merge master

This commit is contained in:
timothycarambat 2024-10-22 14:08:46 -07:00
commit a6a5084565
98 changed files with 2920 additions and 842 deletions

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@ -5,6 +5,7 @@
"AIbitat", "AIbitat",
"allm", "allm",
"anythingllm", "anythingllm",
"Apipie",
"Astra", "Astra",
"Chartable", "Chartable",
"cleancss", "cleancss",
@ -18,6 +19,7 @@
"elevenlabs", "elevenlabs",
"Embeddable", "Embeddable",
"epub", "epub",
"fireworksai",
"GROQ", "GROQ",
"hljs", "hljs",
"huggingface", "huggingface",
@ -40,17 +42,18 @@
"pagerender", "pagerender",
"Qdrant", "Qdrant",
"royalblue", "royalblue",
"searxng",
"SearchApi", "SearchApi",
"searxng",
"Serper", "Serper",
"Serply", "Serply",
"streamable", "streamable",
"textgenwebui", "textgenwebui",
"togetherai", "togetherai",
"fireworksai",
"Unembed", "Unembed",
"uuidv",
"vectordbs", "vectordbs",
"Weaviate", "Weaviate",
"XAILLM",
"Zilliz" "Zilliz"
], ],
"eslint.experimental.useFlatConfig": true, "eslint.experimental.useFlatConfig": true,

View File

@ -94,6 +94,8 @@ AnythingLLM divides your documents into objects called `workspaces`. A Workspace
- [KoboldCPP](https://github.com/LostRuins/koboldcpp) - [KoboldCPP](https://github.com/LostRuins/koboldcpp)
- [LiteLLM](https://github.com/BerriAI/litellm) - [LiteLLM](https://github.com/BerriAI/litellm)
- [Text Generation Web UI](https://github.com/oobabooga/text-generation-webui) - [Text Generation Web UI](https://github.com/oobabooga/text-generation-webui)
- [Apipie](https://apipie.ai/)
- [xAI](https://x.ai/)
**Embedder models:** **Embedder models:**
@ -116,6 +118,7 @@ AnythingLLM divides your documents into objects called `workspaces`. A Workspace
- [PiperTTSLocal - runs in browser](https://github.com/rhasspy/piper) - [PiperTTSLocal - runs in browser](https://github.com/rhasspy/piper)
- [OpenAI TTS](https://platform.openai.com/docs/guides/text-to-speech/voice-options) - [OpenAI TTS](https://platform.openai.com/docs/guides/text-to-speech/voice-options)
- [ElevenLabs](https://elevenlabs.io/) - [ElevenLabs](https://elevenlabs.io/)
- Any OpenAI Compatible TTS service.
**STT (speech-to-text) support:** **STT (speech-to-text) support:**

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@ -16,12 +16,14 @@ const extensions = require("./extensions");
const { processRawText } = require("./processRawText"); const { processRawText } = require("./processRawText");
const { verifyPayloadIntegrity } = require("./middleware/verifyIntegrity"); const { verifyPayloadIntegrity } = require("./middleware/verifyIntegrity");
const app = express(); const app = express();
const FILE_LIMIT = "3GB";
app.use(cors({ origin: true })); app.use(cors({ origin: true }));
app.use( app.use(
bodyParser.text(), bodyParser.text({ limit: FILE_LIMIT }),
bodyParser.json(), bodyParser.json({ limit: FILE_LIMIT }),
bodyParser.urlencoded({ bodyParser.urlencoded({
limit: FILE_LIMIT,
extended: true, extended: true,
}) })
); );

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@ -33,6 +33,7 @@
"mime": "^3.0.0", "mime": "^3.0.0",
"moment": "^2.29.4", "moment": "^2.29.4",
"node-html-parser": "^6.1.13", "node-html-parser": "^6.1.13",
"node-xlsx": "^0.24.0",
"officeparser": "^4.0.5", "officeparser": "^4.0.5",
"openai": "4.38.5", "openai": "4.38.5",
"pdf-parse": "^1.1.1", "pdf-parse": "^1.1.1",

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@ -27,7 +27,8 @@ async function scrapeGenericUrl(link, textOnly = false) {
} }
const url = new URL(link); const url = new URL(link);
const filename = (url.host + "-" + url.pathname).replace(".", "_"); const decodedPathname = decodeURIComponent(url.pathname);
const filename = `${url.hostname}${decodedPathname.replace(/\//g, "_")}`;
const data = { const data = {
id: v4(), id: v4(),

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@ -0,0 +1,113 @@
const { v4 } = require("uuid");
const xlsx = require("node-xlsx").default;
const path = require("path");
const fs = require("fs");
const {
createdDate,
trashFile,
writeToServerDocuments,
} = require("../../utils/files");
const { tokenizeString } = require("../../utils/tokenizer");
const { default: slugify } = require("slugify");
function convertToCSV(data) {
return data
.map((row) =>
row
.map((cell) => {
if (cell === null || cell === undefined) return "";
if (typeof cell === "string" && cell.includes(","))
return `"${cell}"`;
return cell;
})
.join(",")
)
.join("\n");
}
async function asXlsx({ fullFilePath = "", filename = "" }) {
const documents = [];
const folderName = slugify(`${path.basename(filename)}-${v4().slice(0, 4)}`, {
lower: true,
trim: true,
});
const outFolderPath =
process.env.NODE_ENV === "development"
? path.resolve(
__dirname,
`../../../server/storage/documents/${folderName}`
)
: path.resolve(process.env.STORAGE_DIR, `documents/${folderName}`);
try {
const workSheetsFromFile = xlsx.parse(fullFilePath);
if (!fs.existsSync(outFolderPath))
fs.mkdirSync(outFolderPath, { recursive: true });
for (const sheet of workSheetsFromFile) {
try {
const { name, data } = sheet;
const content = convertToCSV(data);
if (!content?.length) {
console.warn(`Sheet "${name}" is empty. Skipping.`);
continue;
}
console.log(`-- Processing sheet: ${name} --`);
const sheetData = {
id: v4(),
url: `file://${path.join(outFolderPath, `${slugify(name)}.csv`)}`,
title: `${filename} - Sheet:${name}`,
docAuthor: "Unknown",
description: `Spreadsheet data from sheet: ${name}`,
docSource: "an xlsx file uploaded by the user.",
chunkSource: "",
published: createdDate(fullFilePath),
wordCount: content.split(/\s+/).length,
pageContent: content,
token_count_estimate: tokenizeString(content).length,
};
const document = writeToServerDocuments(
sheetData,
`sheet-${slugify(name)}`,
outFolderPath
);
documents.push(document);
console.log(
`[SUCCESS]: Sheet "${name}" converted & ready for embedding.`
);
} catch (err) {
console.error(`Error processing sheet "${name}":`, err);
continue;
}
}
} catch (err) {
console.error("Could not process xlsx file!", err);
return {
success: false,
reason: `Error processing ${filename}: ${err.message}`,
documents: [],
};
} finally {
trashFile(fullFilePath);
}
if (documents.length === 0) {
console.error(`No valid sheets found in ${filename}.`);
return {
success: false,
reason: `No valid sheets found in ${filename}.`,
documents: [],
};
}
console.log(
`[SUCCESS]: ${filename} fully processed. Created ${documents.length} document(s).\n`
);
return { success: true, reason: null, documents };
}
module.exports = asXlsx;

View File

@ -38,7 +38,7 @@ async function processSingleFile(targetFilename, options = {}) {
}; };
const fileExtension = path.extname(fullFilePath).toLowerCase(); const fileExtension = path.extname(fullFilePath).toLowerCase();
if (!fileExtension) { if (fullFilePath.includes(".") && !fileExtension) {
return { return {
success: false, success: false,
reason: `No file extension found. This file cannot be processed.`, reason: `No file extension found. This file cannot be processed.`,

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@ -11,6 +11,10 @@ const ACCEPTED_MIMES = {
".pptx", ".pptx",
], ],
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet": [
".xlsx",
],
"application/vnd.oasis.opendocument.text": [".odt"], "application/vnd.oasis.opendocument.text": [".odt"],
"application/vnd.oasis.opendocument.presentation": [".odp"], "application/vnd.oasis.opendocument.presentation": [".odp"],
@ -41,6 +45,8 @@ const SUPPORTED_FILETYPE_CONVERTERS = {
".odt": "./convert/asOfficeMime.js", ".odt": "./convert/asOfficeMime.js",
".odp": "./convert/asOfficeMime.js", ".odp": "./convert/asOfficeMime.js",
".xlsx": "./convert/asXlsx.js",
".mbox": "./convert/asMbox.js", ".mbox": "./convert/asMbox.js",
".epub": "./convert/asEPub.js", ".epub": "./convert/asEPub.js",

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@ -29,20 +29,36 @@ class GitHubRepoLoader {
} }
#validGithubUrl() { #validGithubUrl() {
const UrlPattern = require("url-pattern"); try {
const pattern = new UrlPattern( const url = new URL(this.repo);
"https\\://github.com/(:author)/(:project(*))",
{
// fixes project names with special characters (.github)
segmentValueCharset: "a-zA-Z0-9-._~%/+",
}
);
const match = pattern.match(this.repo);
if (!match) return false;
this.author = match.author; // Not a github url at all.
this.project = match.project; if (url.hostname !== "github.com") {
console.log(
`[Github Loader]: Invalid Github URL provided! Hostname must be 'github.com'. Got ${url.hostname}`
);
return false;
}
// Assume the url is in the format of github.com/{author}/{project}
// Remove the first slash from the pathname so we can split it properly.
const [author, project, ..._rest] = url.pathname.slice(1).split("/");
if (!author || !project) {
console.log(
`[Github Loader]: Invalid Github URL provided! URL must be in the format of 'github.com/{author}/{project}'. Got ${url.pathname}`
);
return false;
}
this.author = author;
this.project = project;
return true; return true;
} catch (e) {
console.log(
`[Github Loader]: Invalid Github URL provided! Error: ${e.message}`
);
return false;
}
} }
// Ensure the branch provided actually exists // Ensure the branch provided actually exists

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@ -108,7 +108,8 @@ async function bulkScrapePages(links, outFolderPath) {
} }
const url = new URL(link); const url = new URL(link);
const filename = (url.host + "-" + url.pathname).replace(".", "_"); const decodedPathname = decodeURIComponent(url.pathname);
const filename = `${url.hostname}${decodedPathname.replace(/\//g, "_")}`;
const data = { const data = {
id: v4(), id: v4(),

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@ -1,5 +1,5 @@
const MimeLib = require("mime"); const MimeLib = require("mime");
const path = require("path");
class MimeDetector { class MimeDetector {
nonTextTypes = ["multipart", "image", "model", "audio", "video"]; nonTextTypes = ["multipart", "image", "model", "audio", "video"];
badMimes = [ badMimes = [
@ -44,8 +44,26 @@ class MimeDetector {
); );
} }
// These are file types that are not detected by the mime library and need to be processed as text files.
// You should only add file types that are not detected by the mime library, are parsable as text, and are files
// with no extension. Otherwise, their extension should be added to the overrides array.
#specialTextFileTypes = ["dockerfile", "jenkinsfile"];
/**
* Returns the MIME type of the file. If the file has no extension found, it will be processed as a text file.
* @param {string} filepath
* @returns {string}
*/
getType(filepath) { getType(filepath) {
return this.lib.getType(filepath); const parsedMime = this.lib.getType(filepath);
if (!!parsedMime) return parsedMime;
// If the mime could not be parsed, it could be a special file type like Dockerfile or Jenkinsfile
// which we can reliably process as text files.
const baseName = path.basename(filepath)?.toLowerCase();
if (this.#specialTextFileTypes.includes(baseName)) return "text/plain";
return null;
} }
} }

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@ -2326,6 +2326,13 @@ node-html-parser@^6.1.13:
css-select "^5.1.0" css-select "^5.1.0"
he "1.2.0" he "1.2.0"
node-xlsx@^0.24.0:
version "0.24.0"
resolved "https://registry.yarnpkg.com/node-xlsx/-/node-xlsx-0.24.0.tgz#a6a365acb18ad37c66c2b254b6ebe0c22dc9dc6f"
integrity sha512-1olwK48XK9nXZsyH/FCltvGrQYvXXZuxVitxXXv2GIuRm51aBi1+5KwR4rWM4KeO61sFU+00913WLZTD+AcXEg==
dependencies:
xlsx "https://cdn.sheetjs.com/xlsx-0.20.2/xlsx-0.20.2.tgz"
nodemailer@6.9.13: nodemailer@6.9.13:
version "6.9.13" version "6.9.13"
resolved "https://registry.yarnpkg.com/nodemailer/-/nodemailer-6.9.13.tgz#5b292bf1e92645f4852ca872c56a6ba6c4a3d3d6" resolved "https://registry.yarnpkg.com/nodemailer/-/nodemailer-6.9.13.tgz#5b292bf1e92645f4852ca872c56a6ba6c4a3d3d6"
@ -3528,6 +3535,10 @@ ws@8.14.2:
resolved "https://registry.yarnpkg.com/ws/-/ws-8.14.2.tgz#6c249a806eb2db7a20d26d51e7709eab7b2e6c7f" resolved "https://registry.yarnpkg.com/ws/-/ws-8.14.2.tgz#6c249a806eb2db7a20d26d51e7709eab7b2e6c7f"
integrity sha512-wEBG1ftX4jcglPxgFCMJmZ2PLtSbJ2Peg6TmpJFTbe9GZYOQCDPdMYu/Tm0/bGZkw8paZnJY45J4K2PZrLYq8g== integrity sha512-wEBG1ftX4jcglPxgFCMJmZ2PLtSbJ2Peg6TmpJFTbe9GZYOQCDPdMYu/Tm0/bGZkw8paZnJY45J4K2PZrLYq8g==
"xlsx@https://cdn.sheetjs.com/xlsx-0.20.2/xlsx-0.20.2.tgz":
version "0.20.2"
resolved "https://cdn.sheetjs.com/xlsx-0.20.2/xlsx-0.20.2.tgz#0f64eeed3f1a46e64724620c3553f2dbd3cd2d7d"
xml2js@^0.6.2: xml2js@^0.6.2:
version "0.6.2" version "0.6.2"
resolved "https://registry.yarnpkg.com/xml2js/-/xml2js-0.6.2.tgz#dd0b630083aa09c161e25a4d0901e2b2a929b499" resolved "https://registry.yarnpkg.com/xml2js/-/xml2js-0.6.2.tgz#dd0b630083aa09c161e25a4d0901e2b2a929b499"

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@ -105,6 +105,14 @@ GID='1000'
# FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key' # FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key'
# FIREWORKS_AI_LLM_MODEL_PREF='accounts/fireworks/models/llama-v3p1-8b-instruct' # FIREWORKS_AI_LLM_MODEL_PREF='accounts/fireworks/models/llama-v3p1-8b-instruct'
# LLM_PROVIDER='apipie'
# APIPIE_LLM_API_KEY='sk-123abc'
# APIPIE_LLM_MODEL_PREF='openrouter/llama-3.1-8b-instruct'
# LLM_PROVIDER='xai'
# XAI_LLM_API_KEY='xai-your-api-key-here'
# XAI_LLM_MODEL_PREF='grok-beta'
########################################### ###########################################
######## Embedding API SElECTION ########## ######## Embedding API SElECTION ##########
########################################### ###########################################
@ -215,6 +223,11 @@ GID='1000'
# TTS_OPEN_AI_KEY=sk-example # TTS_OPEN_AI_KEY=sk-example
# TTS_OPEN_AI_VOICE_MODEL=nova # TTS_OPEN_AI_VOICE_MODEL=nova
# TTS_PROVIDER="generic-openai"
# TTS_OPEN_AI_COMPATIBLE_KEY=sk-example
# TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL=nova
# TTS_OPEN_AI_COMPATIBLE_ENDPOINT="https://api.openai.com/v1"
# TTS_PROVIDER="elevenlabs" # TTS_PROVIDER="elevenlabs"
# TTS_ELEVEN_LABS_KEY= # TTS_ELEVEN_LABS_KEY=
# TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel # TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel
@ -271,3 +284,11 @@ GID='1000'
#------ SearXNG ----------- https://github.com/searxng/searxng #------ SearXNG ----------- https://github.com/searxng/searxng
# AGENT_SEARXNG_API_URL= # AGENT_SEARXNG_API_URL=
###########################################
######## Other Configurations ############
###########################################
# Disable viewing chat history from the UI and frontend APIs.
# See https://docs.anythingllm.com/configuration#disable-view-chat-history for more information.
# DISABLE_VIEW_CHAT_HISTORY=1

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@ -22,7 +22,6 @@ const WorkspaceChat = lazy(() => import("@/pages/WorkspaceChat"));
const AdminUsers = lazy(() => import("@/pages/Admin/Users")); const AdminUsers = lazy(() => import("@/pages/Admin/Users"));
const AdminInvites = lazy(() => import("@/pages/Admin/Invitations")); const AdminInvites = lazy(() => import("@/pages/Admin/Invitations"));
const AdminWorkspaces = lazy(() => import("@/pages/Admin/Workspaces")); const AdminWorkspaces = lazy(() => import("@/pages/Admin/Workspaces"));
const AdminSystem = lazy(() => import("@/pages/Admin/System"));
const AdminLogs = lazy(() => import("@/pages/Admin/Logging")); const AdminLogs = lazy(() => import("@/pages/Admin/Logging"));
const AdminAgents = lazy(() => import("@/pages/Admin/Agents")); const AdminAgents = lazy(() => import("@/pages/Admin/Agents"));
const GeneralChats = lazy(() => import("@/pages/GeneralSettings/Chats")); const GeneralChats = lazy(() => import("@/pages/GeneralSettings/Chats"));
@ -168,10 +167,6 @@ export default function App() {
path="/settings/workspace-chats" path="/settings/workspace-chats"
element={<ManagerRoute Component={GeneralChats} />} element={<ManagerRoute Component={GeneralChats} />}
/> />
<Route
path="/settings/system-preferences"
element={<ManagerRoute Component={AdminSystem} />}
/>
<Route <Route
path="/settings/invites" path="/settings/invites"
element={<ManagerRoute Component={AdminInvites} />} element={<ManagerRoute Component={AdminInvites} />}

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@ -0,0 +1,50 @@
import { useEffect, useState } from "react";
import { FullScreenLoader } from "@/components/Preloader";
import System from "@/models/system";
import paths from "@/utils/paths";
/**
* Protects the view from system set ups who cannot view chat history.
* If the user cannot view chat history, they are redirected to the home page.
* @param {React.ReactNode} children
*/
export function CanViewChatHistory({ children }) {
const { loading, viewable } = useCanViewChatHistory();
if (loading) return <FullScreenLoader />;
if (!viewable) {
window.location.href = paths.home();
return <FullScreenLoader />;
}
return <>{children}</>;
}
/**
* Provides the `viewable` state to the children.
* @returns {React.ReactNode}
*/
export function CanViewChatHistoryProvider({ children }) {
const { loading, viewable } = useCanViewChatHistory();
if (loading) return null;
return <>{children({ viewable })}</>;
}
/**
* Hook that fetches the can view chat history state from local storage or the system settings.
* @returns {Promise<{viewable: boolean, error: string | null}>}
*/
export function useCanViewChatHistory() {
const [loading, setLoading] = useState(true);
const [viewable, setViewable] = useState(false);
useEffect(() => {
async function fetchViewable() {
const { viewable } = await System.fetchCanViewChatHistory();
setViewable(viewable);
setLoading(false);
}
fetchViewable();
}, []);
return { loading, viewable };
}

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@ -36,6 +36,8 @@ export default function VoyageAiOptions({ settings }) {
"voyage-code-2", "voyage-code-2",
"voyage-large-2", "voyage-large-2",
"voyage-2", "voyage-2",
"voyage-3",
"voyage-3-lite",
].map((model) => { ].map((model) => {
return ( return (
<option key={model} value={model}> <option key={model} value={model}>

View File

@ -0,0 +1,101 @@
import System from "@/models/system";
import { useState, useEffect } from "react";
export default function ApiPieLLMOptions({ settings }) {
return (
<div className="flex flex-col gap-y-4 mt-1.5">
<div className="flex gap-[36px]">
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
APIpie API Key
</label>
<input
type="password"
name="ApipieLLMApiKey"
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="APIpie API Key"
defaultValue={settings?.ApipieLLMApiKey ? "*".repeat(20) : ""}
required={true}
autoComplete="off"
spellCheck={false}
/>
</div>
{!settings?.credentialsOnly && (
<APIPieModelSelection settings={settings} />
)}
</div>
</div>
);
}
function APIPieModelSelection({ settings }) {
const [groupedModels, setGroupedModels] = useState({});
const [loading, setLoading] = useState(true);
useEffect(() => {
async function findCustomModels() {
setLoading(true);
const { models } = await System.customModels("apipie");
if (models?.length > 0) {
const modelsByOrganization = models.reduce((acc, model) => {
acc[model.organization] = acc[model.organization] || [];
acc[model.organization].push(model);
return acc;
}, {});
setGroupedModels(modelsByOrganization);
}
setLoading(false);
}
findCustomModels();
}, []);
if (loading || Object.keys(groupedModels).length === 0) {
return (
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Chat Model Selection
</label>
<select
name="ApipieLLMModelPref"
disabled={true}
className="bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
>
<option disabled={true} selected={true}>
-- loading available models --
</option>
</select>
</div>
);
}
return (
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Chat Model Selection
</label>
<select
name="ApipieLLMModelPref"
required={true}
className="bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
>
{Object.keys(groupedModels)
.sort()
.map((organization) => (
<optgroup key={organization} label={organization}>
{groupedModels[organization].map((model) => (
<option
key={model.id}
value={model.id}
selected={settings?.ApipieLLMModelPref === model.id}
>
{model.name}
</option>
))}
</optgroup>
))}
</select>
</div>
);
}

