From 2bc11d3f1a6a736d578b5d31af30ec26062b9c3e Mon Sep 17 00:00:00 2001
From: Timothy Carambat <rambat1010@gmail.com>
Date: Tue, 6 Feb 2024 09:17:51 -0800
Subject: [PATCH] Implement support for HuggingFace Inference Endpoints (#680)
---
docker/.env.example | 5 +
.../LLMSelection/HuggingFaceOptions/index.jsx | 56 ++++++
.../src/media/llmprovider/huggingface.png | Bin 0 -> 17572 bytes
.../GeneralSettings/LLMPreference/index.jsx | 10 +
.../Steps/DataHandling/index.jsx | 8 +
.../Steps/LLMPreference/index.jsx | 10 +
server/.env.example | 5 +
server/models/systemSettings.js | 14 ++
server/utils/AiProviders/huggingface/index.js | 185 ++++++++++++++++++
server/utils/chats/stream.js | 106 ++++++++++
server/utils/helpers/index.js | 3 +
server/utils/helpers/updateENV.js | 23 ++-
12 files changed, 424 insertions(+), 1 deletion(-)
create mode 100644 frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx
create mode 100644 frontend/src/media/llmprovider/huggingface.png
create mode 100644 server/utils/AiProviders/huggingface/index.js
diff --git a/docker/.env.example b/docker/.env.example
index 4213c3ff5..b7674e91b 100644
--- a/docker/.env.example
+++ b/docker/.env.example
@@ -48,6 +48,11 @@ GID='1000'
# MISTRAL_API_KEY='example-mistral-ai-api-key'
# MISTRAL_MODEL_PREF='mistral-tiny'
+# LLM_PROVIDER='huggingface'
+# HUGGING_FACE_LLM_ENDPOINT=https://uuid-here.us-east-1.aws.endpoints.huggingface.cloud
+# HUGGING_FACE_LLM_API_KEY=hf_xxxxxx
+# HUGGING_FACE_LLM_TOKEN_LIMIT=8000
+
###########################################
######## Embedding API SElECTION ##########
###########################################
diff --git a/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx b/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx
new file mode 100644
index 000000000..7e8747da1
--- /dev/null
+++ b/frontend/src/components/LLMSelection/HuggingFaceOptions/index.jsx
@@ -0,0 +1,56 @@
+export default function HuggingFaceOptions({ settings }) {
+ return (
+ <div className="w-full flex flex-col">
+ <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">
+ HuggingFace Inference Endpoint
+ </label>
+ <input
+ type="url"
+ name="HuggingFaceLLMEndpoint"
+ className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="https://example.endpoints.huggingface.cloud"
+ defaultValue={settings?.HuggingFaceLLMEndpoint}
+ 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">
+ HuggingFace Access Token
+ </label>
+ <input
+ type="password"
+ name="HuggingFaceLLMAccessToken"
+ className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="HuggingFace Access Token"
+ defaultValue={
+ settings?.HuggingFaceLLMAccessToken ? "*".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 Token Limit
+ </label>
+ <input
+ type="number"
+ name="HuggingFaceLLMTokenLimit"
+ className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="4096"
+ min={1}
+ onScroll={(e) => e.target.blur()}
+ defaultValue={settings?.HuggingFaceLLMTokenLimit}
+ required={true}
+ autoComplete="off"
+ />
+ </div>
+ </div>
+ </div>
+ );
+}
diff --git a/frontend/src/media/llmprovider/huggingface.png b/frontend/src/media/llmprovider/huggingface.png
new file mode 100644
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diff --git a/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx b/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx
index 1efa818d3..ac9ab71f8 100644
--- a/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx
+++ b/frontend/src/pages/GeneralSettings/LLMPreference/index.jsx
