diff --git a/.vscode/settings.json b/.vscode/settings.json
new file mode 100644
index 0000000000000000000000000000000000000000..450dd7797a88421c0d6298c274c9b79d1c01cb59
--- /dev/null
+++ b/.vscode/settings.json
@@ -0,0 +1,5 @@
+{
+ "cSpell.words": [
+ "openai"
+ ]
+}
\ No newline at end of file
diff --git a/docker/.env.example b/docker/.env.example
index e44acd022560c7ef0e67d1962429dc11c273989f..6b9791eb5fc1c652ed017d95824db501f3c16204 100644
--- a/docker/.env.example
+++ b/docker/.env.example
@@ -1,8 +1,24 @@
SERVER_PORT=3001
-OPEN_AI_KEY=
-OPEN_MODEL_PREF='gpt-3.5-turbo'
CACHE_VECTORS="true"
+# JWT_SECRET="my-random-string-for-seeding" # Only needed if AUTH_TOKEN is set. Please generate random string at least 12 chars long.
+
+###########################################
+######## LLM API SElECTION ################
+###########################################
+LLM_PROVIDER='openai'
+# OPEN_AI_KEY=
+OPEN_MODEL_PREF='gpt-3.5-turbo'
+# LLM_PROVIDER='azure'
+# AZURE_OPENAI_ENDPOINT=
+# AZURE_OPENAI_KEY=
+# OPEN_MODEL_PREF='my-gpt35-deployment' # This is the "deployment" on Azure you want to use. Not the base model.
+# EMBEDDING_MODEL_PREF='embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002
+
+
+###########################################
+######## Vector Database Selection ########
+###########################################
# Enable all below if you are using vector database: Chroma.
# VECTOR_DB="chroma"
# CHROMA_ENDPOINT='http://localhost:8000'
@@ -18,7 +34,6 @@ PINECONE_INDEX=
# CLOUD DEPLOYMENT VARIRABLES ONLY
# AUTH_TOKEN="hunter2" # This is the password to your application if remote hosting.
-# JWT_SECRET="my-random-string-for-seeding" # Only needed if AUTH_TOKEN is set. Please generate random string at least 12 chars long.
# NO_DEBUG="true"
STORAGE_DIR="./server/storage"
GOOGLE_APIS_KEY=
diff --git a/frontend/src/components/Modals/Settings/Keys/index.jsx b/frontend/src/components/Modals/Settings/Keys/index.jsx
deleted file mode 100644
index 84b75373d3e3aa7bb10f31d5233a5480dda1adfc..0000000000000000000000000000000000000000
--- a/frontend/src/components/Modals/Settings/Keys/index.jsx
+++ /dev/null
@@ -1,220 +0,0 @@
-import React, { useState } from "react";
-import { AlertCircle, Loader } from "react-feather";
-import System from "../../../../models/system";
-
-const noop = () => false;
-export default function SystemKeys({ hideModal = noop, user, settings = {} }) {
- const canDebug = settings.MultiUserMode
- ? settings?.CanDebug && user?.role === "admin"
- : settings?.CanDebug;
- function validSettings(settings) {
- return (
- settings?.OpenAiKey &&
- !!settings?.OpenAiModelPref &&
- !!settings?.VectorDB &&
- (settings?.VectorDB === "chroma" ? !!settings?.ChromaEndpoint : true) &&
- (settings?.VectorDB === "pinecone"
- ? !!settings?.PineConeKey &&
- !!settings?.PineConeEnvironment &&
- !!settings?.PineConeIndex
- : true)
- );
- }
-
- return (
- <div className="relative w-full max-w-2xl max-h-full">
- <div className="relative bg-white rounded-lg shadow dark:bg-stone-700">
- <div className="flex items-start justify-between px-6 py-4">
- <p className="text-gray-800 dark:text-stone-200 text-base ">
- These are the credentials and settings for how your AnythingLLM
- instance will function. Its important these keys are current and
- correct.
- </p>
- </div>
- <div className="p-6 space-y-6 flex h-full w-full">
- <div className="w-full flex flex-col gap-y-4">
- {!validSettings(settings) && (
- <div className="bg-orange-300 p-4 rounded-lg border border-orange-600 text-orange-700 w-full items-center flex gap-x-2">
- <AlertCircle className="h-8 w-8" />
- <p className="text-sm md:text-base ">
- Ensure all fields are green before attempting to use
- AnythingLLM or it may not function as expected!
- </p>
- </div>
- )}
- <ShowKey
- name="OpenAI API Key"
- env="OpenAiKey"
- value={settings?.OpenAiKey ? "*".repeat(20) : ""}
- valid={settings?.OpenAiKey}
- allowDebug={canDebug}
- />
- <ShowKey
- name="OpenAI Model for chats"
- env="OpenAiModelPref"
- value={settings?.OpenAiModelPref}
- valid={!!settings?.OpenAiModelPref}
- allowDebug={canDebug}
- />
- </div>
- </div>
- <div className="flex items-center p-6 space-x-2 border-t border-gray-200 rounded-b dark:border-gray-600">
- <button
- onClick={hideModal}
- type="button"
- className="text-gray-500 bg-white hover:bg-gray-100 focus:ring-4 focus:outline-none focus:ring-blue-300 rounded-lg border border-gray-200 text-sm font-medium px-5 py-2.5 hover:text-gray-900 focus:z-10 dark:bg-gray-700 dark:text-gray-300 dark:border-gray-500 dark:hover:text-white dark:hover:bg-gray-600 dark:focus:ring-gray-600"
- >
- Close
- </button>
- </div>
- </div>
- </div>
- );
-}
-
-function ShowKey({ name, env, value, valid, allowDebug = true }) {
- const [isValid, setIsValid] = useState(valid);
- const [debug, setDebug] = useState(false);
- const [saving, setSaving] = useState(false);
- const handleSubmit = async (e) => {
- e.preventDefault();
- setSaving(true);
- const data = {};
- const form = new FormData(e.target);
- for (var [key, value] of form.entries()) data[key] = value;
- const { error } = await System.updateSystem(data);
- if (!!error) {
- alert(error);
- setSaving(false);
- setIsValid(false);
- return;
- }
-
- setSaving(false);
- setDebug(false);
- setIsValid(true);
- };
-
- if (!isValid) {
- return (
- <form onSubmit={handleSubmit}>
- <div>
- <label
- htmlFor="error"
- className="block mb-2 text-sm font-medium text-red-700 dark:text-red-500"
- >
- {name}
- </label>
- <input
- type="text"
- id="error"
- name={env}
- disabled={!debug}
- className="bg-red-50 border border-red-500 text-red-900 placeholder-red-700 text-sm rounded-lg focus:ring-red-500 dark:bg-gray-700 focus:border-red-500 block w-full p-2.5 dark:text-red-500 dark:placeholder-red-500 dark:border-red-500"
- placeholder={name}
- defaultValue={value}
- required={true}
- autoComplete="off"
- />
- <div className="flex items-center justify-between">
- <p className="mt-2 text-sm text-red-600 dark:text-red-500">
- Need setup in .env file.
