diff --git a/collector/index.js b/collector/index.js
index 9ebe5f1ce160cae31f7a11cf1404feb1f11cf416..a1142d75665b95617f89c86841ad648a75471e1a 100644
--- a/collector/index.js
+++ b/collector/index.js
@@ -25,7 +25,7 @@ app.use(
);
app.post("/process", async function (request, response) {
- const { filename } = reqBody(request);
+ const { filename, options = {} } = reqBody(request);
try {
const targetFilename = path
.normalize(filename)
@@ -34,7 +34,7 @@ app.post("/process", async function (request, response) {
success,
reason,
documents = [],
- } = await processSingleFile(targetFilename);
+ } = await processSingleFile(targetFilename, options);
response
.status(200)
.json({ filename: targetFilename, success, reason, documents });
diff --git a/collector/package.json b/collector/package.json
index d145ab86568332ddec49ba4533f4937a5455588b..8a0441d78202d10531ffb5ea47e38e1a617a4aa3 100644
--- a/collector/package.json
+++ b/collector/package.json
@@ -33,6 +33,7 @@
"moment": "^2.29.4",
"multer": "^1.4.5-lts.1",
"officeparser": "^4.0.5",
+ "openai": "^3.2.1",
"pdf-parse": "^1.1.1",
"puppeteer": "~21.5.2",
"slugify": "^1.6.6",
@@ -46,4 +47,4 @@
"nodemon": "^2.0.22",
"prettier": "^2.4.1"
}
-}
+}
\ No newline at end of file
diff --git a/collector/processSingleFile/convert/asAudio.js b/collector/processSingleFile/convert/asAudio.js
index 15ae5cf001b258a9cdd1bf631403a8869f38d3c4..170426e4068ffadd880895f4b710f8eb653593c4 100644
--- a/collector/processSingleFile/convert/asAudio.js
+++ b/collector/processSingleFile/convert/asAudio.js
@@ -1,5 +1,3 @@
-const fs = require("fs");
-const path = require("path");
const { v4 } = require("uuid");
const {
createdDate,
@@ -9,39 +7,35 @@ const {
const { tokenizeString } = require("../../utils/tokenizer");
const { default: slugify } = require("slugify");
const { LocalWhisper } = require("../../utils/WhisperProviders/localWhisper");
+const { OpenAiWhisper } = require("../../utils/WhisperProviders/OpenAiWhisper");
-async function asAudio({ fullFilePath = "", filename = "" }) {
- const whisper = new LocalWhisper();
+const WHISPER_PROVIDERS = {
+ openai: OpenAiWhisper,
+ local: LocalWhisper,
+};
+
+async function asAudio({ fullFilePath = "", filename = "", options = {} }) {
+ const WhisperProvider = WHISPER_PROVIDERS.hasOwnProperty(
+ options?.whisperProvider
+ )
+ ? WHISPER_PROVIDERS[options?.whisperProvider]
+ : WHISPER_PROVIDERS.local;
console.log(`-- Working ${filename} --`);
- const transcriberPromise = new Promise((resolve) =>
- whisper.client().then((client) => resolve(client))
- );
- const audioDataPromise = new Promise((resolve) =>
- convertToWavAudioData(fullFilePath).then((audioData) => resolve(audioData))
- );
- const [audioData, transcriber] = await Promise.all([
- audioDataPromise,
- transcriberPromise,
- ]);
+ const whisper = new WhisperProvider({ options });
+ const { content, error } = await whisper.processFile(fullFilePath, filename);
- if (!audioData) {
- console.error(`Failed to parse content from ${filename}.`);
+ if (!!error) {
+ console.error(`Error encountered for parsing of ${filename}.`);
trashFile(fullFilePath);
return {
success: false,
- reason: `Failed to parse content from ${filename}.`,
+ reason: error,
documents: [],
};
}
- console.log(`[Model Working]: Transcribing audio data to text`);
- const { text: content } = await transcriber(audioData, {
- chunk_length_s: 30,
- stride_length_s: 5,
- });
-
- if (!content.length) {
+ if (!content?.length) {
console.error(`Resulting text content was empty for ${filename}.`);
trashFile(fullFilePath);
return {
@@ -76,79 +70,4 @@ async function asAudio({ fullFilePath = "", filename = "" }) {
return { success: true, reason: null, documents: [document] };
}
-async function convertToWavAudioData(sourcePath) {
- try {
- let buffer;
- const wavefile = require("wavefile");
- const ffmpeg = require("fluent-ffmpeg");
- const outFolder = path.resolve(__dirname, `../../storage/tmp`);
- if (!fs.existsSync(outFolder)) fs.mkdirSync(outFolder, { recursive: true });
-
- const fileExtension = path.extname(sourcePath).toLowerCase();
- if (fileExtension !== ".wav") {
- console.log(
- `[Conversion Required] ${fileExtension} file detected - converting to .wav`
- );
- const outputFile = path.resolve(outFolder, `${v4()}.wav`);
- const convert = new Promise((resolve) => {
- ffmpeg(sourcePath)
- .toFormat("wav")
- .on("error", (error) => {
- console.error(`[Conversion Error] ${error.message}`);
- resolve(false);
- })
- .on("progress", (progress) =>
- console.log(
- `[Conversion Processing]: ${progress.targetSize}KB converted`
- )
- )
- .on("end", () => {
- console.log("[Conversion Complete]: File converted to .wav!");
- resolve(true);
- })
- .save(outputFile);
- });
- const success = await convert;
- if (!success)
- throw new Error(
- "[Conversion Failed]: Could not convert file to .wav format!"
