set embedder output dimensions for LocalAI and Gemini (gemini-embedding-001) (#4980)

2026-02-10 08:28:34 -08:00 · 2026-02-10 08:28:34 -08:00 · 1c91d369c3
commit 1c91d369c3
parent 1f93753058
6 changed files with 221 additions and 54 deletions
--- a/frontend/src/components/EmbeddingSelection/GeminiOptions/index.jsx
+++ b/frontend/src/components/EmbeddingSelection/GeminiOptions/index.jsx
@ -1,3 +1,6 @@
+import { Info } from "@phosphor-icons/react";
+import { Tooltip } from "react-tooltip";
+
 const DEFAULT_MODELS = [
  {
    id: "gemini-embedding-001",
@ -7,47 +10,93 @@ const DEFAULT_MODELS = [

 export default function GeminiOptions({ settings }) {
  return (
-    <div className="w-full flex flex-col gap-y-4">
-      <div className="w-full flex items-center gap-[36px] mt-1.5">
-        <div className="flex flex-col w-60">
-          <label className="text-white text-sm font-semibold block mb-3">
-            API Key
+    <div className="w-full flex flex-col gap-y-6">
+      <div className="w-full flex flex-col gap-y-4">
+        <div className="w-full flex items-center gap-[36px] mt-1.5">
+          <div className="flex flex-col w-60">
+            <label className="text-white text-sm font-semibold block mb-3">
+              API Key
+            </label>
+            <input
+              type="password"
+              name="GeminiEmbeddingApiKey"
+              className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
+              placeholder="Gemini API Key"
+              defaultValue={
+                settings?.GeminiEmbeddingApiKey ? "*".repeat(20) : ""
+              }
+              required={true}
+              autoComplete="off"
+              spellCheck={false}
+            />
+          </div>
+          <div className="flex flex-col w-60">
+            <label className="text-white text-sm font-semibold block mb-3">
+              Model Preference
+            </label>
+            <select
+              name="EmbeddingModelPref"
+              required={true}
+              className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+            >
+              <optgroup label="Available embedding models">
+                {DEFAULT_MODELS.map((model) => {
+                  return (
+                    <option
+                      key={model.id}
+                      value={model.id}
+                      selected={settings?.EmbeddingModelPref === model.id}
+                    >
+                      {model.name}
+                    </option>
+                  );
+                })}
+              </optgroup>
+            </select>
+          </div>
+        </div>
+      </div>
+      <div className="flex flex-col w-60">
+        <div
+          data-tooltip-id="embedding-output-dimensions-tooltip"
+          className="flex gap-x-1 items-center mb-3"
+        >
+          <label className="text-white text-sm font-semibold block">
+            Output dimensions
          </label>
-          <input
-            type="password"
-            name="GeminiEmbeddingApiKey"
-            className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
-            placeholder="Gemini API Key"
-            defaultValue={settings?.GeminiEmbeddingApiKey ? "*".repeat(20) : ""}
-            required={true}
-            autoComplete="off"
-            spellCheck={false}
+          <Info
+            size={16}
+            className="text-theme-text-secondary cursor-pointer"
          />
-        </div>
-        <div className="flex flex-col w-60">
-          <label className="text-white text-sm font-semibold block mb-3">
-            Model Preference
-          </label>
-          <select
-            name="EmbeddingModelPref"
-            required={true}
-            className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+          <Tooltip
+            id="embedding-output-dimensions-tooltip"
+            place="top"
+            delayShow={300}
+            className="tooltip !text-xs !opacity-100"
+            style={{
+              maxWidth: "250px",
+              whiteSpace: "normal",
+              wordWrap: "break-word",
+            }}
          >
-            <optgroup label="Available embedding models">
-              {DEFAULT_MODELS.map((model) => {
-                return (
-                  <option
-                    key={model.id}
-                    value={model.id}
-                    selected={settings?.EmbeddingModelPref === model.id}
-                  >
-                    {model.name}
-                  </option>
-                );
-              })}
-            </optgroup>
-          </select>
+            The number of dimensions the resulting output embeddings should have
+            if it supports multiple dimensions output.
+            <br />
+            <br /> Leave blank to use the default dimensions for the selected
+            model.
+          </Tooltip>
        </div>
+        <input
+          type="number"
+          name="EmbeddingOutputDimensions"
+          className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
+          placeholder="Assume default dimensions"
+          min={1}
+          onScroll={(e) => e.target.blur()}
+          defaultValue={settings?.EmbeddingOutputDimensions}
+          required={false}
+          autoComplete="off"
+        />
      </div>
    </div>
  );
--- a/frontend/src/components/EmbeddingSelection/LocalAiOptions/index.jsx
+++ b/frontend/src/components/EmbeddingSelection/LocalAiOptions/index.jsx
@ -30,20 +30,70 @@ export default function LocalAiOptions({ settings }) {
          apiKey={apiKey}
          basePath={basePath.value}
        />
+        <div className="flex flex-col w-60">
+          <div className="flex flex-col gap-y-1 mb-2">
+            <div className="flex gap-x-1 items-center">
+              <label className="text-white text-sm font-semibold block">
+                Local AI API Key
