merge master

.vscode/settings.json

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

README.md

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

collector/index.js

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

collector/package.json

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

collector/processLink/convert/generic.js

@@ -27,7 +27,8 @@ async function scrapeGenericUrl(link, textOnly = false) {
   }
 
   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 = {
     id: v4(),

collector/processSingleFile/convert/asXlsx.js

@@ -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;

collector/processSingleFile/index.js

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

collector/utils/constants.js

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

collector/utils/extensions/RepoLoader/GithubRepo/RepoLoader/index.js

@@ -29,20 +29,36 @@ class GitHubRepoLoader {
   }
 
   #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") {
-    return true;
+        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;
+    } catch (e) {
+      console.log(
+        `[Github Loader]: Invalid Github URL provided! Error: ${e.message}`
+      );
+      return false;
+    }
   }
 
   // Ensure the branch provided actually exists

collector/utils/extensions/WebsiteDepth/index.js

@@ -108,7 +108,8 @@ async function bulkScrapePages(links, outFolderPath) {
       }
 
       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 = {
         id: v4(),

collector/utils/files/mime.js

@@ -1,5 +1,5 @@
 const MimeLib = require("mime");
-
+const path = require("path");
 class MimeDetector {
   nonTextTypes = ["multipart", "image", "model", "audio", "video"];
   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) {
-    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;
   }
 }
 

collector/yarn.lock

@@ -2326,6 +2326,13 @@ node-html-parser@^6.1.13:
     css-select "^5.1.0"
     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:
   version "6.9.13"
   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"
   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:
   version "0.6.2"
   resolved "https://registry.yarnpkg.com/xml2js/-/xml2js-0.6.2.tgz#dd0b630083aa09c161e25a4d0901e2b2a929b499"

docker/.env.example

@@ -105,6 +105,14 @@ GID='1000'
 # FIREWORKS_AI_LLM_API_KEY='my-fireworks-ai-key'
 # 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 ##########
 ###########################################
@@ -215,6 +223,11 @@ GID='1000'
 # TTS_OPEN_AI_KEY=sk-example
 # 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_ELEVEN_LABS_KEY=
 # TTS_ELEVEN_LABS_VOICE_MODEL=21m00Tcm4TlvDq8ikWAM # Rachel
@@ -271,3 +284,11 @@ GID='1000'
 
 #------ SearXNG ----------- https://github.com/searxng/searxng
 # 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

frontend/src/App.jsx

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

frontend/src/components/CanViewChatHistory/index.jsx

@@ -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 };
+}

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

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

frontend/src/components/LLMSelection/ApiPieOptions/index.jsx

@@ -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>
+  );
+}

frontend/src/components/LLMSelection/AzureAiOptions/index.jsx

@@ -71,23 +71,6 @@ export default function AzureAiOptions({ settings }) {
             </option>
           </select>
         </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>
   );

frontend/src/components/LLMSelection/XAiLLMOptions/index.jsx

@@ -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>
+  );
+}

frontend/src/components/Modals/ManageWorkspace/Documents/Directory/FileRow/index.jsx

@@ -31,7 +31,7 @@ export default function FileRow({ item, selected, toggleSelection }) {
           className="shrink-0 text-base font-bold w-4 h-4 mr-[3px]"
           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)}
         </p>
       </div>

frontend/src/components/Modals/ManageWorkspace/Documents/Directory/FolderRow/index.jsx

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

frontend/src/components/Modals/ManageWorkspace/Documents/WorkspaceDirectory/WorkspaceFileRow/index.jsx

@@ -83,7 +83,7 @@ export default function WorkspaceFileRow({
           className="shrink-0 text-base font-bold w-4 h-4 mr-[3px] ml-1"
           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)}
         </p>
       </div>

frontend/src/components/SettingsButton/index.jsx

@@ -29,9 +29,7 @@ export default function SettingsButton() {
   return (
     <ToolTipWrapper id="open-settings">
       <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"
         aria-label="Settings"
         data-tooltip-id="open-settings"

frontend/src/components/SettingsSidebar/MenuOption/index.jsx

@@ -149,17 +149,32 @@ function useIsExpanded({
   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 = []) {
   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 && !!user && !roles.includes(user?.role)) return false;
     return true;
   }
 
   return childOptions.some((opt) =>
-    isVisible({ roles: opt.roles, user, flex: opt.flex })
+    isVisible({ roles: opt.roles, user, flex: opt.flex, hidden: opt.hidden })
   );
 }
 

frontend/src/components/SettingsSidebar/index.jsx

@@ -21,6 +21,7 @@ import { useTranslation } from "react-i18next";
 import showToast from "@/utils/toast";
 import System from "@/models/system";
 import Option from "./MenuOption";
+import { CanViewChatHistoryProvider } from "../CanViewChatHistory";
 
 export default function SettingsSidebar() {
   const { t } = useTranslation();
@@ -208,156 +209,157 @@ function SupportEmail() {
 }
 