- </p>
- {allowDebug && (
- <>
- {debug ? (
- <div className="flex items-center gap-x-2 mt-2">
- {saving ? (
- <>
- <Loader className="animate-spin h-4 w-4 text-slate-300 dark:text-slate-500" />
- </>
- ) : (
- <>
- <button
- type="button"
- onClick={() => setDebug(false)}
- className="text-xs text-slate-300 dark:text-slate-500"
- >
- Cancel
- </button>
- <button
- type="submit"
- className="text-xs text-blue-300 dark:text-blue-500"
- >
- Save
- </button>
- </>
- )}
- </div>
- ) : (
- <button
- type="button"
- onClick={() => setDebug(true)}
- className="mt-2 text-xs text-slate-300 dark:text-slate-500"
- >
- Change
- </button>
- )}
- </>
- )}
- </div>
- </div>
- </form>
- );
- }
-
- return (
- <form onSubmit={handleSubmit}>
- <div className="mb-6">
- <label
- htmlFor="success"
- className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200"
- >
- {name}
- </label>
- <input
- type="text"
- id="success"
- name={env}
- disabled={!debug}
- className="border border-white text-green-900 dark:text-green-400 placeholder-green-700 dark:placeholder-green-500 text-sm rounded-lg focus:ring-green-500 focus:border-green-500 block w-full p-2.5 dark:bg-gray-700 dark:border-green-500"
- defaultValue={value}
- required={true}
- autoComplete="off"
- />
- {allowDebug && (
- <div className="flex items-center justify-end">
- {debug ? (
- <div className="flex items-center gap-x-2 mt-2">
- {saving ? (
- <>
- <Loader className="animate-spin h-4 w-4 text-slate-300 dark:text-slate-500" />
- </>
- ) : (
- <>
- <button
- onClick={() => setDebug(false)}
- className="text-xs text-slate-300 dark:text-slate-500"
- >
- Cancel
- </button>
- <button className="text-xs text-blue-300 dark:text-blue-500">
- Save
- </button>
- </>
- )}
- </div>
- ) : (
- <button
- onClick={() => setDebug(true)}
- className="mt-2 text-xs text-slate-300 dark:text-slate-500"
- >
- Change
- </button>
- )}
- </div>
- )}
- </div>
- </form>
- );
-}
diff --git a/frontend/src/components/Modals/Settings/LLMSelection/index.jsx b/frontend/src/components/Modals/Settings/LLMSelection/index.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..94b75ace83ef35701150803e0f3e504d7df0dec4
--- /dev/null
+++ b/frontend/src/components/Modals/Settings/LLMSelection/index.jsx
@@ -0,0 +1,281 @@
+import React, { useState } from "react";
+import System from "../../../../models/system";
+import OpenAiLogo from "../../../../media/llmprovider/openai.png";
+import AzureOpenAiLogo from "../../../../media/llmprovider/azure.png";
+import AnthropicLogo from "../../../../media/llmprovider/anthropic.png";
+
+const noop = () => false;
+export default function LLMSelection({
+ hideModal = noop,
+ user,
+ settings = {},
+}) {
+ const [hasChanges, setHasChanges] = useState(false);
+ const [llmChoice, setLLMChoice] = useState(settings?.LLMProvider || "openai");
+ const [saving, setSaving] = useState(false);
+ const [error, setError] = useState(null);
+ const canDebug = settings.MultiUserMode
+ ? settings?.CanDebug && user?.role === "admin"
+ : settings?.CanDebug;
+
+ function updateLLMChoice(selection) {
+ if (!canDebug || selection === llmChoice) return false;
+ setHasChanges(true);
+ setLLMChoice(selection);
+ }
+
+ const handleSubmit = async (e) => {
+ e.preventDefault();
+ setSaving(true);
+ setError(null);
+ const data = {};
+ const form = new FormData(e.target);
+ for (var [key, value] of form.entries()) data[key] = value;
+ const { error } = await System.updateSystem(data);
+ setError(error);
+ setSaving(false);
+ setHasChanges(!!error ? true : false);
+ };
+ return (
+ <div className="relative w-full max-w-2xl max-h-full">
+ <div className="relative bg-white rounded-lg shadow dark:bg-stone-700">
+ <div className="flex items-start justify-between px-6 py-4">
+ <p className="text-gray-800 dark:text-stone-200 text-base ">
+ These are the credentials and settings for your preferred LLM chat &
+ embedding provider. Its important these keys are current and correct
+ or else AnythingLLM will not function properly.
+ </p>
+ </div>
+
+ {!!error && (
+ <div className="mb-8 bg-red-700 dark:bg-orange-800 bg-opacity-30 border border-red-800 dark:border-orange-600 p-4 rounded-lg w-[90%] flex mx-auto">
+ <p className="text-red-800 dark:text-orange-300 text-sm">{error}</p>
+ </div>
+ )}
+
+ <form onSubmit={handleSubmit} onChange={() => setHasChanges(true)}>
+ <div className="px-6 space-y-6 flex h-full w-full">
+ <div className="w-full flex flex-col gap-y-4">
+ <p className="block text-sm font-medium text-gray-800 dark:text-slate-200">
+ LLM providers
+ </p>
+ <div className="w-full flex overflow-x-scroll gap-x-4 no-scroll">
+ <input hidden={true} name="LLMProvider" value={llmChoice} />
+ <LLMProviderOption
+ name="OpenAI"
+ value="openai"
+ link="openai.com"
+ description="The standard option for most non-commercial use. Provides both chat and embedding."
+ checked={llmChoice === "openai"}
+ image={OpenAiLogo}
+ onClick={updateLLMChoice}
+ />
+ <LLMProviderOption
+ name="Azure OpenAi"
+ value="azure"
+ link="azure.microsoft.com"
+ description="The enterprise option of OpenAI hosted on Azure services. Provides both chat and embedding."
+ checked={llmChoice === "azure"}
+ image={AzureOpenAiLogo}
+ onClick={updateLLMChoice}
+ />
+ <LLMProviderOption
+ name="Anthropic Claude 2"
+ value="anthropic-claude-2"
+ link="anthropic.com"
+ description="[COMING SOON] A friendly AI Assistant hosted by Anthropic. Provides chat services only!"
