diff --git a/docker/.env.example b/docker/.env.example index 1bd2b708..5905c578 100644 --- a/docker/.env.example +++ b/docker/.env.example @@ -23,6 +23,11 @@ CACHE_VECTORS="true" # LMSTUDIO_BASE_PATH='http://your-server:1234/v1' # LMSTUDIO_MODEL_TOKEN_LIMIT=4096 +# LLM_PROVIDER='localai' +# LOCAL_AI_BASE_PATH='http://host.docker.internal:8080/v1' +# LOCAL_AI_MODEL_PREF='luna-ai-llama2' +# LOCAL_AI_MODEL_TOKEN_LIMIT=4096 + ########################################### ######## Embedding API SElECTION ########## ########################################### diff --git a/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx b/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx new file mode 100644 index 00000000..a09a47d7 --- /dev/null +++ b/frontend/src/components/LLMSelection/LocalAiOptions/index.jsx @@ -0,0 +1,140 @@ +import { useEffect, useState } from "react"; +import { Info } from "@phosphor-icons/react"; +import paths from "../../../utils/paths"; +import System from "../../../models/system"; + +export default function LocalAiOptions({ settings, showAlert = false }) { + const [basePathValue, setBasePathValue] = useState(settings?.LocalAiBasePath); + const [basePath, setBasePath] = useState(settings?.LocalAiBasePath); + function updateBasePath() { + setBasePath(basePathValue); + } + + return ( +
+ {showAlert && ( +
+
+ +

+ LocalAI as your LLM requires you to set an embedding service to + use. +

+
+ + Manage embedding → + +
+ )} +
+
+ + setBasePathValue(e.target.value)} + onBlur={updateBasePath} + /> +
+ +
+ + e.target.blur()} + defaultValue={settings?.LocalAiTokenLimit} + required={true} + autoComplete="off" + /> +
+
+
+ ); +} + +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/media/llmprovider/localai.png b/frontend/src/media/llmprovider/localai.png new file mode 100644 index 00000000..0d23596d Binary files /dev/null and b/frontend/src/media/llmprovider/localai.png differ diff --git a/frontend/src/models/system.js b/frontend/src/models/system.js index 43f7a918..f69636a4 100644 --- a/frontend/src/models/system.js +++ b/frontend/src/models/system.js @@ -319,13 +319,14 @@ const System = { return false; }); }, - customModels: async function (provider, apiKey) { + customModels: async function (provider, apiKey = null, basePath = null) { return fetch(`${API_BASE}/system/custom-models`, { method: "POST", headers: baseHeaders(), body: JSON.stringify({ provider, apiKey, + basePath, }), }) .then((res) => { diff --git a/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx b/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx index ee0540bc..0e83f655 100644 --- a/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx +++ b/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx @@ -9,12 +9,14 @@ import OpenAiLogo from "../../../media/llmprovider/openai.png"; import AzureOpenAiLogo from "../../../media/llmprovider/azure.png"; import AnthropicLogo from "../../../media/llmprovider/anthropic.png"; import LMStudioLogo from "../../../media/llmprovider/lmstudio.png"; +import LocalAiLogo from "../../../media/llmprovider/localai.png"; import PreLoader from "../../../components/Preloader"; import LLMProviderOption from "../../../components/LLMSelection/LLMProviderOption"; import OpenAiOptions from "../../../components/LLMSelection/OpenAiOptions"; import AzureAiOptions from "../../../components/LLMSelection/AzureAiOptions"; import AnthropicAiOptions from "../../../components/LLMSelection/AnthropicAiOptions"; import LMStudioOptions from "../../../components/LLMSelection/LMStudioOptions"; +import LocalAiOptions from "../../../components/LLMSelection/LocalAiOptions"; export default function GeneralLLMPreference() { const [saving, setSaving] = useState(false); @@ -141,6 +143,15 @@ export default function GeneralLLMPreference() { image={LMStudioLogo} onClick={updateLLMChoice} /> +