 const SidebarOptions = ({ user = null, t }) => (
-  <>
+  <CanViewChatHistoryProvider>
-    <Option
+    {({ viewable: canViewChatHistory }) => (
-      btnText={t("settings.ai-providers")}
+      <>
-      icon={<Gear className="h-5 w-5 flex-shrink-0" />}
+        <Option
-      user={user}
+          btnText={t("settings.ai-providers")}
-      childOptions={[
+          icon={<Gear className="h-5 w-5 flex-shrink-0" />}
-        {
+          user={user}
-          btnText: t("settings.llm"),
+          childOptions={[
-          href: paths.settings.llmPreference(),
+            {
-          flex: true,
+              btnText: t("settings.llm"),
-          roles: ["admin"],
+              href: paths.settings.llmPreference(),
-        },
+              flex: true,
-        {
+              roles: ["admin"],
-          btnText: t("settings.vector-database"),
+            },
-          href: paths.settings.vectorDatabase(),
+            {
-          flex: true,
+              btnText: t("settings.vector-database"),
-          roles: ["admin"],
+              href: paths.settings.vectorDatabase(),
-        },
+              flex: true,
-        {
+              roles: ["admin"],
-          btnText: t("settings.embedder"),
+            },
-          href: paths.settings.embedder.modelPreference(),
+            {
-          flex: true,
+              btnText: t("settings.embedder"),
-          roles: ["admin"],
+              href: paths.settings.embedder.modelPreference(),
-        },
+              flex: true,
-        {
+              roles: ["admin"],
-          btnText: t("settings.text-splitting"),
+            },
-          href: paths.settings.embedder.chunkingPreference(),
+            {
-          flex: true,
+              btnText: t("settings.text-splitting"),
-          roles: ["admin"],
+              href: paths.settings.embedder.chunkingPreference(),
-        },
+              flex: true,
-        {
+              roles: ["admin"],
-          btnText: t("settings.voice-speech"),
+            },
-          href: paths.settings.audioPreference(),
+            {
-          flex: true,
+              btnText: t("settings.voice-speech"),
-          roles: ["admin"],
+              href: paths.settings.audioPreference(),
-        },
+              flex: true,
-        {
+              roles: ["admin"],
-          btnText: t("settings.transcription"),
+            },
-          href: paths.settings.transcriptionPreference(),
+            {
-          flex: true,
+              btnText: t("settings.transcription"),
-          roles: ["admin"],
+              href: paths.settings.transcriptionPreference(),
-        },
+              flex: true,
-      ]}
+              roles: ["admin"],
-    />
+            },
-    <Option
+          ]}
-      btnText={t("settings.admin")}
+        />
-      icon={<UserCircleGear className="h-5 w-5 flex-shrink-0" />}
+        <Option
-      user={user}
+          btnText={t("settings.admin")}
-      childOptions={[
+          icon={<UserCircleGear className="h-5 w-5 flex-shrink-0" />}
-        {
+          user={user}
-          btnText: t("settings.users"),
+          childOptions={[
-          href: paths.settings.users(),
+            {
-          roles: ["admin", "manager"],
+              btnText: t("settings.users"),
-        },
+              href: paths.settings.users(),
-        {
+              roles: ["admin", "manager"],
-          btnText: t("settings.workspaces"),
+            },
-          href: paths.settings.workspaces(),
+            {
-          roles: ["admin", "manager"],
+              btnText: t("settings.workspaces"),
-        },
+              href: paths.settings.workspaces(),
-        {
+              roles: ["admin", "manager"],
-          btnText: t("settings.workspace-chats"),
+            },
-          href: paths.settings.chats(),
+            {
-          flex: true,
+              hidden: !canViewChatHistory,
-          roles: ["admin", "manager"],
+              btnText: t("settings.workspace-chats"),
-        },
+              href: paths.settings.chats(),
-        {
+              flex: true,
-          btnText: t("settings.invites"),
+              roles: ["admin", "manager"],
-          href: paths.settings.invites(),
+            },
-          roles: ["admin", "manager"],
+            {
-        },
+              btnText: t("settings.invites"),
-        {
+              href: paths.settings.invites(),
-          btnText: t("settings.system"),
+              roles: ["admin", "manager"],
-          href: paths.settings.system(),
+            },
-          roles: ["admin", "manager"],
+          ]}
-        },
+        />
-      ]}
+        <Option
-    />
+          btnText={t("settings.agent-skills")}
-    <Option
+          icon={<Robot className="h-5 w-5 flex-shrink-0" />}
-      btnText={t("settings.agent-skills")}
+          href={paths.settings.agentSkills()}
-      icon={<Robot className="h-5 w-5 flex-shrink-0" />}
+          user={user}
-      href={paths.settings.agentSkills()}
+          flex={true}
-      user={user}
+          roles={["admin"]}
-      flex={true}
+        />
-      roles={["admin"]}
+        <Option
-    />
+          btnText={t("settings.customization")}
-    <Option
+          icon={<PencilSimpleLine className="h-5 w-5 flex-shrink-0" />}
-      btnText={t("settings.customization")}
+          href={paths.settings.appearance()}
-      icon={<PencilSimpleLine className="h-5 w-5 flex-shrink-0" />}
+          user={user}
-      href={paths.settings.appearance()}
+          flex={true}
-      user={user}
+          roles={["admin", "manager"]}
-      flex={true}
+        />
-      roles={["admin", "manager"]}
+        <Option
-    />
+          btnText={t("settings.tools")}
-    <Option
+          icon={<Toolbox className="h-5 w-5 flex-shrink-0" />}
-      btnText={t("settings.tools")}
+          user={user}
-      icon={<Toolbox className="h-5 w-5 flex-shrink-0" />}
+          childOptions={[
-      user={user}
+            {
-      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,
+              roles: ["admin"],
-          roles: ["admin"],
+            },
-        },
+            {
-        {
+              btnText: t("settings.embeds"),
-          btnText: t("settings.embeds"),
+              href: paths.settings.embedSetup(),
-          href: paths.settings.embedSetup(),
+              flex: true,
-          flex: true,
+              roles: ["admin"],
-          roles: ["admin"],
+            },
-        },
+            {
-        {
+              btnText: t("settings.event-logs"),
-          btnText: t("settings.event-logs"),
+              href: paths.settings.logs(),
-          href: paths.settings.logs(),
+              flex: true,
-          flex: true,
+              roles: ["admin"],
-          roles: ["admin"],
+            },
-        },
+            {
-        {
+              btnText: t("settings.api-keys"),
-          btnText: t("settings.api-keys"),
+              href: paths.settings.apiKeys(),
-          href: paths.settings.apiKeys(),
+              flex: true,
-          flex: true,
+              roles: ["admin"],
-          roles: ["admin"],
+            },
-        },
+            {
-        {
+              btnText: t("settings.browser-extension"),
-          btnText: t("settings.browser-extension"),
+              href: paths.settings.browserExtension(),
-          href: paths.settings.browserExtension(),
+              flex: true,
-          flex: true,
+              roles: ["admin", "manager"],
-          roles: ["admin", "manager"],
+            },
-        },
+          ]}
-      ]}
+        />
-    />
+        <Option
-    <Option
+          btnText={t("settings.security")}
-      btnText={t("settings.security")}
+          icon={<Nut className="h-5 w-5 flex-shrink-0" />}
-      icon={<Nut className="h-5 w-5 flex-shrink-0" />}
+          href={paths.settings.security()}
-      href={paths.settings.security()}
+          user={user}
-      user={user}
+          flex={true}
-      flex={true}
+          roles={["admin", "manager"]}
-      roles={["admin", "manager"]}
+          hidden={user?.role}
-      hidden={user?.role}
+        />
-    />
+        <HoldToReveal key="exp_features">
-    <HoldToReveal key="exp_features">
+          <Option
-      <Option
+            btnText={t("settings.experimental-features")}
-        btnText={t("settings.experimental-features")}
+            icon={<Flask className="h-5 w-5 flex-shrink-0" />}
-        icon={<Flask className="h-5 w-5 flex-shrink-0" />}
+            href={paths.settings.experimental()}
-        href={paths.settings.experimental()}
+            user={user}
-        user={user}
+            flex={true}
-        flex={true}
+            roles={["admin"]}
-        roles={["admin"]}
+          />
-      />
+        </HoldToReveal>
-    </HoldToReveal>
+      </>
-  </>
+    )}
+  </CanViewChatHistoryProvider>
 );
 
 function HoldToReveal({ children, holdForMs = 3_000 }) {

frontend/src/components/TextToSpeech/OpenAiGenericOptions/index.jsx

@@ -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>
+  );
+}

frontend/src/components/UserMenu/AccountModal/index.jsx

@@ -135,7 +135,7 @@ export default function AccountModal({ user, hideModal }) {
                 autoComplete="off"
               />
               <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
               </p>
             </div>

frontend/src/components/WorkspaceChat/ChatContainer/ChatHistory/HistoricalMessage/Actions/TTSButton/index.jsx

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

frontend/src/components/WorkspaceChat/ChatContainer/ChatHistory/HistoricalMessage/index.jsx

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

frontend/src/components/WorkspaceChat/ChatContainer/DnDWrapper/index.jsx

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

frontend/src/components/WorkspaceChat/ChatContainer/PromptInput/index.jsx

@@ -122,9 +122,22 @@ export default function PromptInput({
 
     const pasteText = e.clipboardData.getData("text/plain");
     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);
       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;
   };

frontend/src/hooks/useGetProvidersModels.js

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

frontend/src/models/system.js

@@ -9,6 +9,7 @@ const System = {
     footerIcons: "anythingllm_footer_links",
     supportEmail: "anythingllm_support_email",
     customAppName: "anythingllm_custom_app_name",
+    canViewChatHistory: "anythingllm_can_view_chat_history",
   },
   ping: async function () {
     return await fetch(`${API_BASE}/ping`)
@@ -675,6 +676,36 @@ const System = {
         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: {
     liveSync: LiveDocumentSync,
     agentPlugins: AgentPlugins,

frontend/src/pages/Admin/Agents/WebSearchSelection/SearchProviderOptions/index.jsx