+ checked={llmChoice === "anthropic-claude-2"}
+ image={AnthropicLogo}
+ />
+ </div>
+ {llmChoice === "openai" && (
+ <>
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ API Key
+ </label>
+ <input
+ type="text"
+ name="OpenAiKey"
+ disabled={!canDebug}
+ className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
+ placeholder="OpenAI API Key"
+ defaultValue={settings?.OpenAiKey ? "*".repeat(20) : ""}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ Chat Model Selection
+ </label>
+ <select
+ disabled={!canDebug}
+ name="OpenAiModelPref"
+ defaultValue={settings?.OpenAiModelPref}
+ required={true}
+ className="bg-gray-50 border border-gray-500 text-gray-900 text-sm rounded-lg block w-full p-2.5 dark:bg-stone-700 dark:border-slate-200 dark:placeholder-stone-500 dark:text-slate-200"
+ >
+ {[
+ "gpt-3.5-turbo",
+ "gpt-3.5-turbo-0613",
+ "gpt-3.5-turbo-16k",
+ "gpt-4",
+ "gpt-4-0613",
+ "gpt-4-32k",
+ "gpt-4-32k-0613",
+ ].map((model) => {
+ return (
+ <option key={model} value={model}>
+ {model}
+ </option>
+ );
+ })}
+ </select>
+ </div>
+ </>
+ )}
+
+ {llmChoice === "azure" && (
+ <>
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ Azure Service Endpoint
+ </label>
+ <input
+ type="url"
+ name="AzureOpenAiEndpoint"
+ disabled={!canDebug}
+ className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
+ placeholder="https://my-azure.openai.azure.com"
+ defaultValue={settings?.AzureOpenAiEndpoint}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ API Key
+ </label>
+ <input
+ type="password"
+ name="AzureOpenAiKey"
+ disabled={!canDebug}
+ className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
+ placeholder="Azure OpenAI API Key"
+ defaultValue={
+ settings?.AzureOpenAiKey ? "*".repeat(20) : ""
+ }
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ Chat Model Deployment Name
+ </label>
+ <input
+ type="text"
+ name="AzureOpenAiModelPref"
+ disabled={!canDebug}
+ className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
+ placeholder="Azure OpenAI chat model deployment name"
+ defaultValue={settings?.AzureOpenAiModelPref}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+
+ <div>
+ <label className="block mb-2 text-sm font-medium text-gray-800 dark:text-slate-200">
+ Embedding Model Deployment Name
+ </label>
+ <input
+ type="text"
+ name="AzureOpenAiEmbeddingModelPref"
+ disabled={!canDebug}
+ className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
+ placeholder="Azure OpenAI embedding model deployment name"
+ defaultValue={settings?.AzureOpenAiEmbeddingModelPref}
+ required={true}
+ autoComplete="off"
+ spellCheck={false}
+ />
+ </div>
+ </>
+ )}
+
+ {llmChoice === "anthropic-claude-2" && (
+ <div className="w-full h-40 items-center justify-center flex">
+ <p className="text-gray-800 dark:text-slate-400">
+ This provider is unavailable and cannot be used in
+ AnythingLLM currently.
+ </p>
+ </div>
+ )}
+ </div>
+ </div>
+ <div className="w-full p-4">
+ <button
+ hidden={!hasChanges}
+ disabled={saving}
+ type="submit"
+ className="w-full text-gray-500 bg-white hover:bg-gray-100 focus:ring-4 focus:outline-none focus:ring-blue-300 rounded-lg border border-gray-200 text-sm font-medium px-5 py-2.5 hover:text-gray-900 focus:z-10 dark:bg-gray-700 dark:text-gray-300 dark:border-gray-500 dark:hover:text-white dark:hover:bg-gray-600 dark:focus:ring-gray-600"
+ >
+ {saving ? "Saving..." : "Save changes"}
+ </button>
+ </div>
+ </form>
+ <div className="flex items-center p-6 space-x-2 border-t border-gray-200 rounded-b dark:border-gray-600">
+ <button
+ onClick={hideModal}
+ type="button"
+ className="text-gray-500 bg-white hover:bg-gray-100 focus:ring-4 focus:outline-none focus:ring-blue-300 rounded-lg border border-gray-200 text-sm font-medium px-5 py-2.5 hover:text-gray-900 focus:z-10 dark:bg-gray-700 dark:text-gray-300 dark:border-gray-500 dark:hover:text-white dark:hover:bg-gray-600 dark:focus:ring-gray-600"
+ >
+ Close
+ </button>
+ </div>
+ </div>
+ </div>
+ );
+}
+
+const LLMProviderOption = ({
+ name,
+ link,
+ description,
+ value,
+ image,
+ checked = false,
+ onClick,
+}) => {
+ return (
+ <div onClick={() => onClick(value)}>
+ <input
+ type="checkbox"
+ value={value}
+ className="peer hidden"
+ checked={checked}
+ readOnly={true}
+ formNoValidate={true}
+ />
+ <label className="transition-all duration-300 inline-flex h-full w-60 cursor-pointer items-center justify-between rounded-lg border border-gray-200 bg-white p-5 text-gray-500 hover:bg-gray-50 hover:text-gray-600 peer-checked:border-blue-600 peer-checked:bg-blue-50 peer-checked:dark:bg-stone-800 peer-checked:text-gray-600 dark:border-slate-200 dark:bg-stone-800 dark:text-slate-400 dark:hover:bg-stone-700 dark:hover:text-slate-300 dark:peer-checked:text-slate-300">
+ <div className="block">
+ <img src={image} alt={name} className="mb-2 h-10 w-10 rounded-full" />
+ <div className="w-full text-lg font-semibold">{name}</div>
+ <div className="flex w-full flex-col gap-y-1 text-sm">
+ <p className="text-xs text-slate-400">{link}</p>
+ {description}
+ </div>
+ </div>
+ </label>
+ </div>
+ );
+};
diff --git a/frontend/src/components/Modals/Settings/VectorDbs/index.jsx b/frontend/src/components/Modals/Settings/VectorDbs/index.jsx
index 0c4f5a3866e904a22a6c4b2f9bc871cbaace5fda..c4ad0aec1f10fa489d1c6614de2fa5a9d0a9d1ca 100644
--- a/frontend/src/components/Modals/Settings/VectorDbs/index.jsx
+++ b/frontend/src/components/Modals/Settings/VectorDbs/index.jsx
@@ -57,7 +57,7 @@ export default function VectorDBSelection({
<div className="px-6 space-y-6 flex h-full w-full">
<div className="w-full flex flex-col gap-y-4">
<p className="block text-sm font-medium text-gray-800 dark:text-slate-200">
- Vector database provider
+ Vector database providers
</p>
<div className="w-full flex overflow-x-scroll gap-x-4 no-scroll">
<input hidden={true} name="VectorDB" value={vectorDB} />
@@ -96,7 +96,7 @@ export default function VectorDBSelection({
Pinecone DB API Key
</label>
<input
- type="text"
+ type="password"
name="PineConeKey"
disabled={!canDebug}
className="bg-gray-50 border border-gray-500 text-gray-900 placeholder-gray-500 text-sm rounded-lg dark:bg-stone-700 focus:border-stone-500 block w-full p-2.5 dark:text-slate-200 dark:placeholder-stone-500 dark:border-slate-200"
diff --git a/frontend/src/components/Modals/Settings/index.jsx b/frontend/src/components/Modals/Settings/index.jsx
index 246b9ad3784496d18bea7b12b86fff11a000698f..bdf8e6e56306b1a4ffcfd4766b00f740f484e643 100644
--- a/frontend/src/components/Modals/Settings/index.jsx
+++ b/frontend/src/components/Modals/Settings/index.jsx
@@ -1,15 +1,22 @@
import React, { useEffect, useState } from "react";
-import { Archive, Lock, Key, X, Users, Database } from "react-feather";
-import SystemKeys from "./Keys";