{llmChoice === "openai" && ( @@ -155,6 +166,9 @@ export default function GeneralLLMPreference() { {llmChoice === "lmstudio" && ( )} + {llmChoice === "localai" && ( + + )}
diff --git a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/DataHandling/index.jsx b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/DataHandling/index.jsx index 9e670552..2f133ff5 100644 --- a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/DataHandling/index.jsx +++ b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/DataHandling/index.jsx @@ -4,6 +4,7 @@ import OpenAiLogo from "../../../../../media/llmprovider/openai.png"; import AzureOpenAiLogo from "../../../../../media/llmprovider/azure.png"; import AnthropicLogo from "../../../../../media/llmprovider/anthropic.png"; import LMStudioLogo from "../../../../../media/llmprovider/lmstudio.png"; +import LocalAiLogo from "../../../../../media/llmprovider/localai.png"; import ChromaLogo from "../../../../../media/vectordbs/chroma.png"; import PineconeLogo from "../../../../../media/vectordbs/pinecone.png"; import LanceDbLogo from "../../../../../media/vectordbs/lancedb.png"; @@ -43,6 +44,13 @@ const LLM_SELECTION_PRIVACY = { ], logo: LMStudioLogo, }, + localai: { + name: "LocalAI", + description: [ + "Your model and chats are only accessible on the server running LocalAI", + ], + logo: LocalAiLogo, + }, }; const VECTOR_DB_PRIVACY = { diff --git a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/LLMSelection/index.jsx b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/LLMSelection/index.jsx index 429a0a66..e3582309 100644 --- a/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/LLMSelection/index.jsx +++ b/frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/LLMSelection/index.jsx @@ -3,6 +3,7 @@ import OpenAiLogo from "../../../../../media/llmprovider/openai.png"; import AzureOpenAiLogo from "../../../../../media/llmprovider/azure.png"; import AnthropicLogo from "../../../../../media/llmprovider/anthropic.png"; import LMStudioLogo from "../../../../../media/llmprovider/lmstudio.png"; +import LocalAiLogo from "../../../../../media/llmprovider/localai.png"; import System from "../../../../../models/system"; import PreLoader from "../../../../../components/Preloader"; import LLMProviderOption from "../../../../../components/LLMSelection/LLMProviderOption"; @@ -10,6 +11,7 @@ import OpenAiOptions from "../../../../../components/LLMSelection/OpenAiOptions" import AzureAiOptions from "../../../../../components/LLMSelection/AzureAiOptions"; import AnthropicAiOptions from "../../../../../components/LLMSelection/AnthropicAiOptions"; import LMStudioOptions from "../../../../../components/LLMSelection/LMStudioOptions"; +import LocalAiOptions from "../../../../../components/LLMSelection/LocalAiOptions"; function LLMSelection({ nextStep, prevStep, currentStep }) { const [llmChoice, setLLMChoice] = useState("openai"); @@ -47,8 +49,8 @@ function LLMSelection({ nextStep, prevStep, currentStep }) { switch (data.LLMProvider) { case "anthropic": - return nextStep("embedding_preferences"); case "lmstudio": + case "localai": return nextStep("embedding_preferences"); default: return nextStep("vector_database"); @@ -107,6 +109,15 @@ function LLMSelection({ nextStep, prevStep, currentStep }) { image={LMStudioLogo} onClick={updateLLMChoice} /> +
{llmChoice === "openai" && } @@ -117,6 +128,7 @@ function LLMSelection({ nextStep, prevStep, currentStep }) { {llmChoice === "lmstudio" && ( )} + {llmChoice === "localai" && }