@@ -281,3 +281,38 @@ export function SearXNGOptions({ settings }) {
     </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>
+    </>
+  );
+}

frontend/src/pages/Admin/Agents/WebSearchSelection/icons/tavily.svg

@@ -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>

frontend/src/pages/Admin/Agents/WebSearchSelection/index.jsx

@@ -7,6 +7,7 @@ import SerperDotDevIcon from "./icons/serper.png";
 import BingSearchIcon from "./icons/bing.png";
 import SerplySearchIcon from "./icons/serply.png";
 import SearXNGSearchIcon from "./icons/searxng.png";
+import TavilySearchIcon from "./icons/tavily.svg";
 import {
   CaretUpDown,
   MagnifyingGlass,
@@ -22,6 +23,7 @@ import {
   BingSearchOptions,
   SerplySearchOptions,
   SearXNGOptions,
+  TavilySearchOptions,
 } from "./SearchProviderOptions";
 
 const SEARCH_PROVIDERS = [
@@ -81,6 +83,14 @@ const SEARCH_PROVIDERS = [
     description:
       "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({

frontend/src/pages/Admin/System/index.jsx

@@ -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>
-  );
-}

frontend/src/pages/Admin/Users/NewUserModal/index.jsx

@@ -2,11 +2,15 @@ import React, { useState } from "react";
 import { X } from "@phosphor-icons/react";
 import Admin from "@/models/admin";
 import { userFromStorage } from "@/utils/request";
-import { RoleHintDisplay } from "..";
+import { MessageLimitInput, RoleHintDisplay } from "..";
 
 export default function NewUserModal({ closeModal }) {
   const [error, setError] = useState(null);
   const [role, setRole] = useState("default");
+  const [messageLimit, setMessageLimit] = useState({
+    enabled: false,
+    limit: 10,
+  });
 
   const handleCreate = async (e) => {
     setError(null);
@@ -14,6 +18,8 @@ export default function NewUserModal({ closeModal }) {
     const data = {};
     const form = new FormData(e.target);
     for (var [key, value] of form.entries()) data[key] = value;
+    data.dailyMessageLimit = messageLimit.enabled ? messageLimit.limit : null;
+
     const { user, error } = await Admin.newUser(data);
     if (!!user) window.location.reload();
     setError(error);
@@ -58,13 +64,13 @@ export default function NewUserModal({ closeModal }) {
                   pattern="^[a-z0-9_-]+$"
                   onInvalid={(e) =>
                     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("")}
                 />
                 <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
                 </p>
               </div>
@@ -110,6 +116,12 @@ export default function NewUserModal({ closeModal }) {
                 </select>
                 <RoleHintDisplay role={role} />
               </div>
+              <MessageLimitInput
+                role={role}
+                enabled={messageLimit.enabled}
+                limit={messageLimit.limit}
+                updateState={setMessageLimit}
+              />
               {error && <p className="text-red-400 text-sm">Error: {error}</p>}
               <p className="text-white text-xs md:text-sm">
                 After creating a user they will need to login with their initial

frontend/src/pages/Admin/Users/UserRow/EditUserModal/index.jsx

@@ -1,11 +1,15 @@
 import React, { useState } from "react";
 import { X } from "@phosphor-icons/react";
 import Admin from "@/models/admin";
-import { RoleHintDisplay } from "../..";
+import { MessageLimitInput, RoleHintDisplay } from "../..";
 
 export default function EditUserModal({ currentUser, user, closeModal }) {
   const [role, setRole] = useState(user.role);
   const [error, setError] = useState(null);
+  const [messageLimit, setMessageLimit] = useState({
+    enabled: user.dailyMessageLimit !== null,
+    limit: user.dailyMessageLimit || 10,
+  });
 
   const handleUpdate = async (e) => {
     setError(null);
@@ -16,6 +20,12 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
       if (!value || value === null) continue;
       data[key] = value;
     }
+    if (messageLimit.enabled) {
+      data.dailyMessageLimit = messageLimit.limit;
+    } else {
+      data.dailyMessageLimit = null;
+    }
+
     const { success, error } = await Admin.updateUser(user.id, data);
     if (success) window.location.reload();
     setError(error);
@@ -58,7 +68,7 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
                   autoComplete="off"
                 />
                 <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
                 </p>
               </div>
@@ -103,6 +113,12 @@ export default function EditUserModal({ currentUser, user, closeModal }) {
                 </select>
                 <RoleHintDisplay role={role} />
               </div>
+              <MessageLimitInput
+                role={role}
+                enabled={messageLimit.enabled}
+                limit={messageLimit.limit}
+                updateState={setMessageLimit}
+              />
               {error && <p className="text-red-400 text-sm">Error: {error}</p>}
             </div>
           </div>

frontend/src/pages/Admin/Users/index.jsx

@@ -135,3 +135,58 @@ export function RoleHintDisplay({ role }) {
     </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>
+  );
+}

frontend/src/pages/GeneralSettings/AudioPreference/tts.jsx

@@ -8,10 +8,13 @@ import OpenAiLogo from "@/media/llmprovider/openai.png";
 import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
 import ElevenLabsIcon from "@/media/ttsproviders/elevenlabs.png";
 import PiperTTSIcon from "@/media/ttsproviders/piper.png";
+import GenericOpenAiLogo from "@/media/ttsproviders/generic-openai.png";
+
 import BrowserNative from "@/components/TextToSpeech/BrowserNative";
 import OpenAiTTSOptions from "@/components/TextToSpeech/OpenAiOptions";
 import ElevenLabsTTSOptions from "@/components/TextToSpeech/ElevenLabsOptions";
 import PiperTTSOptions from "@/components/TextToSpeech/PiperTTSOptions";
+import OpenAiGenericTTSOptions from "@/components/TextToSpeech/OpenAiGenericOptions";
 
 const PROVIDERS = [
   {
@@ -42,6 +45,14 @@ const PROVIDERS = [
     options: (settings) => <PiperTTSOptions settings={settings} />,
     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 }) {

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

@@ -11,6 +11,7 @@ import { CaretDown, Download, Sparkle, Trash } from "@phosphor-icons/react";
 import { saveAs } from "file-saver";
 import { useTranslation } from "react-i18next";
 import paths from "@/utils/paths";
+import { CanViewChatHistory } from "@/components/CanViewChatHistory";
 
 const exportOptions = {
   csv: {
@@ -106,7 +107,8 @@ export default function WorkspaceChats() {
 
   useEffect(() => {
     async function fetchChats() {
-      const { chats: _chats, hasPages = false } = await System.chats(offset);
+      const { chats: _chats = [], hasPages = false } =
+        await System.chats(offset);
       setChats(_chats);
       setCanNext(hasPages);
       setLoading(false);
@@ -115,85 +117,87 @@ export default function WorkspaceChats() {
   }, [offset]);
 
