diff --git a/docker/.env.example b/docker/.env.example index 5905c578..74ab3ef6 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -35,6 +35,15 @@ CACHE_VECTORS="true" # EMBEDDING_ENGINE='openai' # OPEN_AI_KEY=sk-xxxx +# EMBEDDING_ENGINE='azure' +# AZURE_OPENAI_ENDPOINT= +# AZURE_OPENAI_KEY= +# EMBEDDING_MODEL_PREF='my-embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002 + +# EMBEDDING_ENGINE='localai' +# EMBEDDING_BASE_PATH='https://localhost:8080/v1' +# EMBEDDING_MODEL_PREF='text-embedding-ada-002' + ########################################### ######## Vector Database Selection ######## ########################################### diff --git a/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx b/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx index 7485d0a9..52b818ff 100644 --- a/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx +++ b/frontend/src/components/Modals/MangeWorkspace/Documents/index.jsx @@ -8,7 +8,11 @@ import WorkspaceDirectory from "./WorkspaceDirectory"; const COST_PER_TOKEN = 0.0004; -export default function DocumentSettings({ workspace, fileTypes }) { +export default function DocumentSettings({ + workspace, + fileTypes, + systemSettings, +}) { const [highlightWorkspace, setHighlightWorkspace] = useState(false); const [availableDocs, setAvailableDocs] = useState([]); const [loading, setLoading] = useState(true); @@ -135,8 +139,15 @@ export default function DocumentSettings({ workspace, fileTypes }) { } }); - const dollarAmount = (totalTokenCount / 1000) * COST_PER_TOKEN; - setEmbeddingsCost(dollarAmount); + // Do not do cost estimation unless the embedding engine is OpenAi. + if ( + !systemSettings?.EmbeddingEngine || + systemSettings.EmbeddingEngine === "openai" + ) { + const dollarAmount = (totalTokenCount / 1000) * COST_PER_TOKEN; + setEmbeddingsCost(dollarAmount); + } + setMovedItems([...movedItems, ...newMovedItems]); let newAvailableDocs = JSON.parse(JSON.stringify(availableDocs)); diff --git a/frontend/src/components/Modals/MangeWorkspace/index.jsx b/frontend/src/components/Modals/MangeWorkspace/index.jsx index d38cc353..946e96d2 100644 --- a/frontend/src/components/Modals/MangeWorkspace/index.jsx +++ b/frontend/src/components/Modals/MangeWorkspace/index.jsx @@ -15,11 +15,14 @@ const ManageWorkspace = ({ hideModal = noop, providedSlug = null }) => { const [selectedTab, setSelectedTab] = useState("documents"); const [workspace, setWorkspace] = useState(null); const [fileTypes, setFileTypes] = useState(null); + const [settings, setSettings] = useState({}); useEffect(() => { async function checkSupportedFiletypes() { const acceptedTypes = await System.acceptedDocumentTypes(); + const _settings = await System.keys(); setFileTypes(acceptedTypes ?? {}); + setSettings(_settings ?? {}); } checkSupportedFiletypes(); }, []); @@ -104,7 +107,11 @@ const ManageWorkspace = ({ hideModal = noop, providedSlug = null }) => { Loading...}>
- +
diff --git a/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx b/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx index dd5b1433..c81b0e52 100644 --- a/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx +++ b/frontend/src/pages/GeneralSettings/EmbeddingPreference/index.jsx @@ -7,6 +7,7 @@ import System from "../../../models/system"; import showToast from "../../../utils/toast"; import OpenAiLogo from "../../../media/llmprovider/openai.png"; import AzureOpenAiLogo from "../../../media/llmprovider/azure.png"; +import LocalAiLogo from "../../../media/llmprovider/localai.png"; import PreLoader from "../../../components/Preloader"; import LLMProviderOption from "../../../components/LLMSelection/LLMProviderOption"; @@ -16,6 +17,8 @@ export default function GeneralEmbeddingPreference() { const [embeddingChoice, setEmbeddingChoice] = useState("openai"); const [settings, setSettings] = useState(null); const [loading, setLoading] = useState(true); + const [basePathValue, setBasePathValue] = useState(""); + const [basePath, setBasePath] = useState(""); const handleSubmit = async (e) => { e.preventDefault(); @@ -38,11 +41,17 @@ export default function GeneralEmbeddingPreference() { setHasChanges(true); }; + function updateBasePath() { + setBasePath(basePathValue); + } + useEffect(() => { async function fetchKeys() { const _settings = await System.keys(); setSettings(_settings); setEmbeddingChoice(_settings?.EmbeddingEngine || "openai"); + setBasePath(_settings?.EmbeddingBasePath || ""); + setBasePathValue(_settings?.EmbeddingBasePath || ""); setLoading(false); } fetchKeys(); @@ -136,6 +145,15 @@ export default function GeneralEmbeddingPreference() { image={AzureOpenAiLogo} onClick={updateChoice} /> +