@@ -13,6 +13,7 @@ import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
import LocalAiLogo from "@/media/llmprovider/localai.png";
import TogetherAILogo from "@/media/llmprovider/togetherai.png";
import MistralLogo from "@/media/llmprovider/mistral.jpeg";
+import HuggingFaceLogo from "@/media/llmprovider/huggingface.png";
import PreLoader from "@/components/Preloader";
import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
import AzureAiOptions from "@/components/LLMSelection/AzureAiOptions";
@@ -24,6 +25,7 @@ import GeminiLLMOptions from "@/components/LLMSelection/GeminiLLMOptions";
import OllamaLLMOptions from "@/components/LLMSelection/OllamaLLMOptions";
import TogetherAiOptions from "@/components/LLMSelection/TogetherAiOptions";
import MistralOptions from "@/components/LLMSelection/MistralOptions";
+import HuggingFaceOptions from "@/components/LLMSelection/HuggingFaceOptions";
import LLMItem from "@/components/LLMSelection/LLMItem";
import { MagnifyingGlass } from "@phosphor-icons/react";
@@ -107,6 +109,14 @@ export default function GeneralLLMPreference() {
options: <GeminiLLMOptions settings={settings} />,
description: "Google's largest and most capable AI model",
},
+ {
+ name: "HuggingFace",
+ value: "huggingface",
+ logo: HuggingFaceLogo,
+ options: <HuggingFaceOptions settings={settings} />,
+ description:
+ "Access 150,000+ open-source LLMs and the world's AI community",
+ },
{
name: "Ollama",
value: "ollama",
diff --git a/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx b/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
index 60a3b6da4..c86a62a43 100644
--- a/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
+++ b/frontend/src/pages/OnboardingFlow/Steps/DataHandling/index.jsx
@@ -10,6 +10,7 @@ import TogetherAILogo from "@/media/llmprovider/togetherai.png";
import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
import LocalAiLogo from "@/media/llmprovider/localai.png";
import MistralLogo from "@/media/llmprovider/mistral.jpeg";
+import HuggingFaceLogo from "@/media/llmprovider/huggingface.png";
import ZillizLogo from "@/media/vectordbs/zilliz.png";
import AstraDBLogo from "@/media/vectordbs/astraDB.png";
import ChromaLogo from "@/media/vectordbs/chroma.png";
@@ -101,6 +102,13 @@ const LLM_SELECTION_PRIVACY = {
],
logo: MistralLogo,
},
+ huggingface: {
+ name: "HuggingFace",
+ description: [
+ "Your prompts and document text used in response are sent to your HuggingFace managed endpoint",
+ ],
+ logo: HuggingFaceLogo,
+ },
};
const VECTOR_DB_PRIVACY = {
diff --git a/frontend/src/pages/OnboardingFlow/Steps/LLMPreference/index.jsx b/frontend/src/pages/OnboardingFlow/Steps/LLMPreference/index.jsx
index 9e8ab84a9..6970dfa1f 100644
--- a/frontend/src/pages/OnboardingFlow/Steps/LLMPreference/index.jsx
+++ b/frontend/src/pages/OnboardingFlow/Steps/LLMPreference/index.jsx
@@ -10,6 +10,7 @@ import LocalAiLogo from "@/media/llmprovider/localai.png";
import TogetherAILogo from "@/media/llmprovider/togetherai.png";
import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
import MistralLogo from "@/media/llmprovider/mistral.jpeg";
+import HuggingFaceLogo from "@/media/llmprovider/huggingface.png";
import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
import AzureAiOptions from "@/components/LLMSelection/AzureAiOptions";
import AnthropicAiOptions from "@/components/LLMSelection/AnthropicAiOptions";
@@ -19,6 +20,7 @@ import NativeLLMOptions from "@/components/LLMSelection/NativeLLMOptions";
import GeminiLLMOptions from "@/components/LLMSelection/GeminiLLMOptions";