   return (
-    <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
+    <CanViewChatHistory>
-      <Sidebar />
+      <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
-      <div
+        <Sidebar />
-        style={{ height: isMobile ? "100%" : "calc(100% - 32px)" }}
+        <div
-        className="relative md:ml-[2px] md:mr-[16px] md:my-[16px] md:rounded-[16px] bg-main-gradient w-full h-full overflow-y-scroll"
+          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"
-        <div 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="flex flex-col w-full px-1 md:pl-6 md:pr-[50px] md:py-6 py-16">
-            <div className="flex gap-x-4 items-center">
+            <div className="w-full flex flex-col gap-y-1 pb-6 border-white border-b-2 border-opacity-10">
-              <p className="text-lg leading-6 font-bold text-white">
+              <div className="flex gap-x-4 items-center">
-                {t("recorded.title")}
+                <p className="text-lg leading-6 font-bold text-white">
-              </p>
+                  {t("recorded.title")}
-              <div className="relative">
+                </p>
-                <button
+                <div className="relative">
-                  ref={openMenuButton}
+                  <button
-                  onClick={toggleMenu}
+                    ref={openMenuButton}
-                  className="flex items-center gap-x-2 px-4 py-1 rounded-lg bg-primary-button hover:text-white text-xs font-semibold hover:bg-secondary shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
+                    onClick={toggleMenu}
-                >
+                    className="flex items-center gap-x-2 px-4 py-1 rounded-lg bg-primary-button hover:text-white text-xs font-semibold hover:bg-secondary shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
-                  <Download size={18} weight="bold" />
+                  >
-                  {t("recorded.export")}
+                    <Download size={18} weight="bold" />
-                  <CaretDown size={18} weight="bold" />
+                    {t("recorded.export")}
-                </button>
+                    <CaretDown size={18} weight="bold" />
-                <div
+                  </button>
-                  ref={menuRef}
+                  <div
-                  className={`${
+                    ref={menuRef}
-                    showMenu ? "slide-down" : "slide-up hidden"
+                    className={`${
-                  } z-20 w-fit rounded-lg absolute top-full right-0 bg-secondary mt-2 shadow-md`}
+                      showMenu ? "slide-down" : "slide-up hidden"
-                >
+                    } z-20 w-fit rounded-lg absolute top-full right-0 bg-secondary mt-2 shadow-md`}
-                  <div className="py-2">
+                  >
-                    {Object.entries(exportOptions).map(([key, data]) => (
+                    <div className="py-2">
-                      <button
+                      {Object.entries(exportOptions).map(([key, data]) => (
-                        key={key}
+                        <button
-                        onClick={() => {
+                          key={key}
-                          handleDumpChats(key);
+                          onClick={() => {
-                          setShowMenu(false);
+                            handleDumpChats(key);
-                        }}
+                            setShowMenu(false);
-                        className="w-full text-left px-4 py-2 text-white text-sm hover:bg-[#3D4147]"
+                          }}
-                      >
+                          className="w-full text-left px-4 py-2 text-white text-sm hover:bg-[#3D4147]"
-                        {data.name}
+                        >
-                      </button>
+                          {data.name}
-                    ))}
+                        </button>
+                      ))}
+                    </div>
                   </div>
                 </div>
+                {chats.length > 0 && (
+                  <>
+                    <button
+                      onClick={handleClearAllChats}
+                      className="flex items-center gap-x-2 px-4 py-1 border hover:border-transparent border-white/40 text-white/40 rounded-lg bg-transparent hover:text-white text-xs font-semibold hover:bg-red-500 shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
+                    >
+                      <Trash size={18} weight="bold" />
+                      Clear Chats
+                    </button>
+                    <a
+                      href={paths.orderFineTune()}
+                      className="flex items-center gap-x-2 px-4 py-1 border hover:border-transparent border-yellow-300 text-yellow-300/80 rounded-lg bg-transparent hover:text-white text-xs font-semibold hover:bg-yellow-300/75 shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
+                    >
+                      <Sparkle size={18} weight="bold" />
+                      Order Fine-Tune Model
+                    </a>
+                  </>
+                )}
               </div>
-              {chats.length > 0 && (
+              <p className="text-xs leading-[18px] font-base text-white text-opacity-60">
-                <>
+                {t("recorded.description")}
-                  <button
+              </p>
-                    onClick={handleClearAllChats}
-                    className="flex items-center gap-x-2 px-4 py-1 border hover:border-transparent border-white/40 text-white/40 rounded-lg bg-transparent hover:text-white text-xs font-semibold hover:bg-red-500 shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
-                  >
-                    <Trash size={18} weight="bold" />
-                    Clear Chats
-                  </button>
-                  <a
-                    href={paths.orderFineTune()}
-                    className="flex items-center gap-x-2 px-4 py-1 border hover:border-transparent border-yellow-300 text-yellow-300/80 rounded-lg bg-transparent hover:text-white text-xs font-semibold hover:bg-yellow-300/75 shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
-                  >
-                    <Sparkle size={18} weight="bold" />
-                    Order Fine-Tune Model
-                  </a>
-                </>
-              )}
             </div>
-            <p className="text-xs leading-[18px] font-base text-white text-opacity-60">
+            <ChatsContainer
-              {t("recorded.description")}
+              loading={loading}
-            </p>
+              chats={chats}
+              setChats={setChats}
+              offset={offset}
+              setOffset={setOffset}
+              canNext={canNext}
+              t={t}
+            />
           </div>
-          <ChatsContainer
-            loading={loading}
-            chats={chats}
-            setChats={setChats}
-            offset={offset}
-            setOffset={setOffset}
-            canNext={canNext}
-            t={t}
-          />
         </div>
       </div>
-    </div>
+    </CanViewChatHistory>
   );
 }
 

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

@@ -11,6 +11,7 @@ import { CaretDown, Download } from "@phosphor-icons/react";
 import showToast from "@/utils/toast";
 import { saveAs } from "file-saver";
 import System from "@/models/system";
+import { CanViewChatHistory } from "@/components/CanViewChatHistory";
 
 const exportOptions = {
   csv: {
@@ -88,59 +89,61 @@ export default function EmbedChats() {
   }, []);
 
   return (
-    <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
+    <CanViewChatHistory>
-      <Sidebar />
+      <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
-      <div
+        <Sidebar />
-        style={{ height: isMobile ? "100%" : "calc(100% - 32px)" }}
+        <div
-        className="relative md:ml-[2px] md:mr-[16px] md:my-[16px] md:rounded-[16px] bg-main-gradient w-full h-full overflow-y-scroll"
+          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"
-        <div className="flex flex-col w-full px-1 md:pl-6 md:pr-[86px] 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="flex flex-col w-full px-1 md:pl-6 md:pr-[86px] md:py-6 py-16">
-            <div className="flex gap-x-4 items-center">
+            <div className="w-full flex flex-col gap-y-1 pb-6 border-white border-b-2 border-opacity-10">
-              <p className="text-lg leading-6 font-bold text-white">
+              <div className="flex gap-x-4 items-center">
-                {t("embed-chats.title")}
+                <p className="text-lg leading-6 font-bold text-white">
-              </p>
+                  {t("embed-chats.title")}
-              <div className="relative">
+                </p>
-                <button
+                <div className="relative">
-                  ref={openMenuButton}
+                  <button
-                  onClick={toggleMenu}
+                    ref={openMenuButton}
-                  className="flex items-center gap-x-2 px-4 py-1 rounded-lg bg-primary-button hover:text-white text-xs font-semibold hover:bg-secondary shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
+                    onClick={toggleMenu}
-                >
+                    className="flex items-center gap-x-2 px-4 py-1 rounded-lg bg-primary-button hover:text-white text-xs font-semibold hover:bg-secondary shadow-[0_4px_14px_rgba(0,0,0,0.25)] h-[34px] w-fit"
-                  <Download size={18} weight="bold" />
+                  >
-                  {t("embed-chats.export")}
+                    <Download size={18} weight="bold" />
-                  <CaretDown size={18} weight="bold" />
+                    {t("embed-chats.export")}
-                </button>
+                    <CaretDown size={18} weight="bold" />
-                <div
+                  </button>
-                  ref={menuRef}
+                  <div
-                  className={`${
+                    ref={menuRef}
-                    showMenu ? "slide-down" : "slide-up hidden"
+                    className={`${
-                  } z-20 w-fit rounded-lg absolute top-full right-0 bg-secondary mt-2 shadow-md`}
+                      showMenu ? "slide-down" : "slide-up hidden"
-                >
+                    } z-20 w-fit rounded-lg absolute top-full right-0 bg-secondary mt-2 shadow-md`}
-                  <div className="py-2">
+                  >
-                    {Object.entries(exportOptions).map(([key, data]) => (
+                    <div className="py-2">
-                      <button
+                      {Object.entries(exportOptions).map(([key, data]) => (
-                        key={key}
+                        <button
-                        onClick={() => {
+                          key={key}
-                          handleDumpChats(key);
+                          onClick={() => {
-                          setShowMenu(false);
+                            handleDumpChats(key);
-                        }}
+                            setShowMenu(false);
-                        className="w-full text-left px-4 py-2 text-white text-sm hover:bg-[#3D4147]"
+                          }}
-                      >
+                          className="w-full text-left px-4 py-2 text-white text-sm hover:bg-[#3D4147]"
-                        {data.name}
+                        >
-                      </button>
+                          {data.name}
-                    ))}
+                        </button>
+                      ))}
+                    </div>
                   </div>
                 </div>
               </div>
+              <p className="text-xs leading-[18px] font-base text-white text-opacity-60">
+                {t("embed-chats.description")}
+              </p>
             </div>
-            <p className="text-xs leading-[18px] font-base text-white text-opacity-60">
+            <ChatsContainer />
-              {t("embed-chats.description")}
-            </p>
           </div>
-          <ChatsContainer />
         </div>
       </div>
-    </div>
+    </CanViewChatHistory>
   );
 }
 