+import {
+ Archive,
+ Lock,
+ X,
+ Users,
+ Database,
+ MessageSquare,
+} from "react-feather";
import ExportOrImportData from "./ExportImport";
import PasswordProtection from "./PasswordProtection";
import System from "../../../models/system";
import MultiUserMode from "./MultiUserMode";
import useUser from "../../../hooks/useUser";
import VectorDBSelection from "./VectorDbs";
+import LLMSelection from "./LLMSelection";
const TABS = {
- keys: SystemKeys,
+ llm: LLMSelection,
exportimport: ExportOrImportData,
password: PasswordProtection,
multiuser: MultiUserMode,
@@ -20,9 +27,9 @@ const noop = () => false;
export default function SystemSettingsModal({ hideModal = noop }) {
const { user } = useUser();
const [loading, setLoading] = useState(true);
- const [selectedTab, setSelectedTab] = useState("keys");
+ const [selectedTab, setSelectedTab] = useState("llm");
const [settings, setSettings] = useState(null);
- const Component = TABS[selectedTab || "keys"];
+ const Component = TABS[selectedTab || "llm"];
useEffect(() => {
async function fetchKeys() {
@@ -87,10 +94,10 @@ function SettingTabs({ selectedTab, changeTab, settings, user }) {
return (
<ul className="flex overflow-x-scroll no-scroll -mb-px text-sm gap-x-2 font-medium text-center text-gray-500 dark:text-gray-400">
<SettingTab
- active={selectedTab === "keys"}
- displayName="Keys"
- tabName="keys"
- icon={<Key className="h-4 w-4 flex-shrink-0" />}
+ active={selectedTab === "llm"}
+ displayName="LLM Choice"
+ tabName="llm"
+ icon={<MessageSquare className="h-4 w-4 flex-shrink-0" />}
onClick={changeTab}
/>
<SettingTab
diff --git a/frontend/src/media/llmprovider/anthropic.png b/frontend/src/media/llmprovider/anthropic.png
new file mode 100644
index 0000000000000000000000000000000000000000..09ff1535ff00e0c4761063b4972eca905980a5d6
Binary files /dev/null and b/frontend/src/media/llmprovider/anthropic.png differ
diff --git a/frontend/src/media/llmprovider/azure.png b/frontend/src/media/llmprovider/azure.png
new file mode 100644
index 0000000000000000000000000000000000000000..4ce890ca26b4192029b44685f2c3f8f4295b41fb
Binary files /dev/null and b/frontend/src/media/llmprovider/azure.png differ
diff --git a/frontend/src/media/llmprovider/openai.png b/frontend/src/media/llmprovider/openai.png
new file mode 100644
index 0000000000000000000000000000000000000000..b720ec753d1108c5f02107c3e4e46d1e3d9b6437
Binary files /dev/null and b/frontend/src/media/llmprovider/openai.png differ
diff --git a/server/.env.example b/server/.env.example
index f671f78dfcefc5e4fc735814177d01253fa34eac..e06c0f7e7cb5d482a41a902343bf4d2df24861e2 100644
--- a/server/.env.example
+++ b/server/.env.example
@@ -1,8 +1,23 @@
SERVER_PORT=3001
-OPEN_AI_KEY=
-OPEN_MODEL_PREF='gpt-3.5-turbo'
CACHE_VECTORS="true"
+JWT_SECRET="my-random-string-for-seeding" # Please generate random string at least 12 chars long.
+
+###########################################
+######## LLM API SElECTION ################
+###########################################
+LLM_PROVIDER='openai'
+# OPEN_AI_KEY=
+OPEN_MODEL_PREF='gpt-3.5-turbo'
+# LLM_PROVIDER='azure'
+# AZURE_OPENAI_ENDPOINT=
+# AZURE_OPENAI_KEY=
+# OPEN_MODEL_PREF='my-gpt35-deployment' # This is the "deployment" on Azure you want to use. Not the base model.
+# EMBEDDING_MODEL_PREF='embedder-model' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002
+
+###########################################
+######## Vector Database Selection ########
+###########################################
# Enable all below if you are using vector database: Chroma.
# VECTOR_DB="chroma"
# CHROMA_ENDPOINT='http://localhost:8000'
@@ -16,8 +31,6 @@ PINECONE_INDEX=
# Enable all below if you are using vector database: LanceDB.
# VECTOR_DB="lancedb"
-JWT_SECRET="my-random-string-for-seeding" # Please generate random string at least 12 chars long.
-
# 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/endpoints/system.js b/server/endpoints/system.js
index e78af6add7b89f11528cfce9d1c07740d2601163..98354f4a91427c48d500d56586238b68213b32b0 100644
--- a/server/endpoints/system.js
+++ b/server/endpoints/system.js
@@ -38,17 +38,16 @@ function systemEndpoints(app) {
app.get("/setup-complete", async (_, response) => {
try {
+ const llmProvider = process.env.LLM_PROVIDER || "openai";
const vectorDB = process.env.VECTOR_DB || "pinecone";
const results = {
CanDebug: !!!process.env.NO_DEBUG,
RequiresAuth: !!process.env.AUTH_TOKEN,
- VectorDB: vectorDB,
- OpenAiKey: !!process.env.OPEN_AI_KEY,
- OpenAiModelPref: process.env.OPEN_MODEL_PREF || "gpt-3.5-turbo",
AuthToken: !!process.env.AUTH_TOKEN,
JWTSecret: !!process.env.JWT_SECRET,
StorageDir: process.env.STORAGE_DIR,
MultiUserMode: await SystemSettings.isMultiUserMode(),
+ VectorDB: vectorDB,
...(vectorDB === "pinecone"
? {
PineConeEnvironment: process.env.PINECONE_ENVIRONMENT,
@@ -61,6 +60,22 @@ function systemEndpoints(app) {
ChromaEndpoint: process.env.CHROMA_ENDPOINT,
}
: {}),
+ LLMProvider: llmProvider,
+ ...(llmProvider === "openai"
+ ? {
+ OpenAiKey: !!process.env.OPEN_AI_KEY,
+ OpenAiModelPref: process.env.OPEN_MODEL_PREF || "gpt-3.5-turbo",
+ }
+ : {}),
+
+ ...(llmProvider === "azure"
+ ? {
+ AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
+ AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
+ AzureOpenAiModelPref: process.env.OPEN_MODEL_PREF,
+ AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
+ }
+ : {}),
};
response.status(200).json({ results });
} catch (e) {
diff --git a/server/package.json b/server/package.json
index 24b84210a5f23c46bf8b2996d686108fb3e86aaa..3d8ec2b80a355ce9f1993c91d5211a4144ed961b 100644
--- a/server/package.json
+++ b/server/package.json
@@ -15,6 +15,7 @@
"lint": "yarn prettier --write ./endpoints ./models ./utils index.js"
},
"dependencies": {
+ "@azure/openai": "^1.0.0-beta.3",
"@googleapis/youtube": "^9.0.0",
"@pinecone-database/pinecone": "^0.1.6",
"archiver": "^5.3.1",
@@ -43,4 +44,4 @@
"nodemon": "^2.0.22",
"prettier": "^2.4.1"
}
-}
\ No newline at end of file
+}
diff --git a/server/utils/AiProviders/azureOpenAi/index.js b/server/utils/AiProviders/azureOpenAi/index.js
new file mode 100644
index 0000000000000000000000000000000000000000..8743cc8aaabe0ef74618249058b982d932315e5e
--- /dev/null
+++ b/server/utils/AiProviders/azureOpenAi/index.js
@@ -0,0 +1,99 @@
+class AzureOpenAi {
+ constructor() {
+ const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
+ const openai = new OpenAIClient(
+ process.env.AZURE_OPENAI_ENDPOINT,
+ new AzureKeyCredential(process.env.AZURE_OPENAI_KEY)
+ );
+ this.openai = openai;
+ }
+
+ isValidChatModel(_modelName = "") {
+ // The Azure user names their "models" as deployments and they can be any name
+ // so we rely on the user to put in the correct deployment as only they would
+ // know it.