diff --git a/server/.env.example b/server/.env.example index 327aa6ee..127c0052 100644 --- a/server/.env.example +++ b/server/.env.example @@ -23,6 +23,11 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea # LMSTUDIO_BASE_PATH='http://your-server:1234/v1' # LMSTUDIO_MODEL_TOKEN_LIMIT=4096 +# LLM_PROVIDER='localai' +# LOCAL_AI_BASE_PATH='http://localhost:8080/v1' +# LOCAL_AI_MODEL_PREF='luna-ai-llama2' +# LOCAL_AI_MODEL_TOKEN_LIMIT=4096 + ########################################### ######## Embedding API SElECTION ########## ########################################### diff --git a/server/endpoints/system.js b/server/endpoints/system.js index f4440353..fd07d03c 100644 --- a/server/endpoints/system.js +++ b/server/endpoints/system.js @@ -615,8 +615,12 @@ function systemEndpoints(app) { [validatedRequest], async (request, response) => { try { - const { provider, apiKey } = reqBody(request); - const { models, error } = await getCustomModels(provider, apiKey); + const { provider, apiKey = null, basePath = null } = reqBody(request); + const { models, error } = await getCustomModels( + provider, + apiKey, + basePath + ); return response.status(200).json({ models, error, diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js index b28c5e86..92ffea36 100644 --- a/server/models/systemSettings.js +++ b/server/models/systemSettings.js @@ -94,6 +94,20 @@ const SystemSettings = { AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF, } : {}), + + ...(llmProvider === "localai" + ? { + LocalAiBasePath: process.env.LOCAL_AI_BASE_PATH, + LocalAiModelPref: process.env.LOCAL_AI_MODEL_PREF, + LocalAiTokenLimit: process.env.LOCAL_AI_MODEL_TOKEN_LIMIT, + + // For embedding credentials when localai is selected. + OpenAiKey: !!process.env.OPEN_AI_KEY, + AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT, + AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY, + AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF, + } + : {}), }; }, diff --git a/server/utils/AiProviders/localAi/index.js b/server/utils/AiProviders/localAi/index.js new file mode 100644 index 00000000..616213a2 --- /dev/null +++ b/server/utils/AiProviders/localAi/index.js @@ -0,0 +1,182 @@ +const { chatPrompt } = require("../../chats"); + +class LocalAiLLM { + constructor(embedder = null) { + if (!process.env.LOCAL_AI_BASE_PATH) + throw new Error("No LocalAI Base Path was set."); + + const { Configuration, OpenAIApi } = require("openai"); + const config = new Configuration({ + basePath: process.env.LOCAL_AI_BASE_PATH, + }); + this.openai = new OpenAIApi(config); + this.model = process.env.LOCAL_AI_MODEL_PREF; + this.limits = { + history: this.promptWindowLimit() * 0.15, + system: this.promptWindowLimit() * 0.15, + user: this.promptWindowLimit() * 0.7, + }; + + if (!embedder) + throw new Error( + "INVALID LOCAL AI SETUP. No embedding engine has been set. Go to instance settings and set up an embedding interface to use LocalAI as your LLM." + ); + this.embedder = embedder; + } + + streamingEnabled() { + return "streamChat" in this && "streamGetChatCompletion" in this; + } + + // Ensure the user set a value for the token limit + // and if undefined - assume 4096 window. + promptWindowLimit() { + const limit = process.env.LOCAL_AI_MODEL_TOKEN_LIMIT || 4096; + if (!limit || isNaN(Number(limit))) + throw new Error("No LocalAi token context limit was set."); + return Number(limit); + } + + async isValidChatCompletionModel(_ = "") { + return true; + } + + constructPrompt({ + systemPrompt = "", + contextTexts = [], + chatHistory = [], + userPrompt = "", + }) { + const prompt = { + role: "system", + content: `${systemPrompt} +Context: + ${contextTexts + .map((text, i) => { + return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`; + }) + .join("")}`, + }; + return [prompt, ...chatHistory, { role: "user", content: userPrompt }]; + } + + async isSafe(_input = "") { + // Not implemented so must be stubbed + return { safe: true, reasons: [] }; + } + + async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) { + if (!