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

@@ -25,6 +25,8 @@ import CohereLogo from "@/media/llmprovider/cohere.png";
 import LiteLLMLogo from "@/media/llmprovider/litellm.png";
 import AWSBedrockLogo from "@/media/llmprovider/bedrock.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 OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
@@ -48,6 +50,8 @@ import TextGenWebUIOptions from "@/components/LLMSelection/TextGenWebUIOptions";
 import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions";
 import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions";
 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 { CaretUpDown, MagnifyingGlass, X } from "@phosphor-icons/react";
@@ -219,6 +223,27 @@ export const AVAILABLE_LLM_PROVIDERS = [
     description: "Run DeepSeek's powerful LLMs.",
     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",
     value: "generic-openai",
@@ -243,17 +268,12 @@ export const AVAILABLE_LLM_PROVIDERS = [
   //   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",
-    ],
   },
 ];
 

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

@@ -21,6 +21,8 @@ import TextGenWebUILogo from "@/media/llmprovider/text-generation-webui.png";
 import LiteLLMLogo from "@/media/llmprovider/litellm.png";
 import AWSBedrockLogo from "@/media/llmprovider/bedrock.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 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"],
     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 = {

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

@@ -20,6 +20,8 @@ import TextGenWebUILogo from "@/media/llmprovider/text-generation-webui.png";
 import LiteLLMLogo from "@/media/llmprovider/litellm.png";
 import AWSBedrockLogo from "@/media/llmprovider/bedrock.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 OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
@@ -43,6 +45,8 @@ import TextGenWebUIOptions from "@/components/LLMSelection/TextGenWebUIOptions";
 import LiteLLMOptions from "@/components/LLMSelection/LiteLLMOptions";
 import AWSBedrockLLMOptions from "@/components/LLMSelection/AwsBedrockLLMOptions";
 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 System from "@/models/system";
@@ -193,6 +197,13 @@ const LLMS = [
     options: (settings) => <DeepSeekOptions settings={settings} />,
     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",
     value: "generic-openai",
@@ -216,6 +227,13 @@ const LLMS = [
     options: (settings) => <AWSBedrockLLMOptions settings={settings} />,
     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({

frontend/src/pages/WorkspaceSettings/AgentConfig/AgentLLMSelection/index.jsx

@@ -24,6 +24,9 @@ const ENABLED_PROVIDERS = [
   "bedrock",
   "fireworksai",
   "deepseek",
+  "litellm",
+  "apipie",
+  "xai",
   // TODO: More agent 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.

frontend/src/pages/WorkspaceSettings/AgentConfig/AgentModelSelection/index.jsx

@@ -5,14 +5,30 @@ import paths from "@/utils/paths";
 import { useTranslation } from "react-i18next";
 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 = "") {
-  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({

frontend/src/pages/WorkspaceSettings/AgentConfig/index.jsx

@@ -8,8 +8,10 @@ import Admin from "@/models/admin";
 import * as Skeleton from "react-loading-skeleton";
 import "react-loading-skeleton/dist/skeleton.css";
 import paths from "@/utils/paths";
+import useUser from "@/hooks/useUser";
 
 export default function WorkspaceAgentConfiguration({ workspace }) {
+  const { user } = useUser();
   const [settings, setSettings] = useState({});
   const [hasChanges, setHasChanges] = useState(false);
   const [saving, setSaving] = useState(false);
@@ -84,21 +86,26 @@ export default function WorkspaceAgentConfiguration({ workspace }) {
           workspace={workspace}
           setHasChanges={setHasChanges}
         />
-        {!hasChanges && (
+        {(!user || user?.role === "admin") && (
-          <div className="flex flex-col gap-y-4">
+          <>
-            <a
+            {!hasChanges && (
-              className="w-fit transition-all duration-300 border border-slate-200 px-5 py-2.5 rounded-lg text-white text-sm items-center flex gap-x-2 hover:bg-slate-200 hover:text-slate-800 focus:ring-gray-800"
+              <div className="flex flex-col gap-y-4">
-              href={paths.settings.agentSkills()}
+                <a
-            >
+                  className="w-fit transition-all duration-300 border border-slate-200 px-5 py-2.5 rounded-lg text-white text-sm items-center flex gap-x-2 hover:bg-slate-200 hover:text-slate-800 focus:ring-gray-800"
-              Configure Agent Skills
+                  href={paths.settings.agentSkills()}
-            </a>
+                >
-            <p className="text-white text-opacity-60 text-xs font-medium">
+                  Configure Agent Skills
-              Customize and enhance the default agent's capabilities by enabling
+                </a>
-              or disabling specific skills. These settings will be applied
+                <p className="text-white text-opacity-60 text-xs font-medium">
-              across all workspaces.
+                  Customize and enhance the default agent's capabilities by
-            </p>
+                  enabling or disabling specific skills. These settings will be
-          </div>
+                  applied across all workspaces.
+                </p>
+              </div>
+            )}
+          </>
         )}
+
         {hasChanges && (
           <button
             type="submit"

frontend/src/pages/WorkspaceSettings/ChatSettings/WorkspaceLLMSelection/index.jsx

@@ -8,15 +8,18 @@ import { useTranslation } from "react-i18next";
 import { Link } from "react-router-dom";
 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 = {
   name: "System default",
   value: "default",
@@ -65,8 +68,8 @@ export default function WorkspaceLLMSelection({
     );
     setFilteredLLMs(filtered);
   }, [LLMS, searchQuery, selectedLLM]);
-
   const selectedLLMObject = LLMS.find((llm) => llm.value === selectedLLM);
+
   return (
     <div className="border-b border-white/40 pb-8">
       <div className="flex flex-col">
@@ -155,30 +158,66 @@ export default function WorkspaceLLMSelection({
           </button>
         )}
       </div>
-      {NO_MODEL_SELECTION.includes(selectedLLM) ? (
+      <ModelSelector
-        <>
+        selectedLLM={selectedLLM}
-          {selectedLLM !== "default" && (
+        workspace={workspace}
-            <div className="w-full h-10 justify-center items-center flex mt-4">
+        setHasChanges={setHasChanges}
-              <p className="text-sm font-base text-white text-opacity-60 text-center">
+      />
-                Multi-model support is not supported for this provider yet.
+    </div>
-                <br />
+  );
-                This workspace will use{" "}
+}
-                <Link to={paths.settings.llmPreference()} className="underline">
+
-                  the model set for the system.
+// TODO: Add this to agent selector as well as make generic component.
-                </Link>
+function ModelSelector({ selectedLLM, workspace, setHasChanges }) {
-              </p>
+  if (NO_MODEL_SELECTION.includes(selectedLLM)) {
-            </div>
+    if (selectedLLM !== "default") {
-          )}
+      return (
-        </>
+        <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">
-        <div className="mt-4 flex flex-col gap-y-1">
+            Multi-model support is not supported for this provider yet.
-          <ChatModelSelection
+            <br />
-            provider={selectedLLM}
+            This workspace will use{" "}
-            workspace={workspace}
+            <Link to={paths.settings.llmPreference()} className="underline">
-            setHasChanges={setHasChanges}
+              the model set for the system.
-          />
+            </Link>
-        </div>
+          </p>
-      )}
+        </div>
+      );
+    }
+    return null;
+  }
+
+  if (FREE_FORM_LLM_SELECTION.includes(selectedLLM)) {
+    return (
+      <FreeFormLLMInput workspace={workspace} setHasChanges={setHasChanges} />
+    );
+  }
+
+  return (
+    <ChatModelSelection
+      provider={selectedLLM}
+      workspace={workspace}
+      setHasChanges={setHasChanges}
+    />
+  );
+}
+
+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>
   );
 }

frontend/src/utils/paths.js

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

server/.env.example

@@ -95,6 +95,14 @@ SIG_SALT='salt' # Please generate random string at least 32 chars long.
 # COHERE_API_KEY=
 # 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 ##########
 ###########################################
@@ -209,6 +217,11 @@ TTS_PROVIDER="native"
 # TTS_ELEVEN_LABS_KEY=
 # 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
 # AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
 # STORAGE_DIR= # absolute filesystem path with no trailing slash
@@ -260,3 +273,11 @@ TTS_PROVIDER="native"
 