+ return true;
+ }
+
+ async isSafe(_input = "") {
+ // Not implemented by Azure OpenAI so must be stubbed
+ return { safe: true, reasons: [] };
+ }
+
+ async sendChat(chatHistory = [], prompt, workspace = {}) {
+ const model = process.env.OPEN_MODEL_PREF;
+ if (!model)
+ throw new Error(
+ "No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
+ );
+
+ const textResponse = await this.openai
+ .getChatCompletions(
+ model,
+ [
+ { role: "system", content: "" },
+ ...chatHistory,
+ { role: "user", content: prompt },
+ ],
+ {
+ temperature: Number(workspace?.openAiTemp ?? 0.7),
+ n: 1,
+ }
+ )
+ .then((res) => {
+ if (!res.hasOwnProperty("choices"))
+ throw new Error("OpenAI chat: No results!");
+ if (res.choices.length === 0)
+ throw new Error("OpenAI chat: No results length!");
+ return res.choices[0].message.content;
+ })
+ .catch((error) => {
+ console.log(error);
+ throw new Error(
+ `AzureOpenAI::getChatCompletions failed with: ${error.message}`
+ );
+ });
+ return textResponse;
+ }
+
+ async getChatCompletion(messages = [], { temperature = 0.7 }) {
+ const model = process.env.OPEN_MODEL_PREF;
+ if (!model)
+ throw new Error(
+ "No OPEN_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an LLM chat model like GPT-3.5."
+ );
+
+ const data = await this.openai.getChatCompletions(model, messages, {
+ temperature,
+ });
+ if (!data.hasOwnProperty("choices")) return null;
+ return data.choices[0].message.content;
+ }
+
+ async embedTextInput(textInput) {
+ const result = await this.embedChunks(textInput);
+ return result?.[0] || [];
+ }
+
+ async embedChunks(textChunks = []) {
+ const textEmbeddingModel =
+ process.env.EMBEDDING_MODEL_PREF || "text-embedding-ada-002";
+ if (!textEmbeddingModel)
+ throw new Error(
+ "No EMBEDDING_MODEL_PREF ENV defined. This must the name of a deployment on your Azure account for an embedding model."
+ );
+
+ const { data = [] } = await this.openai.getEmbeddings(
+ textEmbeddingModel,
+ textChunks
+ );
+ return data.length > 0 &&
+ data.every((embd) => embd.hasOwnProperty("embedding"))
+ ? data.map((embd) => embd.embedding)
+ : null;
+ }
+}
+
+module.exports = {
+ AzureOpenAi,
+};
diff --git a/server/utils/AiProviders/openAi/index.js b/server/utils/AiProviders/openAi/index.js
index 64b64bdcdba58b768cc102963f015100e89a5f62..bacc56da0760780569db817a1bae5113945a8d5a 100644
--- a/server/utils/AiProviders/openAi/index.js
+++ b/server/utils/AiProviders/openAi/index.js
@@ -1,7 +1,6 @@
-const { Configuration, OpenAIApi } = require("openai");
-
class OpenAi {
constructor() {
+ const { Configuration, OpenAIApi } = require("openai");
const config = new Configuration({
apiKey: process.env.OPEN_AI_KEY,
});
diff --git a/server/utils/chats/index.js b/server/utils/chats/index.js
index b6f74c158e2129212117a608ccda2b1b246c406b..a3a96bc28e8032bd919e2ab6d8d31eb77e7727fc 100644
--- a/server/utils/chats/index.js
+++ b/server/utils/chats/index.js
@@ -3,7 +3,8 @@ const { OpenAi } = require("../AiProviders/openAi");
const { WorkspaceChats } = require("../../models/workspaceChats");
const { resetMemory } = require("./commands/reset");
const moment = require("moment");
-const { getVectorDbClass } = require("../helpers");
+const { getVectorDbClass, getLLMProvider } = require("../helpers");
+const { AzureOpenAi } = require("../AiProviders/azureOpenAi");
function convertToChatHistory(history = []) {
const formattedHistory = [];
@@ -66,7 +67,7 @@ async function chatWithWorkspace(
user = null
) {
const uuid = uuidv4();
- const openai = new OpenAi();
+ const LLMConnector = getLLMProvider();
const VectorDb = getVectorDbClass();
const command = grepCommand(message);
@@ -74,7 +75,7 @@ async function chatWithWorkspace(
return await VALID_COMMANDS[command](workspace, message, uuid, user);
}
- const { safe, reasons = [] } = await openai.isSafe(message);
+ const { safe, reasons = [] } = await LLMConnector.isSafe(message);
if (!safe) {
return {
id: uuid,
@@ -93,7 +94,11 @@ async function chatWithWorkspace(
if (!hasVectorizedSpace || embeddingsCount === 0) {
const rawHistory = await WorkspaceChats.forWorkspace(workspace.id);
const chatHistory = convertToPromptHistory(rawHistory);
- const response = await openai.sendChat(chatHistory, message, workspace);
+ const response = await LLMConnector.sendChat(
+ chatHistory,
+ message,
+ workspace
+ );
const data = { text: response, sources: [], type: "chat" };
await WorkspaceChats.new({
diff --git a/server/utils/helpers/index.js b/server/utils/helpers/index.js
index 1a5aac863e84cf81c24d00710fe5f4a7cd72f753..5be565074290a8b3101f66b7d97068b2424a791a 100644
--- a/server/utils/helpers/index.js
+++ b/server/utils/helpers/index.js
@@ -1,21 +1,34 @@
function getVectorDbClass() {
- const { Pinecone } = require("../vectorDbProviders/pinecone");
- const { Chroma } = require("../vectorDbProviders/chroma");
- const { LanceDb } = require("../vectorDbProviders/lance");
-
const vectorSelection = process.env.VECTOR_DB || "pinecone";
switch (vectorSelection) {
case "pinecone":
+ const { Pinecone } = require("../vectorDbProviders/pinecone");
return Pinecone;
case "chroma":
+ const { Chroma } = require("../vectorDbProviders/chroma");
return Chroma;
case "lancedb":
+ const { LanceDb } = require("../vectorDbProviders/lance");
return LanceDb;
default:
throw new Error("ENV: No VECTOR_DB value found in environment!");
}
}
+function getLLMProvider() {
+ const vectorSelection = process.env.LLM_PROVIDER || "openai";
+ switch (vectorSelection) {
+ case "openai":
+ const { OpenAi } = require("../AiProviders/openAi");
+ return new OpenAi();
+ case "azure":
+ const { AzureOpenAi } = require("../AiProviders/azureOpenAi");
+ return new AzureOpenAi();
+ default:
+ throw new Error("ENV: No LLM_PROVIDER value found in environment!");
+ }
+}
+
function toChunks(arr, size) {
return Array.from({ length: Math.ceil(arr.length / size) }, (_v, i) =>
arr.slice(i * size, i * size + size)
@@ -24,5 +37,6 @@ function toChunks(arr, size) {
module.exports = {
getVectorDbClass,
+ getLLMProvider,
toChunks,
};
diff --git a/server/utils/helpers/updateENV.js b/server/utils/helpers/updateENV.js