(await this.isValidChatCompletionModel(this.model))) + throw new Error( + `LocalAI chat: ${this.model} is not valid for chat completion!` + ); + + const textResponse = await this.openai + .createChatCompletion({ + model: this.model, + temperature: Number(workspace?.openAiTemp ?? 0.7), + n: 1, + messages: await this.compressMessages( + { + systemPrompt: chatPrompt(workspace), + userPrompt: prompt, + chatHistory, + }, + rawHistory + ), + }) + .then((json) => { + const res = json.data; + if (!res.hasOwnProperty("choices")) + throw new Error("LocalAI chat: No results!"); + if (res.choices.length === 0) + throw new Error("LocalAI chat: No results length!"); + return res.choices[0].message.content; + }) + .catch((error) => { + throw new Error( + `LocalAI::createChatCompletion failed with: ${error.message}` + ); + }); + + return textResponse; + } + + async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) { + if (!(await this.isValidChatCompletionModel(this.model))) + throw new Error( + `LocalAI chat: ${this.model} is not valid for chat completion!` + ); + + const streamRequest = await this.openai.createChatCompletion( + { + model: this.model, + stream: true, + temperature: Number(workspace?.openAiTemp ?? 0.7), + n: 1, + messages: await this.compressMessages( + { + systemPrompt: chatPrompt(workspace), + userPrompt: prompt, + chatHistory, + }, + rawHistory + ), + }, + { responseType: "stream" } + ); + return streamRequest; + } + + async getChatCompletion(messages = null, { temperature = 0.7 }) { + if (!(await this.isValidChatCompletionModel(this.model))) + throw new Error( + `LocalAI chat: ${this.model} is not valid for chat completion!` + ); + + const { data } = await this.openai.createChatCompletion({ + model: this.model, + messages, + temperature, + }); + + if (!data.hasOwnProperty("choices")) return null; + return data.choices[0].message.content; + } + + async streamGetChatCompletion(messages = null, { temperature = 0.7 }) { + if (!(await this.isValidChatCompletionModel(this.model))) + throw new Error( + `LocalAi chat: ${this.model} is not valid for chat completion!` + ); + + const streamRequest = await this.openai.createChatCompletion( + { + model: this.model, + stream: true, + messages, + temperature, + }, + { responseType: "stream" } + ); + return streamRequest; + } + + // Simple wrapper for dynamic embedder & normalize interface for all LLM implementations + async embedTextInput(textInput) { + return await this.embedder.embedTextInput(textInput); + } + async embedChunks(textChunks = []) { + return await this.embedder.embedChunks(textChunks); + } + + async compressMessages(promptArgs = {}, rawHistory = []) { + const { messageArrayCompressor } = require("../../helpers/chat"); + const messageArray = this.constructPrompt(promptArgs); + return await messageArrayCompressor(this, messageArray, rawHistory); + } +} + +module.exports = { + LocalAiLLM, +}; diff --git a/server/utils/chats/stream.js b/server/utils/chats/stream.js index b6d011bd..237831e7 100644 --- a/server/utils/chats/stream.js +++ b/server/utils/chats/stream.js @@ -211,12 +211,18 @@ function handleStreamResponses(response, stream, responseProps) { .filter((line) => line.trim() !== ""); for (const line of lines) { + let validJSON = false; const message = chunk + line.replace(/^data: /, ""); // JSON chunk is incomplete and has not ended yet // so we need to stitch it together. You would think JSON // chunks would only come complete - but they don't! - if (message.slice(-3) !