[FEAT] Add support for Voyage AI embedder (#1401)

* add support for voyageai embedder

* remove unneeded import

* linting

* Add ENV examples
Update how chunks are processed for Voyage
use correct langchain import
Add data handling

---------

Co-authored-by: Timothy Carambat <rambat1010@gmail.com>

docker/.env.example

@@ -124,6 +124,10 @@ GID='1000'
 # COHERE_API_KEY=
 # EMBEDDING_MODEL_PREF='embed-english-v3.0'
 
+# EMBEDDING_ENGINE='voyageai'
+# VOYAGEAI_API_KEY=
+# EMBEDDING_MODEL_PREF='voyage-large-2-instruct'
+
 ###########################################
 ######## Vector Database Selection ########
 ###########################################

frontend/src/components/EmbeddingSelection/VoyageAiOptions/index.jsx

@@ -0,0 +1,50 @@
+export default function VoyageAiOptions({ settings }) {
+  return (
+    <div className="w-full flex flex-col gap-y-4">
+      <div className="w-full flex items-center gap-4">
+        <div className="flex flex-col w-60">
+          <label className="text-white text-sm font-semibold block mb-4">
+            API Key
+          </label>
+          <input
+            type="password"
+            name="VoyageAiApiKey"
+            className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:border-white block w-full p-2.5"
+            placeholder="Voyage AI API Key"
+            defaultValue={settings?.VoyageAiApiKey ? "*".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-4">
+            Model Preference
+          </label>
+          <select
+            name="EmbeddingModelPref"
+            required={true}
+            defaultValue={settings?.EmbeddingModelPref}
+            className="bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+          >
+            <optgroup label="Available embedding models">
+              {[
+                "voyage-large-2-instruct",
+                "voyage-law-2",
+                "voyage-code-2",
+                "voyage-large-2",
+                "voyage-2",
+              ].map((model) => {
+                return (
+                  <option key={model} value={model}>
+                    {model}
+                  </option>
+                );
+              })}
+            </optgroup>
+          </select>
+        </div>
+      </div>
+    </div>
+  );
+}

frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx

@@ -10,6 +10,8 @@ import LocalAiLogo from "@/media/llmprovider/localai.png";
 import OllamaLogo from "@/media/llmprovider/ollama.png";
 import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
 import CohereLogo from "@/media/llmprovider/cohere.png";
+import VoyageAiLogo from "@/media/embeddingprovider/voyageai.png";
+
 import PreLoader from "@/components/Preloader";
 import ChangeWarningModal from "@/components/ChangeWarning";
 import OpenAiOptions from "@/components/EmbeddingSelection/OpenAiOptions";
@@ -19,6 +21,7 @@ import NativeEmbeddingOptions from "@/components/EmbeddingSelection/NativeEmbedd
 import OllamaEmbeddingOptions from "@/components/EmbeddingSelection/OllamaOptions";
 import LMStudioEmbeddingOptions from "@/components/EmbeddingSelection/LMStudioOptions";
 import CohereEmbeddingOptions from "@/components/EmbeddingSelection/CohereOptions";
+import VoyageAiOptions from "@/components/EmbeddingSelection/VoyageAiOptions";
 
 import EmbedderItem from "@/components/EmbeddingSelection/EmbedderItem";
 import { CaretUpDown, MagnifyingGlass, X } from "@phosphor-icons/react";
@@ -78,6 +81,13 @@ const EMBEDDERS = [
     options: (settings) => <CohereEmbeddingOptions settings={settings} />,
     description: "Run powerful embedding models from Cohere.",
   },
+  {
+    name: "Voyage AI",
+    value: "voyageai",
+    logo: VoyageAiLogo,
+    options: (settings) => <VoyageAiOptions settings={settings} />,
+    description: "Run powerful embedding models from Voyage AI.",
+  },
 ];
 
 export default function GeneralEmbeddingPreference() {

frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx

@@ -28,6 +28,8 @@ import LanceDbLogo from "@/media/vectordbs/lancedb.png";
 import WeaviateLogo from "@/media/vectordbs/weaviate.png";
 import QDrantLogo from "@/media/vectordbs/qdrant.png";
 import MilvusLogo from "@/media/vectordbs/milvus.png";
+import VoyageAiLogo from "@/media/embeddingprovider/voyageai.png";
+
 import React, { useState, useEffect } from "react";
 import paths from "@/utils/paths";
 import { useNavigate } from "react-router-dom";
@@ -292,6 +294,13 @@ export const EMBEDDING_ENGINE_PRIVACY = {
     ],
     logo: CohereLogo,
   },
+  voyageai: {
+    name: "Voyage AI",
+    description: [
+      "Data sent to Voyage AI's servers is shared according to the terms of service of voyageai.com.",
+    ],
+    logo: VoyageAiLogo,
+  },
 };
 
 export default function DataHandling({ setHeader, setForwardBtn, setBackBtn }) {

server/.env.example

@@ -121,6 +121,10 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea
 # COHERE_API_KEY=
 # EMBEDDING_MODEL_PREF='embed-english-v3.0'
 