+              </label>
+              <Info
+                size={16}
+                data-tooltip-id="localai-api-key-tooltip"
+                className="text-theme-text-secondary cursor-pointer"
+              />
+              <Tooltip
+                id="localai-api-key-tooltip"
+                place="top"
+                delayShow={300}
+                className="tooltip !text-xs !opacity-100"
+                style={{
+                  maxWidth: "250px",
+                  whiteSpace: "normal",
+                  wordWrap: "break-word",
+                }}
+              >
+                The API key for the LocalAI server (if applicable).
+              </Tooltip>
+            </div>
+          </div>
+          <input
+            type="password"
+            name="LocalAiApiKey"
+            className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
+            placeholder="sk-mysecretkey"
+            defaultValue={settings?.LocalAiApiKey ? "*".repeat(20) : ""}
+            autoComplete="off"
+            spellCheck={false}
+            onChange={(e) => setApiKeyValue(e.target.value)}
+            onBlur={() => setApiKey(apiKeyValue)}
+          />
+        </div>
+      </div>
+      <div className="w-full flex items-center gap-[36px] mt-1.5">
        <div className="flex flex-col w-60">
          <div
            data-tooltip-place="top"
            data-tooltip-id="max-embedding-chunk-length-tooltip"
            className="flex gap-x-1 items-center mb-3"
          >
+            <label className="text-white text-sm font-semibold block">
+              Max embedding chunk length
+            </label>
            <Info
              size={16}
              className="text-theme-text-secondary cursor-pointer"
            />
-            <label className="text-white text-sm font-semibold block">
-              Max embedding chunk length
-            </label>
-            <Tooltip id="max-embedding-chunk-length-tooltip">
+            <Tooltip
+              id="max-embedding-chunk-length-tooltip"
+              place="top"
+              delayShow={300}
+              className="tooltip !text-xs !opacity-100"
+              style={{
+                maxWidth: "250px",
+                whiteSpace: "normal",
+                wordWrap: "break-word",
+              }}
+            >
              Maximum length of text chunks, in characters, for embedding.
            </Tooltip>
          </div>
@ -59,23 +109,47 @@ export default function LocalAiOptions({ settings }) {
            autoComplete="off"
          />
        </div>
+
        <div className="flex flex-col w-60">
-          <div className="flex flex-col gap-y-1 mb-2">
-            <label className="text-white text-sm font-semibold flex items-center gap-x-2">
-              Local AI API Key{" "}
-              <p className="!text-xs !italic !font-thin">optional</p>
+          <div
+            data-tooltip-id="embedding-output-dimensions-tooltip"
+            className="flex gap-x-1 items-center mb-3"
+          >
+            <label className="text-white text-sm font-semibold block">
+              Output dimensions
            </label>
+            <Info
+              size={16}
+              className="text-theme-text-secondary cursor-pointer"
+            />
+            <Tooltip
+              id="embedding-output-dimensions-tooltip"
+              place="top"
+              delayShow={300}
+              className="tooltip !text-xs !opacity-100"
+              style={{
+                maxWidth: "250px",
+                whiteSpace: "normal",
+                wordWrap: "break-word",
+              }}
+            >
+              The number of dimensions the resulting output embeddings should
+              have if it supports multiple dimensions output.
+              <br />
+              <br /> Leave blank to use the default dimensions for the selected
+              model.
+            </Tooltip>
          </div>
          <input
-            type="password"
-            name="LocalAiApiKey"
+            type="number"
+            name="EmbeddingOutputDimensions"
            className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
-            placeholder="sk-mysecretkey"
-            defaultValue={settings?.LocalAiApiKey ? "*".repeat(20) : ""}
+            placeholder="Assume default dimensions"
+            min={1}
+            onScroll={(e) => e.target.blur()}
+            defaultValue={settings?.EmbeddingOutputDimensions}
+            required={false}
            autoComplete="off"
-            spellCheck={false}
-            onChange={(e) => setApiKeyValue(e.target.value)}
-            onBlur={() => setApiKey(apiKeyValue)}
          />
        </div>
      </div>
--- a/server/models/systemSettings.js
+++ b/server/models/systemSettings.js
@ -233,6 +233,8 @@ const SystemSettings = {
        embeddingEngine === "native"
          ? NativeEmbedder._getEmbeddingModel()
          : process.env.EMBEDDING_MODEL_PREF,
+      EmbeddingOutputDimensions:
+        process.env.EMBEDDING_OUTPUT_DIMENSIONS || null,
      EmbeddingModelMaxChunkLength:
        process.env.EMBEDDING_MODEL_MAX_CHUNK_LENGTH,
      OllamaEmbeddingBatchSize: process.env.OLLAMA_EMBEDDING_BATCH_SIZE || 1,
--- a/server/utils/EmbeddingEngines/gemini/index.js
+++ b/server/utils/EmbeddingEngines/gemini/index.js
@ -23,7 +23,10 @@ class GeminiEmbedder {
    // https://ai.google.dev/gemini-api/docs/models/gemini#text-embedding-and-embedding
    this.embeddingMaxChunkLength = MODEL_MAP[this.model] || 2_048;
    this.log(
-      `Initialized with ${this.model} - Max Size: ${this.embeddingMaxChunkLength}`
+      `Initialized with ${this.model} - Max Size: ${this.embeddingMaxChunkLength}` +
+        (this.outputDimensions
+          ? ` - Output Dimensions: ${this.outputDimensions}`
+          : " Assuming default output dimensions")
    );
  }