import OllamaLLMOptions from "@/components/LLMSelection/OllamaLLMOptions";
import MistralOptions from "@/components/LLMSelection/MistralOptions";
+import HuggingFaceOptions from "@/components/LLMSelection/HuggingFaceOptions";
import LLMItem from "@/components/LLMSelection/LLMItem";
import System from "@/models/system";
import paths from "@/utils/paths";
@@ -82,6 +84,14 @@ export default function LLMPreference({
options: <GeminiLLMOptions settings={settings} />,
description: "Google's largest and most capable AI model",
},
+ {
+ name: "HuggingFace",
+ value: "huggingface",
+ logo: HuggingFaceLogo,
+ options: <HuggingFaceOptions settings={settings} />,
+ description:
+ "Access 150,000+ open-source LLMs and the world's AI community",
+ },
{
name: "Ollama",
value: "ollama",
diff --git a/server/.env.example b/server/.env.example
index 96cbd58ae..ec6abcac9 100644
--- a/server/.env.example
+++ b/server/.env.example
@@ -45,6 +45,11 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea
# MISTRAL_API_KEY='example-mistral-ai-api-key'
# MISTRAL_MODEL_PREF='mistral-tiny'
+# LLM_PROVIDER='huggingface'
+# HUGGING_FACE_LLM_ENDPOINT=https://uuid-here.us-east-1.aws.endpoints.huggingface.cloud
+# HUGGING_FACE_LLM_API_KEY=hf_xxxxxx
+# HUGGING_FACE_LLM_TOKEN_LIMIT=8000
+
###########################################
######## Embedding API SElECTION ##########
###########################################
diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js
index b8c46524c..abb930127 100644
--- a/server/models/systemSettings.js
+++ b/server/models/systemSettings.js
@@ -194,6 +194,20 @@ const SystemSettings = {
AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
}
: {}),
+
+ ...(llmProvider === "huggingface"
+ ? {
+ HuggingFaceLLMEndpoint: process.env.HUGGING_FACE_LLM_ENDPOINT,
+ HuggingFaceLLMAccessToken: !!process.env.HUGGING_FACE_LLM_API_KEY,
+ HuggingFaceLLMTokenLimit: process.env.HUGGING_FACE_LLM_TOKEN_LIMIT,
+
+ // For embedding credentials when Anthropic 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/huggingface/index.js b/server/utils/AiProviders/huggingface/index.js
new file mode 100644
index 000000000..4faf9b30f
--- /dev/null
+++ b/server/utils/AiProviders/huggingface/index.js
@@ -0,0 +1,185 @@
+const { NativeEmbedder } = require("../../EmbeddingEngines/native");
+const { OpenAiEmbedder } = require("../../EmbeddingEngines/openAi");
+const { chatPrompt } = require("../../chats");
+
+class HuggingFaceLLM {
+ constructor(embedder = null, _modelPreference = null) {
+ const { Configuration, OpenAIApi } = require("openai");
+ if (!process.env.HUGGING_FACE_LLM_ENDPOINT)
+ throw new Error("No HuggingFace Inference Endpoint was set.");
+ if (!process.env.HUGGING_FACE_LLM_API_KEY)
+ throw new Error("No HuggingFace Access Token was set.");
+
+ const config = new Configuration({
+ basePath: `${process.env.HUGGING_FACE_LLM_ENDPOINT}/v1`,
+ apiKey: process.env.HUGGING_FACE_LLM_API_KEY,
+ });
+ this.openai = new OpenAIApi(config);
+ // When using HF inference server - the model param is not required so
+ // we can stub it here. HF Endpoints can only run one model at a time.
+ // We set to 'tgi' so that endpoint for HF can accept message format
+ this.model = "tgi";
+ this.limits = {
+ history: this.promptWindowLimit() * 0.15,
+ system: this.promptWindowLimit() * 0.15,
+ user: this.promptWindowLimit() * 0.7,
+ };
+
+ if (!embedder)
+ console.warn(
+ "No embedding provider defined for HuggingFaceLLM - falling back to Native for embedding!"