View File

@ -71,23 +71,6 @@ export default function AzureAiOptions({ settings }) {
</option> </option>
</select> </select>
</div> </div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Embedding Deployment Name
</label>
<input
type="text"
name="AzureOpenAiEmbeddingModelPref"
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="Azure OpenAI embedding model deployment name"
defaultValue={settings?.AzureOpenAiEmbeddingModelPref}
required={true}
autoComplete="off"
spellCheck={false}
/>
</div>
<div className="flex-flex-col w-60"></div>
</div> </div>
</div> </div>
); );

View File

@ -0,0 +1,114 @@
import { useState, useEffect } from "react";
import System from "@/models/system";
export default function XAILLMOptions({ settings }) {
const [inputValue, setInputValue] = useState(settings?.XAIApiKey);
const [apiKey, setApiKey] = useState(settings?.XAIApiKey);
return (
<div className="flex gap-[36px] mt-1.5">
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
xAI API Key
</label>
<input
type="password"
name="XAIApiKey"
className="border-none bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="xAI API Key"
defaultValue={settings?.XAIApiKey ? "*".repeat(20) : ""}
required={true}
autoComplete="off"
spellCheck={false}
onChange={(e) => setInputValue(e.target.value)}
onBlur={() => setApiKey(inputValue)}
/>
</div>
{!settings?.credentialsOnly && (
<XAIModelSelection settings={settings} apiKey={apiKey} />
)}
</div>
);
}
function XAIModelSelection({ apiKey, settings }) {
const [customModels, setCustomModels] = useState([]);
const [loading, setLoading] = useState(true);
useEffect(() => {
async function findCustomModels() {
if (!apiKey) {
setCustomModels([]);
setLoading(true);
return;
}
try {
setLoading(true);
const { models } = await System.customModels("xai", apiKey);
setCustomModels(models || []);
} catch (error) {
console.error("Failed to fetch custom models:", error);
setCustomModels([]);
} finally {
setLoading(false);
}
}
findCustomModels();
}, [apiKey]);
if (loading) {
return (
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Chat Model Selection
</label>
<select
name="XAIModelPref"
disabled={true}
className="border-none bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
>
<option disabled={true} selected={true}>
--loading available models--
</option>
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Enter a valid API key to view all available models for your account.
</p>
</div>
);
}
return (
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Chat Model Selection
</label>
<select
name="XAIModelPref"
required={true}
className="border-none bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
>
{customModels.length > 0 && (
<optgroup label="Available models">
{customModels.map((model) => {
return (
<option
key={model.id}
value={model.id}
selected={settings?.XAIModelPref === model.id}
>
{model.id}
</option>
);
})}
</optgroup>
)}
</select>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Select the xAI model you want to use for your conversations.
</p>
</div>
);
}

View File

@ -31,7 +31,7 @@ export default function FileRow({ item, selected, toggleSelection }) {
className="shrink-0 text-base font-bold w-4 h-4 mr-[3px]" className="shrink-0 text-base font-bold w-4 h-4 mr-[3px]"
weight="fill" weight="fill"
/> />
<p className="whitespace-nowrap overflow-hidden text-ellipsis"> <p className="whitespace-nowrap overflow-hidden text-ellipsis max-w-[400px]">
{middleTruncate(item.title, 55)} {middleTruncate(item.title, 55)}
</p> </p>
</div> </div>

View File

@ -51,7 +51,7 @@ export default function FolderRow({
className="shrink-0 text-base font-bold w-4 h-4 mr-[3px]" className="shrink-0 text-base font-bold w-4 h-4 mr-[3px]"
weight="fill" weight="fill"
/> />
<p className="whitespace-nowrap overflow-show"> <p className="whitespace-nowrap overflow-show max-w-[400px]">
{middleTruncate(item.name, 35)} {middleTruncate(item.name, 35)}
</p> </p>
</div> </div>

View File

@ -83,7 +83,7 @@ export default function WorkspaceFileRow({
className="shrink-0 text-base font-bold w-4 h-4 mr-[3px] ml-1" className="shrink-0 text-base font-bold w-4 h-4 mr-[3px] ml-1"
weight="fill" weight="fill"
/> />
<p className="whitespace-nowrap overflow-hidden text-ellipsis"> <p className="whitespace-nowrap overflow-hidden text-ellipsis max-w-[400px]">
{middleTruncate(item.title, 50)} {middleTruncate(item.title, 50)}
</p> </p>
</div> </div>

View File

@ -29,9 +29,7 @@ export default function SettingsButton() {
return ( return (
<ToolTipWrapper id="open-settings"> <ToolTipWrapper id="open-settings">
<Link <Link
to={ to={paths.settings.appearance()}
!!user?.role ? paths.settings.system() : paths.settings.appearance()
}
className="transition-all duration-300 p-2 rounded-full text-white bg-sidebar-button hover:bg-menu-item-selected-gradient hover:border-slate-100 hover:border-opacity-50 border-transparent border" className="transition-all duration-300 p-2 rounded-full text-white bg-sidebar-button hover:bg-menu-item-selected-gradient hover:border-slate-100 hover:border-opacity-50 border-transparent border"
aria-label="Settings" aria-label="Settings"
data-tooltip-id="open-settings" data-tooltip-id="open-settings"

View File

@ -149,17 +149,32 @@ function useIsExpanded({
return { isExpanded, setIsExpanded }; return { isExpanded, setIsExpanded };
} }
/**
* Checks if the child options are visible to the user.
* This hides the top level options if the child options are not visible
* for either the users permissions or the child options hidden prop is set to true by other means.
* If all child options return false for `isVisible` then the parent option will not be visible as well.
* @param {object} user - The user object.
* @param {array} childOptions - The child options.
* @returns {boolean} - True if the child options are visible, false otherwise.
*/
function hasVisibleOptions(user = null, childOptions = []) { function hasVisibleOptions(user = null, childOptions = []) {
if (!Array.isArray(childOptions) || childOptions?.length === 0) return false; if (!Array.isArray(childOptions) || childOptions?.length === 0) return false;
function isVisible({ roles = [], user = null, flex = false }) { function isVisible({
roles = [],
user = null,
flex = false,
hidden = false,
}) {
if (hidden) return false;
if (!flex && !roles.includes(user?.role)) return false; if (!flex && !roles.includes(user?.role)) return false;
if (flex && !!user && !roles.includes(user?.role)) return false; if (flex && !!user && !roles.includes(user?.role)) return false;
return true; return true;
} }
return childOptions.some((opt) => return childOptions.some((opt) =>
isVisible({ roles: opt.roles, user, flex: opt.flex }) isVisible({ roles: opt.roles, user, flex: opt.flex, hidden: opt.hidden })
); );
} }

View File

@ -21,6 +21,7 @@ import { useTranslation } from "react-i18next";
import showToast from "@/utils/toast"; import showToast from "@/utils/toast";
import System from "@/models/system"; import System from "@/models/system";
import Option from "./MenuOption"; import Option from "./MenuOption";
import { CanViewChatHistoryProvider } from "../CanViewChatHistory";
export default function SettingsSidebar() { export default function SettingsSidebar() {
const { t } = useTranslation(); const { t } = useTranslation();
@ -208,6 +209,8 @@ function SupportEmail() {
} }
const SidebarOptions = ({ user = null, t }) => ( const SidebarOptions = ({ user = null, t }) => (
<CanViewChatHistoryProvider>
{({ viewable: canViewChatHistory }) => (
<> <>
<Option <Option
btnText={t("settings.ai-providers")} btnText={t("settings.ai-providers")}
@ -268,6 +271,7 @@ const SidebarOptions = ({ user = null, t }) => (
roles: ["admin", "manager"], roles: ["admin", "manager"],
}, },
{ {
hidden: !canViewChatHistory,
btnText: t("settings.workspace-chats"), btnText: t("settings.workspace-chats"),
href: paths.settings.chats(), href: paths.settings.chats(),
flex: true, flex: true,
@ -278,11 +282,6 @@ const SidebarOptions = ({ user = null, t }) => (
href: paths.settings.invites(), href: paths.settings.invites(),
roles: ["admin", "manager"], roles: ["admin", "manager"],
}, },
{
btnText: t("settings.system"),
href: paths.settings.system(),
roles: ["admin", "manager"],
},
]} ]}
/> />
<Option <Option
@ -307,6 +306,7 @@ const SidebarOptions = ({ user = null, t }) => (
user={user} user={user}
childOptions={[ childOptions={[
{ {
hidden: !canViewChatHistory,
btnText: t("settings.embed-chats"), btnText: t("settings.embed-chats"),
href: paths.settings.embedChats(), href: paths.settings.embedChats(),
flex: true, flex: true,
@ -358,6 +358,8 @@ const SidebarOptions = ({ user = null, t }) => (
/> />
</HoldToReveal> </HoldToReveal>
</> </>
)}
</CanViewChatHistoryProvider>
); );
function HoldToReveal({ children, holdForMs = 3_000 }) { function HoldToReveal({ children, holdForMs = 3_000 }) {

View File

@ -0,0 +1,69 @@
import React from "react";
export default function OpenAiGenericTextToSpeechOptions({ settings }) {
return (
<div className="w-full flex flex-col gap-y-7">
<div className="flex gap-x-4">
<div className="flex flex-col w-60">
<div className="flex justify-between items-center mb-2">
<label className="text-white text-sm font-semibold">Base URL</label>
</div>
<input
type="url"
name="TTSOpenAICompatibleEndpoint"
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="http://localhost:7851/v1"
defaultValue={settings?.TTSOpenAICompatibleEndpoint}
required={false}
autoComplete="off"
spellCheck={false}
/>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
This should be the base URL of the OpenAI compatible TTS service you
will generate TTS responses from.
</p>
</div>
<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="TTSOpenAICompatibleKey"
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="API Key"
defaultValue={
settings?.TTSOpenAICompatibleKey ? "*".repeat(20) : ""
}
autoComplete="off"
spellCheck={false}
/>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Some TTS services require an API key to generate TTS responses -
this is optional if your service does not require one.
</p>
</div>
<div className="flex flex-col w-60">
<label className="text-white text-sm font-semibold block mb-3">
Voice Model
</label>
<input
type="text"
name="TTSOpenAICompatibleVoiceModel"
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="Your voice model identifier"
defaultValue={settings?.TTSOpenAICompatibleVoiceModel}
required={true}
autoComplete="off"
spellCheck={false}
/>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
Most TTS services will have several voice models available, this is
the identifier for the voice model you want to use.
</p>
</div>
</div>
</div>
);
}

View File

@ -135,7 +135,7 @@ export default function AccountModal({ user, hideModal }) {
autoComplete="off" autoComplete="off"
/> />
<p className="mt-2 text-xs text-white/60"> <p className="mt-2 text-xs text-white/60">
Username must be only contain lowercase letters, numbers, Username must only contain lowercase letters, numbers,
underscores, and hyphens with no spaces underscores, and hyphens with no spaces
</p> </p>
</div> </div>

View File

@ -23,6 +23,7 @@ export default function TTSMessage({ slug, chatId, message }) {
switch (provider) { switch (provider) {
case "openai": case "openai":
case "generic-openai":
case "elevenlabs": case "elevenlabs":
return <AsyncTTSMessage slug={slug} chatId={chatId} />; return <AsyncTTSMessage slug={slug} chatId={chatId} />;
case "piper_local": case "piper_local":

View File

@ -81,11 +81,13 @@ const HistoricalMessage = ({
<div className="flex flex-col items-center"> <div className="flex flex-col items-center">
<ProfileImage role={role} workspace={workspace} /> <ProfileImage role={role} workspace={workspace} />
<div className="mt-1 -mb-10"> <div className="mt-1 -mb-10">
{role === "assistant" && (
<TTSMessage <TTSMessage
slug={workspace?.slug} slug={workspace?.slug}
chatId={chatId} chatId={chatId}
message={message} message={message}
/> />
)}
</div> </div>
</div> </div>
{isEditing ? ( {isEditing ? (

View File

@ -30,7 +30,7 @@ export function DnDFileUploaderProvider({ workspace, children }) {
const { user } = useUser(); const { user } = useUser();
useEffect(() => { useEffect(() => {
if (!!user && user.role === "default") return false; if (!!user && user.role === "default") return;
System.checkDocumentProcessorOnline().then((status) => setReady(status)); System.checkDocumentProcessorOnline().then((status) => setReady(status));
}, [user]); }, [user]);

View File

@ -122,9 +122,22 @@ export default function PromptInput({
const pasteText = e.clipboardData.getData("text/plain"); const pasteText = e.clipboardData.getData("text/plain");
if (pasteText) { if (pasteText) {
const newPromptInput = promptInput + pasteText.trim(); const textarea = textareaRef.current;
const start = textarea.selectionStart;
const end = textarea.selectionEnd;
const newPromptInput =
promptInput.substring(0, start) +
pasteText +
promptInput.substring(end);
setPromptInput(newPromptInput); setPromptInput(newPromptInput);
onChange({ target: { value: newPromptInput } }); onChange({ target: { value: newPromptInput } });
// Set the cursor position after the pasted text
// we need to use setTimeout to prevent the cursor from being set to the end of the text
setTimeout(() => {
textarea.selectionStart = textarea.selectionEnd =
start + pasteText.length;
}, 0);
} }
return; return;
}; };

View File

@ -49,6 +49,7 @@ const PROVIDER_DEFAULT_MODELS = {
textgenwebui: [], textgenwebui: [],
"generic-openai": [], "generic-openai": [],
bedrock: [], bedrock: [],
xai: ["grok-beta"],
}; };
// For providers with large model lists (e.g. togetherAi) - we subgroup the options // For providers with large model lists (e.g. togetherAi) - we subgroup the options

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@ -9,6 +9,7 @@ const System = {
footerIcons: "anythingllm_footer_links", footerIcons: "anythingllm_footer_links",
supportEmail: "anythingllm_support_email", supportEmail: "anythingllm_support_email",
customAppName: "anythingllm_custom_app_name", customAppName: "anythingllm_custom_app_name",
canViewChatHistory: "anythingllm_can_view_chat_history",
}, },
ping: async function () { ping: async function () {
return await fetch(`${API_BASE}/ping`) return await fetch(`${API_BASE}/ping`)
@ -675,6 +676,36 @@ const System = {
return false; return false;
}); });
}, },
/**
* Fetches the can view chat history state from local storage or the system settings.
* Notice: This is an instance setting that cannot be changed via the UI and it is cached
* in local storage for 24 hours.
* @returns {Promise<{viewable: boolean, error: string | null}>}
*/
fetchCanViewChatHistory: async function () {
const cache = window.localStorage.getItem(
this.cacheKeys.canViewChatHistory
);
const { viewable, lastFetched } = cache
? safeJsonParse(cache, { viewable: false, lastFetched: 0 })
: { viewable: false, lastFetched: 0 };
// Since this is an instance setting that cannot be changed via the UI,
// we can cache it in local storage for a day and if the admin changes it,
// they should instruct the users to clear local storage.
if (typeof viewable === "boolean" && Date.now() - lastFetched < 8.64e7)
return { viewable, error: null };
const res = await System.keys();
const isViewable = res?.DisableViewChatHistory === false;
window.localStorage.setItem(
this.cacheKeys.canViewChatHistory,
JSON.stringify({ viewable: isViewable, lastFetched: Date.now() })
);
return { viewable: isViewable, error: null };
},
experimentalFeatures: { experimentalFeatures: {
liveSync: LiveDocumentSync, liveSync: LiveDocumentSync,
agentPlugins: AgentPlugins, agentPlugins: AgentPlugins,

View File

@ -281,3 +281,38 @@ export function SearXNGOptions({ settings }) {
</div> </div>
); );
} }
export function TavilySearchOptions({ settings }) {
return (
<>
<p className="text-sm text-white/60 my-2">
You can get an API key{" "}
<a
href="https://tavily.com/"
target="_blank"
rel="noreferrer"
className="text-blue-300 underline"
>
from Tavily.
</a>
</p>
<div className="flex gap-x-4">
<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="env::AgentTavilyApiKey"
className="border-none bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="Tavily API Key"
defaultValue={settings?.AgentTavilyApiKey ? "*".repeat(20) : ""}
required={true}
autoComplete="off"
spellCheck={false}
/>
</div>
</div>
</>
);
}

View File

@ -0,0 +1 @@
<svg xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" width="500" zoomAndPan="magnify" viewBox="0 0 375 374.999991" height="500" preserveAspectRatio="xMidYMid meet" version="1.0"><defs><clipPath id="d0348dc115"><path d="M 109.378906 231.132812 L 146.484375 231.132812 L 146.484375 268.238281 L 109.378906 268.238281 Z M 109.378906 231.132812 " clip-rule="nonzero"/></clipPath><clipPath id="a28b194a7a"><path d="M 127.933594 231.132812 C 117.6875 231.132812 109.378906 239.4375 109.378906 249.6875 C 109.378906 259.933594 117.6875 268.238281 127.933594 268.238281 C 138.179688 268.238281 146.484375 259.933594 146.484375 249.6875 C 146.484375 239.4375 138.179688 231.132812 127.933594 231.132812 Z M 127.933594 231.132812 " clip-rule="nonzero"/></clipPath></defs><path stroke-linecap="round" transform="matrix(0, -2.578223, 2.578223, 0, 113.745458, 254.140061)" fill="none" stroke-linejoin="miter" d="M 5.499573 5.500038 L 79.114962 5.500038 " stroke="#f25022" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(0, -2.578223, 2.578223, 0, 113.745458, 254.140061)" fill="none" stroke-linejoin="round" d="M 59.865692 -10.999336 L 81.864858 5.500038 L 59.865692 21.999412 " stroke="#f25022" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(2.578223, -0.000251357, 0.000251357, 2.578223, 126.828174, 239.987372)" fill="none" stroke-linejoin="miter" d="M 5.500751 5.50068 L 72.398214 5.499627 " stroke="#ffb901" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(2.578223, -0.000251357, 0.000251357, 2.578223, 126.828174, 239.987372)" fill="none" stroke-linejoin="round" d="M 53.149037 -11.000109 L 75.148109 5.499895 L 53.14885 22.000154 " stroke="#ffb901" stroke-width="11" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(-1.692446, 1.944957, -1.944957, -1.692446, 134.219043, 258.208373)" fill="none" stroke-linejoin="miter" d="M 4.499518 4.49999 L 38.441562 4.500107 " stroke="#04a3ec" stroke-width="9" stroke-opacity="1" stroke-miterlimit="4"/><path stroke-linecap="round" transform="matrix(-1.692446, 1.944957, -1.944957, -1.692446, 134.219043, 258.208373)" fill="none" stroke-linejoin="round" d="M 22.691248 -9.000192 L 40.69038 4.49943 L 22.68978 17.999994 " stroke="#04a3ec" stroke-width="9" stroke-opacity="1" stroke-miterlimit="4"/><g clip-path="url(#d0348dc115)"><g clip-path="url(#a28b194a7a)"><path fill="#32b37f" d="M 109.378906 231.132812 L 146.484375 231.132812 L 146.484375 268.238281 L 109.378906 268.238281 Z M 109.378906 231.132812 " fill-opacity="1" fill-rule="nonzero"/></g></g></svg>

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View File

@ -7,6 +7,7 @@ import SerperDotDevIcon from "./icons/serper.png";
import BingSearchIcon from "./icons/bing.png"; import BingSearchIcon from "./icons/bing.png";
import SerplySearchIcon from "./icons/serply.png"; import SerplySearchIcon from "./icons/serply.png";
import SearXNGSearchIcon from "./icons/searxng.png"; import SearXNGSearchIcon from "./icons/searxng.png";
import TavilySearchIcon from "./icons/tavily.svg";
import { import {
CaretUpDown, CaretUpDown,
MagnifyingGlass, MagnifyingGlass,
@ -22,6 +23,7 @@ import {
BingSearchOptions, BingSearchOptions,
SerplySearchOptions, SerplySearchOptions,
SearXNGOptions, SearXNGOptions,
TavilySearchOptions,
} from "./SearchProviderOptions"; } from "./SearchProviderOptions";
const SEARCH_PROVIDERS = [ const SEARCH_PROVIDERS = [
@ -81,6 +83,14 @@ const SEARCH_PROVIDERS = [
description: description:
"Free, open-source, internet meta-search engine with no tracking.", "Free, open-source, internet meta-search engine with no tracking.",
}, },
{
name: "Tavily Search",
value: "tavily-search",
logo: TavilySearchIcon,
options: (settings) => <TavilySearchOptions settings={settings} />,
description:
"Tavily Search API. Offers a free tier with 1000 queries per month.",
},
]; ];
export default function AgentWebSearchSelection({ export default function AgentWebSearchSelection({