- );
-
- const chunks = [];
- const stream = fs.createReadStream(outputFile);
- for await (let chunk of stream) chunks.push(chunk);
- buffer = Buffer.concat(chunks);
- fs.rmSync(outputFile);
- } else {
- const chunks = [];
- const stream = fs.createReadStream(sourcePath);
- for await (let chunk of stream) chunks.push(chunk);
- buffer = Buffer.concat(chunks);
- }
-
- const wavFile = new wavefile.WaveFile(buffer);
- wavFile.toBitDepth("32f");
- wavFile.toSampleRate(16000);
-
- let audioData = wavFile.getSamples();
- if (Array.isArray(audioData)) {
- if (audioData.length > 1) {
- const SCALING_FACTOR = Math.sqrt(2);
-
- // Merge channels into first channel to save memory
- for (let i = 0; i < audioData[0].length; ++i) {
- audioData[0][i] =
- (SCALING_FACTOR * (audioData[0][i] + audioData[1][i])) / 2;
- }
- }
- audioData = audioData[0];
- }
-
- return audioData;
- } catch (error) {
- console.error(`convertToWavAudioData`, error);
- return null;
- }
-}
-
module.exports = asAudio;
diff --git a/collector/processSingleFile/index.js b/collector/processSingleFile/index.js
index 569a2cde27ad996932633b55c3214e3a5afe3c15..5d9e6a38af91856d89b3c52e34b57c5f1061a389 100644
--- a/collector/processSingleFile/index.js
+++ b/collector/processSingleFile/index.js
@@ -7,7 +7,7 @@ const {
const { trashFile, isTextType } = require("../utils/files");
const RESERVED_FILES = ["__HOTDIR__.md"];
-async function processSingleFile(targetFilename) {
+async function processSingleFile(targetFilename, options = {}) {
const fullFilePath = path.resolve(WATCH_DIRECTORY, targetFilename);
if (RESERVED_FILES.includes(targetFilename))
return {
@@ -54,6 +54,7 @@ async function processSingleFile(targetFilename) {
return await FileTypeProcessor({
fullFilePath,
filename: targetFilename,
+ options,
});
}
diff --git a/collector/utils/WhisperProviders/OpenAiWhisper.js b/collector/utils/WhisperProviders/OpenAiWhisper.js
new file mode 100644
index 0000000000000000000000000000000000000000..3b9d08e6a65905b0a2ff3184135cd5f5ff4ebf6c
--- /dev/null
+++ b/collector/utils/WhisperProviders/OpenAiWhisper.js
@@ -0,0 +1,44 @@
+const fs = require("fs");
+
+class OpenAiWhisper {
+ constructor({ options }) {
+ const { Configuration, OpenAIApi } = require("openai");
+ if (!options.openAiKey) throw new Error("No OpenAI API key was set.");
+
+ const config = new Configuration({
+ apiKey: options.openAiKey,
+ });
+ this.openai = new OpenAIApi(config);
+ this.model = "whisper-1";
+ this.temperature = 0;
+ this.#log("Initialized.");
+ }
+
+ #log(text, ...args) {
+ console.log(`\x1b[32m[OpenAiWhisper]\x1b[0m ${text}`, ...args);
+ }
+
+ async processFile(fullFilePath) {
+ return await this.openai
+ .createTranscription(
+ fs.createReadStream(fullFilePath),
+ this.model,
+ undefined,
+ "text",
+ this.temperature
+ )
+ .then((res) => {
+ if (res.hasOwnProperty("data"))
+ return { content: res.data, error: null };
+ return { content: "", error: "No content was able to be transcribed." };
+ })
+ .catch((e) => {
+ this.#log(`Could not get any response from openai whisper`, e.message);
+ return { content: "", error: e.message };
+ });
+ }
+}
+
+module.exports = {
+ OpenAiWhisper,
+};
diff --git a/collector/utils/WhisperProviders/localWhisper.js b/collector/utils/WhisperProviders/localWhisper.js