index 0ff95fa492fa2c1096939cc405a6c4bb5b5476f9..64c9198849cf10e170cdec3c7eaf72c0b2abac1e 100644
--- a/server/utils/helpers/updateENV.js
+++ b/server/utils/helpers/updateENV.js
@@ -1,4 +1,9 @@
const KEY_MAPPING = {
+ LLMProvider: {
+ envKey: "LLM_PROVIDER",
+ checks: [isNotEmpty, supportedLLM],
+ },
+ // OpenAI Settings
OpenAiKey: {
envKey: "OPEN_AI_KEY",
checks: [isNotEmpty, validOpenAIKey],
@@ -7,6 +12,25 @@ const KEY_MAPPING = {
envKey: "OPEN_MODEL_PREF",
checks: [isNotEmpty, validOpenAIModel],
},
+ // Azure OpenAI Settings
+ AzureOpenAiEndpoint: {
+ envKey: "AZURE_OPENAI_ENDPOINT",
+ checks: [isNotEmpty, validAzureURL],
+ },
+ AzureOpenAiKey: {
+ envKey: "AZURE_OPENAI_KEY",
+ checks: [isNotEmpty],
+ },
+ AzureOpenAiModelPref: {
+ envKey: "OPEN_MODEL_PREF",
+ checks: [isNotEmpty],
+ },
+ AzureOpenAiEmbeddingModelPref: {
+ envKey: "EMBEDDING_MODEL_PREF",
+ checks: [isNotEmpty],
+ },
+
+ // Vector Database Selection Settings
VectorDB: {
envKey: "VECTOR_DB",
checks: [isNotEmpty, supportedVectorDB],
@@ -27,6 +51,8 @@ const KEY_MAPPING = {
envKey: "PINECONE_INDEX",
checks: [],
},
+
+ // System Settings
AuthToken: {
envKey: "AUTH_TOKEN",
checks: [],
@@ -56,6 +82,10 @@ function validOpenAIKey(input = "") {
return input.startsWith("sk-") ? null : "OpenAI Key must start with sk-";
}
+function supportedLLM(input = "") {
+ return ["openai", "azure"].includes(input);
+}
+
function validOpenAIModel(input = "") {
const validModels = [
"gpt-4",
@@ -85,6 +115,17 @@ function validChromaURL(input = "") {
: null;
}
+function validAzureURL(input = "") {
+ try {
+ new URL(input);
+ if (!input.includes("openai.azure.com"))
+ return "URL must include openai.azure.com";
+ return null;
+ } catch {
+ return "Not a valid URL";
+ }
+}
+
// This will force update .env variables which for any which reason were not able to be parsed or
// read from an ENV file as this seems to be a complicating step for many so allowing people to write
// to the process will at least alleviate that issue. It does not perform comprehensive validity checks or sanity checks
diff --git a/server/utils/vectorDbProviders/chroma/index.js b/server/utils/vectorDbProviders/chroma/index.js
index ee8ac48506a6b760a6c2fdcd4c1e5e5a1b47f589..4a527ac72f1adb8cdca0b252a98b3984efc0625e 100644
--- a/server/utils/vectorDbProviders/chroma/index.js
+++ b/server/utils/vectorDbProviders/chroma/index.js
@@ -1,14 +1,9 @@
-const { ChromaClient, OpenAIEmbeddingFunction } = require("chromadb");
-const { Chroma: ChromaStore } = require("langchain/vectorstores/chroma");
-const { OpenAI } = require("langchain/llms/openai");
-const { VectorDBQAChain } = require("langchain/chains");
-const { OpenAIEmbeddings } = require("langchain/embeddings/openai");
+const { ChromaClient } = require("chromadb");
const { RecursiveCharacterTextSplitter } = require("langchain/text_splitter");
const { storeVectorResult, cachedVectorInformation } = require("../../files");
const { v4: uuidv4 } = require("uuid");
-const { toChunks } = require("../../helpers");
+const { toChunks, getLLMProvider } = require("../../helpers");
const { chatPrompt } = require("../../chats");
-const { OpenAi } = require("../../AiProviders/openAi");
const Chroma = {
name: "Chroma",
@@ -49,22 +44,6 @@ const Chroma = {
const namespace = await this.namespace(client, _namespace);
return namespace?.vectorCount || 0;
},
- embeddingFunc: function () {
- return new OpenAIEmbeddingFunction({
- openai_api_key: process.env.OPEN_AI_KEY,
- });
- },
- embedder: function () {
- return new OpenAIEmbeddings({ openAIApiKey: process.env.OPEN_AI_KEY });
- },
- llm: function ({ temperature = 0.7 }) {
- const model = process.env.OPEN_MODEL_PREF || "gpt-3.5-turbo";
- return new OpenAI({
- openAIApiKey: process.env.OPEN_AI_KEY,
- modelName: model,
- temperature,
- });
- },
similarityResponse: async function (client, namespace, queryVector) {
const collection = await client.getCollection({ name: namespace });
const result = {
@@ -131,7 +110,6 @@ const Chroma = {
const collection = await client.getOrCreateCollection({
name: namespace,
metadata: { "hnsw:space": "cosine" },
- embeddingFunction: this.embeddingFunc(),
});
const { chunks } = cacheResult;
const documentVectors = [];
@@ -176,10 +154,10 @@ const Chroma = {
const textChunks = await textSplitter.splitText(pageContent);
console.log("Chunks created from document:", textChunks.length);
- const openAiConnector = new OpenAi();
+ const LLMConnector = getLLMProvider();
const documentVectors = [];
const vectors = [];
- const vectorValues = await openAiConnector.embedChunks(textChunks);
+ const vectorValues = await LLMConnector.embedChunks(textChunks);
const submission = {
ids: [],
embeddings: [],
@@ -216,7 +194,6 @@ const Chroma = {
const collection = await client.getOrCreateCollection({
name: namespace,
metadata: { "hnsw:space": "cosine" },
- embeddingFunction: this.embeddingFunc(),
});
if (vectors.length > 0) {
@@ -245,7 +222,6 @@ const Chroma = {
if (!(await this.namespaceExists(client, namespace))) return;
const collection = await client.getCollection({
name: namespace,
- embeddingFunction: this.embeddingFunc(),
});
const knownDocuments = await DocumentVectors.where(`docId = '${docId}'`);
@@ -271,22 +247,36 @@ const Chroma = {
};
}
- const vectorStore = await ChromaStore.fromExistingCollection(
- this.embedder(),
- { collectionName: namespace, url: process.env.CHROMA_ENDPOINT }
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
+ const { contextTexts, sourceDocuments } = await this.similarityResponse(
+ client,
+ namespace,
+ queryVector
);
- const model = this.llm({
+ const prompt = {
+ role: "system",
+ content: `${chatPrompt(workspace)}
+ Context:
+ ${contextTexts
+ .map((text, i) => {
+ return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+ })
+ .join("")}`,
+ };
+ const memory = [prompt, { role: "user", content: input }];
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
- const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
- k: 5,
- returnSourceDocuments: true,
+ // When we roll out own response we have separate metadata and texts,
+ // so for source collection we need to combine them.