View File

@ -1,128 +0,0 @@
import { useEffect, useState } from "react";
import Sidebar from "@/components/SettingsSidebar";
import { isMobile } from "react-device-detect";
import Admin from "@/models/admin";
import showToast from "@/utils/toast";
import CTAButton from "@/components/lib/CTAButton";
export default function AdminSystem() {
const [saving, setSaving] = useState(false);
const [hasChanges, setHasChanges] = useState(false);
const [messageLimit, setMessageLimit] = useState({
enabled: false,
limit: 10,
});
const handleSubmit = async (e) => {
e.preventDefault();
setSaving(true);
await Admin.updateSystemPreferences({
limit_user_messages: messageLimit.enabled,
message_limit: messageLimit.limit,
});
setSaving(false);
setHasChanges(false);
showToast("System preferences updated successfully.", "success");
};
useEffect(() => {
async function fetchSettings() {
const settings = (await Admin.systemPreferences())?.settings;
if (!settings) return;
setMessageLimit({
enabled: settings.limit_user_messages,
limit: settings.message_limit,
});
}
fetchSettings();
}, []);
return (
<div className="w-screen h-screen overflow-hidden bg-sidebar flex">
<Sidebar />
<div
style={{ height: isMobile ? "100%" : "calc(100% - 32px)" }}
className="relative md:ml-[2px] md:mr-[16px] md:my-[16px] md:rounded-[16px] bg-main-gradient w-full h-full overflow-y-scroll"
>
<form
onSubmit={handleSubmit}
onChange={() => setHasChanges(true)}
className="flex flex-col w-full px-1 md:pl-6 md:pr-[50px] md:py-6 py-16"
>
<div className="w-full flex flex-col gap-y-1 pb-6 border-white border-b-2 border-opacity-10">
<div className="items-center">
<p className="text-lg leading-6 font-bold text-white">
System Preferences
</p>
</div>
<p className="text-xs leading-[18px] font-base text-white text-opacity-60">
These are the overall settings and configurations of your
instance.
</p>
</div>
{hasChanges && (
<div className="flex justify-end">
<CTAButton onClick={handleSubmit} className="mt-3 mr-0">
{saving ? "Saving..." : "Save changes"}
</CTAButton>
</div>
)}
<div className="mt-4 mb-8">
<div className="flex flex-col gap-y-1">
<h2 className="text-base leading-6 font-bold text-white">
Limit messages per user per day
</h2>
<p className="text-xs leading-[18px] font-base text-white/60">
Restrict non-admin users to a number of successful queries or
chats within a 24 hour window. Enable this to prevent users from
running up OpenAI costs.
</p>
<div className="mt-2">
<label className="relative inline-flex cursor-pointer items-center">
<input
type="checkbox"
name="limit_user_messages"
value="yes"
checked={messageLimit.enabled}
onChange={(e) => {
setMessageLimit({
...messageLimit,
enabled: e.target.checked,
});
}}
className="peer sr-only"
/>
<div className="pointer-events-none peer h-6 w-11 rounded-full bg-stone-400 after:absolute after:left-[2px] after:top-[2px] after:h-5 after:w-5 after:rounded-full after:shadow-xl after:border after:border-gray-600 after:bg-white after:box-shadow-md after:transition-all after:content-[''] peer-checked:bg-lime-300 peer-checked:after:translate-x-full peer-checked:after:border-white peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-blue-800"></div>
<span className="ml-3 text-sm font-medium text-gray-900 dark:text-gray-300"></span>
</label>
</div>
</div>
{messageLimit.enabled && (
<div className="mt-4">
<label className="text-white text-sm font-semibold block mb-4">
Message limit per day
</label>
<div className="relative mt-2">
<input
type="number"
name="message_limit"
onScroll={(e) => e.target.blur()}
onChange={(e) => {
setMessageLimit({
enabled: true,
limit: Number(e?.target?.value || 0),
});
}}
value={messageLimit.limit}
min={1}
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:border-white block w-60 p-2.5"
/>
</div>
</div>
)}
</div>
</form>
</div>
</div>
);
}

View File

@ -2,11 +2,15 @@ import React, { useState } from "react";
import { X } from "@phosphor-icons/react"; import { X } from "@phosphor-icons/react";
import Admin from "@/models/admin"; import Admin from "@/models/admin";
import { userFromStorage } from "@/utils/request"; import { userFromStorage } from "@/utils/request";
import { RoleHintDisplay } from ".."; import { MessageLimitInput, RoleHintDisplay } from "..";
export default function NewUserModal({ closeModal }) { export default function NewUserModal({ closeModal }) {
const [error, setError] = useState(null); const [error, setError] = useState(null);
const [role, setRole] = useState("default"); const [role, setRole] = useState("default");
const [messageLimit, setMessageLimit] = useState({
enabled: false,
limit: 10,
});
const handleCreate = async (e) => { const handleCreate = async (e) => {
setError(null); setError(null);
@ -14,6 +18,8 @@ export default function NewUserModal({ closeModal }) {
const data = {}; const data = {};
const form = new FormData(e.target); const form = new FormData(e.target);
for (var [key, value] of form.entries()) data[key] = value; for (var [key, value] of form.entries()) data[key] = value;
data.dailyMessageLimit = messageLimit.enabled ? messageLimit.limit : null;
const { user, error } = await Admin.newUser(data); const { user, error } = await Admin.newUser(data);
if (!!user) window.location.reload(); if (!!user) window.location.reload();
setError(error); setError(error);
@ -58,13 +64,13 @@ export default function NewUserModal({ closeModal }) {
pattern="^[a-z0-9_-]+$" pattern="^[a-z0-9_-]+$"
onInvalid={(e) => onInvalid={(e) =>
e.target.setCustomValidity( e.target.setCustomValidity(
"Username must be only contain lowercase letters, numbers, underscores, and hyphens with no spaces" "Username must only contain lowercase letters, numbers, underscores, and hyphens with no spaces"
) )
} }
onChange={(e) => e.target.setCustomValidity("")} onChange={(e) => e.target.setCustomValidity("")}
/> />
<p className="mt-2 text-xs text-white/60"> <p className="mt-2 text-xs text-white/60">
Username must be only contain lowercase letters, numbers, Username must only contain lowercase letters, numbers,
underscores, and hyphens with no spaces underscores, and hyphens with no spaces
</p> </p>
</div> </div>
@ -110,6 +116,12 @@ export default function NewUserModal({ closeModal }) {
</select> </select>
<RoleHintDisplay role={role} /> <RoleHintDisplay role={role} />
</div> </div>
<MessageLimitInput
role={role}
enabled={messageLimit.enabled}
limit={messageLimit.limit}
updateState={setMessageLimit}
/>
{error && <p className="text-red-400 text-sm">Error: {error}</p>} {error && <p className="text-red-400 text-sm">Error: {error}</p>}
<p className="text-white text-xs md:text-sm"> <p className="text-white text-xs md:text-sm">
After creating a user they will need to login with their initial After creating a user they will need to login with their initial

View File

@ -1,11 +1,15 @@
import React, { useState } from "react"; import React, { useState } from "react";
import { X } from "@phosphor-icons/react"; import { X } from "@phosphor-icons/react";
import Admin from "@/models/admin"; import Admin from "@/models/admin";
import { RoleHintDisplay } from "../.."; import { MessageLimitInput, RoleHintDisplay } from "../..";
export default function EditUserModal({ currentUser, user, closeModal }) { export default function EditUserModal({ currentUser, user, closeModal }) {
const [role, setRole] = useState(user.role); const [role, setRole] = useState(user.role);
const [error, setError] = useState(null); const [error, setError] = useState(null);
const [messageLimit, setMessageLimit] = useState({
enabled: user.dailyMessageLimit !== null,
limit: user.dailyMessageLimit || 10,
});
const handleUpdate = async (e) => { const handleUpdate = async (e) => {
setError(null); setError(null);
@ -16,6 +20,12 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
if (!value || value === null) continue; if (!value || value === null) continue;
data[key] = value; data[key] = value;
} }
if (messageLimit.enabled) {
data.dailyMessageLimit = messageLimit.limit;
} else {
data.dailyMessageLimit = null;
}
const { success, error } = await Admin.updateUser(user.id, data); const { success, error } = await Admin.updateUser(user.id, data);
if (success) window.location.reload(); if (success) window.location.reload();
setError(error); setError(error);
@ -58,7 +68,7 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
autoComplete="off" autoComplete="off"
/> />
<p className="mt-2 text-xs text-white/60"> <p className="mt-2 text-xs text-white/60">
Username must be only contain lowercase letters, numbers, Username must only contain lowercase letters, numbers,
underscores, and hyphens with no spaces underscores, and hyphens with no spaces
</p> </p>
</div> </div>
@ -103,6 +113,12 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
</select> </select>
<RoleHintDisplay role={role} /> <RoleHintDisplay role={role} />
</div> </div>
<MessageLimitInput
role={role}
enabled={messageLimit.enabled}
limit={messageLimit.limit}
updateState={setMessageLimit}
/>
{error && <p className="text-red-400 text-sm">Error: {error}</p>} {error && <p className="text-red-400 text-sm">Error: {error}</p>}
</div> </div>
</div> </div>

View File

@ -135,3 +135,58 @@ export function RoleHintDisplay({ role }) {
</div> </div>
); );
} }
export function MessageLimitInput({ enabled, limit, updateState, role }) {
if (role === "admin") return null;
return (
<div className="mt-4 mb-8">
<div className="flex flex-col gap-y-1">
<div className="flex items-center gap-x-2">
<h2 className="text-base leading-6 font-bold text-white">
Limit messages per day
</h2>
<label className="relative inline-flex cursor-pointer items-center">
<input
type="checkbox"
checked={enabled}
onChange={(e) => {
updateState((prev) => ({
...prev,
enabled: e.target.checked,
}));
}}
className="peer sr-only"
/>
<div className="pointer-events-none peer h-6 w-11 rounded-full bg-stone-400 after:absolute after:left-[2px] after:top-[2px] after:h-5 after:w-5 after:rounded-full after:shadow-xl after:border after:border-gray-600 after:bg-white after:box-shadow-md after:transition-all after:content-[''] peer-checked:bg-lime-300 peer-checked:after:translate-x-full peer-checked:after:border-white peer-focus:outline-none peer-focus:ring-4 peer-focus:ring-blue-800"></div>
</label>
</div>
<p className="text-xs leading-[18px] font-base text-white/60">
Restrict this user to a number of successful queries or chats within a
24 hour window.
</p>
</div>
{enabled && (
<div className="mt-4">
<label className="text-white text-sm font-semibold block mb-4">
Message limit per day
</label>
<div className="relative mt-2">
<input
type="number"
onScroll={(e) => e.target.blur()}
onChange={(e) => {
updateState({
enabled: true,
limit: Number(e?.target?.value || 0),
});
}}
value={limit}
min={1}
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:border-white block w-60 p-2.5"
/>
</div>
</div>
)}
</div>
);
}

View File

@ -8,10 +8,13 @@ import OpenAiLogo from "@/media/llmprovider/openai.png";
import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png"; import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
import ElevenLabsIcon from "@/media/ttsproviders/elevenlabs.png"; import ElevenLabsIcon from "@/media/ttsproviders/elevenlabs.png";
import PiperTTSIcon from "@/media/ttsproviders/piper.png"; import PiperTTSIcon from "@/media/ttsproviders/piper.png";
import GenericOpenAiLogo from "@/media/ttsproviders/generic-openai.png";
import BrowserNative from "@/components/TextToSpeech/BrowserNative"; import BrowserNative from "@/components/TextToSpeech/BrowserNative";
import OpenAiTTSOptions from "@/components/TextToSpeech/OpenAiOptions"; import OpenAiTTSOptions from "@/components/TextToSpeech/OpenAiOptions";
import ElevenLabsTTSOptions from "@/components/TextToSpeech/ElevenLabsOptions"; import ElevenLabsTTSOptions from "@/components/TextToSpeech/ElevenLabsOptions";
import PiperTTSOptions from "@/components/TextToSpeech/PiperTTSOptions"; import PiperTTSOptions from "@/components/TextToSpeech/PiperTTSOptions";
import OpenAiGenericTTSOptions from "@/components/TextToSpeech/OpenAiGenericOptions";
const PROVIDERS = [ const PROVIDERS = [
{ {
@ -42,6 +45,14 @@ const PROVIDERS = [
options: (settings) => <PiperTTSOptions settings={settings} />, options: (settings) => <PiperTTSOptions settings={settings} />,
description: "Run TTS models locally in your browser privately.", description: "Run TTS models locally in your browser privately.",
}, },
{
name: "OpenAI Compatible",
value: "generic-openai",
logo: GenericOpenAiLogo,
options: (settings) => <OpenAiGenericTTSOptions settings={settings} />,
description:
"Connect to an OpenAI compatible TTS service running locally or remotely.",
},
]; ];
export default function TextToSpeechProvider({ settings }) { export default function TextToSpeechProvider({ settings }) {

View File

@ -11,6 +11,7 @@ import { CaretDown, Download, Sparkle, Trash } from "@phosphor-icons/react";
import { saveAs } from "file-saver"; import { saveAs } from "file-saver";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import paths from "@/utils/paths"; import paths from "@/utils/paths";
import { CanViewChatHistory } from "@/components/CanViewChatHistory";
const exportOptions = { const exportOptions = {
csv: { csv: {
@ -106,7 +107,8 @@ export default function WorkspaceChats() {
useEffect(() => { useEffect(() => {
async function fetchChats() { async function fetchChats() {
const { chats: _chats, hasPages = false } = await System.chats(offset); const { chats: _chats = [], hasPages = false } =
await System.chats(offset);
setChats(_chats); setChats(_chats);
setCanNext(hasPages); setCanNext(hasPages);
setLoading(false); setLoading(false);
@ -115,6 +117,7 @@ export default function WorkspaceChats() {
}, [offset]); }, [offset]);
return ( return (
<CanViewChatHistory>
<div className="w-screen h-screen overflow-hidden bg-sidebar flex"> <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
<Sidebar /> <Sidebar />
<div <div
@ -194,6 +197,7 @@ export default function WorkspaceChats() {
</div> </div>
</div> </div>
</div> </div>
</CanViewChatHistory>
); );
} }

View File

@ -11,6 +11,7 @@ import { CaretDown, Download } from "@phosphor-icons/react";
import showToast from "@/utils/toast"; import showToast from "@/utils/toast";
import { saveAs } from "file-saver"; import { saveAs } from "file-saver";
import System from "@/models/system"; import System from "@/models/system";
import { CanViewChatHistory } from "@/components/CanViewChatHistory";
const exportOptions = { const exportOptions = {
csv: { csv: {
@ -88,6 +89,7 @@ export default function EmbedChats() {
}, []); }, []);
return ( return (
<CanViewChatHistory>
<div className="w-screen h-screen overflow-hidden bg-sidebar flex"> <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
<Sidebar /> <Sidebar />
<div <div
@ -141,6 +143,7 @@ export default function EmbedChats() {
</div> </div>
</div> </div>
</div> </div>
</CanViewChatHistory>
); );
} }

View File

@ -25,6 +25,8 @@ import CohereLogo from "@/media/llmprovider/cohere.png";
import LiteLLMLogo from "@/media/llmprovider/litellm.png"; import LiteLLMLogo from "@/media/llmprovider/litellm.png";
import AWSBedrockLogo from "@/media/llmprovider/bedrock.png"; import AWSBedrockLogo from "@/media/llmprovider/bedrock.png";
import DeepSeekLogo from "@/media/llmprovider/deepseek.png"; import DeepSeekLogo from "@/media/llmprovider/deepseek.png";
import APIPieLogo from "@/media/llmprovider/apipie.png";
import XAILogo from "@/media/llmprovider/xai.png";
import PreLoader from "@/components/Preloader"; import PreLoader from "@/components/Preloader";
import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions"; import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
@ -48,6 +50,8 @@ import TextGenWebUIOptions from "@/components/LLMSelection/TextGenWebUIOptions";
import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions"; import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions";
import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions"; import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions";
import DeepSeekOptions from "@/components/LLMSelection/DeepSeekOptions"; import DeepSeekOptions from "@/components/LLMSelection/DeepSeekOptions";
import ApiPieLLMOptions from "@/components/LLMSelection/ApiPieOptions";
import XAILLMOptions from "@/components/LLMSelection/XAiLLMOptions";
import LLMItem from "@/components/LLMSelection/LLMItem"; import LLMItem from "@/components/LLMSelection/LLMItem";
import { CaretUpDown, MagnifyingGlass, X } from "@phosphor-icons/react"; import { CaretUpDown, MagnifyingGlass, X } from "@phosphor-icons/react";
@ -219,6 +223,27 @@ export const AVAILABLE_LLM_PROVIDERS = [
description: "Run DeepSeek's powerful LLMs.", description: "Run DeepSeek's powerful LLMs.",
requiredConfig: ["DeepSeekApiKey"], requiredConfig: ["DeepSeekApiKey"],
}, },
{
name: "AWS Bedrock",
value: "bedrock",
logo: AWSBedrockLogo,
options: (settings) => <AWSBedrockLLMOptions settings={settings} />,
description: "Run powerful foundation models privately with AWS Bedrock.",
requiredConfig: [
"AwsBedrockLLMAccessKeyId",
"AwsBedrockLLMAccessKey",
"AwsBedrockLLMRegion",
"AwsBedrockLLMModel",
],
},
{
name: "APIpie",
value: "apipie",
logo: APIPieLogo,
options: (settings) => <ApiPieLLMOptions settings={settings} />,
description: "A unified API of AI services from leading providers",
requiredConfig: ["ApipieLLMApiKey", "ApipieLLMModelPref"],
},
{ {
name: "Generic OpenAI", name: "Generic OpenAI",
value: "generic-openai", value: "generic-openai",
@ -243,17 +268,12 @@ export const AVAILABLE_LLM_PROVIDERS = [
// requiredConfig: [], // requiredConfig: [],
// }, // },
{ {
name: "AWS Bedrock", name: "xAI",
value: "bedrock", value: "xai",
logo: AWSBedrockLogo, logo: XAILogo,
options: (settings) => <AWSBedrockLLMOptions settings={settings} />, options: (settings) => <XAILLMOptions settings={settings} />,
description: "Run powerful foundation models privately with AWS Bedrock.", description: "Run xAI's powerful LLMs like Grok-2 and more.",
requiredConfig: [ requiredConfig: ["XAIApiKey", "XAIModelPref"],
"AwsBedrockLLMAccessKeyId",
"AwsBedrockLLMAccessKey",
"AwsBedrockLLMRegion",
"AwsBedrockLLMModel",
],
}, },
]; ];

View File

@ -21,6 +21,8 @@ import TextGenWebUILogo from "@/media/llmprovider/text-generation-webui.png";
import LiteLLMLogo from "@/media/llmprovider/litellm.png"; import LiteLLMLogo from "@/media/llmprovider/litellm.png";
import AWSBedrockLogo from "@/media/llmprovider/bedrock.png"; import AWSBedrockLogo from "@/media/llmprovider/bedrock.png";
import DeepSeekLogo from "@/media/llmprovider/deepseek.png"; import DeepSeekLogo from "@/media/llmprovider/deepseek.png";
import APIPieLogo from "@/media/llmprovider/apipie.png";
import XAILogo from "@/media/llmprovider/xai.png";
import CohereLogo from "@/media/llmprovider/cohere.png"; import CohereLogo from "@/media/llmprovider/cohere.png";
import ZillizLogo from "@/media/vectordbs/zilliz.png"; import ZillizLogo from "@/media/vectordbs/zilliz.png";
@ -202,6 +204,20 @@ export const LLM_SELECTION_PRIVACY = {
description: ["Your model and chat contents are visible to DeepSeek"], description: ["Your model and chat contents are visible to DeepSeek"],
logo: DeepSeekLogo, logo: DeepSeekLogo,
}, },
apipie: {
name: "APIpie.AI",
description: [
"Your model and chat contents are visible to APIpie in accordance with their terms of service.",
],
logo: APIPieLogo,
},
xai: {
name: "xAI",
description: [
"Your model and chat contents are visible to xAI in accordance with their terms of service.",
],
logo: XAILogo,
},
}; };
export const VECTOR_DB_PRIVACY = { export const VECTOR_DB_PRIVACY = {

View File

@ -20,6 +20,8 @@ import TextGenWebUILogo from "@/media/llmprovider/text-generation-webui.png";
import LiteLLMLogo from "@/media/llmprovider/litellm.png"; import LiteLLMLogo from "@/media/llmprovider/litellm.png";
import AWSBedrockLogo from "@/media/llmprovider/bedrock.png"; import AWSBedrockLogo from "@/media/llmprovider/bedrock.png";
import DeepSeekLogo from "@/media/llmprovider/deepseek.png"; import DeepSeekLogo from "@/media/llmprovider/deepseek.png";
import APIPieLogo from "@/media/llmprovider/apipie.png";
import XAILogo from "@/media/llmprovider/xai.png";
import CohereLogo from "@/media/llmprovider/cohere.png"; import CohereLogo from "@/media/llmprovider/cohere.png";
import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions"; import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
@ -43,6 +45,8 @@ import TextGenWebUIOptions from "@/components/LLMSelection/TextGenWebUIOptions";
import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions"; import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions";
import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions"; import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions";
import DeepSeekOptions from "@/components/LLMSelection/DeepSeekOptions"; import DeepSeekOptions from "@/components/LLMSelection/DeepSeekOptions";
import ApiPieLLMOptions from "@/components/LLMSelection/ApiPieOptions";
import XAILLMOptions from "@/components/LLMSelection/XAiLLMOptions";
import LLMItem from "@/components/LLMSelection/LLMItem"; import LLMItem from "@/components/LLMSelection/LLMItem";
import System from "@/models/system"; import System from "@/models/system";
@ -193,6 +197,13 @@ const LLMS = [
options: (settings) => <DeepSeekOptions settings={settings} />, options: (settings) => <DeepSeekOptions settings={settings} />,
description: "Run DeepSeek's powerful LLMs.", description: "Run DeepSeek's powerful LLMs.",
}, },
{
name: "APIpie",
value: "apipie",
logo: APIPieLogo,
options: (settings) => <ApiPieLLMOptions settings={settings} />,
description: "A unified API of AI services from leading providers",
},
{ {
name: "Generic OpenAI", name: "Generic OpenAI",
value: "generic-openai", value: "generic-openai",
@ -216,6 +227,13 @@ const LLMS = [
options: (settings) => <AWSBedrockLLMOptions settings={settings} />, options: (settings) => <AWSBedrockLLMOptions settings={settings} />,
description: "Run powerful foundation models privately with AWS Bedrock.", description: "Run powerful foundation models privately with AWS Bedrock.",
}, },
{
name: "xAI",
value: "xai",
logo: XAILogo,
options: (settings) => <XAILLMOptions settings={settings} />,
description: "Run xAI's powerful LLMs like Grok-2 and more.",
},
]; ];
export default function LLMPreference({ export default function LLMPreference({

View File

@ -24,6 +24,9 @@ const ENABLED_PROVIDERS = [
"bedrock", "bedrock",
"fireworksai", "fireworksai",
"deepseek", "deepseek",
"litellm",
"apipie",
"xai",
// TODO: More agent support. // TODO: More agent support.
// "cohere", // Has tool calling and will need to build explicit support // "cohere", // Has tool calling and will need to build explicit support
// "huggingface" // Can be done but already has issues with no-chat templated. Needs to be tested. // "huggingface" // Can be done but already has issues with no-chat templated. Needs to be tested.