index 6503e2021ebf63920a36d1617bad8276eb5eea18..46dbe226b4d675ad50b02f8c844b2e8b89643aa2 100644
--- a/collector/utils/WhisperProviders/localWhisper.js
+++ b/collector/utils/WhisperProviders/localWhisper.js
@@ -1,5 +1,6 @@
-const path = require("path");
const fs = require("fs");
+const path = require("path");
+const { v4 } = require("uuid");
class LocalWhisper {
constructor() {
@@ -16,12 +17,94 @@ class LocalWhisper {
// Make directory when it does not exist in existing installations
if (!fs.existsSync(this.cacheDir))
fs.mkdirSync(this.cacheDir, { recursive: true });
+
+ this.#log("Initialized.");
+ }
+
+ #log(text, ...args) {
+ console.log(`\x1b[32m[LocalWhisper]\x1b[0m ${text}`, ...args);
+ }
+
+ async #convertToWavAudioData(sourcePath) {
+ try {
+ let buffer;
+ const wavefile = require("wavefile");
+ const ffmpeg = require("fluent-ffmpeg");
+ const outFolder = path.resolve(__dirname, `../../storage/tmp`);
+ if (!fs.existsSync(outFolder))
+ fs.mkdirSync(outFolder, { recursive: true });
+
+ const fileExtension = path.extname(sourcePath).toLowerCase();
+ if (fileExtension !== ".wav") {
+ this.#log(
+ `File conversion required! ${fileExtension} file detected - converting to .wav`
+ );
+ const outputFile = path.resolve(outFolder, `${v4()}.wav`);
+ const convert = new Promise((resolve) => {
+ ffmpeg(sourcePath)
+ .toFormat("wav")
+ .on("error", (error) => {
+ this.#log(`Conversion Error! ${error.message}`);
+ resolve(false);
+ })
+ .on("progress", (progress) =>
+ this.#log(
+ `Conversion Processing! ${progress.targetSize}KB converted`
+ )
+ )
+ .on("end", () => {
+ this.#log(`Conversion Complete! File converted to .wav!`);
+ resolve(true);
+ })
+ .save(outputFile);
+ });
+ const success = await convert;
+ if (!success)
+ throw new Error(
+ "[Conversion Failed]: Could not convert file to .wav format!"
+ );
+
+ const chunks = [];
+ const stream = fs.createReadStream(outputFile);
+ for await (let chunk of stream) chunks.push(chunk);
+ buffer = Buffer.concat(chunks);
+ fs.rmSync(outputFile);
+ } else {
+ const chunks = [];
+ const stream = fs.createReadStream(sourcePath);
+ for await (let chunk of stream) chunks.push(chunk);
+ buffer = Buffer.concat(chunks);
+ }
+
+ const wavFile = new wavefile.WaveFile(buffer);
+ wavFile.toBitDepth("32f");
+ wavFile.toSampleRate(16000);
+
+ let audioData = wavFile.getSamples();
+ if (Array.isArray(audioData)) {
+ if (audioData.length > 1) {
+ const SCALING_FACTOR = Math.sqrt(2);
+
+ // Merge channels into first channel to save memory
+ for (let i = 0; i < audioData[0].length; ++i) {
+ audioData[0][i] =
+ (SCALING_FACTOR * (audioData[0][i] + audioData[1][i])) / 2;
+ }
+ }
+ audioData = audioData[0];
+ }
+
+ return audioData;
+ } catch (error) {
+ console.error(`convertToWavAudioData`, error);
+ return null;
+ }
}
async client() {
if (!fs.existsSync(this.modelPath)) {
- console.log(
- "\x1b[34m[INFO]\x1b[0m The native whisper model has never been run and will be downloaded right now. Subsequent runs will be faster. (~250MB)\n\n"
+ this.#log(
+ `The native whisper model has never been run and will be downloaded right now. Subsequent runs will be faster. (~250MB)`
);
}
@@ -48,10 +131,45 @@ class LocalWhisper {
: {}),
});
} catch (error) {
- console.error("Failed to load the native whisper model:", error);
+ this.#log("Failed to load the native whisper model:", error);
throw error;