@ -31,6 +34,16 @@ class GeminiEmbedder {
    console.log(`\x1b[36m[${this.className}]\x1b[0m ${text}`, ...args);
  }

+  get outputDimensions() {
+    if (
+      process.env.EMBEDDING_OUTPUT_DIMENSIONS &&
+      !isNaN(process.env.EMBEDDING_OUTPUT_DIMENSIONS) &&
+      process.env.EMBEDDING_OUTPUT_DIMENSIONS > 0
+    )
+      return parseInt(process.env.EMBEDDING_OUTPUT_DIMENSIONS);
+    return null;
+  }
+
  /**
   * Embeds a single text input
   * @param {string|string[]} textInput - The text to embed
@ -62,6 +75,7 @@ class GeminiEmbedder {
            .create({
              model: this.model,
              input: chunk,
+              dimensions: this.outputDimensions,
            })
            .then((result) => {
              resolve({ data: result?.data, error: null });
--- a/server/utils/EmbeddingEngines/localAi/index.js
+++ b/server/utils/EmbeddingEngines/localAi/index.js
@ -7,7 +7,9 @@ class LocalAiEmbedder {
    if (!process.env.EMBEDDING_MODEL_PREF)
      throw new Error("No embedding model was set.");

+    this.className = "LocalAiEmbedder";
    const { OpenAI: OpenAIApi } = require("openai");
+    this.model = process.env.EMBEDDING_MODEL_PREF;
    this.openai = new OpenAIApi({
      baseURL: process.env.EMBEDDING_BASE_PATH,
      apiKey: process.env.LOCAL_AI_API_KEY ?? null,
@ -16,6 +18,27 @@ class LocalAiEmbedder {
    // Limit of how many strings we can process in a single pass to stay with resource or network limits
    this.maxConcurrentChunks = 50;
    this.embeddingMaxChunkLength = maximumChunkLength();
+
+    this.log(
+      `Initialized with ${this.model} - Max Size: ${this.embeddingMaxChunkLength}` +
+        (this.outputDimensions
+          ? ` - Output Dimensions: ${this.outputDimensions}`
+          : " Assuming default output dimensions")
+    );
+  }
+
+  log(text, ...args) {
+    console.log(`\x1b[36m[${this.className}]\x1b[0m ${text}`, ...args);
+  }
+
+  get outputDimensions() {
+    if (
+      process.env.EMBEDDING_OUTPUT_DIMENSIONS &&
+      !isNaN(process.env.EMBEDDING_OUTPUT_DIMENSIONS) &&
+      process.env.EMBEDDING_OUTPUT_DIMENSIONS > 0
+    )
+      return parseInt(process.env.EMBEDDING_OUTPUT_DIMENSIONS);
+    return null;
  }

  async embedTextInput(textInput) {
@ -32,8 +55,9 @@ class LocalAiEmbedder {
        new Promise((resolve) => {
          this.openai.embeddings
            .create({
-              model: process.env.EMBEDDING_MODEL_PREF,
+              model: this.model,
              input: chunk,
+              dimensions: this.outputDimensions,
            })
            .then((result) => {
              resolve({ data: result?.data, error: null });
--- a/server/utils/helpers/updateENV.js
+++ b/server/utils/helpers/updateENV.js
@ -307,6 +307,10 @@ const KEY_MAPPING = {
    envKey: "EMBEDDING_MODEL_MAX_CHUNK_LENGTH",
    checks: [nonZero],
  },
+  EmbeddingOutputDimensions: {
+    envKey: "EMBEDDING_OUTPUT_DIMENSIONS",
+    checks: [],
+  },
  OllamaEmbeddingBatchSize: {
    envKey: "OLLAMA_EMBEDDING_BATCH_SIZE",
    checks: [nonZero],