View File

@ -5,14 +5,30 @@ import paths from "@/utils/paths";
import { useTranslation } from "react-i18next"; import { useTranslation } from "react-i18next";
import { Link, useParams } from "react-router-dom"; import { Link, useParams } from "react-router-dom";
// These models do NOT support function calling /**
* These models do NOT support function calling
* or do not support system prompts
* and therefore are not supported for agents.
* @param {string} provider - The AI provider.
* @param {string} model - The model name.
* @returns {boolean} Whether the model is supported for agents.
*/
function supportedModel(provider, model = "") { function supportedModel(provider, model = "") {
if (provider !== "openai") return true; if (provider === "openai") {
return ( return (
["gpt-3.5-turbo-0301", "gpt-4-turbo-2024-04-09", "gpt-4-turbo"].includes( [
model "gpt-3.5-turbo-0301",
) === false "gpt-4-turbo-2024-04-09",
"gpt-4-turbo",
"o1-preview",
"o1-preview-2024-09-12",
"o1-mini",
"o1-mini-2024-09-12",
].includes(model) === false
); );
}
return true;
} }
export default function AgentModelSelection({ export default function AgentModelSelection({

View File

@ -8,8 +8,10 @@ import Admin from "@/models/admin";
import * as Skeleton from "react-loading-skeleton"; import * as Skeleton from "react-loading-skeleton";
import "react-loading-skeleton/dist/skeleton.css"; import "react-loading-skeleton/dist/skeleton.css";
import paths from "@/utils/paths"; import paths from "@/utils/paths";
import useUser from "@/hooks/useUser";
export default function WorkspaceAgentConfiguration({ workspace }) { export default function WorkspaceAgentConfiguration({ workspace }) {
const { user } = useUser();
const [settings, setSettings] = useState({}); const [settings, setSettings] = useState({});
const [hasChanges, setHasChanges] = useState(false); const [hasChanges, setHasChanges] = useState(false);
const [saving, setSaving] = useState(false); const [saving, setSaving] = useState(false);
@ -84,6 +86,8 @@ export default function WorkspaceAgentConfiguration({ workspace }) {
workspace={workspace} workspace={workspace}
setHasChanges={setHasChanges} setHasChanges={setHasChanges}
/> />
{(!user || user?.role === "admin") && (
<>
{!hasChanges && ( {!hasChanges && (
<div className="flex flex-col gap-y-4"> <div className="flex flex-col gap-y-4">
<a <a
@ -93,12 +97,15 @@ export default function WorkspaceAgentConfiguration({ workspace }) {
Configure Agent Skills Configure Agent Skills
</a> </a>
<p className="text-white text-opacity-60 text-xs font-medium"> <p className="text-white text-opacity-60 text-xs font-medium">
Customize and enhance the default agent's capabilities by enabling Customize and enhance the default agent's capabilities by
or disabling specific skills. These settings will be applied enabling or disabling specific skills. These settings will be
across all workspaces. applied across all workspaces.
</p> </p>
</div> </div>
)} )}
</>
)}
{hasChanges && ( {hasChanges && (
<button <button
type="submit" type="submit"

View File

@ -8,15 +8,18 @@ import { useTranslation } from "react-i18next";
import { Link } from "react-router-dom"; import { Link } from "react-router-dom";
import paths from "@/utils/paths"; import paths from "@/utils/paths";
// Some providers can only be associated with a single model. // Some providers do not support model selection via /models.
// In that case there is no selection to be made so we can just move on. // In that case we allow the user to enter the model name manually and hope they
const NO_MODEL_SELECTION = [ // type it correctly.
"default", const FREE_FORM_LLM_SELECTION = ["bedrock", "azure", "generic-openai"];
"huggingface",
"generic-openai", // Some providers do not support model selection via /models
"bedrock", // and only have a fixed single-model they can use.
]; const NO_MODEL_SELECTION = ["default", "huggingface"];
const DISABLED_PROVIDERS = ["azure", "native"];
// Some providers we just fully disable for ease of use.
const DISABLED_PROVIDERS = ["native"];
const LLM_DEFAULT = { const LLM_DEFAULT = {
name: "System default", name: "System default",
value: "default", value: "default",
@ -65,8 +68,8 @@ export default function WorkspaceLLMSelection({
); );
setFilteredLLMs(filtered); setFilteredLLMs(filtered);
}, [LLMS, searchQuery, selectedLLM]); }, [LLMS, searchQuery, selectedLLM]);
const selectedLLMObject = LLMS.find((llm) => llm.value === selectedLLM); const selectedLLMObject = LLMS.find((llm) => llm.value === selectedLLM);
return ( return (
<div className="border-b border-white/40 pb-8"> <div className="border-b border-white/40 pb-8">
<div className="flex flex-col"> <div className="flex flex-col">
@ -155,9 +158,20 @@ export default function WorkspaceLLMSelection({
</button> </button>
)} )}
</div> </div>
{NO_MODEL_SELECTION.includes(selectedLLM) ? ( <ModelSelector
<> selectedLLM={selectedLLM}
{selectedLLM !== "default" && ( workspace={workspace}
setHasChanges={setHasChanges}
/>
</div>
);
}
// TODO: Add this to agent selector as well as make generic component.
function ModelSelector({ selectedLLM, workspace, setHasChanges }) {
if (NO_MODEL_SELECTION.includes(selectedLLM)) {
if (selectedLLM !== "default") {
return (
<div className="w-full h-10 justify-center items-center flex mt-4"> <div className="w-full h-10 justify-center items-center flex mt-4">
<p className="text-sm font-base text-white text-opacity-60 text-center"> <p className="text-sm font-base text-white text-opacity-60 text-center">
Multi-model support is not supported for this provider yet. Multi-model support is not supported for this provider yet.
@ -168,17 +182,42 @@ export default function WorkspaceLLMSelection({
</Link> </Link>
</p> </p>
</div> </div>
)} );
</> }
) : ( return null;
<div className="mt-4 flex flex-col gap-y-1"> }
if (FREE_FORM_LLM_SELECTION.includes(selectedLLM)) {
return (
<FreeFormLLMInput workspace={workspace} setHasChanges={setHasChanges} />
);
}
return (
<ChatModelSelection <ChatModelSelection
provider={selectedLLM} provider={selectedLLM}
workspace={workspace} workspace={workspace}
setHasChanges={setHasChanges} setHasChanges={setHasChanges}
/> />
</div> );
)} }
function FreeFormLLMInput({ workspace, setHasChanges }) {
const { t } = useTranslation();
return (
<div className="mt-4 flex flex-col gap-y-1">
<label className="block input-label">{t("chat.model.title")}</label>
<p className="text-white text-opacity-60 text-xs font-medium py-1.5">
{t("chat.model.description")}
</p>
<input
type="text"
name="chatModel"
defaultValue={workspace?.chatModel || ""}
onChange={() => setHasChanges(true)}
className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
placeholder="Enter model name exactly as referenced in the API (e.g., gpt-3.5-turbo)"
/>
</div> </div>
); );
} }

View File

@ -80,9 +80,6 @@ export default {
return `/fine-tuning`; return `/fine-tuning`;
}, },
settings: { settings: {
system: () => {
return `/settings/system-preferences`;
},
users: () => { users: () => {
return `/settings/users`; return `/settings/users`;
}, },

View File

@ -95,6 +95,14 @@ SIG_SALT='salt' # Please generate random string at least 32 chars long.
# COHERE_API_KEY= # COHERE_API_KEY=
# COHERE_MODEL_PREF='command-r' # COHERE_MODEL_PREF='command-r'
# LLM_PROVIDER='apipie'
# APIPIE_LLM_API_KEY='sk-123abc'
# APIPIE_LLM_MODEL_PREF='openrouter/llama-3.1-8b-instruct'
# LLM_PROVIDER='xai'
# XAI_LLM_API_KEY='xai-your-api-key-here'
# XAI_LLM_MODEL_PREF='grok-beta'
########################################### ###########################################
######## Embedding API SElECTION ########## ######## Embedding API SElECTION ##########
########################################### ###########################################
@ -209,6 +217,11 @@ TTS_PROVIDER="native"
# TTS_ELEVEN_LABS_KEY= # TTS_ELEVEN_LABS_KEY=
# TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel # TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel
# TTS_PROVIDER="generic-openai"
# TTS_OPEN_AI_COMPATIBLE_KEY=sk-example
# TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL=nova
# TTS_OPEN_AI_COMPATIBLE_ENDPOINT="https://api.openai.com/v1"
# CLOUD DEPLOYMENT VARIRABLES ONLY # CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting. # AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
# STORAGE_DIR= # absolute filesystem path with no trailing slash # STORAGE_DIR= # absolute filesystem path with no trailing slash
@ -260,3 +273,11 @@ TTS_PROVIDER="native"
#------ SearXNG ----------- https://github.com/searxng/searxng #------ SearXNG ----------- https://github.com/searxng/searxng
# AGENT_SEARXNG_API_URL= # AGENT_SEARXNG_API_URL=
###########################################
######## Other Configurations ############
###########################################
# Disable viewing chat history from the UI and frontend APIs.
# See https://docs.anythingllm.com/configuration#disable-view-chat-history for more information.
# DISABLE_VIEW_CHAT_HISTORY=1

View File

@ -347,14 +347,6 @@ function adminEndpoints(app) {
: await SystemSettings.get({ label }); : await SystemSettings.get({ label });
switch (label) { switch (label) {
case "limit_user_messages":
requestedSettings[label] = setting?.value === "true";
break;
case "message_limit":
requestedSettings[label] = setting?.value
? Number(setting.value)
: 10;
break;
case "footer_data": case "footer_data":
requestedSettings[label] = setting?.value ?? JSON.stringify([]); requestedSettings[label] = setting?.value ?? JSON.stringify([]);
break; break;
@ -422,13 +414,6 @@ function adminEndpoints(app) {
try { try {
const embedder = getEmbeddingEngineSelection(); const embedder = getEmbeddingEngineSelection();
const settings = { const settings = {
limit_user_messages:
(await SystemSettings.get({ label: "limit_user_messages" }))
?.value === "true",
message_limit:
Number(
(await SystemSettings.get({ label: "message_limit" }))?.value
) || 10,
footer_data: footer_data:
(await SystemSettings.get({ label: "footer_data" }))?.value || (await SystemSettings.get({ label: "footer_data" }))?.value ||
JSON.stringify([]), JSON.stringify([]),

View File

@ -595,56 +595,6 @@ function apiAdminEndpoints(app) {
} }
); );
app.get("/v1/admin/preferences", [validApiKey], async (request, response) => {
/*
#swagger.tags = ['Admin']
#swagger.description = 'Show all multi-user preferences for instance. Methods are disabled until multi user mode is enabled via the UI.'
#swagger.responses[200] = {
content: {
"application/json": {
schema: {
type: 'object',
example: {
settings: {
limit_user_messages: false,
message_limit: 10,
}
}
}
}
}
}
#swagger.responses[403] = {
schema: {
"$ref": "#/definitions/InvalidAPIKey"
}
}
#swagger.responses[401] = {
description: "Instance is not in Multi-User mode. Method denied",
}
*/
try {
if (!multiUserMode(response)) {
response.sendStatus(401).end();
return;
}
const settings = {
limit_user_messages:
(await SystemSettings.get({ label: "limit_user_messages" }))
?.value === "true",
message_limit:
Number(
(await SystemSettings.get({ label: "message_limit" }))?.value
) || 10,
};
response.status(200).json({ settings });
} catch (e) {
console.error(e);
response.sendStatus(500).end();
}
});
app.post( app.post(
"/v1/admin/preferences", "/v1/admin/preferences",
[validApiKey], [validApiKey],
@ -658,8 +608,7 @@ function apiAdminEndpoints(app) {
content: { content: {
"application/json": { "application/json": {
example: { example: {
limit_user_messages: true, support_email: "support@example.com",
message_limit: 5,
} }
} }
} }

View File

@ -31,12 +31,14 @@ function apiWorkspaceThreadEndpoints(app) {
type: 'string' type: 'string'
} }
#swagger.requestBody = { #swagger.requestBody = {
description: 'Optional userId associated with the thread', description: 'Optional userId associated with the thread, thread slug and thread name',
required: false, required: false,
content: { content: {
"application/json": { "application/json": {
example: { example: {
userId: 1 userId: 1,
name: 'Name',
slug: 'thread-slug'
} }
} }
} }
@ -67,9 +69,9 @@ function apiWorkspaceThreadEndpoints(app) {
} }
*/ */
try { try {
const { slug } = request.params; const wslug = request.params.slug;
let { userId = null } = reqBody(request); let { userId = null, name = null, slug = null } = reqBody(request);
const workspace = await Workspace.get({ slug }); const workspace = await Workspace.get({ slug: wslug });
if (!workspace) { if (!workspace) {
response.sendStatus(400).end(); response.sendStatus(400).end();
@ -83,7 +85,8 @@ function apiWorkspaceThreadEndpoints(app) {
const { thread, message } = await WorkspaceThread.new( const { thread, message } = await WorkspaceThread.new(
workspace, workspace,
userId ? Number(userId) : null userId ? Number(userId) : null,
{ name, slug }
); );
await Telemetry.sendTelemetry("workspace_thread_created", { await Telemetry.sendTelemetry("workspace_thread_created", {

View File

@ -1,8 +1,6 @@
const { v4: uuidv4 } = require("uuid"); const { v4: uuidv4 } = require("uuid");
const { reqBody, userFromSession, multiUserMode } = require("../utils/http"); const { reqBody, userFromSession, multiUserMode } = require("../utils/http");
const { validatedRequest } = require("../utils/middleware/validatedRequest"); const { validatedRequest } = require("../utils/middleware/validatedRequest");
const { WorkspaceChats } = require("../models/workspaceChats");
const { SystemSettings } = require("../models/systemSettings");
const { Telemetry } = require("../models/telemetry"); const { Telemetry } = require("../models/telemetry");
const { streamChatWithWorkspace } = require("../utils/chats/stream"); const { streamChatWithWorkspace } = require("../utils/chats/stream");
const { const {
@ -16,6 +14,7 @@ const {
} = require("../utils/middleware/validWorkspace"); } = require("../utils/middleware/validWorkspace");
const { writeResponseChunk } = require("../utils/helpers/chat/responses"); const { writeResponseChunk } = require("../utils/helpers/chat/responses");
const { WorkspaceThread } = require("../models/workspaceThread"); const { WorkspaceThread } = require("../models/workspaceThread");
const { User } = require("../models/user");
const truncate = require("truncate"); const truncate = require("truncate");
function chatEndpoints(app) { function chatEndpoints(app) {
@ -48,40 +47,17 @@ function chatEndpoints(app) {
response.setHeader("Connection", "keep-alive"); response.setHeader("Connection", "keep-alive");
response.flushHeaders(); response.flushHeaders();
if (multiUserMode(response) && user.role !== ROLES.admin) { if (multiUserMode(response) && !(await User.canSendChat(user))) {
const limitMessagesSetting = await SystemSettings.get({
label: "limit_user_messages",
});
const limitMessages = limitMessagesSetting?.value === "true";
if (limitMessages) {
const messageLimitSetting = await SystemSettings.get({
label: "message_limit",
});
const systemLimit = Number(messageLimitSetting?.value);
if (!!systemLimit) {
const currentChatCount = await WorkspaceChats.count({
user_id: user.id,
createdAt: {
gte: new Date(new Date() - 24 * 60 * 60 * 1000),
},
});
if (currentChatCount >= systemLimit) {
writeResponseChunk(response, { writeResponseChunk(response, {
id: uuidv4(), id: uuidv4(),
type: "abort", type: "abort",
textResponse: null, textResponse: null,
sources: [], sources: [],
close: true, close: true,
error: `You have met your maximum 24 hour chat quota of ${systemLimit} chats set by the instance administrators. Try again later.`, error: `You have met your maximum 24 hour chat quota of ${user.dailyMessageLimit} chats. Try again later.`,
}); });
return; return;
} }
}
}
}
await streamChatWithWorkspace( await streamChatWithWorkspace(
response, response,
@ -157,42 +133,17 @@ function chatEndpoints(app) {
response.setHeader("Connection", "keep-alive"); response.setHeader("Connection", "keep-alive");
response.flushHeaders(); response.flushHeaders();
if (multiUserMode(response) && user.role !== ROLES.admin) { if (multiUserMode(response) && !(await User.canSendChat(user))) {
const limitMessagesSetting = await SystemSettings.get({
label: "limit_user_messages",
});
const limitMessages = limitMessagesSetting?.value === "true";
if (limitMessages) {
const messageLimitSetting = await SystemSettings.get({
label: "message_limit",
});
const systemLimit = Number(messageLimitSetting?.value);
if (!!systemLimit) {
// Chat qty includes all threads because any user can freely
// create threads and would bypass this rule.
const currentChatCount = await WorkspaceChats.count({
user_id: user.id,
createdAt: {
gte: new Date(new Date() - 24 * 60 * 60 * 1000),
},
});
if (currentChatCount >= systemLimit) {
writeResponseChunk(response, { writeResponseChunk(response, {
id: uuidv4(), id: uuidv4(),
type: "abort", type: "abort",
textResponse: null, textResponse: null,
sources: [], sources: [],
close: true, close: true,
error: `You have met your maximum 24 hour chat quota of ${systemLimit} chats set by the instance administrators. Try again later.`, error: `You have met your maximum 24 hour chat quota of ${user.dailyMessageLimit} chats. Try again later.`,
}); });
return; return;
} }
}
}
}
await streamChatWithWorkspace( await streamChatWithWorkspace(
response, response,