}
}
+
+ async processFile(fullFilePath, filename) {
+ try {
+ const transcriberPromise = new Promise((resolve) =>
+ this.client().then((client) => resolve(client))
+ );
+ const audioDataPromise = new Promise((resolve) =>
+ this.#convertToWavAudioData(fullFilePath).then((audioData) =>
+ resolve(audioData)
+ )
+ );
+ const [audioData, transcriber] = await Promise.all([
+ audioDataPromise,
+ transcriberPromise,
+ ]);
+
+ if (!audioData) {
+ this.#log(`Failed to parse content from ${filename}.`);
+ return {
+ content: null,
+ error: `Failed to parse content from ${filename}.`,
+ };
+ }
+
+ this.#log(`Transcribing audio data to text...`);
+ const { text } = await transcriber(audioData, {
+ chunk_length_s: 30,
+ stride_length_s: 5,
+ });
+
+ return { content: text, error: null };
+ } catch (error) {
+ return { content: null, error: error.message };
+ }
+ }
}
module.exports = {
diff --git a/collector/yarn.lock b/collector/yarn.lock
index bf979c86c0d3981a4fc615fc20a5a73be0a18943..3bb0f1ea79429a1028485fc86ced00bacc0d50c6 100644
--- a/collector/yarn.lock
+++ b/collector/yarn.lock
@@ -372,6 +372,13 @@ asynckit@^0.4.0:
resolved "https://registry.yarnpkg.com/asynckit/-/asynckit-0.4.0.tgz#c79ed97f7f34cb8f2ba1bc9790bcc366474b4b79"
integrity sha512-Oei9OH4tRh0YqU3GxhX79dM/mwVgvbZJaSNaRk+bshkj0S5cfHcgYakreBjrHwatXKbz+IoIdYLxrKim2MjW0Q==
+axios@^0.26.0:
+ version "0.26.1"
+ resolved "https://registry.yarnpkg.com/axios/-/axios-0.26.1.tgz#1ede41c51fcf51bbbd6fd43669caaa4f0495aaa9"
+ integrity sha512-fPwcX4EvnSHuInCMItEhAGnaSEXRBjtzh9fOtsE6E1G6p7vl7edEeZe11QHf18+6+9gR5PbKV/sGKNaD8YaMeA==
+ dependencies:
+ follow-redirects "^1.14.8"
+
b4a@^1.6.4:
version "1.6.4"
resolved "https://registry.yarnpkg.com/b4a/-/b4a-1.6.4.tgz#ef1c1422cae5ce6535ec191baeed7567443f36c9"
@@ -1203,6 +1210,11 @@ fluent-ffmpeg@^2.1.2:
async ">=0.2.9"
which "^1.1.1"
+follow-redirects@^1.14.8:
+ version "1.15.6"
+ resolved "https://registry.yarnpkg.com/follow-redirects/-/follow-redirects-1.15.6.tgz#7f815c0cda4249c74ff09e95ef97c23b5fd0399b"
+ integrity sha512-wWN62YITEaOpSK584EZXJafH1AGpO8RVgElfkuXbTOrPX4fIfOyEpW/CsiNd8JdYrAoOvafRTOEnvsO++qCqFA==
+
form-data-encoder@1.7.2:
version "1.7.2"
resolved "https://registry.yarnpkg.com/form-data-encoder/-/form-data-encoder-1.7.2.tgz#1f1ae3dccf58ed4690b86d87e4f57c654fbab040"
@@ -2304,6 +2316,14 @@ onnxruntime-web@1.14.0:
onnxruntime-common "~1.14.0"
platform "^1.3.6"
+openai@^3.2.1:
+ version "3.3.0"
+ resolved "https://registry.yarnpkg.com/openai/-/openai-3.3.0.tgz#a6408016ad0945738e1febf43f2fccca83a3f532"
+ integrity sha512-uqxI/Au+aPRnsaQRe8CojU0eCR7I0mBiKjD3sNMzY6DaC1ZVrc85u98mtJW6voDug8fgGN+DIZmTDxTthxb7dQ==
+ dependencies:
+ axios "^0.26.0"
+ form-data "^4.0.0"
+
openai@^4.19.0:
version "4.20.1"
resolved "https://registry.yarnpkg.com/openai/-/openai-4.20.1.tgz#afa0d496d125b5a0f6cebcb4b9aeabf71e00214e"
diff --git a/docker/.env.example b/docker/.env.example
index ae4913dc44c6680ee8fdd74e0f1175714c23a325..ed6fd3bce635b565ac09efbb6c8897787b029c2f 100644
--- a/docker/.env.example
+++ b/docker/.env.example
@@ -131,6 +131,16 @@ GID='1000'
# ASTRA_DB_APPLICATION_TOKEN=
# ASTRA_DB_ENDPOINT=
+###########################################
+######## Audio Model Selection ############
+###########################################
+# (default) use built-in whisper-small model.