 #------ SearXNG ----------- https://github.com/searxng/searxng
 # 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

server/endpoints/admin.js

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

server/endpoints/api/admin/index.js

@@ -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(
     "/v1/admin/preferences",
     [validApiKey],
@@ -658,8 +608,7 @@ function apiAdminEndpoints(app) {
       content: {
         "application/json": {
           example: {
-            limit_user_messages: true,
+            support_email: "support@example.com",
-            message_limit: 5,
           }
         }
       }

server/endpoints/api/workspaceThread/index.js

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

server/endpoints/chat.js

@@ -1,8 +1,6 @@
 const { v4: uuidv4 } = require("uuid");
 const { reqBody, userFromSession, multiUserMode } = require("../utils/http");
 const { validatedRequest } = require("../utils/middleware/validatedRequest");
-const { WorkspaceChats } = require("../models/workspaceChats");
-const { SystemSettings } = require("../models/systemSettings");
 const { Telemetry } = require("../models/telemetry");
 const { streamChatWithWorkspace } = require("../utils/chats/stream");
 const {
@@ -16,6 +14,7 @@ const {
 } = require("../utils/middleware/validWorkspace");
 const { writeResponseChunk } = require("../utils/helpers/chat/responses");
 const { WorkspaceThread } = require("../models/workspaceThread");
+const { User } = require("../models/user");
 const truncate = require("truncate");
 
 function chatEndpoints(app) {
@@ -48,39 +47,16 @@ function chatEndpoints(app) {
         response.setHeader("Connection", "keep-alive");
         response.flushHeaders();
 
-        if (multiUserMode(response) && user.role !== ROLES.admin) {
+        if (multiUserMode(response) && !(await User.canSendChat(user))) {
-          const limitMessagesSetting = await SystemSettings.get({
+          writeResponseChunk(response, {
-            label: "limit_user_messages",
+            id: uuidv4(),
+            type: "abort",
+            textResponse: null,
+            sources: [],
+            close: true,
+            error: `You have met your maximum 24 hour chat quota of ${user.dailyMessageLimit} chats. Try again later.`,
           });
-          const limitMessages = limitMessagesSetting?.value === "true";
+          return;
-
-          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, {
-                  id: uuidv4(),
-                  type: "abort",
-                  textResponse: null,
-                  sources: [],
-                  close: true,
-                  error: `You have met your maximum 24 hour chat quota of ${systemLimit} chats set by the instance administrators. Try again later.`,
-                });
-                return;
-              }
-            }
-          }
         }
 
         await streamChatWithWorkspace(
@@ -157,41 +133,16 @@ function chatEndpoints(app) {
         response.setHeader("Connection", "keep-alive");
         response.flushHeaders();
 
-        if (multiUserMode(response) && user.role !== ROLES.admin) {
+        if (multiUserMode(response) && !(await User.canSendChat(user))) {
-          const limitMessagesSetting = await SystemSettings.get({
+          writeResponseChunk(response, {
-            label: "limit_user_messages",
+            id: uuidv4(),
+            type: "abort",
+            textResponse: null,
+            sources: [],
+            close: true,
+            error: `You have met your maximum 24 hour chat quota of ${user.dailyMessageLimit} chats. Try again later.`,
           });
-          const limitMessages = limitMessagesSetting?.value === "true";
+          return;
-
-          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, {
-                  id: uuidv4(),
-                  type: "abort",
-                  textResponse: null,
-                  sources: [],
-                  close: true,
-                  error: `You have met your maximum 24 hour chat quota of ${systemLimit} chats set by the instance administrators. Try again later.`,
-                });
-                return;
-              }
-            }
-          }
         }
 
         await streamChatWithWorkspace(

server/endpoints/embed/index.js

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

server/endpoints/embedManagement.js

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

server/endpoints/system.js

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

server/models/embedChats.js

@@ -1,5 +1,17 @@
+const { safeJsonParse } = require("../utils/http");
 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 = {
   new: async function ({
     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 (
     embedId = null,
     sessionId = null,
     limit = null,
-    orderBy = null
+    orderBy = null,
+    filterSources = false
   ) {
     if (!embedId || !sessionId) return [];
 
@@ -43,7 +80,7 @@ const EmbedChats = {
         ...(limit !== null ? { take: limit } : {}),
         ...(orderBy !== null ? { orderBy } : { orderBy: { id: "asc" } }),
       });
-      return chats;
+      return filterSources ? this.filterSources(chats) : chats;
     } catch (error) {
       console.error(error.message);
       return [];

server/models/systemSettings.js

@@ -21,8 +21,6 @@ function isNullOrNaN(value) {
 const SystemSettings = {
   protectedFields: ["multi_user_mode"],
   publicFields: [
-    "limit_user_messages",
-    "message_limit",
     "footer_data",
     "support_email",
     "text_splitter_chunk_size",
@@ -38,8 +36,6 @@ const SystemSettings = {
     "meta_page_favicon",
   ],
   supportedFields: [
-    "limit_user_messages",
-    "message_limit",
     "logo_filename",
     "telemetry_id",
     "footer_data",
@@ -108,6 +104,7 @@ const SystemSettings = {
             "bing-search",
             "serply-engine",
             "searxng-engine",
+            "tavily-search",
           ].includes(update)
         )
           throw new Error("Invalid SERP provider.");
@@ -229,12 +226,18 @@ const SystemSettings = {
       TextToSpeechProvider: process.env.TTS_PROVIDER || "native",
       TTSOpenAIKey: !!process.env.TTS_OPEN_AI_KEY,
       TTSOpenAIVoiceModel: process.env.TTS_OPEN_AI_VOICE_MODEL,
+
       // Eleven Labs TTS
       TTSElevenLabsKey: !!process.env.TTS_ELEVEN_LABS_KEY,
       TTSElevenLabsVoiceModel: process.env.TTS_ELEVEN_LABS_VOICE_MODEL,
       // Piper TTS
       TTSPiperTTSVoiceModel:
         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
@@ -247,6 +250,14 @@ const SystemSettings = {
       AgentBingSearchApiKey: !!process.env.AGENT_BING_SEARCH_API_KEY || null,
       AgentSerplyApiKey: !!process.env.AGENT_SERPLY_API_KEY || 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
       DeepSeekApiKey: !!process.env.DEEPSEEK_API_KEY,
       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,
     };
   },
 

server/models/user.js

@@ -1,6 +1,17 @@
 const prisma = require("../utils/prisma");
 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 = {
   usernameRegex: new RegExp(/^[a-z0-9_-]+$/),
   writable: [
@@ -10,6 +21,7 @@ const User = {
     "pfpFilename",
     "role",
     "suspended",
+    "dailyMessageLimit",
   ],
   validations: {
     username: (newValue = "") => {
@@ -32,12 +44,24 @@ const User = {
       }
       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.
   castColumnValue: function (key, value) {
     switch (key) {
       case "suspended":
         return Number(Boolean(value));
+      case "dailyMessageLimit":
+        return value === null ? null : Number(value);
       default:
         return String(value);
     }
@@ -48,7 +72,12 @@ const User = {
     return { ...rest };
   },
 
-  create: async function ({ username, password, role = "default" }) {
+  create: async function ({
+    username,
+    password,
+    role = "default",
+    dailyMessageLimit = null,
+  }) {
     const passwordCheck = this.checkPasswordComplexity(password);
     if (!passwordCheck.checkedOK) {
       return { user: null, error: passwordCheck.error };
@@ -58,7 +87,7 @@ const User = {
       // Do not allow new users to bypass validation
       if (!this.usernameRegex.test(username))
         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");
@@ -68,6 +97,8 @@ const User = {
           username: this.validations.username(username),
           password: hashedPassword,
           role: this.validations.role(role),
+          dailyMessageLimit:
+            this.validations.dailyMessageLimit(dailyMessageLimit),
         },
       });
       return { user: this.filterFields(user), error: null };
@@ -135,7 +166,7 @@ const User = {
         return {
           success: false,
           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({
@@ -260,6 +291,29 @@ const User = {
 