View File

@ -56,6 +56,7 @@ function embeddedEndpoints(app) {
writeResponseChunk(response, { writeResponseChunk(response, {
id: uuidv4(), id: uuidv4(),
type: "abort", type: "abort",
sources: [],
textResponse: null, textResponse: null,
close: true, close: true,
error: e.message, error: e.message,
@ -72,11 +73,15 @@ function embeddedEndpoints(app) {
try { try {
const { sessionId } = request.params; const { sessionId } = request.params;
const embed = response.locals.embedConfig; const embed = response.locals.embedConfig;
const history = await EmbedChats.forEmbedByUser(
embed.id,
sessionId,
null,
null,
true
);
const history = await EmbedChats.forEmbedByUser(embed.id, sessionId); response.status(200).json({ history: convertToChatHistory(history) });
response.status(200).json({
history: convertToChatHistory(history),
});
} catch (e) { } catch (e) {
console.error(e.message, e); console.error(e.message, e);
response.sendStatus(500).end(); response.sendStatus(500).end();

View File

@ -1,7 +1,6 @@
const { EmbedChats } = require("../models/embedChats"); const { EmbedChats } = require("../models/embedChats");
const { EmbedConfig } = require("../models/embedConfig"); const { EmbedConfig } = require("../models/embedConfig");
const { EventLogs } = require("../models/eventLogs"); const { EventLogs } = require("../models/eventLogs");
const { Workspace } = require("../models/workspace");
const { reqBody, userFromSession } = require("../utils/http"); const { reqBody, userFromSession } = require("../utils/http");
const { validEmbedConfigId } = require("../utils/middleware/embedMiddleware"); const { validEmbedConfigId } = require("../utils/middleware/embedMiddleware");
const { const {
@ -9,6 +8,9 @@ const {
ROLES, ROLES,
} = require("../utils/middleware/multiUserProtected"); } = require("../utils/middleware/multiUserProtected");
const { validatedRequest } = require("../utils/middleware/validatedRequest"); const { validatedRequest } = require("../utils/middleware/validatedRequest");
const {
chatHistoryViewable,
} = require("../utils/middleware/chatHistoryViewable");
function embedManagementEndpoints(app) { function embedManagementEndpoints(app) {
if (!app) return; if (!app) return;
@ -90,7 +92,7 @@ function embedManagementEndpoints(app) {
app.post( app.post(
"/embed/chats", "/embed/chats",
[validatedRequest, flexUserRoleValid([ROLES.admin])], [chatHistoryViewable, validatedRequest, flexUserRoleValid([ROLES.admin])],
async (request, response) => { async (request, response) => {
try { try {
const { offset = 0, limit = 20 } = reqBody(request); const { offset = 0, limit = 20 } = reqBody(request);

View File

@ -55,6 +55,9 @@ const {
const { SlashCommandPresets } = require("../models/slashCommandsPresets"); const { SlashCommandPresets } = require("../models/slashCommandsPresets");
const { EncryptionManager } = require("../utils/EncryptionManager"); const { EncryptionManager } = require("../utils/EncryptionManager");
const { BrowserExtensionApiKey } = require("../models/browserExtensionApiKey"); const { BrowserExtensionApiKey } = require("../models/browserExtensionApiKey");
const {
chatHistoryViewable,
} = require("../utils/middleware/chatHistoryViewable");
function systemEndpoints(app) { function systemEndpoints(app) {
if (!app) return; if (!app) return;
@ -495,8 +498,6 @@ function systemEndpoints(app) {
await SystemSettings._updateSettings({ await SystemSettings._updateSettings({
multi_user_mode: true, multi_user_mode: true,
limit_user_messages: false,
message_limit: 25,
}); });
await BrowserExtensionApiKey.migrateApiKeysToMultiUser(user.id); await BrowserExtensionApiKey.migrateApiKeysToMultiUser(user.id);
@ -968,7 +969,11 @@ function systemEndpoints(app) {
app.post( app.post(
"/system/workspace-chats", "/system/workspace-chats",
[validatedRequest, flexUserRoleValid([ROLES.admin, ROLES.manager])], [
chatHistoryViewable,
validatedRequest,
flexUserRoleValid([ROLES.admin, ROLES.manager]),
],
async (request, response) => { async (request, response) => {
try { try {
const { offset = 0, limit = 20 } = reqBody(request); const { offset = 0, limit = 20 } = reqBody(request);
@ -1008,7 +1013,11 @@ function systemEndpoints(app) {
app.get( app.get(
"/system/export-chats", "/system/export-chats",
[validatedRequest, flexUserRoleValid([ROLES.manager, ROLES.admin])], [
chatHistoryViewable,
validatedRequest,
flexUserRoleValid([ROLES.manager, ROLES.admin]),
],
async (request, response) => { async (request, response) => {
try { try {
const { type = "jsonl", chatType = "workspace" } = request.query; const { type = "jsonl", chatType = "workspace" } = request.query;

View File

@ -1,5 +1,17 @@
const { safeJsonParse } = require("../utils/http");
const prisma = require("../utils/prisma"); const prisma = require("../utils/prisma");
/**
* @typedef {Object} EmbedChat
* @property {number} id
* @property {number} embed_id
* @property {string} prompt
* @property {string} response
* @property {string} connection_information
* @property {string} session_id
* @property {boolean} include
*/
const EmbedChats = { const EmbedChats = {
new: async function ({ new: async function ({
embedId, embedId,
@ -25,11 +37,36 @@ const EmbedChats = {
} }
}, },
/**
* Loops through each chat and filters out the sources from the response object.
* We do this when returning /history of an embed to the frontend to prevent inadvertent leaking
* of private sources the user may not have intended to share with users.
* @param {EmbedChat[]} chats
* @returns {EmbedChat[]} Returns a new array of chats with the sources filtered out of responses
*/
filterSources: function (chats) {
return chats.map((chat) => {
const { response, ...rest } = chat;
const { sources, ...responseRest } = safeJsonParse(response);
return { ...rest, response: JSON.stringify(responseRest) };
});
},
/**
* Fetches chats for a given embed and session id.
* @param {number} embedId the id of the embed to fetch chats for
* @param {string} sessionId the id of the session to fetch chats for
* @param {number|null} limit the maximum number of chats to fetch
* @param {string|null} orderBy the order to fetch chats in
* @param {boolean} filterSources whether to filter out the sources from the response (default: false)
* @returns {Promise<EmbedChat[]>} Returns an array of chats for the given embed and session
*/
forEmbedByUser: async function ( forEmbedByUser: async function (
embedId = null, embedId = null,
sessionId = null, sessionId = null,
limit = null, limit = null,
orderBy = null orderBy = null,
filterSources = false
) { ) {
if (!embedId || !sessionId) return []; if (!embedId || !sessionId) return [];
@ -43,7 +80,7 @@ const EmbedChats = {
...(limit !== null ? { take: limit } : {}), ...(limit !== null ? { take: limit } : {}),
...(orderBy !== null ? { orderBy } : { orderBy: { id: "asc" } }), ...(orderBy !== null ? { orderBy } : { orderBy: { id: "asc" } }),
}); });
return chats; return filterSources ? this.filterSources(chats) : chats;
} catch (error) { } catch (error) {
console.error(error.message); console.error(error.message);
return []; return [];

View File

@ -21,8 +21,6 @@ function isNullOrNaN(value) {
const SystemSettings = { const SystemSettings = {
protectedFields: ["multi_user_mode"], protectedFields: ["multi_user_mode"],
publicFields: [ publicFields: [
"limit_user_messages",
"message_limit",
"footer_data", "footer_data",
"support_email", "support_email",
"text_splitter_chunk_size", "text_splitter_chunk_size",
@ -38,8 +36,6 @@ const SystemSettings = {
"meta_page_favicon", "meta_page_favicon",
], ],
supportedFields: [ supportedFields: [
"limit_user_messages",
"message_limit",
"logo_filename", "logo_filename",
"telemetry_id", "telemetry_id",
"footer_data", "footer_data",
@ -108,6 +104,7 @@ const SystemSettings = {
"bing-search", "bing-search",
"serply-engine", "serply-engine",
"searxng-engine", "searxng-engine",
"tavily-search",
].includes(update) ].includes(update)
) )
throw new Error("Invalid SERP provider."); throw new Error("Invalid SERP provider.");
@ -229,12 +226,18 @@ const SystemSettings = {
TextToSpeechProvider: process.env.TTS_PROVIDER || "native", TextToSpeechProvider: process.env.TTS_PROVIDER || "native",
TTSOpenAIKey: !!process.env.TTS_OPEN_AI_KEY, TTSOpenAIKey: !!process.env.TTS_OPEN_AI_KEY,
TTSOpenAIVoiceModel: process.env.TTS_OPEN_AI_VOICE_MODEL, TTSOpenAIVoiceModel: process.env.TTS_OPEN_AI_VOICE_MODEL,
// Eleven Labs TTS // Eleven Labs TTS
TTSElevenLabsKey: !!process.env.TTS_ELEVEN_LABS_KEY, TTSElevenLabsKey: !!process.env.TTS_ELEVEN_LABS_KEY,
TTSElevenLabsVoiceModel: process.env.TTS_ELEVEN_LABS_VOICE_MODEL, TTSElevenLabsVoiceModel: process.env.TTS_ELEVEN_LABS_VOICE_MODEL,
// Piper TTS // Piper TTS
TTSPiperTTSVoiceModel: TTSPiperTTSVoiceModel:
process.env.TTS_PIPER_VOICE_MODEL ?? "en_US-hfc_female-medium", process.env.TTS_PIPER_VOICE_MODEL ?? "en_US-hfc_female-medium",
// OpenAI Generic TTS
TTSOpenAICompatibleKey: !!process.env.TTS_OPEN_AI_COMPATIBLE_KEY,
TTSOpenAICompatibleVoiceModel:
process.env.TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL,
TTSOpenAICompatibleEndpoint: process.env.TTS_OPEN_AI_COMPATIBLE_ENDPOINT,
// -------------------------------------------------------- // --------------------------------------------------------
// Agent Settings & Configs // Agent Settings & Configs
@ -247,6 +250,14 @@ const SystemSettings = {
AgentBingSearchApiKey: !!process.env.AGENT_BING_SEARCH_API_KEY || null, AgentBingSearchApiKey: !!process.env.AGENT_BING_SEARCH_API_KEY || null,
AgentSerplyApiKey: !!process.env.AGENT_SERPLY_API_KEY || null, AgentSerplyApiKey: !!process.env.AGENT_SERPLY_API_KEY || null,
AgentSearXNGApiUrl: process.env.AGENT_SEARXNG_API_URL || null, AgentSearXNGApiUrl: process.env.AGENT_SEARXNG_API_URL || null,
AgentTavilyApiKey: !!process.env.AGENT_TAVILY_API_KEY || null,
// --------------------------------------------------------
// Compliance Settings
// --------------------------------------------------------
// Disable View Chat History for the whole instance.
DisableViewChatHistory:
"DISABLE_VIEW_CHAT_HISTORY" in process.env || false,
}; };
}, },
@ -515,6 +526,14 @@ const SystemSettings = {
// DeepSeek API Keys // DeepSeek API Keys
DeepSeekApiKey: !!process.env.DEEPSEEK_API_KEY, DeepSeekApiKey: !!process.env.DEEPSEEK_API_KEY,
DeepSeekModelPref: process.env.DEEPSEEK_MODEL_PREF, DeepSeekModelPref: process.env.DEEPSEEK_MODEL_PREF,
// APIPie LLM API Keys
ApipieLLMApiKey: !!process.env.APIPIE_LLM_API_KEY,
ApipieLLMModelPref: process.env.APIPIE_LLM_MODEL_PREF,
// xAI LLM API Keys
XAIApiKey: !!process.env.XAI_LLM_API_KEY,
XAIModelPref: process.env.XAI_LLM_MODEL_PREF,
}; };
}, },

View File

@ -1,6 +1,17 @@
const prisma = require("../utils/prisma"); const prisma = require("../utils/prisma");
const { EventLogs } = require("./eventLogs"); const { EventLogs } = require("./eventLogs");
/**
* @typedef {Object} User
* @property {number} id
* @property {string} username
* @property {string} password
* @property {string} pfpFilename
* @property {string} role
* @property {boolean} suspended
* @property {number|null} dailyMessageLimit
*/
const User = { const User = {
usernameRegex: new RegExp(/^[a-z0-9_-]+$/), usernameRegex: new RegExp(/^[a-z0-9_-]+$/),
writable: [ writable: [
@ -10,6 +21,7 @@ const User = {
"pfpFilename", "pfpFilename",
"role", "role",
"suspended", "suspended",
"dailyMessageLimit",
], ],
validations: { validations: {
username: (newValue = "") => { username: (newValue = "") => {
@ -32,12 +44,24 @@ const User = {
} }
return String(role); return String(role);
}, },
dailyMessageLimit: (dailyMessageLimit = null) => {
if (dailyMessageLimit === null) return null;
const limit = Number(dailyMessageLimit);
if (isNaN(limit) || limit < 1) {
throw new Error(
"Daily message limit must be null or a number greater than or equal to 1"
);
}
return limit;
},
}, },
// validations for the above writable fields. // validations for the above writable fields.
castColumnValue: function (key, value) { castColumnValue: function (key, value) {
switch (key) { switch (key) {
case "suspended": case "suspended":
return Number(Boolean(value)); return Number(Boolean(value));
case "dailyMessageLimit":
return value === null ? null : Number(value);
default: default:
return String(value); return String(value);
} }
@ -48,7 +72,12 @@ const User = {
return { ...rest }; return { ...rest };
}, },
create: async function ({ username, password, role = "default" }) { create: async function ({
username,
password,
role = "default",
dailyMessageLimit = null,
}) {
const passwordCheck = this.checkPasswordComplexity(password); const passwordCheck = this.checkPasswordComplexity(password);
if (!passwordCheck.checkedOK) { if (!passwordCheck.checkedOK) {
return { user: null, error: passwordCheck.error }; return { user: null, error: passwordCheck.error };
@ -58,7 +87,7 @@ const User = {
// Do not allow new users to bypass validation // Do not allow new users to bypass validation
if (!this.usernameRegex.test(username)) if (!this.usernameRegex.test(username))
throw new Error( throw new Error(
"Username must be only contain lowercase letters, numbers, underscores, and hyphens with no spaces" "Username must only contain lowercase letters, numbers, underscores, and hyphens with no spaces"
); );
const bcrypt = require("bcrypt"); const bcrypt = require("bcrypt");
@ -68,6 +97,8 @@ const User = {
username: this.validations.username(username), username: this.validations.username(username),
password: hashedPassword, password: hashedPassword,
role: this.validations.role(role), role: this.validations.role(role),
dailyMessageLimit:
this.validations.dailyMessageLimit(dailyMessageLimit),
}, },
}); });
return { user: this.filterFields(user), error: null }; return { user: this.filterFields(user), error: null };
@ -135,7 +166,7 @@ const User = {
return { return {
success: false, success: false,
error: error:
"Username must be only contain lowercase letters, numbers, underscores, and hyphens with no spaces", "Username must only contain lowercase letters, numbers, underscores, and hyphens with no spaces",
}; };
const user = await prisma.users.update({ const user = await prisma.users.update({
@ -260,6 +291,29 @@ const User = {
return { checkedOK: true, error: "No error." }; return { checkedOK: true, error: "No error." };
}, },
/**
* Check if a user can send a chat based on their daily message limit.
* This limit is system wide and not per workspace and only applies to
* multi-user mode AND non-admin users.
* @param {User} user The user object record.
* @returns {Promise<boolean>} True if the user can send a chat, false otherwise.
*/
canSendChat: async function (user) {
const { ROLES } = require("../utils/middleware/multiUserProtected");
if (!user || user.dailyMessageLimit === null || user.role === ROLES.admin)
return true;
const { WorkspaceChats } = require("./workspaceChats");
const currentChatCount = await WorkspaceChats.count({
user_id: user.id,
createdAt: {
gte: new Date(new Date() - 24 * 60 * 60 * 1000), // 24 hours
},
});
return currentChatCount < user.dailyMessageLimit;
},
}; };
module.exports = { User }; module.exports = { User };

View File

@ -1,16 +1,44 @@
const prisma = require("../utils/prisma"); const prisma = require("../utils/prisma");
const slugifyModule = require("slugify");
const { v4: uuidv4 } = require("uuid"); const { v4: uuidv4 } = require("uuid");
const WorkspaceThread = { const WorkspaceThread = {
defaultName: "Thread", defaultName: "Thread",
writable: ["name"], writable: ["name"],
new: async function (workspace, userId = null) { /**
* The default Slugify module requires some additional mapping to prevent downstream issues
* if the user is able to define a slug externally. We have to block non-escapable URL chars
* so that is the slug is rendered it doesn't break the URL or UI when visited.
* @param {...any} args - slugify args for npm package.
* @returns {string}
*/
slugify: function (...args) {
slugifyModule.extend({
"+": " plus ",
"!": " bang ",
"@": " at ",
"*": " splat ",
".": " dot ",
":": "",
"~": "",
"(": "",
")": "",
"'": "",
'"': "",
"|": "",
});
return slugifyModule(...args);
},
new: async function (workspace, userId = null, data = {}) {
try { try {
const thread = await prisma.workspace_threads.create({ const thread = await prisma.workspace_threads.create({
data: { data: {
name: this.defaultName, name: data.name ? String(data.name) : this.defaultName,
slug: uuidv4(), slug: data.slug
? this.slugify(data.slug, { lowercase: true })
: uuidv4(),
user_id: userId ? Number(userId) : null, user_id: userId ? Number(userId) : null,
workspace_id: workspace.id, workspace_id: workspace.id,
}, },

View File

@ -0,0 +1,2 @@
-- AlterTable
ALTER TABLE "users" ADD COLUMN "dailyMessageLimit" INTEGER;

View File

@ -67,6 +67,7 @@ model users {
seen_recovery_codes Boolean? @default(false) seen_recovery_codes Boolean? @default(false)
createdAt DateTime @default(now()) createdAt DateTime @default(now())
lastUpdatedAt DateTime @default(now()) lastUpdatedAt DateTime @default(now())
dailyMessageLimit Int?
workspace_chats workspace_chats[] workspace_chats workspace_chats[]
workspace_users workspace_users[] workspace_users workspace_users[]
embed_configs embed_configs[] embed_configs embed_configs[]

View File

@ -4,8 +4,6 @@ const prisma = new PrismaClient();
async function main() { async function main() {
const settings = [ const settings = [
{ label: "multi_user_mode", value: "false" }, { label: "multi_user_mode", value: "false" },
{ label: "limit_user_messages", value: "false" },
{ label: "message_limit", value: "25" },
{ label: "logo_filename", value: "anything-llm.png" }, { label: "logo_filename", value: "anything-llm.png" },
]; ];

View File

@ -2,3 +2,4 @@ Xenova
downloaded/* downloaded/*
!downloaded/.placeholder !downloaded/.placeholder
openrouter openrouter
apipie

View File

@ -693,52 +693,6 @@
} }
}, },
"/v1/admin/preferences": { "/v1/admin/preferences": {
"get": {
"tags": [
"Admin"
],
"description": "Show all multi-user preferences for instance. Methods are disabled until multi user mode is enabled via the UI.",
"parameters": [],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"type": "object",
"example": {
"settings": {
"limit_user_messages": false,
"message_limit": 10
}
}
}
}
}
},
"401": {
"description": "Instance is not in Multi-User mode. Method denied"
},
"403": {
"description": "Forbidden",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/InvalidAPIKey"
}
},
"application/xml": {
"schema": {
"$ref": "#/components/schemas/InvalidAPIKey"
}
}
}
},
"500": {
"description": "Internal Server Error"
}
}
},
"post": { "post": {
"tags": [ "tags": [
"Admin" "Admin"
@ -788,8 +742,7 @@
"content": { "content": {
"application/json": { "application/json": {
"example": { "example": {
"limit_user_messages": true, "support_email": "support@example.com"
"message_limit": 5
} }
} }
} }
@ -2438,12 +2391,14 @@
} }
}, },
"requestBody": { "requestBody": {
"description": "Optional userId associated with the thread", "description": "Optional userId associated with the thread, thread slug and thread name",
"required": false, "required": false,
"content": { "content": {
"application/json": { "application/json": {
"example": { "example": {
"userId": 1 "userId": 1,
"name": "Name",
"slug": "thread-slug"
} }
} }
} }