+# WHISPER_PROVIDER="local"
+
+# use openai hosted whisper model.
+# WHISPER_PROVIDER="openai"
+# OPEN_AI_KEY=sk-xxxxxxxx
+
# CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
# DISABLE_TELEMETRY="false"
diff --git a/frontend/src/App.jsx b/frontend/src/App.jsx
index 86f6eb08ae2b20c5e40df08fda9cc3da75d03f8f..8a57d27bb65bfd44d66f80daf778aab3cf61e883 100644
--- a/frontend/src/App.jsx
+++ b/frontend/src/App.jsx
@@ -29,6 +29,9 @@ const GeneralApiKeys = lazy(() => import("@/pages/GeneralSettings/ApiKeys"));
const GeneralLLMPreference = lazy(
() => import("@/pages/GeneralSettings/LLMPreference")
);
+const GeneralTranscriptionPreference = lazy(
+ () => import("@/pages/GeneralSettings/TranscriptionPreference")
+);
const GeneralEmbeddingPreference = lazy(
() => import("@/pages/GeneralSettings/EmbeddingPreference")
);
@@ -76,6 +79,12 @@ export default function App() {
path="/settings/llm-preference"
element={<AdminRoute Component={GeneralLLMPreference} />}
/>
+ <Route
+ path="/settings/transcription-preference"
+ element={
+ <AdminRoute Component={GeneralTranscriptionPreference} />
+ }
+ />
<Route
path="/settings/embedding-preference"
element={<AdminRoute Component={GeneralEmbeddingPreference} />}
diff --git a/frontend/src/components/SettingsSidebar/index.jsx b/frontend/src/components/SettingsSidebar/index.jsx
index 84b78064a3a501ad8138edf69ff5683055467f57..a7aca7ffe21b03389e56597636973f850c0872ec 100644
--- a/frontend/src/components/SettingsSidebar/index.jsx
+++ b/frontend/src/components/SettingsSidebar/index.jsx
@@ -19,6 +19,7 @@ import {
Notepad,
CodeBlock,
Barcode,
+ ClosedCaptioning,
} from "@phosphor-icons/react";
import useUser from "@/hooks/useUser";
import { USER_BACKGROUND_COLOR } from "@/utils/constants";
@@ -278,9 +279,17 @@ const SidebarOptions = ({ user = null }) => (
flex={true}
allowedRole={["admin"]}
/>
+ <Option
+ href={paths.settings.transcriptionPreference()}
+ btnText="Transcription Model"
+ icon={<ClosedCaptioning className="h-5 w-5 flex-shrink-0" />}
+ user={user}
+ flex={true}
+ allowedRole={["admin"]}
+ />
<Option
href={paths.settings.embeddingPreference()}
- btnText="Embedding Preference"
+ btnText="Embedding Model"
icon={<FileCode className="h-5 w-5 flex-shrink-0" />}
user={user}
flex={true}
diff --git a/frontend/src/components/TranscriptionSelection/NativeTranscriptionOptions/index.jsx b/frontend/src/components/TranscriptionSelection/NativeTranscriptionOptions/index.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..07ee12126aee45fe04c3e2607e46f8f4f14dfd5e
--- /dev/null
+++ b/frontend/src/components/TranscriptionSelection/NativeTranscriptionOptions/index.jsx
@@ -0,0 +1,38 @@
+import { Gauge } from "@phosphor-icons/react";
+export default function NativeTranscriptionOptions() {
+ return (
+ <div className="w-full flex flex-col gap-y-4">
+ <div className="flex flex-col md:flex-row md:items-center gap-x-2 text-white mb-4 bg-blue-800/30 w-fit rounded-lg px-4 py-2">
+ <div className="gap-x-2 flex items-center">
+ <Gauge size={25} />
+ <p className="text-sm">
+ Using the local whisper model on machines with limited RAM or CPU
+ can stall AnythingLLM when processing media files.
+ <br />
+ We recommend at least 2GB of RAM and upload files <10Mb.
+ <br />
+ <br />
+ <i>
+ The built-in model will automatically download on the first use.