== "}]}") { + try { + JSON.parse(message); + validJSON = true; + } catch {} + + if (!validJSON) { chunk += message; continue; } else { @@ -234,12 +240,12 @@ function handleStreamResponses(response, stream, responseProps) { }); resolve(fullText); } else { - let finishReason; + let finishReason = null; let token = ""; try { const json = JSON.parse(message); token = json?.choices?.[0]?.delta?.content; - finishReason = json?.choices?.[0]?.finish_reason; + finishReason = json?.choices?.[0]?.finish_reason || null; } catch { continue; } diff --git a/server/utils/helpers/customModels.js b/server/utils/helpers/customModels.js index a1b2eda8..e5bc1fcf 100644 --- a/server/utils/helpers/customModels.js +++ b/server/utils/helpers/customModels.js @@ -1,12 +1,14 @@ -const SUPPORT_CUSTOM_MODELS = ["openai"]; +const SUPPORT_CUSTOM_MODELS = ["openai", "localai"]; -async function getCustomModels(provider = "", apiKey = null) { +async function getCustomModels(provider = "", apiKey = null, basePath = null) { if (!SUPPORT_CUSTOM_MODELS.includes(provider)) return { models: [], error: "Invalid provider for custom models" }; switch (provider) { case "openai": return await openAiModels(apiKey); + case "localai": + return await localAIModels(basePath); default: return { models: [], error: "Invalid provider for custom models" }; } @@ -33,6 +35,23 @@ async function openAiModels(apiKey = null) { return { models, error: null }; } +async function localAIModels(basePath = null) { + const { Configuration, OpenAIApi } = require("openai"); + const config = new Configuration({ + basePath, + }); + const openai = new OpenAIApi(config); + const models = await openai + .listModels() + .then((res) => res.data.data) + .catch((e) => { + console.error(`LocalAI:listModels`, e.message); + return []; + }); + + return { models, error: null }; +} + module.exports = { getCustomModels, }; diff --git a/server/utils/helpers/index.js b/server/utils/helpers/index.js index cf48937a..bbc69a0e 100644 --- a/server/utils/helpers/index.js +++ b/server/utils/helpers/index.js @@ -39,6 +39,10 @@ function getLLMProvider() { const { LMStudioLLM } = require("../AiProviders/lmStudio"); embedder = getEmbeddingEngineSelection(); return new LMStudioLLM(embedder); + case "localai": + const { LocalAiLLM } = require("../AiProviders/localAi"); + embedder = getEmbeddingEngineSelection(); + return new LocalAiLLM(embedder); default: throw new Error("ENV: No LLM_PROVIDER value found in environment!"); } diff --git a/server/utils/helpers/updateENV.js b/server/utils/helpers/updateENV.js index e97f9791..8290f7eb 100644 --- a/server/utils/helpers/updateENV.js +++ b/server/utils/helpers/updateENV.js @@ -47,13 +47,27 @@ const KEY_MAPPING = { // LMStudio Settings LMStudioBasePath: { envKey: "LMSTUDIO_BASE_PATH", - checks: [isNotEmpty, validLMStudioBasePath], + checks: [isNotEmpty, validLLMExternalBasePath], }, LMStudioTokenLimit: { envKey: "LMSTUDIO_MODEL_TOKEN_LIMIT", checks: [nonZero], }, + // LocalAI Settings + LocalAiBasePath: { + envKey: "LOCAL_AI_BASE_PATH", + checks: [isNotEmpty, validLLMExternalBasePath], + }, + LocalAiModelPref: { + envKey: "LOCAL_AI_MODEL_PREF", + checks: [], + }, + LocalAiTokenLimit: { + envKey: "LOCAL_AI_MODEL_TOKEN_LIMIT", + checks: [nonZero], + }, + EmbeddingEngine: { envKey: "EMBEDDING_ENGINE", checks: [supportedEmbeddingModel], @@ -151,7 +165,7 @@ function validAnthropicApiKey(input = "") { : "Anthropic Key must start with sk-ant-"; } -function validLMStudioBasePath(input = "") { +function validLLMExternalBasePath(input = "") { try { new URL(input); if (!input.includes("v1")) return "URL must include /v1"; @@ -164,7 +178,9 @@ function validLMStudioBasePath(input = "") { } function supportedLLM(input = "") { - return ["openai", "azure", "anthropic", "lmstudio"].includes(input); + return ["openai", "azure", "anthropic", "lmstudio", "localai"].includes( + input + ); } function validAnthropicModel(input = "") {