View File

@ -0,0 +1,336 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
const { v4: uuidv4 } = require("uuid");
const {
writeResponseChunk,
clientAbortedHandler,
} = require("../../helpers/chat/responses");
const fs = require("fs");
const path = require("path");
const { safeJsonParse } = require("../../http");
const cacheFolder = path.resolve(
process.env.STORAGE_DIR
? path.resolve(process.env.STORAGE_DIR, "models", "apipie")
: path.resolve(__dirname, `../../../storage/models/apipie`)
);
class ApiPieLLM {
constructor(embedder = null, modelPreference = null) {
if (!process.env.APIPIE_LLM_API_KEY)
throw new Error("No ApiPie LLM API key was set.");
const { OpenAI: OpenAIApi } = require("openai");
this.basePath = "https://apipie.ai/v1";
this.openai = new OpenAIApi({
baseURL: this.basePath,
apiKey: process.env.APIPIE_LLM_API_KEY ?? null,
});
this.model =
modelPreference ||
process.env.APIPIE_LLM_MODEL_PREF ||
"openrouter/mistral-7b-instruct";
this.limits = {
history: this.promptWindowLimit() * 0.15,
system: this.promptWindowLimit() * 0.15,
user: this.promptWindowLimit() * 0.7,
};
this.embedder = embedder ?? new NativeEmbedder();
this.defaultTemp = 0.7;
if (!fs.existsSync(cacheFolder))
fs.mkdirSync(cacheFolder, { recursive: true });
this.cacheModelPath = path.resolve(cacheFolder, "models.json");
this.cacheAtPath = path.resolve(cacheFolder, ".cached_at");
}
log(text, ...args) {
console.log(`\x1b[36m[${this.constructor.name}]\x1b[0m ${text}`, ...args);
}
// This checks if the .cached_at file has a timestamp that is more than 1Week (in millis)
// from the current date. If it is, then we will refetch the API so that all the models are up
// to date.
#cacheIsStale() {
const MAX_STALE = 6.048e8; // 1 Week in MS
if (!fs.existsSync(this.cacheAtPath)) return true;
const now = Number(new Date());
const timestampMs = Number(fs.readFileSync(this.cacheAtPath));
return now - timestampMs > MAX_STALE;
}
// This function fetches the models from the ApiPie API and caches them locally.
// We do this because the ApiPie API has a lot of models, and we need to get the proper token context window
// for each model and this is a constructor property - so we can really only get it if this cache exists.
// We used to have this as a chore, but given there is an API to get the info - this makes little sense.
// This might slow down the first request, but we need the proper token context window
// for each model and this is a constructor property - so we can really only get it if this cache exists.
async #syncModels() {
if (fs.existsSync(this.cacheModelPath) && !this.#cacheIsStale())
return false;
this.log("Model cache is not present or stale. Fetching from ApiPie API.");
await fetchApiPieModels();
return;
}
#appendContext(contextTexts = []) {
if (!contextTexts || !contextTexts.length) return "";
return (
"\nContext:\n" +
contextTexts
.map((text, i) => {
return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
})
.join("")
);
}
models() {
if (!fs.existsSync(this.cacheModelPath)) return {};
return safeJsonParse(
fs.readFileSync(this.cacheModelPath, { encoding: "utf-8" }),
{}
);
}
streamingEnabled() {
return "streamGetChatCompletion" in this;
}
static promptWindowLimit(modelName) {
const cacheModelPath = path.resolve(cacheFolder, "models.json");
const availableModels = fs.existsSync(cacheModelPath)
? safeJsonParse(
fs.readFileSync(cacheModelPath, { encoding: "utf-8" }),
{}
)
: {};
return availableModels[modelName]?.maxLength || 4096;
}
promptWindowLimit() {
const availableModels = this.models();
return availableModels[this.model]?.maxLength || 4096;
}
async isValidChatCompletionModel(model = "") {
await this.#syncModels();
const availableModels = this.models();
return availableModels.hasOwnProperty(model);
}
/**
* Generates appropriate content array for a message + attachments.
* @param {{userPrompt:string, attachments: import("../../helpers").Attachment[]}}
* @returns {string|object[]}
*/
#generateContent({ userPrompt, attachments = [] }) {
if (!attachments.length) {
return userPrompt;
}
const content = [{ type: "text", text: userPrompt }];
for (let attachment of attachments) {
content.push({
type: "image_url",
image_url: {
url: attachment.contentString,
detail: "auto",
},
});
}
return content.flat();
}
constructPrompt({
systemPrompt = "",
contextTexts = [],
chatHistory = [],
userPrompt = "",
attachments = [],
}) {
const prompt = {
role: "system",
content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
};
return [
prompt,
...chatHistory,
{
role: "user",
content: this.#generateContent({ userPrompt, attachments }),
},
];
}
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!(await this.isValidChatCompletionModel(this.model)))
throw new Error(
`ApiPie chat: ${this.model} is not valid for chat completion!`
);
const result = await this.openai.chat.completions
.create({
model: this.model,
messages,
temperature,
})
.catch((e) => {
throw new Error(e.message);
});
if (!result.hasOwnProperty("choices") || result.choices.length === 0)
return null;
return result.choices[0].message.content;
}
// APIPie says it supports streaming, but it does not work across all models and providers.
// Notably, it is not working for OpenRouter models at all.
// async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
// if (!(await this.isValidChatCompletionModel(this.model)))
// throw new Error(
// `ApiPie chat: ${this.model} is not valid for chat completion!`
// );
// const streamRequest = await this.openai.chat.completions.create({
// model: this.model,
// stream: true,
// messages,
// temperature,
// });
// return streamRequest;
// }
handleStream(response, stream, responseProps) {
const { uuid = uuidv4(), sources = [] } = responseProps;
return new Promise(async (resolve) => {
let fullText = "";
// Establish listener to early-abort a streaming response
// in case things go sideways or the user does not like the response.
// We preserve the generated text but continue as if chat was completed
// to preserve previously generated content.
const handleAbort = () => clientAbortedHandler(resolve, fullText);
response.on("close", handleAbort);
try {
for await (const chunk of stream) {
const message = chunk?.choices?.[0];
const token = message?.delta?.content;
if (token) {
fullText += token;
writeResponseChunk(response, {
uuid,
sources: [],
type: "textResponseChunk",
textResponse: token,
close: false,
error: false,
});
}
if (message === undefined || message.finish_reason !== null) {
writeResponseChunk(response, {
uuid,
sources,
type: "textResponseChunk",
textResponse: "",
close: true,
error: false,
});
response.removeListener("close", handleAbort);
resolve(fullText);
}
}
} catch (e) {
writeResponseChunk(response, {
uuid,
sources,
type: "abort",
textResponse: null,
close: true,
error: e.message,
});
response.removeListener("close", handleAbort);
resolve(fullText);
}
});
}
// handleStream(response, stream, responseProps) {
// return handleDefaultStreamResponseV2(response, stream, responseProps);
// }
// 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);
}
}
async function fetchApiPieModels(providedApiKey = null) {
const apiKey = providedApiKey || process.env.APIPIE_LLM_API_KEY || null;
return await fetch(`https://apipie.ai/v1/models`, {
method: "GET",
headers: {
"Content-Type": "application/json",
...(apiKey ? { Authorization: `Bearer ${apiKey}` } : {}),
},
})
.then((res) => res.json())
.then(({ data = [] }) => {
const models = {};
data.forEach((model) => {
models[`${model.provider}/${model.model}`] = {
id: `${model.provider}/${model.model}`,
name: `${model.provider}/${model.model}`,
organization: model.provider,
maxLength: model.max_tokens,
};
});
// Cache all response information
if (!fs.existsSync(cacheFolder))
fs.mkdirSync(cacheFolder, { recursive: true });
fs.writeFileSync(
path.resolve(cacheFolder, "models.json"),
JSON.stringify(models),
{
encoding: "utf-8",
}
);
fs.writeFileSync(
path.resolve(cacheFolder, ".cached_at"),
String(Number(new Date())),
{
encoding: "utf-8",
}
);
return models;
})
.catch((e) => {
console.error(e);
return {};
});
}
module.exports = {
ApiPieLLM,
fetchApiPieModels,
};

View File

@ -5,7 +5,7 @@ const {
} = require("../../helpers/chat/responses"); } = require("../../helpers/chat/responses");
class AzureOpenAiLLM { class AzureOpenAiLLM {
constructor(embedder = null, _modelPreference = null) { constructor(embedder = null, modelPreference = null) {
const { OpenAIClient, AzureKeyCredential } = require("@azure/openai"); const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
if (!process.env.AZURE_OPENAI_ENDPOINT) if (!process.env.AZURE_OPENAI_ENDPOINT)
throw new Error("No Azure API endpoint was set."); throw new Error("No Azure API endpoint was set.");
@ -16,7 +16,7 @@ class AzureOpenAiLLM {
process.env.AZURE_OPENAI_ENDPOINT, process.env.AZURE_OPENAI_ENDPOINT,
new AzureKeyCredential(process.env.AZURE_OPENAI_KEY) new AzureKeyCredential(process.env.AZURE_OPENAI_KEY)
); );
this.model = process.env.OPEN_MODEL_PREF; this.model = modelPreference ?? process.env.OPEN_MODEL_PREF;
this.limits = { this.limits = {
history: this.promptWindowLimit() * 0.15, history: this.promptWindowLimit() * 0.15,
system: this.promptWindowLimit() * 0.15, system: this.promptWindowLimit() * 0.15,

View File

@ -7,6 +7,20 @@ const { NativeEmbedder } = require("../../EmbeddingEngines/native");
// Docs: https://js.langchain.com/v0.2/docs/integrations/chat/bedrock_converse // Docs: https://js.langchain.com/v0.2/docs/integrations/chat/bedrock_converse
class AWSBedrockLLM { class AWSBedrockLLM {
/**
* These models do not support system prompts
* It is not explicitly stated but it is observed that they do not use the system prompt
* in their responses and will crash when a system prompt is provided.
* We can add more models to this list as we discover them or new models are added.
* We may want to extend this list or make a user-config if using custom bedrock models.
*/
noSystemPromptModels = [
"amazon.titan-text-express-v1",
"amazon.titan-text-lite-v1",
"cohere.command-text-v14",
"cohere.command-light-text-v14",
];
constructor(embedder = null, modelPreference = null) { constructor(embedder = null, modelPreference = null) {
if (!process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID) if (!process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID)
throw new Error("No AWS Bedrock LLM profile id was set."); throw new Error("No AWS Bedrock LLM profile id was set.");
@ -32,7 +46,7 @@ class AWSBedrockLLM {
#bedrockClient({ temperature = 0.7 }) { #bedrockClient({ temperature = 0.7 }) {
const { ChatBedrockConverse } = require("@langchain/aws"); const { ChatBedrockConverse } = require("@langchain/aws");
return new ChatBedrockConverse({ return new ChatBedrockConverse({
model: process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE, model: this.model,
region: process.env.AWS_BEDROCK_LLM_REGION, region: process.env.AWS_BEDROCK_LLM_REGION,
credentials: { credentials: {
accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID, accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID,
@ -59,6 +73,22 @@ class AWSBedrockLLM {
for (const chat of chats) { for (const chat of chats) {
if (!roleToMessageMap.hasOwnProperty(chat.role)) continue; if (!roleToMessageMap.hasOwnProperty(chat.role)) continue;
// When a model does not support system prompts, we need to handle it.
// We will add a new message that simulates the system prompt via a user message and AI response.
// This will allow the model to respond without crashing but we can still inject context.
if (
this.noSystemPromptModels.includes(this.model) &&
chat.role === "system"
) {
this.#log(
`Model does not support system prompts! Simulating system prompt via Human/AI message pairs.`
);
langchainChats.push(new HumanMessage({ content: chat.content }));
langchainChats.push(new AIMessage({ content: "Okay." }));
continue;
}
const MessageClass = roleToMessageMap[chat.role]; const MessageClass = roleToMessageMap[chat.role];
langchainChats.push(new MessageClass({ content: chat.content })); langchainChats.push(new MessageClass({ content: chat.content }));
} }
@ -78,6 +108,10 @@ class AWSBedrockLLM {
); );
} }
#log(text, ...args) {
console.log(`\x1b[32m[AWSBedrock]\x1b[0m ${text}`, ...args);
}
streamingEnabled() { streamingEnabled() {
return "streamGetChatCompletion" in this; return "streamGetChatCompletion" in this;
} }

View File

@ -37,6 +37,10 @@ class GroqLLM {
); );
} }
#log(text, ...args) {
console.log(`\x1b[32m[GroqAi]\x1b[0m ${text}`, ...args);
}
streamingEnabled() { streamingEnabled() {
return "streamGetChatCompletion" in this; return "streamGetChatCompletion" in this;
} }
@ -53,17 +57,111 @@ class GroqLLM {
return !!modelName; // name just needs to exist return !!modelName; // name just needs to exist
} }
/**
* Generates appropriate content array for a message + attachments.
* @param {{userPrompt:string, attachments: import("../../helpers").Attachment[]}}
* @returns {string|object[]}
*/
#generateContent({ userPrompt, attachments = [] }) {
if (!attachments.length) return userPrompt;
const content = [{ type: "text", text: userPrompt }];
for (let attachment of attachments) {
content.push({
type: "image_url",
image_url: {
url: attachment.contentString,
},
});
}
return content.flat();
}
/**
* Last Updated: October 21, 2024
* According to https://console.groq.com/docs/vision
* the vision models supported all make a mess of prompting depending on the model.
* Currently the llama3.2 models are only in preview and subject to change and the llava model is deprecated - so we will not support attachments for that at all.
*
* Since we can only explicitly support the current models, this is a temporary solution.
* If the attachments are empty or the model is not a vision model, we will return the default prompt structure which will work for all models.
* If the attachments are present and the model is a vision model - we only return the user prompt with attachments - see comment at end of function for more.
*/
#conditionalPromptStruct({
systemPrompt = "",
contextTexts = [],
chatHistory = [],
userPrompt = "",
attachments = [], // This is the specific attachment for only this prompt
}) {
const VISION_MODELS = [
"llama-3.2-90b-vision-preview",
"llama-3.2-11b-vision-preview",
];
const DEFAULT_PROMPT_STRUCT = [
{
role: "system",
content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
},
...chatHistory,
{ role: "user", content: userPrompt },
];
// If there are no attachments or model is not a vision model, return the default prompt structure
// as there is nothing to attach or do and no model limitations to consider
if (!attachments.length) return DEFAULT_PROMPT_STRUCT;
if (!VISION_MODELS.includes(this.model)) {
this.#log(
`${this.model} is not an explicitly supported vision model! Will omit attachments.`
);
return DEFAULT_PROMPT_STRUCT;
}
return [
// Why is the system prompt and history commented out?
// The current vision models for Groq perform VERY poorly with ANY history or text prior to the image.
// In order to not get LLM refusals for every single message, we will not include the "system prompt" or even the chat history.
// This is a temporary solution until Groq fixes their vision models to be more coherent and also handle context prior to the image.
// Note for the future:
// Groq vision models also do not support system prompts - which is why you see the user/assistant emulation used instead of "system".
// This means any vision call is assessed independently of the chat context prior to the image.
/////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////////
// {
// role: "user",
// content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
// },
// {
// role: "assistant",
// content: "OK",
// },
// ...chatHistory,
{
role: "user",
content: this.#generateContent({ userPrompt, attachments }),
},
];
}
/**
* Construct the user prompt for this model.
* @param {{attachments: import("../../helpers").Attachment[]}} param0
* @returns
*/
constructPrompt({ constructPrompt({
systemPrompt = "", systemPrompt = "",
contextTexts = [], contextTexts = [],
chatHistory = [], chatHistory = [],
userPrompt = "", userPrompt = "",
attachments = [], // This is the specific attachment for only this prompt
}) { }) {
const prompt = { // NOTICE: SEE GroqLLM.#conditionalPromptStruct for more information on how attachments are handled with Groq.
role: "system", return this.#conditionalPromptStruct({
content: `${systemPrompt}${this.#appendContext(contextTexts)}`, systemPrompt,
}; contextTexts,
return [prompt, ...chatHistory, { role: "user", content: userPrompt }]; chatHistory,
userPrompt,
attachments,
});
} }
async getChatCompletion(messages = null, { temperature = 0.7 }) { async getChatCompletion(messages = null, { temperature = 0.7 }) {

View File

@ -5,7 +5,7 @@ const {
// hybrid of openAi LLM chat completion for LMStudio // hybrid of openAi LLM chat completion for LMStudio
class LMStudioLLM { class LMStudioLLM {
constructor(embedder = null, _modelPreference = null) { constructor(embedder = null, modelPreference = null) {
if (!process.env.LMSTUDIO_BASE_PATH) if (!process.env.LMSTUDIO_BASE_PATH)
throw new Error("No LMStudio API Base Path was set."); throw new Error("No LMStudio API Base Path was set.");
@ -21,7 +21,10 @@ class LMStudioLLM {
// and any other value will crash inferencing. So until this is patched we will // and any other value will crash inferencing. So until this is patched we will
// try to fetch the `/models` and have the user set it, or just fallback to "Loaded from Chat UI" // try to fetch the `/models` and have the user set it, or just fallback to "Loaded from Chat UI"
// which will not impact users with <v0.2.17 and should work as well once the bug is fixed. // which will not impact users with <v0.2.17 and should work as well once the bug is fixed.
this.model = process.env.LMSTUDIO_MODEL_PREF || "Loaded from Chat UI"; this.model =
modelPreference ||
process.env.LMSTUDIO_MODEL_PREF ||
"Loaded from Chat UI";
this.limits = { this.limits = {
history: this.promptWindowLimit() * 0.15, history: this.promptWindowLimit() * 0.15,
system: this.promptWindowLimit() * 0.15, system: this.promptWindowLimit() * 0.15,

View File

@ -52,11 +52,18 @@ const MODEL_MAP = {
"gpt-4-turbo-preview": 128_000, "gpt-4-turbo-preview": 128_000,
"gpt-4": 8_192, "gpt-4": 8_192,
"gpt-4-32k": 32_000, "gpt-4-32k": 32_000,
"o1-preview": 128_000,
"o1-preview-2024-09-12": 128_000,
"o1-mini": 128_000,
"o1-mini-2024-09-12": 128_000,
}, },
deepseek: { deepseek: {
"deepseek-chat": 128_000, "deepseek-chat": 128_000,
"deepseek-coder": 128_000, "deepseek-coder": 128_000,
}, },
xai: {
"grok-beta": 131_072,
},
}; };
module.exports = { MODEL_MAP }; module.exports = { MODEL_MAP };

View File

@ -23,6 +23,14 @@ class OpenAiLLM {
this.defaultTemp = 0.7; this.defaultTemp = 0.7;
} }
/**
* Check if the model is an o1 model.
* @returns {boolean}
*/
get isO1Model() {
return this.model.startsWith("o1");
}
#appendContext(contextTexts = []) { #appendContext(contextTexts = []) {
if (!contextTexts || !contextTexts.length) return ""; if (!contextTexts || !contextTexts.length) return "";
return ( return (
@ -36,6 +44,7 @@ class OpenAiLLM {
} }
streamingEnabled() { streamingEnabled() {
if (this.isO1Model) return false;
return "streamGetChatCompletion" in this; return "streamGetChatCompletion" in this;
} }
@ -98,8 +107,11 @@ class OpenAiLLM {
userPrompt = "", userPrompt = "",
attachments = [], // This is the specific attachment for only this prompt attachments = [], // This is the specific attachment for only this prompt
}) { }) {
// o1 Models do not support the "system" role
// in order to combat this, we can use the "user" role as a replacement for now
// https://community.openai.com/t/o1-models-do-not-support-system-role-in-chat-completion/953880
const prompt = { const prompt = {
role: "system", role: this.isO1Model ? "user" : "system",
content: `${systemPrompt}${this.#appendContext(contextTexts)}`, content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
}; };
return [ return [
@ -122,7 +134,7 @@ class OpenAiLLM {
.create({ .create({
model: this.model, model: this.model,
messages, messages,
temperature, temperature: this.isO1Model ? 1 : temperature, // o1 models only accept temperature 1
}) })
.catch((e) => { .catch((e) => {
throw new Error(e.message); throw new Error(e.message);
@ -143,7 +155,7 @@ class OpenAiLLM {
model: this.model, model: this.model,
stream: true, stream: true,
messages, messages,
temperature, temperature: this.isO1Model ? 1 : temperature, // o1 models only accept temperature 1
}); });
return streamRequest; return streamRequest;
} }