+ </i>
+ </p>
+ </div>
+ </div>
+ <div className="w-full flex items-center gap-4">
+ <div className="flex flex-col w-60">
+ <label className="text-white text-sm font-semibold block mb-4">
+ Model Selection
+ </label>
+ <select
+ 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}>
+ Xenova/whisper-small
+ </option>
+ </select>
+ </div>
+ </div>
+ </div>
+ );
+}
diff --git a/frontend/src/components/TranscriptionSelection/OpenAiOptions/index.jsx b/frontend/src/components/TranscriptionSelection/OpenAiOptions/index.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..aa48363e9d35be480cf8b69cc1c739dcdb60936b
--- /dev/null
+++ b/frontend/src/components/TranscriptionSelection/OpenAiOptions/index.jsx
@@ -0,0 +1,41 @@
+import { useState } from "react";
+
+export default function OpenAiWhisperOptions({ settings }) {
+ const [inputValue, setInputValue] = useState(settings?.OpenAiKey);
+ const [_openAIKey, setOpenAIKey] = useState(settings?.OpenAiKey);
+
+ return (
+ <div className="flex gap-x-4">
+ <div className="flex flex-col w-60">
+ <label className="text-white text-sm font-semibold block mb-4">
+ API Key
+ </label>
+ <input
+ type="password"
+ name="OpenAiKey"
+ className="bg-zinc-900 text-white placeholder:text-white/20 text-sm rounded-lg focus:border-white block w-full p-2.5"
+ placeholder="OpenAI API Key"
+ defaultValue={settings?.OpenAiKey ? "*".repeat(20) : ""}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ onChange={(e) => setInputValue(e.target.value)}
+ onBlur={() => setOpenAIKey(inputValue)}
+ />
+ </div>
+ <div className="flex flex-col w-60">
+ <label className="text-white text-sm font-semibold block mb-4">
+ Whisper Model
+ </label>
+ <select
+ 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}>
+ Whisper Large
+ </option>
+ </select>
+ </div>
+ </div>
+ );
+}
diff --git a/frontend/src/pages/GeneralSettings/TranscriptionPreference/index.jsx b/frontend/src/pages/GeneralSettings/TranscriptionPreference/index.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..a56dc26e7c922333c76d61d98122739a5181252a
--- /dev/null
+++ b/frontend/src/pages/GeneralSettings/TranscriptionPreference/index.jsx
@@ -0,0 +1,180 @@
+import React, { useEffect, useState } from "react";
+import { isMobile } from "react-device-detect";
+import Sidebar from "@/components/SettingsSidebar";
+import System from "@/models/system";
+import showToast from "@/utils/toast";
+import PreLoader from "@/components/Preloader";
+
+import OpenAiLogo from "@/media/llmprovider/openai.png";
+import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
+import OpenAiWhisperOptions from "@/components/TranscriptionSelection/OpenAiOptions";
+import NativeTranscriptionOptions from "@/components/TranscriptionSelection/NativeTranscriptionOptions";
+import LLMItem from "@/components/LLMSelection/LLMItem";
+import { MagnifyingGlass } from "@phosphor-icons/react";
+
+export default function TranscriptionModelPreference() {
+ const [saving, setSaving] = useState(false);
+ const [hasChanges, setHasChanges] = useState(false);
+ const [settings, setSettings] = useState(null);
+ const [loading, setLoading] = useState(true);
+ const [searchQuery, setSearchQuery] = useState("");
+ const [filteredProviders, setFilteredProviders] = useState([]);
+ const [selectedProvider, setSelectedProvider] = useState(null);
+
+ const handleSubmit = async (e) => {
+ e.preventDefault();
+ const form = e.target;
+ const data = { WhisperProvider: selectedProvider };
+ const formData = new FormData(form);
+
+ for (var [key, value] of formData.entries()) data[key] = value;
+ const { error } = await System.updateSystem(data);
+ setSaving(true);
+
+ if (error) {
+ showToast(`Failed to save preferences: ${error}`, "error");
+ } else {
+ showToast("Transcription preferences saved successfully.", "success");
+ }
+ setSaving(false);
+ setHasChanges(!!error);
+ };
+
+ const updateProviderChoice = (selection) => {
+ setSelectedProvider(selection);
+ setHasChanges(true);
+ };
+
+ useEffect(() => {
+ async function fetchKeys() {
+ const _settings = await System.keys();
+ setSettings(_settings);
+ setSelectedProvider(_settings?.WhisperProvider || "local");
+ setLoading(false);
+ }
+ fetchKeys();
+ }, []);
+
+ useEffect(() => {
+ const filtered = PROVIDERS.filter((provider) =>