     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 };

server/models/workspaceThread.js

@@ -1,16 +1,44 @@
 const prisma = require("../utils/prisma");
+const slugifyModule = require("slugify");
 const { v4: uuidv4 } = require("uuid");
 
 const WorkspaceThread = {
   defaultName: "Thread",
   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 {
       const thread = await prisma.workspace_threads.create({
         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,
           workspace_id: workspace.id,
         },

server/prisma/migrations/20241003192954_init/migration.sql

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

server/prisma/schema.prisma

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

server/prisma/seed.js

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

server/storage/models/.gitignore

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

server/swagger/openapi.json

@@ -693,52 +693,6 @@
       }
     },
     "/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": {
         "tags": [
           "Admin"
@@ -788,8 +742,7 @@
           "content": {
             "application/json": {
               "example": {
-                "limit_user_messages": true,
+                "support_email": "support@example.com"
-                "message_limit": 5
               }
             }
           }
@@ -2438,12 +2391,14 @@
           }
         },
         "requestBody": {
-          "description": "Optional userId associated with the thread",
+          "description": "Optional userId associated with the thread, thread slug and thread name",
           "required": false,
           "content": {
             "application/json": {
               "example": {
-                "userId": 1
+                "userId": 1,
+                "name": "Name",
+                "slug": "thread-slug"
               }
             }
           }

server/utils/AiProviders/apipie/index.js

@@ -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,
+};

server/utils/AiProviders/azureOpenAi/index.js

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

server/utils/AiProviders/bedrock/index.js

@@ -7,6 +7,20 @@ const { NativeEmbedder } = require("../../EmbeddingEngines/native");
 
 // Docs: https://js.langchain.com/v0.2/docs/integrations/chat/bedrock_converse
 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) {
     if (!process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID)
       throw new Error("No AWS Bedrock LLM profile id was set.");
@@ -32,7 +46,7 @@ class AWSBedrockLLM {
   #bedrockClient({ temperature = 0.7 }) {
     const { ChatBedrockConverse } = require("@langchain/aws");
     return new ChatBedrockConverse({
-      model: process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE,
+      model: this.model,
       region: process.env.AWS_BEDROCK_LLM_REGION,
       credentials: {
         accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID,
@@ -59,6 +73,22 @@ class AWSBedrockLLM {
 
     for (const chat of chats) {
       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];
       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() {
     return "streamGetChatCompletion" in this;
   }

server/utils/AiProviders/groq/index.js

@@ -37,6 +37,10 @@ class GroqLLM {
     );
   }
 
+  #log(text, ...args) {
+    console.log(`\x1b[32m[GroqAi]\x1b[0m ${text}`, ...args);
+  }
+
   streamingEnabled() {
     return "streamGetChatCompletion" in this;
   }
@@ -53,17 +57,111 @@ class GroqLLM {
     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}${this.#appendContext(contextTexts)}`,
+      // },
+      // {
+      //   role: "assistant",
+      //   content: "OK",
+      // },
+      // ...chatHistory,
+      {
+        role: "user",
+        content: this.#generateContent({ userPrompt, attachments }),
+      },
+    ];
+  }
+
+  /**
+   * Construct the user prompt for this model.
+   * @param {{attachments: import("../../helpers").Attachment[]}} param0
+   * @returns
+   */
   constructPrompt({
     systemPrompt = "",
     contextTexts = [],
     chatHistory = [],
     userPrompt = "",
+    attachments = [], // This is the specific attachment for only this prompt
   }) {
-    const prompt = {
+    // NOTICE: SEE GroqLLM.#conditionalPromptStruct for more information on how attachments are handled with Groq.
-      role: "system",
+    return this.#conditionalPromptStruct({
-      content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
+      systemPrompt,
-    };
+      contextTexts,
-    return [prompt, ...chatHistory, { role: "user", content: userPrompt }];
+      chatHistory,
+      userPrompt,
+      attachments,
+    });
   }
 
   async getChatCompletion(messages = null, { temperature = 0.7 }) {

server/utils/AiProviders/lmStudio/index.js

@@ -5,7 +5,7 @@ const {
 
 //  hybrid of openAi LLM chat completion for LMStudio
 class LMStudioLLM {
-  constructor(embedder = null, _modelPreference = null) {
+  constructor(embedder = null, modelPreference = null) {
     if (!process.env.LMSTUDIO_BASE_PATH)
       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
     // 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.
-    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 = {
       history: this.promptWindowLimit() * 0.15,
       system: this.promptWindowLimit() * 0.15,

server/utils/AiProviders/modelMap.js

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

server/utils/AiProviders/openAi/index.js

@@ -23,6 +23,14 @@ class OpenAiLLM {
     this.defaultTemp = 0.7;
   }
 
+  /**
+   * Check if the model is an o1 model.
+   * @returns {boolean}
+   */
+  get isO1Model() {
+    return this.model.startsWith("o1");
+  }
+
   #appendContext(contextTexts = []) {
     if (!contextTexts || !contextTexts.length) return "";
     return (
@@ -36,6 +44,7 @@ class OpenAiLLM {
   }
 
   streamingEnabled() {
+    if (this.isO1Model) return false;
     return "streamGetChatCompletion" in this;
   }
 
@@ -98,8 +107,11 @@ class OpenAiLLM {
     userPrompt = "",
     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 = {
-      role: "system",
+      role: this.isO1Model ? "user" : "system",
       content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
     };
     return [
@@ -122,7 +134,7 @@ class OpenAiLLM {
       .create({
         model: this.model,
         messages,
-        temperature,
+        temperature: this.isO1Model ? 1 : temperature, // o1 models only accept temperature 1
       })
       .catch((e) => {
         throw new Error(e.message);
@@ -143,7 +155,7 @@ class OpenAiLLM {
       model: this.model,
       stream: true,
       messages,
-      temperature,
+      temperature: this.isO1Model ? 1 : temperature, // o1 models only accept temperature 1
     });
     return streamRequest;
   }

server/utils/AiProviders/xai/index.js

@@ -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,
+};

server/utils/EmbeddingEngines/voyageAi/index.js

@@ -11,7 +11,7 @@ class VoyageAiEmbedder {
     });
 
     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
     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) {
       case "voyage-finance-2":
       case "voyage-multilingual-2":
+      case "voyage-3":
+      case "voyage-3-lite":
         return 32_000;
       case "voyage-large-2-instruct":
       case "voyage-law-2":

server/utils/TextToSpeech/index.js

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

server/utils/TextToSpeech/openAiGeneric/index.js

@@ -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,
+};

server/utils/agents/aibitat/index.js

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

server/utils/agents/aibitat/plugins/web-browsing.js

@@ -77,6 +77,9 @@ const webBrowsing = {
               case "searxng-engine":
                 engine = "_searXNGEngine";
                 break;
+              case "tavily-search":
+                engine = "_tavilySearch";
+                break;
               default:
                 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)
               return `No information was found online for the search query.`;
             this.super.introspect(

server/utils/agents/aibitat/providers/ai-provider.js

@@ -130,6 +130,30 @@ class Provider {
           apiKey: process.env.FIREWORKS_AI_LLM_API_KEY,
           ...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
       // case "anythingllm_ollama":
@@ -174,14 +198,15 @@ class Provider {
           apiKey: process.env.TEXT_GEN_WEB_UI_API_KEY ?? "not-used",
           ...config,
         });
-      case "deepseek":
+      case "litellm":
         return new ChatOpenAI({
           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,
         });
+
       default:
         throw new Error(`Unsupported provider ${provider} for this task.`);
     }

server/utils/agents/aibitat/providers/apipie.js

@@ -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;

server/utils/agents/aibitat/providers/helpers/untooled.js

@@ -33,7 +33,10 @@ ${JSON.stringify(def.parameters.properties, null, 4)}\n`;
 
       if (Array.isArray(def.examples)) {
         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`;

server/utils/agents/aibitat/providers/index.js

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

server/utils/agents/aibitat/providers/litellm.js

@@ -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;

server/utils/agents/aibitat/providers/lmstudio.js

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

server/utils/agents/aibitat/providers/xai.js

@@ -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;

server/utils/agents/ephemeral.js

@@ -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.
    * 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
    * 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() {
-    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();
   }
 