+ const sources = sourceDocuments.map((metadata, i) => {
+ return { metadata: { ...metadata, text: contextTexts[i] } };
});
- const response = await chain.call({ query: input });
return {
- response: response.text,
- sources: this.curateSources(response.sourceDocuments),
+ response: responseText,
+ sources: this.curateSources(sources),
message: false,
};
},
@@ -312,8 +302,8 @@ const Chroma = {
};
}
- const openAiConnector = new OpenAi();
- const queryVector = await openAiConnector.embedTextInput(input);
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
const { contextTexts, sourceDocuments } = await this.similarityResponse(
client,
namespace,
@@ -330,7 +320,7 @@ const Chroma = {
.join("")}`,
};
const memory = [prompt, ...chatHistory, { role: "user", content: input }];
- const responseText = await openAiConnector.getChatCompletion(memory, {
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
diff --git a/server/utils/vectorDbProviders/lance/index.js b/server/utils/vectorDbProviders/lance/index.js
index 38b30af927b61852e38fd106126e259c2eccefb3..aeb33534bb59821bfaa142f445024b9982037ad8 100644
--- a/server/utils/vectorDbProviders/lance/index.js
+++ b/server/utils/vectorDbProviders/lance/index.js
@@ -1,11 +1,10 @@
const lancedb = require("vectordb");
-const { toChunks } = require("../../helpers");
+const { toChunks, getLLMProvider } = require("../../helpers");
const { OpenAIEmbeddings } = require("langchain/embeddings/openai");
const { RecursiveCharacterTextSplitter } = require("langchain/text_splitter");
const { storeVectorResult, cachedVectorInformation } = require("../../files");
const { v4: uuidv4 } = require("uuid");
const { chatPrompt } = require("../../chats");
-const { OpenAi } = require("../../AiProviders/openAi");
const LanceDb = {
uri: `${
@@ -169,11 +168,11 @@ const LanceDb = {
const textChunks = await textSplitter.splitText(pageContent);
console.log("Chunks created from document:", textChunks.length);
- const openAiConnector = new OpenAi();
+ const LLMConnector = getLLMProvider();
const documentVectors = [];
const vectors = [];
const submissions = [];
- const vectorValues = await openAiConnector.embedChunks(textChunks);
+ const vectorValues = await LLMConnector.embedChunks(textChunks);
if (!!vectorValues && vectorValues.length > 0) {
for (const [i, vector] of vectorValues.entries()) {
@@ -230,9 +229,8 @@ const LanceDb = {
};
}
- // LanceDB does not have langchainJS support so we roll our own here.
- const openAiConnector = new OpenAi();
- const queryVector = await openAiConnector.embedTextInput(input);
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
const { contextTexts, sourceDocuments } = await this.similarityResponse(
client,
namespace,
@@ -249,7 +247,7 @@ const LanceDb = {
.join("")}`,
};
const memory = [prompt, { role: "user", content: input }];
- const responseText = await openAiConnector.getChatCompletion(memory, {
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
@@ -281,8 +279,8 @@ const LanceDb = {
};
}
- const openAiConnector = new OpenAi();
- const queryVector = await openAiConnector.embedTextInput(input);
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
const { contextTexts, sourceDocuments } = await this.similarityResponse(
client,
namespace,
@@ -299,7 +297,7 @@ const LanceDb = {
.join("")}`,
};
const memory = [prompt, ...chatHistory, { role: "user", content: input }];
- const responseText = await openAiConnector.getChatCompletion(memory, {
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
diff --git a/server/utils/vectorDbProviders/pinecone/index.js b/server/utils/vectorDbProviders/pinecone/index.js
index 6021cfa37b6f882da3ddde1e35d0a7c6122ab0a9..91d97578fec5385f161dbb1d30fa8160a4b39271 100644
--- a/server/utils/vectorDbProviders/pinecone/index.js
+++ b/server/utils/vectorDbProviders/pinecone/index.js
@@ -1,14 +1,9 @@
const { PineconeClient } = require("@pinecone-database/pinecone");
-const { PineconeStore } = require("langchain/vectorstores/pinecone");
-const { OpenAI } = require("langchain/llms/openai");
-const { VectorDBQAChain } = require("langchain/chains");
-const { OpenAIEmbeddings } = require("langchain/embeddings/openai");
const { RecursiveCharacterTextSplitter } = require("langchain/text_splitter");
const { storeVectorResult, cachedVectorInformation } = require("../../files");
const { v4: uuidv4 } = require("uuid");
-const { toChunks } = require("../../helpers");
+const { toChunks, getLLMProvider } = require("../../helpers");
const { chatPrompt } = require("../../chats");
-const { OpenAi } = require("../../AiProviders/openAi");
const Pinecone = {
name: "Pinecone",
@@ -29,17 +24,6 @@ const Pinecone = {
if (!status.ready) throw new Error("Pinecode::Index not ready.");
return { client, pineconeIndex, indexName: process.env.PINECONE_INDEX };
},
- embedder: function () {
- return new OpenAIEmbeddings({ openAIApiKey: process.env.OPEN_AI_KEY });
- },
- llm: function ({ temperature = 0.7 }) {
- const model = process.env.OPEN_MODEL_PREF || "gpt-3.5-turbo";
- return new OpenAI({
- openAIApiKey: process.env.OPEN_AI_KEY,
- modelName: model,
- temperature,
- });
- },
totalIndicies: async function () {
const { pineconeIndex } = await this.connect();
const { namespaces } = await pineconeIndex.describeIndexStats1();
@@ -144,10 +128,10 @@ const Pinecone = {
const textChunks = await textSplitter.splitText(pageContent);
console.log("Chunks created from document:", textChunks.length);
- const openAiConnector = new OpenAi();
+ const LLMConnector = getLLMProvider();
const documentVectors = [];
const vectors = [];
- const vectorValues = await openAiConnector.embedChunks(textChunks);
+ const vectorValues = await LLMConnector.embedChunks(textChunks);
if (!!vectorValues && vectorValues.length > 0) {
for (const [i, vector] of vectorValues.entries()) {
@@ -246,22 +230,32 @@ const Pinecone = {
};
}
- const vectorStore = await PineconeStore.fromExistingIndex(this.embedder(), {
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
+ const { contextTexts, sourceDocuments } = await this.similarityResponse(
pineconeIndex,
namespace,
- });
+ queryVector
+ );
+ const prompt = {
+ role: "system",
+ content: `${chatPrompt(workspace)}
+ Context:
+ ${contextTexts
+ .map((text, i) => {
+ return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+ })
+ .join("")}`,
+ };
- const model = this.llm({
+ const memory = [prompt, { role: "user", content: input }];
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
- const chain = VectorDBQAChain.fromLLM(model, vectorStore, {
- k: 5,
- returnSourceDocuments: true,
- });
- const response = await chain.call({ query: input });
+
return {
- response: response.text,
- sources: this.curateSources(response.sourceDocuments),
+ response: responseText,
+ sources: this.curateSources(sourceDocuments),
message: false,
};
},
@@ -284,8 +278,8 @@ const Pinecone = {
"Invalid namespace - has it been collected and seeded yet?"