+ provider.name.toLowerCase().includes(searchQuery.toLowerCase())
+ );
+ setFilteredProviders(filtered);
+ }, [searchQuery, selectedProvider]);
+
+ const PROVIDERS = [
+ {
+ name: "OpenAI",
+ value: "openai",
+ logo: OpenAiLogo,
+ options: <OpenAiWhisperOptions settings={settings} />,
+ description:
+ "Leverage the OpenAI Whisper-large model using your API key.",
+ },
+ {
+ name: "AnythingLLM Built-In",
+ value: "local",
+ logo: AnythingLLMIcon,
+ options: <NativeTranscriptionOptions settings={settings} />,
+ description: "Run a built-in whisper model on this instance privately.",
+ },
+ ];
+
+ return (
+ <div className="w-screen h-screen overflow-hidden bg-sidebar flex">
+ <Sidebar />
+ {loading ? (
+ <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"
+ >
+ <div className="w-full h-full flex justify-center items-center">
+ <PreLoader />
+ </div>
+ </div>
+ ) : (
+ <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} className="flex w-full">
+ <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 gap-x-4 items-center">
+ <p className="text-lg leading-6 font-bold text-white">
+ Transcription Model Preference
+ </p>
+ {hasChanges && (
+ <button
+ type="submit"
+ disabled={saving}
+ className="flex items-center gap-x-2 px-4 py-2 rounded-lg bg-[#2C2F36] text-white text-sm hover:bg-[#3D4147] shadow-md border border-[#3D4147]"
+ >
+ {saving ? "Saving..." : "Save changes"}
+ </button>
+ )}
+ </div>
+ <p className="text-xs leading-[18px] font-base text-white text-opacity-60">
+ These are the credentials and settings for your preferred
+ transcription model provider. Its important these keys are
+ current and correct or else media files and audio will not
+ transcribe.
+ </p>
+ </div>
+ <div className="text-sm font-medium text-white mt-6 mb-4">
+ Transcription Providers
+ </div>
+ <div className="w-full">
+ <div className="w-full relative border-slate-300/20 shadow border-4 rounded-xl text-white">
+ <div className="w-full p-4 absolute top-0 rounded-t-lg backdrop-blur-sm">
+ <div className="w-full flex items-center sticky top-0">
+ <MagnifyingGlass
+ size={16}
+ weight="bold"
+ className="absolute left-4 z-30 text-white"
+ />
+ <input
+ type="text"
+ placeholder="Search audio transcription providers"
+ className="bg-zinc-600 z-20 pl-10 h-[38px] rounded-full w-full px-4 py-1 text-sm border-2 border-slate-300/40 outline-none focus:border-white text-white"
+ onChange={(e) => setSearchQuery(e.target.value)}
+ autoComplete="off"
+ onKeyDown={(e) => {
+ if (e.key === "Enter") e.preventDefault();
+ }}
+ />
+ </div>
+ </div>
+ <div className="px-4 pt-[70px] flex flex-col gap-y-1 max-h-[390px] overflow-y-auto no-scroll pb-4">
+ {filteredProviders.map((provider) => {
+ return (
+ <LLMItem
+ key={provider.name}
+ name={provider.name}
+ value={provider.value}
+ image={provider.logo}
+ description={provider.description}
+ checked={selectedProvider === provider.value}
+ onClick={() => updateProviderChoice(provider.value)}
+ />
+ );
+ })}
+ </div>
+ </div>
+ <div
+ onChange={() => setHasChanges(true)}
+ className="mt-4 flex flex-col gap-y-1"
+ >
+ {selectedProvider &&
+ PROVIDERS.find(
+ (provider) => provider.value === selectedProvider
+ )?.options}
+ </div>
+ </div>
+ </div>
+ </form>
+ </div>
+ )}
+ </div>
+ );
+}
diff --git a/frontend/src/utils/paths.js b/frontend/src/utils/paths.js
index da10aa23cbac4844c8053fcafde38dd22141f58a..6c8745af31b4906e8f153459820eab9c1fb42f7f 100644
--- a/frontend/src/utils/paths.js
+++ b/frontend/src/utils/paths.js
@@ -92,6 +92,9 @@ export default {
llmPreference: () => {
return "/settings/llm-preference";
},
+ transcriptionPreference: () => {
+ return "/settings/transcription-preference";
+ },
embeddingPreference: () => {
return "/settings/embedding-preference";
},
diff --git a/server/.env.example b/server/.env.example
index 88e60182ce0283874bfa19ecb187637cf4fc2bf3..c5681db4a07473d1a85853c5d13bdf11ca4966f7 100644
--- a/server/.env.example
+++ b/server/.env.example
@@ -128,6 +128,16 @@ VECTOR_DB="lancedb"
# ZILLIZ_ENDPOINT="https://sample.api.gcp-us-west1.zillizcloud.com"
# ZILLIZ_API_TOKEN=api-token-here
+###########################################
+######## Audio Model Selection ############
+###########################################
+# (default) use built-in whisper-small model.