+ );
+ this.embedder = !embedder ? new OpenAiEmbedder() : new NativeEmbedder();
+ this.defaultTemp = 0.2;
+ }
+
+ #appendContext(contextTexts = []) {
+ if (!contextTexts || !contextTexts.length) return "";
+ return (
+ "\nContext:\n" +
+ contextTexts
+ .map((text, i) => {
+ return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+ })
+ .join("")
+ );
+ }
+
+ streamingEnabled() {
+ return "streamChat" in this && "streamGetChatCompletion" in this;
+ }
+
+ promptWindowLimit() {
+ const limit = process.env.HUGGING_FACE_LLM_TOKEN_LIMIT || 4096;
+ if (!limit || isNaN(Number(limit)))
+ throw new Error("No HuggingFace token context limit was set.");
+ return Number(limit);
+ }
+
+ async isValidChatCompletionModel(_ = "") {
+ return true;
+ }
+
+ constructPrompt({
+ systemPrompt = "",
+ contextTexts = [],
+ chatHistory = [],
+ userPrompt = "",
+ }) {
+ // System prompt it not enabled for HF model chats
+ const prompt = {
+ role: "user",
+ content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
+ };
+ const assistantResponse = {
+ role: "assistant",
+ content: "Okay, I will follow those instructions",
+ };
+ return [
+ prompt,
+ assistantResponse,
+ ...chatHistory,
+ { role: "user", content: userPrompt },
+ ];
+ }
+
+ async isSafe(_input = "") {
+ // Not implemented so must be stubbed
+ return { safe: true, reasons: [] };
+ }
+
+ async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
+ const textResponse = await this.openai
+ .createChatCompletion({
+ model: this.model,
+ temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
+ 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("HuggingFace chat: No results!");
+ if (res.choices.length === 0)
+ throw new Error("HuggingFace chat: No results length!");
+ return res.choices[0].message.content;
+ })
+ .catch((error) => {
+ throw new Error(
+ `HuggingFace::createChatCompletion failed with: ${error.message}`
+ );
+ });
+
+ return textResponse;
+ }
+
+ async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
+ const streamRequest = await this.openai.createChatCompletion(
+ {
+ model: this.model,
+ stream: true,
+ temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
+ n: 1,
+ messages: await this.compressMessages(
+ {
+ systemPrompt: chatPrompt(workspace),
+ userPrompt: prompt,
+ chatHistory,
+ },
+ rawHistory
+ ),
+ },
+ { responseType: "stream" }
+ );
+ return { type: "huggingFaceStream", stream: streamRequest };
+ }
+
+ async getChatCompletion(messages = null, { temperature = 0.7 }) {
+ 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 }) {
+ const streamRequest = await this.openai.createChatCompletion(
+ {
+ model: this.model,
+ stream: true,
+ messages,
+ temperature,
+ },
+ { responseType: "stream" }
+ );
+ return { type: "huggingFaceStream", stream: 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 = {
+ HuggingFaceLLM,
+};
diff --git a/server/utils/chats/stream.js b/server/utils/chats/stream.js
index 1202ab167..0ee448a5e 100644
--- a/server/utils/chats/stream.js
+++ b/server/utils/chats/stream.js
@@ -383,6 +383,112 @@ function handleStreamResponses(response, stream, responseProps) {
});
}
+ if (stream.type === "huggingFaceStream") {
+ return new Promise((resolve) => {
+ let fullText = "";
+ let chunk = "";
+ stream.stream.data.on("data", (data) => {
+ const lines = data
+ ?.toString()
+ ?.split("\n")
+ .filter((line) => line.trim() !== "");
+
+ for (const line of lines) {
+ let validJSON = false;
+ const message = chunk + line.replace(/^data:/, "");
+ if (message !== "[DONE]") {
+ // 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!
+ try {
+ JSON.parse(message);
+ validJSON = true;
+ } catch {
+ console.log("Failed to parse message", message);
+ }
+
+ if (!validJSON) {
+ // It can be possible that the chunk decoding is running away
+ // and the message chunk fails to append due to string length.
+ // In this case abort the chunk and reset so we can continue.