View File

@ -0,0 +1,168 @@
const { NativeEmbedder } = require("../../EmbeddingEngines/native");
const {
handleDefaultStreamResponseV2,
} = require("../../helpers/chat/responses");
const { MODEL_MAP } = require("../modelMap");
class XAiLLM {
constructor(embedder = null, modelPreference = null) {
if (!process.env.XAI_LLM_API_KEY)
throw new Error("No xAI API key was set.");
const { OpenAI: OpenAIApi } = require("openai");
this.openai = new OpenAIApi({
baseURL: "https://api.x.ai/v1",
apiKey: process.env.XAI_LLM_API_KEY,
});
this.model =
modelPreference || process.env.XAI_LLM_MODEL_PREF || "grok-beta";
this.limits = {
history: this.promptWindowLimit() * 0.15,
system: this.promptWindowLimit() * 0.15,
user: this.promptWindowLimit() * 0.7,
};
this.embedder = embedder ?? new NativeEmbedder();
this.defaultTemp = 0.7;
}
#appendContext(contextTexts = []) {
if (!contextTexts || !contextTexts.length) return "";
return (
"\nContext:\n" +
contextTexts
.map((text, i) => {
return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
})
.join("")
);
}
streamingEnabled() {
return "streamGetChatCompletion" in this;
}
static promptWindowLimit(modelName) {
return MODEL_MAP.xai[modelName] ?? 131_072;
}
promptWindowLimit() {
return MODEL_MAP.xai[this.model] ?? 131_072;
}
isValidChatCompletionModel(modelName = "") {
switch (modelName) {
case "grok-beta":
return true;
default:
return false;
}
}
/**
* Generates appropriate content array for a message + attachments.
* @param {{userPrompt:string, attachments: import("../../helpers").Attachment[]}}
* @returns {string|object[]}
*/
#generateContent({ userPrompt, attachments = [] }) {
if (!attachments.length) {
return userPrompt;
}
const content = [{ type: "text", text: userPrompt }];
for (let attachment of attachments) {
content.push({
type: "image_url",
image_url: {
url: attachment.contentString,
detail: "high",
},
});
}
return content.flat();
}
/**
* Construct the user prompt for this model.
* @param {{attachments: import("../../helpers").Attachment[]}} param0
* @returns
*/
constructPrompt({
systemPrompt = "",
contextTexts = [],
chatHistory = [],
userPrompt = "",
attachments = [], // This is the specific attachment for only this prompt
}) {
const prompt = {
role: "system",
content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
};
return [
prompt,
...chatHistory,
{
role: "user",
content: this.#generateContent({ userPrompt, attachments }),
},
];
}
async getChatCompletion(messages = null, { temperature = 0.7 }) {
if (!this.isValidChatCompletionModel(this.model))
throw new Error(
`xAI chat: ${this.model} is not valid for chat completion!`
);
const result = await this.openai.chat.completions
.create({
model: this.model,
messages,
temperature,
})
.catch((e) => {
throw new Error(e.message);
});
if (!result.hasOwnProperty("choices") || result.choices.length === 0)
return null;
return result.choices[0].message.content;
}
async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
if (!this.isValidChatCompletionModel(this.model))
throw new Error(
`xAI chat: ${this.model} is not valid for chat completion!`
);
const streamRequest = await this.openai.chat.completions.create({
model: this.model,
stream: true,
messages,
temperature,
});
return streamRequest;
}
handleStream(response, stream, responseProps) {
return handleDefaultStreamResponseV2(response, stream, responseProps);
}
// 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 = {
XAiLLM,
};

View File

@ -11,7 +11,7 @@ class VoyageAiEmbedder {
}); });
this.voyage = voyage; this.voyage = voyage;
this.model = process.env.EMBEDDING_MODEL_PREF || "voyage-large-2-instruct"; this.model = process.env.EMBEDDING_MODEL_PREF || "voyage-3-lite";
// Limit of how many strings we can process in a single pass to stay with resource or network limits // 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.batchSize = 128; // Voyage AI's limit per request is 128 https://docs.voyageai.com/docs/rate-limits#use-larger-batches
@ -23,6 +23,8 @@ class VoyageAiEmbedder {
switch (this.model) { switch (this.model) {
case "voyage-finance-2": case "voyage-finance-2":
case "voyage-multilingual-2": case "voyage-multilingual-2":
case "voyage-3":
case "voyage-3-lite":
return 32_000; return 32_000;
case "voyage-large-2-instruct": case "voyage-large-2-instruct":
case "voyage-law-2": case "voyage-law-2":

View File

@ -7,6 +7,9 @@ function getTTSProvider() {
case "elevenlabs": case "elevenlabs":
const { ElevenLabsTTS } = require("./elevenLabs"); const { ElevenLabsTTS } = require("./elevenLabs");
return new ElevenLabsTTS(); return new ElevenLabsTTS();
case "generic-openai":
const { GenericOpenAiTTS } = require("./openAiGeneric");
return new GenericOpenAiTTS();
default: default:
throw new Error("ENV: No TTS_PROVIDER value found in environment!"); throw new Error("ENV: No TTS_PROVIDER value found in environment!");
} }

View File

@ -0,0 +1,50 @@
class GenericOpenAiTTS {
constructor() {
if (!process.env.TTS_OPEN_AI_COMPATIBLE_KEY)
this.#log(
"No OpenAI compatible API key was set. You might need to set this to use your OpenAI compatible TTS service."
);
if (!process.env.TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL)
this.#log(
"No OpenAI compatible voice model was set. We will use the default voice model 'alloy'. This may not exist for your selected endpoint."
);
if (!process.env.TTS_OPEN_AI_COMPATIBLE_ENDPOINT)
throw new Error(
"No OpenAI compatible endpoint was set. Please set this to use your OpenAI compatible TTS service."
);
const { OpenAI: OpenAIApi } = require("openai");
this.openai = new OpenAIApi({
apiKey: process.env.TTS_OPEN_AI_COMPATIBLE_KEY || null,
baseURL: process.env.TTS_OPEN_AI_COMPATIBLE_ENDPOINT,
});
this.voice = process.env.TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL ?? "alloy";
}
#log(text, ...args) {
console.log(`\x1b[32m[OpenAiGenericTTS]\x1b[0m ${text}`, ...args);
}
/**
* Generates a buffer from the given text input using the OpenAI compatible TTS service.
* @param {string} textInput - The text to be converted to audio.
* @returns {Promise<Buffer>} A buffer containing the audio data.
*/
async ttsBuffer(textInput) {
try {
const result = await this.openai.audio.speech.create({
model: "tts-1",
voice: this.voice,
input: textInput,
});
return Buffer.from(await result.arrayBuffer());
} catch (e) {
console.error(e);
}
return null;
}
}
module.exports = {
GenericOpenAiTTS,
};

View File

@ -756,7 +756,7 @@ ${this.getHistory({ to: route.to })
case "anthropic": case "anthropic":
return new Providers.AnthropicProvider({ model: config.model }); return new Providers.AnthropicProvider({ model: config.model });
case "lmstudio": case "lmstudio":
return new Providers.LMStudioProvider({}); return new Providers.LMStudioProvider({ model: config.model });
case "ollama": case "ollama":
return new Providers.OllamaProvider({ model: config.model }); return new Providers.OllamaProvider({ model: config.model });
case "groq": case "groq":
@ -785,6 +785,12 @@ ${this.getHistory({ to: route.to })
return new Providers.FireworksAIProvider({ model: config.model }); return new Providers.FireworksAIProvider({ model: config.model });
case "deepseek": case "deepseek":
return new Providers.DeepSeekProvider({ model: config.model }); return new Providers.DeepSeekProvider({ model: config.model });
case "litellm":
return new Providers.LiteLLMProvider({ model: config.model });
case "apipie":
return new Providers.ApiPieProvider({ model: config.model });
case "xai":
return new Providers.XAIProvider({ model: config.model });
default: default:
throw new Error( throw new Error(

View File

@ -77,6 +77,9 @@ const webBrowsing = {
case "searxng-engine": case "searxng-engine":
engine = "_searXNGEngine"; engine = "_searXNGEngine";
break; break;
case "tavily-search":
engine = "_tavilySearch";
break;
default: default:
engine = "_googleSearchEngine"; engine = "_googleSearchEngine";
} }
@ -436,6 +439,59 @@ const webBrowsing = {
}); });
}); });
if (data.length === 0)
return `No information was found online for the search query.`;
this.super.introspect(
`${this.caller}: I found ${data.length} results - looking over them now.`
);
return JSON.stringify(data);
},
_tavilySearch: async function (query) {
if (!process.env.AGENT_TAVILY_API_KEY) {
this.super.introspect(
`${this.caller}: I can't use Tavily searching because the user has not defined the required API key.\nVisit: https://tavily.com/ to create the API key.`
);
return `Search is disabled and no content was found. This functionality is disabled because the user has not set it up yet.`;
}
this.super.introspect(
`${this.caller}: Using Tavily to search for "${
query.length > 100 ? `${query.slice(0, 100)}...` : query
}"`
);
const url = "https://api.tavily.com/search";
const { response, error } = await fetch(url, {
method: "POST",
headers: {
"Content-Type": "application/json",
},
body: JSON.stringify({
api_key: process.env.AGENT_TAVILY_API_KEY,
query: query,
}),
})
.then((res) => res.json())
.then((data) => {
return { response: data, error: null };
})
.catch((e) => {
return { response: null, error: e.message };
});
if (error)
return `There was an error searching for content. ${error}`;
const data = [];
response.results?.forEach((searchResult) => {
const { title, url, content } = searchResult;
data.push({
title,
link: url,
snippet: content,
});
});
if (data.length === 0) if (data.length === 0)
return `No information was found online for the search query.`; return `No information was found online for the search query.`;
this.super.introspect( this.super.introspect(

View File

@ -130,6 +130,30 @@ class Provider {
apiKey: process.env.FIREWORKS_AI_LLM_API_KEY, apiKey: process.env.FIREWORKS_AI_LLM_API_KEY,
...config, ...config,
}); });
case "apipie":
return new ChatOpenAI({
configuration: {
baseURL: "https://apipie.ai/v1",
},
apiKey: process.env.APIPIE_LLM_API_KEY ?? null,
...config,
});
case "deepseek":
return new ChatOpenAI({
configuration: {
baseURL: "https://api.deepseek.com/v1",
},
apiKey: process.env.DEEPSEEK_API_KEY ?? null,
...config,
});
case "xai":
return new ChatOpenAI({
configuration: {
baseURL: "https://api.x.ai/v1",
},
apiKey: process.env.XAI_LLM_API_KEY ?? null,
...config,
});
// OSS Model Runners // OSS Model Runners
// case "anythingllm_ollama": // case "anythingllm_ollama":
@ -174,14 +198,15 @@ class Provider {
apiKey: process.env.TEXT_GEN_WEB_UI_API_KEY ?? "not-used", apiKey: process.env.TEXT_GEN_WEB_UI_API_KEY ?? "not-used",
...config, ...config,
}); });
case "deepseek": case "litellm":
return new ChatOpenAI({ return new ChatOpenAI({
configuration: { configuration: {
baseURL: "https://api.deepseek.com/v1", baseURL: process.env.LITE_LLM_BASE_PATH,
}, },
apiKey: process.env.DEEPSEEK_API_KEY ?? null, apiKey: process.env.LITE_LLM_API_KEY ?? null,
...config, ...config,
}); });
default: default:
throw new Error(`Unsupported provider ${provider} for this task.`); throw new Error(`Unsupported provider ${provider} for this task.`);
} }

View File

@ -0,0 +1,116 @@
const OpenAI = require("openai");
const Provider = require("./ai-provider.js");
const InheritMultiple = require("./helpers/classes.js");
const UnTooled = require("./helpers/untooled.js");
/**
* The agent provider for the OpenRouter provider.
*/
class ApiPieProvider extends InheritMultiple([Provider, UnTooled]) {
model;
constructor(config = {}) {
const { model = "openrouter/llama-3.1-8b-instruct" } = config;
super();
const client = new OpenAI({
baseURL: "https://apipie.ai/v1",
apiKey: process.env.APIPIE_LLM_API_KEY,
maxRetries: 3,
});
this._client = client;
this.model = model;
this.verbose = true;
}
get client() {
return this._client;
}
async #handleFunctionCallChat({ messages = [] }) {
return await this.client.chat.completions
.create({
model: this.model,
temperature: 0,
messages,
})
.then((result) => {
if (!result.hasOwnProperty("choices"))
throw new Error("ApiPie chat: No results!");
if (result.choices.length === 0)
throw new Error("ApiPie chat: No results length!");
return result.choices[0].message.content;
})
.catch((_) => {
return null;
});
}
/**
* Create a completion based on the received messages.
*
* @param messages A list of messages to send to the API.
* @param functions
* @returns The completion.
*/
async complete(messages, functions = null) {
try {
let completion;
if (functions.length > 0) {
const { toolCall, text } = await this.functionCall(
messages,
functions,
this.#handleFunctionCallChat.bind(this)
);
if (toolCall !== null) {
this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
return {
result: null,
functionCall: {
name: toolCall.name,
arguments: toolCall.arguments,
},
cost: 0,
};
}
completion = { content: text };
}
if (!completion?.content) {
this.providerLog(
"Will assume chat completion without tool call inputs."
);
const response = await this.client.chat.completions.create({
model: this.model,
messages: this.cleanMsgs(messages),
});
completion = response.choices[0].message;
}
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
// from calling the exact same function over and over in a loop within a single chat exchange
// _but_ we should enable it to call previously used tools in a new chat interaction.
this.deduplicator.reset("runs");
return {
result: completion.content,
cost: 0,
};
} catch (error) {
throw error;
}
}
/**
* Get the cost of the completion.
*
* @param _usage The completion to get the cost for.
* @returns The cost of the completion.
*/
getCost(_usage) {
return 0;
}
}
module.exports = ApiPieProvider;

View File

@ -33,7 +33,10 @@ ${JSON.stringify(def.parameters.properties, null, 4)}\n`;
if (Array.isArray(def.examples)) { if (Array.isArray(def.examples)) {
def.examples.forEach(({ prompt, call }) => { def.examples.forEach(({ prompt, call }) => {
shotExample += `Query: "${prompt}"\nJSON: ${call}\n`; shotExample += `Query: "${prompt}"\nJSON: ${JSON.stringify({
name: def.name,
arguments: safeJsonParse(call, {}),
})}\n`;
}); });
} }
output += `${shotExample}-----------\n`; output += `${shotExample}-----------\n`;

View File

@ -15,6 +15,9 @@ const TextWebGenUiProvider = require("./textgenwebui.js");
const AWSBedrockProvider = require("./bedrock.js"); const AWSBedrockProvider = require("./bedrock.js");
const FireworksAIProvider = require("./fireworksai.js"); const FireworksAIProvider = require("./fireworksai.js");
const DeepSeekProvider = require("./deepseek.js"); const DeepSeekProvider = require("./deepseek.js");
const LiteLLMProvider = require("./litellm.js");
const ApiPieProvider = require("./apipie.js");
const XAIProvider = require("./xai.js");
module.exports = { module.exports = {
OpenAIProvider, OpenAIProvider,
@ -34,4 +37,7 @@ module.exports = {
TextWebGenUiProvider, TextWebGenUiProvider,
AWSBedrockProvider, AWSBedrockProvider,
FireworksAIProvider, FireworksAIProvider,
LiteLLMProvider,
ApiPieProvider,
XAIProvider,
}; };

View File

@ -0,0 +1,110 @@
const OpenAI = require("openai");
const Provider = require("./ai-provider.js");
const InheritMultiple = require("./helpers/classes.js");
const UnTooled = require("./helpers/untooled.js");
/**
* The agent provider for LiteLLM.
*/
class LiteLLMProvider extends InheritMultiple([Provider, UnTooled]) {
model;
constructor(config = {}) {
super();
const { model = null } = config;
const client = new OpenAI({
baseURL: process.env.LITE_LLM_BASE_PATH,
apiKey: process.env.LITE_LLM_API_KEY ?? null,
maxRetries: 3,
});
this._client = client;
this.model = model || process.env.LITE_LLM_MODEL_PREF;
this.verbose = true;
}
get client() {
return this._client;
}
async #handleFunctionCallChat({ messages = [] }) {
return await this.client.chat.completions
.create({
model: this.model,
temperature: 0,
messages,
})
.then((result) => {
if (!result.hasOwnProperty("choices"))
throw new Error("LiteLLM chat: No results!");
if (result.choices.length === 0)
throw new Error("LiteLLM chat: No results length!");
return result.choices[0].message.content;
})
.catch((_) => {
return null;
});
}
/**
* Create a completion based on the received messages.
*
* @param messages A list of messages to send to the API.
* @param functions
* @returns The completion.
*/
async complete(messages, functions = null) {
try {
let completion;
if (functions.length > 0) {
const { toolCall, text } = await this.functionCall(
messages,
functions,
this.#handleFunctionCallChat.bind(this)
);
if (toolCall !== null) {
this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
return {
result: null,
functionCall: {
name: toolCall.name,
arguments: toolCall.arguments,
},
cost: 0,
};
}
completion = { content: text };
}
if (!completion?.content) {
this.providerLog(
"Will assume chat completion without tool call inputs."
);
const response = await this.client.chat.completions.create({
model: this.model,
messages: this.cleanMsgs(messages),
});
completion = response.choices[0].message;
}
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
// from calling the exact same function over and over in a loop within a single chat exchange
// _but_ we should enable it to call previously used tools in a new chat interaction.
this.deduplicator.reset("runs");
return {
result: completion.content,
cost: 0,
};
} catch (error) {
throw error;
}
}
getCost(_usage) {
return 0;
}
}
module.exports = LiteLLMProvider;

View File

@ -9,9 +9,14 @@ const UnTooled = require("./helpers/untooled.js");
class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) { class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
model; model;
constructor(_config = {}) { /**
*
* @param {{model?: string}} config
*/
constructor(config = {}) {
super(); super();
const model = process.env.LMSTUDIO_MODEL_PREF || "Loaded from Chat UI"; const model =
config?.model || process.env.LMSTUDIO_MODEL_PREF || "Loaded from Chat UI";
const client = new OpenAI({ const client = new OpenAI({
baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""), // here is the URL to your LMStudio instance baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""), // here is the URL to your LMStudio instance
apiKey: null, apiKey: null,

View File

@ -0,0 +1,116 @@
const OpenAI = require("openai");
const Provider = require("./ai-provider.js");
const InheritMultiple = require("./helpers/classes.js");
const UnTooled = require("./helpers/untooled.js");
/**
* The agent provider for the xAI provider.
*/
class XAIProvider extends InheritMultiple([Provider, UnTooled]) {
model;
constructor(config = {}) {
const { model = "grok-beta" } = config;
super();
const client = new OpenAI({
baseURL: "https://api.x.ai/v1",
apiKey: process.env.XAI_LLM_API_KEY,
maxRetries: 3,
});
this._client = client;
this.model = model;
this.verbose = true;
}
get client() {
return this._client;
}
async #handleFunctionCallChat({ messages = [] }) {
return await this.client.chat.completions
.create({
model: this.model,
temperature: 0,
messages,
})
.then((result) => {
if (!result.hasOwnProperty("choices"))
throw new Error("xAI chat: No results!");
if (result.choices.length === 0)
throw new Error("xAI chat: No results length!");
return result.choices[0].message.content;
})
.catch((_) => {
return null;
});
}
/**
* Create a completion based on the received messages.
*
* @param messages A list of messages to send to the API.
* @param functions
* @returns The completion.
*/
async complete(messages, functions = null) {
try {
let completion;
if (functions.length > 0) {
const { toolCall, text } = await this.functionCall(
messages,
functions,
this.#handleFunctionCallChat.bind(this)
);
if (toolCall !== null) {
this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
return {
result: null,
functionCall: {
name: toolCall.name,
arguments: toolCall.arguments,
},
cost: 0,
};
}
completion = { content: text };
}
if (!completion?.content) {
this.providerLog(
"Will assume chat completion without tool call inputs."
);
const response = await this.client.chat.completions.create({
model: this.model,
messages: this.cleanMsgs(messages),
});
completion = response.choices[0].message;
}
// The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
// from calling the exact same function over and over in a loop within a single chat exchange
// _but_ we should enable it to call previously used tools in a new chat interaction.
this.deduplicator.reset("runs");
return {
result: completion.content,
cost: 0,
};
} catch (error) {
throw error;
}
}
/**
* Get the cost of the completion.
*
* @param _usage The completion to get the cost for.
* @returns The cost of the completion.
*/
getCost(_usage) {
return 0;
}
}
module.exports = XAIProvider;

View File

@ -99,30 +99,69 @@ class EphemeralAgentHandler extends AgentHandler {
} }
} }
/**
* Attempts to find a fallback provider and model to use if the workspace
* does not have an explicit `agentProvider` and `agentModel` set.
* 1. Fallback to the workspace `chatProvider` and `chatModel` if they exist.
* 2. Fallback to the system `LLM_PROVIDER` and try to load the the associated default model via ENV params or a base available model.
* 3. Otherwise, return null - will likely throw an error the user can act on.
* @returns {object|null} - An object with provider and model keys.
*/
#getFallbackProvider() {
// First, fallback to the workspace chat provider and model if they exist
if (this.#workspace.chatProvider && this.#workspace.chatModel) {
return {
provider: this.#workspace.chatProvider,
model: this.#workspace.chatModel,
};
}
// If workspace does not have chat provider and model fallback
// to system provider and try to load provider default model
const systemProvider = process.env.LLM_PROVIDER;
const systemModel = this.providerDefault(systemProvider);
if (systemProvider && systemModel) {
return {
provider: systemProvider,
model: systemModel,
};
}
return null;
}
/** /**
* Finds or assumes the model preference value to use for API calls. * Finds or assumes the model preference value to use for API calls.
* If multi-model loading is supported, we use their agent model selection of the workspace * If multi-model loading is supported, we use their agent model selection of the workspace
* If not supported, we attempt to fallback to the system provider value for the LLM preference * If not supported, we attempt to fallback to the system provider value for the LLM preference
* and if that fails - we assume a reasonable base model to exist. * and if that fails - we assume a reasonable base model to exist.
* @returns {string} the model preference value to use in API calls * @returns {string|null} the model preference value to use in API calls
*/ */
#fetchModel() { #fetchModel() {
if (!Object.keys(this.noProviderModelDefault).includes(this.provider)) // Provider was not explicitly set for workspace, so we are going to run our fallback logic
return this.#workspace.agentModel || this.providerDefault(); // that will set a provider and model for us to use.
if (!this.provider) {
const fallback = this.#getFallbackProvider();
if (!fallback) throw new Error("No valid provider found for the agent.");
this.provider = fallback.provider; // re-set the provider to the fallback provider so it is not null.
return fallback.model; // set its defined model based on fallback logic.
}
// Provider has no reliable default (cant load many models) - so we need to look at system // The provider was explicitly set, so check if the workspace has an agent model set.
// for the model param. if (this.invocation.workspace.agentModel)
const sysModelKey = this.noProviderModelDefault[this.provider]; return this.invocation.workspace.agentModel;
if (!!sysModelKey)
return process.env[sysModelKey] ?? this.providerDefault();
// If all else fails - look at the provider default list // Otherwise, we have no model to use - so guess a default model to use via the provider
// and it's system ENV params and if that fails - we return either a base model or null.
return this.providerDefault(); return this.providerDefault();
} }
#providerSetupAndCheck() { #providerSetupAndCheck() {
this.provider = this.#workspace.agentProvider; this.provider = this.#workspace.agentProvider ?? null;
this.model = this.#fetchModel(); this.model = this.#fetchModel();
if (!this.provider)
throw new Error("No valid provider found for the agent.");
this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`); this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`);
this.checkSetup(); this.checkSetup();
} }