+# EMBEDDING_ENGINE='voyageai'
+# VOYAGEAI_API_KEY=
+# EMBEDDING_MODEL_PREF='voyage-large-2-instruct'
+
 ###########################################
 ######## Vector Database Selection ########
 ###########################################

server/endpoints/api/workspace/index.js

@@ -498,15 +498,18 @@ function apiWorkspaceEndpoints(app) {
         const { slug = null } = request.params;
         const { docPath, pinStatus = false } = reqBody(request);
         const workspace = await Workspace.get({ slug });
-  
+
         const document = await Document.get({
           workspaceId: workspace.id,
           docpath: docPath,
         });
         if (!document) return response.sendStatus(404).end();
-  
+
         await Document.update(document.id, { pinned: pinStatus });
-        return response.status(200).json({ message: 'Pin status updated successfully' }).end();
+        return response
+          .status(200)
+          .json({ message: "Pin status updated successfully" })
+          .end();
       } catch (error) {
         console.error("Error processing the pin status update:", error);
         return response.status(500).end();

server/models/systemSettings.js

@@ -426,6 +426,9 @@ const SystemSettings = {
       // Cohere API Keys
       CohereApiKey: !!process.env.COHERE_API_KEY,
       CohereModelPref: process.env.COHERE_MODEL_PREF,
+
+      // VoyageAi API Keys
+      VoyageAiApiKey: !!process.env.VOYAGEAI_API_KEY,
     };
   },
 

server/swagger/openapi.json

@@ -1999,7 +1999,8 @@
           }
         }
       }
-    },"/v1/workspace/{slug}/update-pin": {
+    },
+    "/workspace/{slug}/update-pin": {
       "post": {
         "tags": [
           "Workspaces"
@@ -2037,6 +2038,9 @@
               }
             }
           },
+          "403": {
+            "description": "Forbidden"
+          },
           "404": {
             "description": "Document not found"
           },
@@ -2047,20 +2051,12 @@
         "requestBody": {
           "description": "JSON object with the document path and pin status to update.",
           "required": true,
+          "type": "object",
           "content": {
             "application/json": {
-              "schema": {
-                "type": "object",
-                "properties": {
-                  "docPath": {
-                    "type": "string",
-                    "example": "custom-documents/my-pdf.pdf-hash.json"
-                  },
-                  "pinStatus": {
-                    "type": "boolean",
-                    "example": true
-                  }
-                }
+              "example": {
+                "docPath": "custom-documents/my-pdf.pdf-hash.json",
+                "pinStatus": true
               }
             }
           }

server/utils/EmbeddingEngines/voyageAi/index.js

@@ -0,0 +1,45 @@
+class VoyageAiEmbedder {
+  constructor() {
+    if (!process.env.VOYAGEAI_API_KEY)
+      throw new Error("No Voyage AI API key was set.");
+
+    const {
+      VoyageEmbeddings,
+    } = require("@langchain/community/embeddings/voyage");
+    const voyage = new VoyageEmbeddings({
+      apiKey: process.env.VOYAGEAI_API_KEY,
+    });
+
+    this.voyage = voyage;
+    this.model = process.env.EMBEDDING_MODEL_PREF || "voyage-large-2-instruct";
+
+    // Limit of how many strings we can process in a single pass to stay with resource or network limits
+    this.batchSize = 128; // Voyage AI's limit per request is 128 https://docs.voyageai.com/docs/rate-limits#use-larger-batches
+    this.embeddingMaxChunkLength = 4000; // https://docs.voyageai.com/docs/embeddings - assume a token is roughly 4 letters with some padding
+  }
+
+  async embedTextInput(textInput) {
+    const result = await this.voyage.embedDocuments(
+      Array.isArray(textInput) ? textInput : [textInput],
+      { modelName: this.model }
+    );
+    return result || [];
+  }
+
+  async embedChunks(textChunks = []) {
+    try {
+      const embeddings = await this.voyage.embedDocuments(textChunks, {
+        modelName: this.model,
+        batchSize: this.batchSize,
+      });
+      return embeddings;
+    } catch (error) {
+      console.error("Voyage AI Failed to embed:", error);
+      throw error;
+    }
+  }
+}
+
+module.exports = {
+  VoyageAiEmbedder,
+};

server/utils/helpers/index.js

@@ -125,6 +125,9 @@ function getEmbeddingEngineSelection() {
     case "cohere":
       const { CohereEmbedder } = require("../EmbeddingEngines/cohere");
       return new CohereEmbedder();
+    case "voyageai":
+      const { VoyageAiEmbedder } = require("../EmbeddingEngines/voyageAi");
+      return new VoyageAiEmbedder();
     default:
       return new NativeEmbedder();
   }

server/utils/helpers/updateENV.js

@@ -350,6 +350,12 @@ const KEY_MAPPING = {
     checks: [isNotEmpty],
   },
 
+  // VoyageAi Options
+  VoyageAiApiKey: {
+    envKey: "VOYAGEAI_API_KEY",
+    checks: [isNotEmpty],
+  },
+
   // Whisper (transcription) providers
   WhisperProvider: {
     envKey: "WHISPER_PROVIDER",
@@ -545,6 +551,7 @@ function supportedEmbeddingModel(input = "") {
     "ollama",
     "lmstudio",
     "cohere",
+    "voyageai",
   ];
   return supported.includes(input)
     ? null