+ // ref: https://github.com/Mintplex-Labs/anything-llm/issues/416
+ try {
+ chunk += message;
+ } catch (e) {
+ console.error(`Chunk appending error`, e);
+ chunk = "";
+ }
+ continue;
+ } else {
+ chunk = "";
+ }
+ }
+
+ if (message == "[DONE]") {
+ writeResponseChunk(response, {
+ uuid,
+ sources,
+ type: "textResponseChunk",
+ textResponse: "",
+ close: true,
+ error: false,
+ });
+ resolve(fullText);
+ } else {
+ let error = null;
+ let finishReason = null;
+ let token = "";
+ try {
+ const json = JSON.parse(message);
+ error = json?.error || null;
+ token = json?.choices?.[0]?.delta?.content;
+ finishReason = json?.choices?.[0]?.finish_reason || null;
+ } catch {
+ continue;
+ }
+
+ if (!!error) {
+ writeResponseChunk(response, {
+ uuid,
+ sources: [],
+ type: "textResponseChunk",
+ textResponse: null,
+ close: true,
+ error,
+ });
+ resolve("");
+ return;
+ }
+
+ if (token) {
+ fullText += token;
+ writeResponseChunk(response, {
+ uuid,
+ sources: [],
+ type: "textResponseChunk",
+ textResponse: token,
+ close: false,
+ error: false,
+ });
+ }
+
+ if (finishReason !== null) {
+ writeResponseChunk(response, {
+ uuid,
+ sources,
+ type: "textResponseChunk",
+ textResponse: "",
+ close: true,
+ error: false,
+ });
+ resolve(fullText);
+ }
+ }
+ }
+ });
+ });
+ }
+
// If stream is not a regular OpenAI Stream (like if using native model, Ollama, or most LangChain interfaces)
// we can just iterate the stream content instead.
if (!stream.hasOwnProperty("data")) {
diff --git a/server/utils/helpers/index.js b/server/utils/helpers/index.js
index 53a76faeb..42ed262f9 100644
--- a/server/utils/helpers/index.js
+++ b/server/utils/helpers/index.js
@@ -64,6 +64,9 @@ function getLLMProvider(modelPreference = null) {
case "native":
const { NativeLLM } = require("../AiProviders/native");
return new NativeLLM(embedder, modelPreference);
+ case "huggingface":
+ const { HuggingFaceLLM } = require("../AiProviders/huggingface");
+ return new HuggingFaceLLM(embedder, modelPreference);
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 50b423474..acd77b2fd 100644
--- a/server/utils/helpers/updateENV.js
+++ b/server/utils/helpers/updateENV.js
@@ -95,6 +95,7 @@ const KEY_MAPPING = {
checks: [nonZero],
},
+ // Mistral AI API Settings
MistralApiKey: {
envKey: "MISTRAL_API_KEY",
checks: [isNotEmpty],
@@ -109,12 +110,25 @@ const KEY_MAPPING = {
envKey: "NATIVE_LLM_MODEL_PREF",
checks: [isDownloadedModel],
},
-
NativeLLMTokenLimit: {
envKey: "NATIVE_LLM_MODEL_TOKEN_LIMIT",
checks: [nonZero],
},
+ // Hugging Face LLM Inference Settings
+ HuggingFaceLLMEndpoint: {
+ envKey: "HUGGING_FACE_LLM_ENDPOINT",
+ checks: [isNotEmpty, isValidURL, validHuggingFaceEndpoint],
+ },
+ HuggingFaceLLMAccessToken: {
+ envKey: "HUGGING_FACE_LLM_API_KEY",
+ checks: [isNotEmpty],
+ },
+ HuggingFaceLLMTokenLimit: {
+ envKey: "HUGGING_FACE_LLM_TOKEN_LIMIT",
+ checks: [nonZero],
+ },
+
EmbeddingEngine: {
envKey: "EMBEDDING_ENGINE",
checks: [supportedEmbeddingModel],
@@ -299,6 +313,7 @@ function supportedLLM(input = "") {
"native",
"togetherai",
"mistral",
+ "huggingface",
].includes(input);
return validSelection ? null : `${input} is not a valid LLM provider.`;
}
@@ -396,6 +411,12 @@ function validDockerizedUrl(input = "") {
return null;
}
+function validHuggingFaceEndpoint(input = "") {
+ return input.slice(-6) !== ".cloud"
+ ? `Your HF Endpoint should end in ".cloud"`
+ : null;
+}
+
// If the LLMProvider has changed we need to reset all workspace model preferences to
// null since the provider<>model name combination will be invalid for whatever the new
// provider is.
--
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