+WHISPER_PROVIDER="local"
+
+# use openai hosted whisper model.
+# WHISPER_PROVIDER="openai"
+# OPEN_AI_KEY=sk-xxxxxxxx
+
# 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
diff --git a/server/models/systemSettings.js b/server/models/systemSettings.js
index b06fe123004beaed95bd29350d562145c75ee30a..680ecf4f7cccc8f1fd813b0dc95a636227932c23 100644
--- a/server/models/systemSettings.js
+++ b/server/models/systemSettings.js
@@ -258,6 +258,7 @@ const SystemSettings = {
AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
}
: {}),
+ WhisperProvider: process.env.WHISPER_PROVIDER || "local",
};
},
diff --git a/server/storage/models/README.md b/server/storage/models/README.md
index 965083dcedbee5a5c0fd183983e20ea8e7cffb8f..432f60572ad8dd453395725e0d7ab382acb6bba4 100644
--- a/server/storage/models/README.md
+++ b/server/storage/models/README.md
@@ -14,6 +14,9 @@ AnythingLLM allows you to upload various audio and video formats as source docum
Once transcribed you can embed these transcriptions into your workspace like you would any other file!
+**Other external model/transcription providers are also live.**
+- [OpenAI Whisper via API key.](https://openai.com/research/whisper)
+
## Text generation (LLM selection)
> [!IMPORTANT]
> Use of a locally running LLM model is **experimental** and may behave unexpectedly, crash, or not function at all.
diff --git a/server/utils/collectorApi/index.js b/server/utils/collectorApi/index.js
index 7e8c11493087c7f0536f472b398645e1a1583fe6..ed27a92892492d27f467ef0ce717e39849112ac6 100644
--- a/server/utils/collectorApi/index.js
+++ b/server/utils/collectorApi/index.js
@@ -5,13 +5,20 @@
class CollectorApi {
constructor() {
- this.endpoint = "http://0.0.0.0:8888";
+ this.endpoint = `http://0.0.0.0:${process.env.COLLECTOR_PORT || 8888}`;
}
log(text, ...args) {
console.log(`\x1b[36m[CollectorApi]\x1b[0m ${text}`, ...args);
}
+ #attachOptions() {
+ return {
+ whisperProvider: process.env.WHISPER_PROVIDER || "local",
+ openAiKey: process.env.OPEN_AI_KEY || null,
+ };
+ }
+
async online() {
return await fetch(this.endpoint)
.then((res) => res.ok)
@@ -38,7 +45,10 @@ class CollectorApi {
headers: {
"Content-Type": "application/json",
},
- body: JSON.stringify({ filename }),
+ body: JSON.stringify({
+ filename,
+ options: this.#attachOptions(),
+ }),
})
.then((res) => {
if (!res.ok) throw new Error("Response could not be completed");
diff --git a/server/utils/helpers/updateENV.js b/server/utils/helpers/updateENV.js
index e46074a7c67d951d455148bf439697dcec4d098b..d0044357e141392489544f3a7f618535288db142 100644
--- a/server/utils/helpers/updateENV.js
+++ b/server/utils/helpers/updateENV.js
@@ -269,6 +269,13 @@ const KEY_MAPPING = {
checks: [isNotEmpty],
},
+ // Whisper (transcription) providers
+ WhisperProvider: {
+ envKey: "WHISPER_PROVIDER",
+ checks: [isNotEmpty, supportedTranscriptionProvider],
+ postUpdate: [],
+ },
+
// System Settings
AuthToken: {
envKey: "AUTH_TOKEN",
@@ -351,6 +358,13 @@ function supportedLLM(input = "") {
return validSelection ? null : `${input} is not a valid LLM provider.`;
}
+function supportedTranscriptionProvider(input = "") {
+ const validSelection = ["openai", "local"].includes(input);
+ return validSelection
+ ? null
+ : `${input} is not a valid transcription model provider.`;
+}
+
function validGeminiModel(input = "") {
const validModels = ["gemini-pro"];
return validModels.includes(input)