{embeddingChoice === "openai" && ( @@ -215,6 +233,32 @@ export default function GeneralEmbeddingPreference() {
)} + + {embeddingChoice === "localai" && ( + <> +
+ + setBasePathValue(e.target.value)} + onBlur={updateBasePath} + required={true} + autoComplete="off" + spellCheck={false} + /> +
+ + + )} )} @@ -225,3 +269,73 @@ export default function GeneralEmbeddingPreference() { ); } + +function LocalAIModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("localai", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} diff --git a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/EmbeddingSelection/index.jsx b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/EmbeddingSelection/index.jsx index 4edde9be..109e4115 100644 --- a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/EmbeddingSelection/index.jsx +++ b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/EmbeddingSelection/index.jsx @@ -1,6 +1,7 @@ import React, { memo, useEffect, useState } from "react"; import OpenAiLogo from "../../../../../media/llmprovider/openai.png"; import AzureOpenAiLogo from "../../../../../media/llmprovider/azure.png"; +import LocalAiLogo from "../../../../../media/llmprovider/localai.png"; import System from "../../../../../models/system"; import PreLoader from "../../../../../components/Preloader"; import LLMProviderOption from "../../../../../components/LLMSelection/LLMProviderOption"; @@ -9,16 +10,23 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) { const [embeddingChoice, setEmbeddingChoice] = useState("openai"); const [settings, setSettings] = useState(null); const [loading, setLoading] = useState(true); + const [basePathValue, setBasePathValue] = useState(""); + const [basePath, setBasePath] = useState(""); const updateChoice = (selection) => { setEmbeddingChoice(selection); }; + function updateBasePath() { + setBasePath(basePathValue); + } + useEffect(() => { async function fetchKeys() { const _settings = await System.keys(); setSettings(_settings); setEmbeddingChoice(_settings?.EmbeddingEngine || "openai"); + setBasePathValue(_settings?.EmbeddingBasePath || ""); setLoading(false); } fetchKeys(); @@ -77,6 +85,15 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) { image={AzureOpenAiLogo} onClick={updateChoice} /> +
{embeddingChoice === "openai" && ( @@ -152,6 +169,32 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) {
)} + + {embeddingChoice === "localai" && ( + <> +
+ + setBasePathValue(e.target.value)} + onBlur={updateBasePath} + required={true} + autoComplete="off" + spellCheck={false} + /> +
+ + + )}
@@ -174,4 +217,74 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) { ); } +function LocalAIModelSelection({ settings, basePath = null }) { + const [customModels, setCustomModels] = useState([]); + const [loading, setLoading] = useState(true); + + useEffect(() => { + async function findCustomModels() { + if (!basePath || !basePath.includes("/v1")) { + setCustomModels([]); + setLoading(false); + return; + } + setLoading(true); + const { models } = await System.customModels("localai", null, basePath); + setCustomModels(models || []); + setLoading(false); + } + findCustomModels(); + }, [basePath]); + + if (loading || customModels.length == 0) { + return ( +
+ + +
+ ); + } + + return ( +
+ + +