View File

@ -11,13 +11,6 @@ const ImportedPlugin = require("./imported");
class AgentHandler { class AgentHandler {
#invocationUUID; #invocationUUID;
#funcsToLoad = []; #funcsToLoad = [];
noProviderModelDefault = {
azure: "OPEN_MODEL_PREF",
lmstudio: "LMSTUDIO_MODEL_PREF",
textgenwebui: null, // does not even use `model` in API req
"generic-openai": "GENERIC_OPEN_AI_MODEL_PREF",
bedrock: "AWS_BEDROCK_LLM_MODEL_PREFERENCE",
};
invocation = null; invocation = null;
aibitat = null; aibitat = null;
channel = null; channel = null;
@ -166,6 +159,20 @@ class AgentHandler {
if (!process.env.DEEPSEEK_API_KEY) if (!process.env.DEEPSEEK_API_KEY)
throw new Error("DeepSeek API Key must be provided to use agents."); throw new Error("DeepSeek API Key must be provided to use agents.");
break; break;
case "litellm":
if (!process.env.LITE_LLM_BASE_PATH)
throw new Error(
"LiteLLM API base path and key must be provided to use agents."
);
break;
case "apipie":
if (!process.env.APIPIE_LLM_API_KEY)
throw new Error("ApiPie API Key must be provided to use agents.");
break;
case "xai":
if (!process.env.XAI_LLM_API_KEY)
throw new Error("xAI API Key must be provided to use agents.");
break;
default: default:
throw new Error( throw new Error(
@ -174,49 +181,72 @@ class AgentHandler {
} }
} }
/**
* Finds the default model for a given provider. If no default model is set for it's associated ENV then
* it will return a reasonable base model for the provider if one exists.
* @param {string} provider - The provider to find the default model for.
* @returns {string|null} The default model for the provider.
*/
providerDefault(provider = this.provider) { providerDefault(provider = this.provider) {
switch (provider) { switch (provider) {
case "openai": case "openai":
return "gpt-4o"; return process.env.OPEN_MODEL_PREF ?? "gpt-4o";
case "anthropic": case "anthropic":
return "claude-3-sonnet-20240229"; return process.env.ANTHROPIC_MODEL_PREF ?? "claude-3-sonnet-20240229";
case "lmstudio": case "lmstudio":
return "server-default"; return process.env.LMSTUDIO_MODEL_PREF ?? "server-default";
case "ollama": case "ollama":
return "llama3:latest"; return process.env.OLLAMA_MODEL_PREF ?? "llama3:latest";
case "groq": case "groq":
return "llama3-70b-8192"; return process.env.GROQ_MODEL_PREF ?? "llama3-70b-8192";
case "togetherai": case "togetherai":
return "mistralai/Mixtral-8x7B-Instruct-v0.1"; return (
process.env.TOGETHER_AI_MODEL_PREF ??
"mistralai/Mixtral-8x7B-Instruct-v0.1"
);
case "azure": case "azure":
return "gpt-3.5-turbo"; return null;
case "koboldcpp": case "koboldcpp":
return null; return process.env.KOBOLD_CPP_MODEL_PREF ?? null;
case "gemini": case "gemini":
return "gemini-pro"; return process.env.GEMINI_MODEL_PREF ?? "gemini-pro";
case "localai": case "localai":
return null; return process.env.LOCAL_AI_MODEL_PREF ?? null;
case "openrouter": case "openrouter":
return "openrouter/auto"; return process.env.OPENROUTER_MODEL_PREF ?? "openrouter/auto";
case "mistral": case "mistral":
return "mistral-medium"; return process.env.MISTRAL_MODEL_PREF ?? "mistral-medium";
case "generic-openai": case "generic-openai":
return null; return process.env.GENERIC_OPEN_AI_MODEL_PREF ?? null;
case "perplexity": case "perplexity":
return "sonar-small-online"; return process.env.PERPLEXITY_MODEL_PREF ?? "sonar-small-online";
case "textgenwebui": case "textgenwebui":
return null; return null;
case "bedrock": case "bedrock":
return null; return process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE ?? null;
case "fireworksai": case "fireworksai":
return null; return process.env.FIREWORKS_AI_LLM_MODEL_PREF ?? null;
case "deepseek": case "deepseek":
return "deepseek-chat"; return process.env.DEEPSEEK_MODEL_PREF ?? "deepseek-chat";
case "litellm":
return process.env.LITE_LLM_MODEL_PREF ?? null;
case "apipie":
return process.env.APIPIE_LLM_MODEL_PREF ?? null;
case "xai":
return process.env.XAI_LLM_MODEL_PREF ?? "grok-beta";
default: default:
return "unknown"; return null;
} }
} }
/**
* Attempts to find a fallback provider and model to use if the workspace
* does not have an explicit `agentProvider` and `agentModel` set.
* 1. Fallback to the workspace `chatProvider` and `chatModel` if they exist.
* 2. Fallback to the system `LLM_PROVIDER` and try to load the the associated default model via ENV params or a base available model.
* 3. Otherwise, return null - will likely throw an error the user can act on.
* @returns {object|null} - An object with provider and model keys.
*/
#getFallbackProvider() { #getFallbackProvider() {
// First, fallback to the workspace chat provider and model if they exist // First, fallback to the workspace chat provider and model if they exist
if ( if (
@ -248,7 +278,7 @@ class AgentHandler {
* If multi-model loading is supported, we use their agent model selection of the workspace * If multi-model loading is supported, we use their agent model selection of the workspace
* If not supported, we attempt to fallback to the system provider value for the LLM preference * If not supported, we attempt to fallback to the system provider value for the LLM preference
* and if that fails - we assume a reasonable base model to exist. * and if that fails - we assume a reasonable base model to exist.
* @returns {string} the model preference value to use in API calls * @returns {string|null} the model preference value to use in API calls
*/ */
#fetchModel() { #fetchModel() {
// Provider was not explicitly set for workspace, so we are going to run our fallback logic // Provider was not explicitly set for workspace, so we are going to run our fallback logic
@ -261,21 +291,11 @@ class AgentHandler {
} }
// The provider was explicitly set, so check if the workspace has an agent model set. // The provider was explicitly set, so check if the workspace has an agent model set.
if (this.invocation.workspace.agentModel) { if (this.invocation.workspace.agentModel)
return this.invocation.workspace.agentModel; return this.invocation.workspace.agentModel;
}
// If the provider we are using is not supported or does not support multi-model loading // Otherwise, we have no model to use - so guess a default model to use via the provider
// then we use the default model for the provider. // and it's system ENV params and if that fails - we return either a base model or null.
if (!Object.keys(this.noProviderModelDefault).includes(this.provider)) {
return this.providerDefault();
}
// Load the model from the system environment variable for providers with no multi-model loading.
const sysModelKey = this.noProviderModelDefault[this.provider];
if (sysModelKey) return process.env[sysModelKey] ?? this.providerDefault();
// Otherwise, we have no model to use - so guess a default model to use.
return this.providerDefault(); return this.providerDefault();
} }
@ -285,7 +305,6 @@ class AgentHandler {
if (!this.provider) if (!this.provider)
throw new Error("No valid provider found for the agent."); throw new Error("No valid provider found for the agent.");
this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`); this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`);
this.checkSetup(); this.checkSetup();
} }

View File

@ -60,8 +60,7 @@ async function streamChatWithForEmbed(
const { rawHistory, chatHistory } = await recentEmbedChatHistory( const { rawHistory, chatHistory } = await recentEmbedChatHistory(
sessionId, sessionId,
embed, embed,
messageLimit, messageLimit
chatMode
); );
// See stream.js comment for more information on this implementation. // See stream.js comment for more information on this implementation.
@ -113,16 +112,27 @@ async function streamChatWithForEmbed(
return; return;
} }
contextTexts = [...contextTexts, ...vectorSearchResults.contextTexts]; const { fillSourceWindow } = require("../helpers/chat");
const filledSources = fillSourceWindow({
nDocs: embed.workspace?.topN || 4,
searchResults: vectorSearchResults.sources,
history: rawHistory,
filterIdentifiers: pinnedDocIdentifiers,
});
// Why does contextTexts get all the info, but sources only get current search?
// This is to give the ability of the LLM to "comprehend" a contextual response without
// populating the Citations under a response with documents the user "thinks" are irrelevant
// due to how we manage backfilling of the context to keep chats with the LLM more correct in responses.
// If a past citation was used to answer the question - that is visible in the history so it logically makes sense
// and does not appear to the user that a new response used information that is otherwise irrelevant for a given prompt.
// TLDR; reduces GitHub issues for "LLM citing document that has no answer in it" while keep answers highly accurate.
contextTexts = [...contextTexts, ...filledSources.contextTexts];
sources = [...sources, ...vectorSearchResults.sources]; sources = [...sources, ...vectorSearchResults.sources];
// If in query mode and no sources are found, do not // If in query mode and no sources are found in current search or backfilled from history, do not
// let the LLM try to hallucinate a response or use general knowledge // let the LLM try to hallucinate a response or use general knowledge
if ( if (chatMode === "query" && contextTexts.length === 0) {
chatMode === "query" &&
sources.length === 0 &&
pinnedDocIdentifiers.length === 0
) {
writeResponseChunk(response, { writeResponseChunk(response, {
id: uuid, id: uuid,
type: "textResponse", type: "textResponse",
@ -178,7 +188,7 @@ async function streamChatWithForEmbed(
await EmbedChats.new({ await EmbedChats.new({
embedId: embed.id, embedId: embed.id,
prompt: message, prompt: message,
response: { text: completeText, type: chatMode }, response: { text: completeText, type: chatMode, sources },
connection_information: response.locals.connection connection_information: response.locals.connection
? { ? {
...response.locals.connection, ...response.locals.connection,
@ -190,15 +200,13 @@ async function streamChatWithForEmbed(
return; return;
} }
// On query we don't return message history. All other chat modes and when chatting /**
// with no embeddings we return history. * @param {string} sessionId the session id of the user from embed widget
async function recentEmbedChatHistory( * @param {Object} embed the embed config object
sessionId, * @param {Number} messageLimit the number of messages to return
embed, * @returns {Promise<{rawHistory: import("@prisma/client").embed_chats[], chatHistory: {role: string, content: string}[]}>
messageLimit = 20, */
chatMode = null async function recentEmbedChatHistory(sessionId, embed, messageLimit = 20) {
) {
if (chatMode === "query") return { rawHistory: [], chatHistory: [] };
const rawHistory = ( const rawHistory = (
await EmbedChats.forEmbedByUser(embed.id, sessionId, messageLimit, { await EmbedChats.forEmbedByUser(embed.id, sessionId, messageLimit, {
id: "desc", id: "desc",

View File

@ -1,4 +1,5 @@
const { fetchOpenRouterModels } = require("../AiProviders/openRouter"); const { fetchOpenRouterModels } = require("../AiProviders/openRouter");
const { fetchApiPieModels } = require("../AiProviders/apipie");
const { perplexityModels } = require("../AiProviders/perplexity"); const { perplexityModels } = require("../AiProviders/perplexity");
const { togetherAiModels } = require("../AiProviders/togetherAi"); const { togetherAiModels } = require("../AiProviders/togetherAi");
const { fireworksAiModels } = require("../AiProviders/fireworksAi"); const { fireworksAiModels } = require("../AiProviders/fireworksAi");
@ -19,6 +20,8 @@ const SUPPORT_CUSTOM_MODELS = [
"elevenlabs-tts", "elevenlabs-tts",
"groq", "groq",
"deepseek", "deepseek",
"apipie",
"xai",
]; ];
async function getCustomModels(provider = "", apiKey = null, basePath = null) { async function getCustomModels(provider = "", apiKey = null, basePath = null) {
@ -56,6 +59,10 @@ async function getCustomModels(provider = "", apiKey = null, basePath = null) {
return await getGroqAiModels(apiKey); return await getGroqAiModels(apiKey);
case "deepseek": case "deepseek":
return await getDeepSeekModels(apiKey); return await getDeepSeekModels(apiKey);
case "apipie":
return await getAPIPieModels(apiKey);
case "xai":
return await getXAIModels(apiKey);
default: default:
return { models: [], error: "Invalid provider for custom models" }; return { models: [], error: "Invalid provider for custom models" };
} }
@ -124,7 +131,7 @@ async function openAiModels(apiKey = null) {
}); });
const gpts = allModels const gpts = allModels
.filter((model) => model.id.startsWith("gpt")) .filter((model) => model.id.startsWith("gpt") || model.id.startsWith("o1"))
.filter( .filter(
(model) => !model.id.includes("vision") && !model.id.includes("instruct") (model) => !model.id.includes("vision") && !model.id.includes("instruct")
) )
@ -355,6 +362,21 @@ async function getOpenRouterModels() {
return { models, error: null }; return { models, error: null };
} }
async function getAPIPieModels(apiKey = null) {
const knownModels = await fetchApiPieModels(apiKey);
if (!Object.keys(knownModels).length === 0)
return { models: [], error: null };
const models = Object.values(knownModels).map((model) => {
return {
id: model.id,
organization: model.organization,
name: model.name,
};
});
return { models, error: null };
}
async function getMistralModels(apiKey = null) { async function getMistralModels(apiKey = null) {
const { OpenAI: OpenAIApi } = require("openai"); const { OpenAI: OpenAIApi } = require("openai");
const openai = new OpenAIApi({ const openai = new OpenAIApi({
@ -447,6 +469,36 @@ async function getDeepSeekModels(apiKey = null) {
return { models, error: null }; return { models, error: null };
} }
async function getXAIModels(_apiKey = null) {
const { OpenAI: OpenAIApi } = require("openai");
const apiKey =
_apiKey === true
? process.env.XAI_LLM_API_KEY
: _apiKey || process.env.XAI_LLM_API_KEY || null;
const openai = new OpenAIApi({
baseURL: "https://api.x.ai/v1",
apiKey,
});
const models = await openai.models
.list()
.then((results) => results.data)
.catch((e) => {
console.error(`XAI:listModels`, e.message);
return [
{
created: 1725148800,
id: "grok-beta",
object: "model",
owned_by: "xai",
},
];
});
// Api Key was successful so lets save it for future uses
if (models.length > 0 && !!apiKey) process.env.XAI_LLM_API_KEY = apiKey;
return { models, error: null };
}
module.exports = { module.exports = {
getCustomModels, getCustomModels,
}; };

View File

@ -162,6 +162,12 @@ function getLLMProvider({ provider = null, model = null } = {}) {
case "deepseek": case "deepseek":
const { DeepSeekLLM } = require("../AiProviders/deepseek"); const { DeepSeekLLM } = require("../AiProviders/deepseek");
return new DeepSeekLLM(embedder, model); return new DeepSeekLLM(embedder, model);
case "apipie":
const { ApiPieLLM } = require("../AiProviders/apipie");
return new ApiPieLLM(embedder, model);
case "xai":
const { XAiLLM } = require("../AiProviders/xai");
return new XAiLLM(embedder, model);
default: default:
throw new Error( throw new Error(
`ENV: No valid LLM_PROVIDER value found in environment! Using ${process.env.LLM_PROVIDER}` `ENV: No valid LLM_PROVIDER value found in environment! Using ${process.env.LLM_PROVIDER}`
@ -285,6 +291,15 @@ function getLLMProviderClass({ provider = null } = {}) {
case "bedrock": case "bedrock":
const { AWSBedrockLLM } = require("../AiProviders/bedrock"); const { AWSBedrockLLM } = require("../AiProviders/bedrock");
return AWSBedrockLLM; return AWSBedrockLLM;
case "deepseek":
const { DeepSeekLLM } = require("../AiProviders/deepseek");
return DeepSeekLLM;
case "apipie":
const { ApiPieLLM } = require("../AiProviders/apipie");
return ApiPieLLM;
case "xai":
const { XAiLLM } = require("../AiProviders/xai");
return XAiLLM;
default: default:
return null; return null;
} }

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@ -469,6 +469,10 @@ const KEY_MAPPING = {
envKey: "AGENT_SEARXNG_API_URL", envKey: "AGENT_SEARXNG_API_URL",
checks: [], checks: [],
}, },
AgentTavilyApiKey: {
envKey: "AGENT_TAVILY_API_KEY",
checks: [],
},
// TTS/STT Integration ENVS // TTS/STT Integration ENVS
TextToSpeechProvider: { TextToSpeechProvider: {
@ -502,6 +506,20 @@ const KEY_MAPPING = {
checks: [], checks: [],
}, },
// OpenAI Generic TTS
TTSOpenAICompatibleKey: {
envKey: "TTS_OPEN_AI_COMPATIBLE_KEY",
checks: [],
},
TTSOpenAICompatibleVoiceModel: {
envKey: "TTS_OPEN_AI_COMPATIBLE_VOICE_MODEL",
checks: [isNotEmpty],
},
TTSOpenAICompatibleEndpoint: {
envKey: "TTS_OPEN_AI_COMPATIBLE_ENDPOINT",
checks: [isValidURL],
},
// DeepSeek Options // DeepSeek Options
DeepSeekApiKey: { DeepSeekApiKey: {
envKey: "DEEPSEEK_API_KEY", envKey: "DEEPSEEK_API_KEY",
@ -511,6 +529,26 @@ const KEY_MAPPING = {
envKey: "DEEPSEEK_MODEL_PREF", envKey: "DEEPSEEK_MODEL_PREF",
checks: [isNotEmpty], checks: [isNotEmpty],
}, },
// APIPie Options
ApipieLLMApiKey: {
envKey: "APIPIE_LLM_API_KEY",
checks: [isNotEmpty],
},
ApipieLLMModelPref: {
envKey: "APIPIE_LLM_MODEL_PREF",
checks: [isNotEmpty],
},
// xAI Options
XAIApiKey: {
envKey: "XAI_LLM_API_KEY",
checks: [isNotEmpty],
},
XAIModelPref: {
envKey: "XAI_LLM_MODEL_PREF",
checks: [isNotEmpty],
},
}; };
function isNotEmpty(input = "") { function isNotEmpty(input = "") {
@ -575,6 +613,7 @@ function supportedTTSProvider(input = "") {
"openai", "openai",
"elevenlabs", "elevenlabs",
"piper_local", "piper_local",
"generic-openai",
].includes(input); ].includes(input);
return validSelection ? null : `${input} is not a valid TTS provider.`; return validSelection ? null : `${input} is not a valid TTS provider.`;
} }
@ -613,6 +652,8 @@ function supportedLLM(input = "") {
"generic-openai", "generic-openai",
"bedrock", "bedrock",
"deepseek", "deepseek",
"apipie",
"xai",
].includes(input); ].includes(input);
return validSelection ? null : `${input} is not a valid LLM provider.`; return validSelection ? null : `${input} is not a valid LLM provider.`;
} }
@ -856,6 +897,8 @@ function dumpENV() {
"ENABLE_HTTPS", "ENABLE_HTTPS",
"HTTPS_CERT_PATH", "HTTPS_CERT_PATH",
"HTTPS_KEY_PATH", "HTTPS_KEY_PATH",
// Other Configuration Keys
"DISABLE_VIEW_CHAT_HISTORY",
]; ];
// Simple sanitization of each value to prevent ENV injection via newline or quote escaping. // Simple sanitization of each value to prevent ENV injection via newline or quote escaping.

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@ -0,0 +1,18 @@
/**
* A simple middleware that validates that the chat history is viewable.
* via the `DISABLE_VIEW_CHAT_HISTORY` environment variable being set AT ALL.
* @param {Request} request - The request object.
* @param {Response} response - The response object.
* @param {NextFunction} next - The next function.
*/
function chatHistoryViewable(_request, response, next) {
if ("DISABLE_VIEW_CHAT_HISTORY" in process.env)
return response
.status(422)
.send("This feature has been disabled by the administrator.");
next();
}
module.exports = {
chatHistoryViewable,
};