   #providerSetupAndCheck() {
-    this.provider = this.#workspace.agentProvider;
+    this.provider = this.#workspace.agentProvider ?? null;
     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.checkSetup();
   }

server/utils/agents/index.js

@@ -11,13 +11,6 @@ const ImportedPlugin = require("./imported");
 class AgentHandler {
   #invocationUUID;
   #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;
   aibitat = null;
   channel = null;
@@ -166,6 +159,20 @@ class AgentHandler {
         if (!process.env.DEEPSEEK_API_KEY)
           throw new Error("DeepSeek API Key must be provided to use agents.");
         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:
         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) {
     switch (provider) {
       case "openai":
-        return "gpt-4o";
+        return process.env.OPEN_MODEL_PREF ?? "gpt-4o";
       case "anthropic":
-        return "claude-3-sonnet-20240229";
+        return process.env.ANTHROPIC_MODEL_PREF ?? "claude-3-sonnet-20240229";
       case "lmstudio":
-        return "server-default";
+        return process.env.LMSTUDIO_MODEL_PREF ?? "server-default";
       case "ollama":
-        return "llama3:latest";
+        return process.env.OLLAMA_MODEL_PREF ?? "llama3:latest";
       case "groq":
-        return "llama3-70b-8192";
+        return process.env.GROQ_MODEL_PREF ?? "llama3-70b-8192";
       case "togetherai":
-        return "mistralai/Mixtral-8x7B-Instruct-v0.1";
+        return (
+          process.env.TOGETHER_AI_MODEL_PREF ??
+          "mistralai/Mixtral-8x7B-Instruct-v0.1"
+        );
       case "azure":
-        return "gpt-3.5-turbo";
+        return null;
       case "koboldcpp":
-        return null;
+        return process.env.KOBOLD_CPP_MODEL_PREF ?? null;
       case "gemini":
-        return "gemini-pro";
+        return process.env.GEMINI_MODEL_PREF ?? "gemini-pro";
       case "localai":
-        return null;
+        return process.env.LOCAL_AI_MODEL_PREF ?? null;
       case "openrouter":
-        return "openrouter/auto";
+        return process.env.OPENROUTER_MODEL_PREF ?? "openrouter/auto";
       case "mistral":
-        return "mistral-medium";
+        return process.env.MISTRAL_MODEL_PREF ?? "mistral-medium";
       case "generic-openai":
-        return null;
+        return process.env.GENERIC_OPEN_AI_MODEL_PREF ?? null;
       case "perplexity":
-        return "sonar-small-online";
+        return process.env.PERPLEXITY_MODEL_PREF ?? "sonar-small-online";
       case "textgenwebui":
         return null;
       case "bedrock":
-        return null;
+        return process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE ?? null;
       case "fireworksai":
-        return null;
+        return process.env.FIREWORKS_AI_LLM_MODEL_PREF ?? null;
       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:
-        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() {
     // First, fallback to the workspace chat provider and model if they exist
     if (
@@ -248,7 +278,7 @@ class AgentHandler {
    * 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
    * 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() {
     // 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.
-    if (this.invocation.workspace.agentModel) {
+    if (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();
   }
 
@@ -285,7 +305,6 @@ class AgentHandler {
 
     if (!this.provider)
       throw new Error("No valid provider found for the agent.");
-
     this.log(`Start ${this.#invocationUUID}::${this.provider}:${this.model}`);
     this.checkSetup();
   }

server/utils/chats/embed.js

@@ -60,8 +60,7 @@ async function streamChatWithForEmbed(
   const { rawHistory, chatHistory } = await recentEmbedChatHistory(
     sessionId,
     embed,
-    messageLimit,
+    messageLimit
-    chatMode
   );
 
   // See stream.js comment for more information on this implementation.
@@ -113,16 +112,27 @@ async function streamChatWithForEmbed(
     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];
 
-  // 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
-  if (
+  if (chatMode === "query" && contextTexts.length === 0) {
-    chatMode === "query" &&
-    sources.length === 0 &&
-    pinnedDocIdentifiers.length === 0
-  ) {
     writeResponseChunk(response, {
       id: uuid,
       type: "textResponse",
@@ -178,7 +188,7 @@ async function streamChatWithForEmbed(
   await EmbedChats.new({
     embedId: embed.id,
     prompt: message,
-    response: { text: completeText, type: chatMode },
+    response: { text: completeText, type: chatMode, sources },
     connection_information: response.locals.connection
       ? {
           ...response.locals.connection,
@@ -190,15 +200,13 @@ async function streamChatWithForEmbed(
   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 = (
     await EmbedChats.forEmbedByUser(embed.id, sessionId, messageLimit, {
       id: "desc",

server/utils/helpers/customModels.js

@@ -1,4 +1,5 @@
 const { fetchOpenRouterModels } = require("../AiProviders/openRouter");
+const { fetchApiPieModels } = require("../AiProviders/apipie");
 const { perplexityModels } = require("../AiProviders/perplexity");
 const { togetherAiModels } = require("../AiProviders/togetherAi");
 const { fireworksAiModels } = require("../AiProviders/fireworksAi");
@@ -19,6 +20,8 @@ const SUPPORT_CUSTOM_MODELS = [
   "elevenlabs-tts",
   "groq",
   "deepseek",
+  "apipie",
+  "xai",
 ];
 
 async function getCustomModels(provider = "", apiKey = null, basePath = null) {
@@ -56,6 +59,10 @@ async function getCustomModels(provider = "", apiKey = null, basePath = null) {
       return await getGroqAiModels(apiKey);
     case "deepseek":
       return await getDeepSeekModels(apiKey);
+    case "apipie":
+      return await getAPIPieModels(apiKey);
+    case "xai":
+      return await getXAIModels(apiKey);
     default:
       return { models: [], error: "Invalid provider for custom models" };
   }
@@ -124,7 +131,7 @@ async function openAiModels(apiKey = null) {
     });
 
   const gpts = allModels
-    .filter((model) => model.id.startsWith("gpt"))
+    .filter((model) => model.id.startsWith("gpt") || model.id.startsWith("o1"))
     .filter(
       (model) => !model.id.includes("vision") && !model.id.includes("instruct")
     )
@@ -355,6 +362,21 @@ async function getOpenRouterModels() {
   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) {
   const { OpenAI: OpenAIApi } = require("openai");
   const openai = new OpenAIApi({
@@ -447,6 +469,36 @@ async function getDeepSeekModels(apiKey = 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 = {
   getCustomModels,
 };

server/utils/helpers/index.js

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

server/utils/helpers/updateENV.js

@@ -469,6 +469,10 @@ const KEY_MAPPING = {
     envKey: "AGENT_SEARXNG_API_URL",
     checks: [],
   },
+  AgentTavilyApiKey: {
+    envKey: "AGENT_TAVILY_API_KEY",
+    checks: [],
+  },
 
   // TTS/STT Integration ENVS
   TextToSpeechProvider: {
@@ -502,6 +506,20 @@ const KEY_MAPPING = {
     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
   DeepSeekApiKey: {
     envKey: "DEEPSEEK_API_KEY",
@@ -511,6 +529,26 @@ const KEY_MAPPING = {
     envKey: "DEEPSEEK_MODEL_PREF",
     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 = "") {
@@ -575,6 +613,7 @@ function supportedTTSProvider(input = "") {
     "openai",
     "elevenlabs",
     "piper_local",
+    "generic-openai",
   ].includes(input);
   return validSelection ? null : `${input} is not a valid TTS provider.`;
 }
@@ -613,6 +652,8 @@ function supportedLLM(input = "") {
     "generic-openai",
     "bedrock",
     "deepseek",
+    "apipie",
+    "xai",
   ].includes(input);
   return validSelection ? null : `${input} is not a valid LLM provider.`;
 }
@@ -856,6 +897,8 @@ function dumpENV() {
     "ENABLE_HTTPS",
     "HTTPS_CERT_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.

server/utils/middleware/chatHistoryViewable.js

@@ -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,
+};