delete process.env.LAT_LLM_MODEL;
+      else process.env.LAT_LLM_MODEL = prevModel;
+    }
+  });
+
+  it('LAT_LLM_ENDPOINT strips trailing slashes', () => {
+    const prev = process.env.LAT_LLM_ENDPOINT;
+    try {
+      process.env.LAT_LLM_ENDPOINT = 'http://localhost:8080/v1/';
+      const p = detectProvider('sk-abc123');
+      expect(p.apiBase).toBe('http://localhost:8080/v1');
+    } finally {
+      if (prev === undefined) delete process.env.LAT_LLM_ENDPOINT;
+      else process.env.LAT_LLM_ENDPOINT = prev;
+    }
+  });
+});
+
+describe('customProvider', () => {
+  it('builds provider with custom model', () => {
+    const p = customProvider('http://localhost:11434/v1', 'nomic-embed-text');
+    expect(p.name).toBe('custom');
+    expect(p.model).toBe('nomic-embed-text');
+  });
+
+  it('defaults model when not specified', () => {
+    const p = customProvider('http://localhost:11434/v1');
+    expect(p.model).toBe('text-embedding-3-small');
+  });
 });
 
 // --- RAG functional tests ---