+ ); +} + export default memo(EmbeddingSelection); diff --git a/server/.env.example b/server/.env.example index 127c0052..03d1eb9b 100644 --- a/server/.env.example +++ b/server/.env.example @@ -35,6 +35,15 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea # EMBEDDING_ENGINE='openai' # OPEN_AI_KEY=sk-xxxx +# EMBEDDING_ENGINE='azure' +# AZURE_OPENAI_ENDPOINT= +# AZURE_OPENAI_KEY= +# EMBEDDING_MODEL_PREF='my-embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002 + +# EMBEDDING_ENGINE='localai' +# EMBEDDING_BASE_PATH='https://localhost:8080/v1' +# EMBEDDING_MODEL_PREF='text-embedding-ada-002' + ########################################### ######## Vector Database Selection ######## ########################################### diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js index 92ffea36..b4bedc71 100644 --- a/server/models/systemSettings.js +++ b/server/models/systemSettings.js @@ -25,6 +25,8 @@ const SystemSettings = { MultiUserMode: await this.isMultiUserMode(), VectorDB: vectorDB, EmbeddingEngine: process.env.EMBEDDING_ENGINE, + EmbeddingBasePath: process.env.EMBEDDING_BASE_PATH, + EmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF, ...(vectorDB === "pinecone" ? { PineConeEnvironment: process.env.PINECONE_ENVIRONMENT, diff --git a/server/utils/EmbeddingEngines/localAi/index.js b/server/utils/EmbeddingEngines/localAi/index.js new file mode 100644 index 00000000..d4b37d39 --- /dev/null +++ b/server/utils/EmbeddingEngines/localAi/index.js @@ -0,0 +1,77 @@ +const { toChunks } = require("../../helpers"); + +class LocalAiEmbedder { + constructor() { + const { Configuration, OpenAIApi } = require("openai"); + if (!process.env.EMBEDDING_BASE_PATH) + throw new Error("No embedding base path was set."); + if (!process.env.EMBEDDING_MODEL_PREF) + throw new Error("No embedding model was set."); + const config = new Configuration({ + basePath: process.env.EMBEDDING_BASE_PATH, + }); + this.openai = new OpenAIApi(config); + + // Arbitrary limit to ensure we stay within reasonable POST request size. + this.embeddingChunkLimit = 1_000; + } + + async embedTextInput(textInput) { + const result = await this.embedChunks(textInput); + return result?.[0] || []; + } + + async embedChunks(textChunks = []) { + const embeddingRequests = []; + for (const chunk of toChunks(textChunks, this.embeddingChunkLimit)) { + embeddingRequests.push( + new Promise((resolve) => { + this.openai + .createEmbedding({ + model: process.env.EMBEDDING_MODEL_PREF, + input: chunk, + }) + .then((res) => { + resolve({ data: res.data?.data, error: null }); + }) + .catch((e) => { + resolve({ data: [], error: e?.error }); + }); + }) + ); + } + + const { data = [], error = null } = await Promise.all( + embeddingRequests + ).then((results) => { + // If any errors were returned from LocalAI abort the entire sequence because the embeddings + // will be incomplete. + const errors = results + .filter((res) => !!res.error) + .map((res) => res.error) + .flat(); + if (errors.length > 0) { + return { + data: [], + error: `(${errors.length}) Embedding Errors! ${errors + .map((error) => `[${error.type}]: ${error.message}`) + .join(", ")}`, + }; + } + return { + data: results.map((res) => res?.data || []).flat(), + error: null, + }; + }); + + if (!!error) throw new Error(`LocalAI Failed to embed: ${error}`); + return data.length > 0 && + data.every((embd) => embd.hasOwnProperty("embedding")) + ? data.map((embd) => embd.embedding) + : null; + } +} + +module.exports = { + LocalAiEmbedder, +}; diff --git a/server/utils/helpers/index.js b/server/utils/helpers/index.js index bbc69a0e..c7c61822 100644 --- a/server/utils/helpers/index.js +++ b/server/utils/helpers/index.js @@ -59,6 +59,9 @@ function getEmbeddingEngineSelection() { AzureOpenAiEmbedder, } = require("../EmbeddingEngines/azureOpenAi"); return new AzureOpenAiEmbedder(); + case "localai": + const { LocalAiEmbedder } = require("../EmbeddingEngines/localAi"); + return new LocalAiEmbedder(); default: return null; } diff --git a/server/utils/helpers/updateENV.js b/server/utils/helpers/updateENV.js index 8290f7eb..b7ecffa1 100644 --- a/server/utils/helpers/updateENV.js +++ b/server/utils/helpers/updateENV.js @@ -72,6 +72,14 @@ const KEY_MAPPING = { envKey: "EMBEDDING_ENGINE", checks: [supportedEmbeddingModel], }, + EmbeddingBasePath: { + envKey: "EMBEDDING_BASE_PATH", + checks: [isNotEmpty, validLLMExternalBasePath], + }, + EmbeddingModelPref: { + envKey: "EMBEDDING_MODEL_PREF", + checks: [isNotEmpty], + }, // Vector Database Selection Settings VectorDB: { @@ -191,7 +199,7 @@ function validAnthropicModel(input = "") { } function supportedEmbeddingModel(input = "") { - const supported = ["openai", "azure"]; + const supported = ["openai", "azure", "localai"]; return supported.includes(input) ? null : `Invalid Embedding model type. Must be one of ${supported.join(", ")}.`;