);
- const openAiConnector = new OpenAi();
- const queryVector = await openAiConnector.embedTextInput(input);
+ const LLMConnector = getLLMProvider();
+ const queryVector = await LLMConnector.embedTextInput(input);
const { contextTexts, sourceDocuments } = await this.similarityResponse(
pineconeIndex,
namespace,
@@ -303,7 +297,7 @@ const Pinecone = {
};
const memory = [prompt, ...chatHistory, { role: "user", content: input }];
- const responseText = await openAiConnector.getChatCompletion(memory, {
+ const responseText = await LLMConnector.getChatCompletion(memory, {
temperature: workspace?.openAiTemp ?? 0.7,
});
diff --git a/server/yarn.lock b/server/yarn.lock
index 1a82497edca368ac19adb2fa54d063693692b666..cd1514e7ac90af0f8c8660af52060e3eaf484e75 100644
--- a/server/yarn.lock
+++ b/server/yarn.lock
@@ -26,6 +26,93 @@
pad-left "^2.1.0"
tslib "^2.5.0"
+"@azure-rest/core-client@^1.1.3":
+ version "1.1.4"
+ resolved "https://registry.yarnpkg.com/@azure-rest/core-client/-/core-client-1.1.4.tgz#628381c3653f6dbae584ca6f2ae5f74a5c015526"
+ integrity sha512-RUIQOA8T0WcbNlddr8hjl2MuC5GVRqmMwPXqBVsgvdKesLy+eg3y/6nf3qe2fvcJMI1gF6VtgU5U4hRaR4w4ag==
+ dependencies:
+ "@azure/abort-controller" "^1.1.0"
+ "@azure/core-auth" "^1.3.0"
+ "@azure/core-rest-pipeline" "^1.5.0"
+ "@azure/core-tracing" "^1.0.1"
+ "@azure/core-util" "^1.0.0"
+ tslib "^2.2.0"
+
+"@azure/abort-controller@^1.0.0", "@azure/abort-controller@^1.1.0":
+ version "1.1.0"
+ resolved "https://registry.yarnpkg.com/@azure/abort-controller/-/abort-controller-1.1.0.tgz#788ee78457a55af8a1ad342acb182383d2119249"
+ integrity sha512-TrRLIoSQVzfAJX9H1JeFjzAoDGcoK1IYX1UImfceTZpsyYfWr09Ss1aHW1y5TrrR3iq6RZLBwJ3E24uwPhwahw==
+ dependencies:
+ tslib "^2.2.0"
+
+"@azure/core-auth@^1.3.0", "@azure/core-auth@^1.4.0":
+ version "1.5.0"
+ resolved "https://registry.yarnpkg.com/@azure/core-auth/-/core-auth-1.5.0.tgz#a41848c5c31cb3b7c84c409885267d55a2c92e44"
+ integrity sha512-udzoBuYG1VBoHVohDTrvKjyzel34zt77Bhp7dQntVGGD0ehVq48owENbBG8fIgkHRNUBQH5k1r0hpoMu5L8+kw==
+ dependencies:
+ "@azure/abort-controller" "^1.0.0"
+ "@azure/core-util" "^1.1.0"
+ tslib "^2.2.0"
+
+"@azure/core-lro@^2.5.3":
+ version "2.5.4"
+ resolved "https://registry.yarnpkg.com/@azure/core-lro/-/core-lro-2.5.4.tgz#b21e2bcb8bd9a8a652ff85b61adeea51a8055f90"
+ integrity sha512-3GJiMVH7/10bulzOKGrrLeG/uCBH/9VtxqaMcB9lIqAeamI/xYQSHJL/KcsLDuH+yTjYpro/u6D/MuRe4dN70Q==
+ dependencies:
+ "@azure/abort-controller" "^1.0.0"
+ "@azure/core-util" "^1.2.0"
+ "@azure/logger" "^1.0.0"
+ tslib "^2.2.0"
+
+"@azure/core-rest-pipeline@^1.10.2", "@azure/core-rest-pipeline@^1.5.0":
+ version "1.12.0"
+ resolved "https://registry.yarnpkg.com/@azure/core-rest-pipeline/-/core-rest-pipeline-1.12.0.tgz#a36dd361807494845522824532c076daa27c2786"
+ integrity sha512-+MnSB0vGZjszSzr5AW8z93/9fkDu2RLtWmAN8gskURq7EW2sSwqy8jZa0V26rjuBVkwhdA3Hw8z3VWoeBUOw+A==
+ dependencies:
+ "@azure/abort-controller" "^1.0.0"
+ "@azure/core-auth" "^1.4.0"
+ "@azure/core-tracing" "^1.0.1"
+ "@azure/core-util" "^1.3.0"
+ "@azure/logger" "^1.0.0"
+ form-data "^4.0.0"
+ http-proxy-agent "^5.0.0"
+ https-proxy-agent "^5.0.0"
+ tslib "^2.2.0"
+
+"@azure/core-tracing@^1.0.1":
+ version "1.0.1"
+ resolved "https://registry.yarnpkg.com/@azure/core-tracing/-/core-tracing-1.0.1.tgz#352a38cbea438c4a83c86b314f48017d70ba9503"
+ integrity sha512-I5CGMoLtX+pI17ZdiFJZgxMJApsK6jjfm85hpgp3oazCdq5Wxgh4wMr7ge/TTWW1B5WBuvIOI1fMU/FrOAMKrw==
+ dependencies:
+ tslib "^2.2.0"
+
+"@azure/core-util@^1.0.0", "@azure/core-util@^1.1.0", "@azure/core-util@^1.2.0", "@azure/core-util@^1.3.0":
+ version "1.4.0"
+ resolved "https://registry.yarnpkg.com/@azure/core-util/-/core-util-1.4.0.tgz#c120a56b3e48a9e4d20619a0b00268ae9de891c7"
+ integrity sha512-eGAyJpm3skVQoLiRqm/xPa+SXi/NPDdSHMxbRAz2lSprd+Zs+qrpQGQQ2VQ3Nttu+nSZR4XoYQC71LbEI7jsig==
+ dependencies:
+ "@azure/abort-controller" "^1.0.0"
+ tslib "^2.2.0"
+
+"@azure/logger@^1.0.0", "@azure/logger@^1.0.3":
+ version "1.0.4"
+ resolved "https://registry.yarnpkg.com/@azure/logger/-/logger-1.0.4.tgz#28bc6d0e5b3c38ef29296b32d35da4e483593fa1"
+ integrity sha512-ustrPY8MryhloQj7OWGe+HrYx+aoiOxzbXTtgblbV3xwCqpzUK36phH3XNHQKj3EPonyFUuDTfR3qFhTEAuZEg==
+ dependencies:
+ tslib "^2.2.0"
+
+"@azure/openai@^1.0.0-beta.3":
+ version "1.0.0-beta.3"
+ resolved "https://registry.yarnpkg.com/@azure/openai/-/openai-1.0.0-beta.3.tgz#bf4f5ec0a5644b3a9ce4372620856a65e7721e24"
+ integrity sha512-gW4odbuy/X/W34SdvXomj/JzR09MyMHCY5Kd2ZxJkQo3IUGqJXz1rEv6QER7IAGgBFgNawE97K6UuJfMmoT0rw==
+ dependencies:
+ "@azure-rest/core-client" "^1.1.3"
+ "@azure/core-auth" "^1.4.0"
+ "@azure/core-lro" "^2.5.3"
+ "@azure/core-rest-pipeline" "^1.10.2"
+ "@azure/logger" "^1.0.3"
+ tslib "^2.4.0"
+
"@fortaine/fetch-event-source@^3.0.6":
version "3.0.6"
resolved "https://registry.yarnpkg.com/@fortaine/fetch-event-source/-/fetch-event-source-3.0.6.tgz#b8552a2ca2c5202f5699b93a92be0188d422b06e"
@@ -86,6 +173,11 @@
resolved "https://registry.yarnpkg.com/@tootallnate/once/-/once-1.1.2.tgz#ccb91445360179a04e7fe6aff78c00ffc1eeaf82"
integrity sha512-RbzJvlNzmRq5c3O09UipeuXno4tA1FE6ikOjxZK0tuxVv3412l64l5t1W5pj4+rJq9vpkm/kwiR07aZXnsKPxw==
+"@tootallnate/once@2":
+ version "2.0.0"
+ resolved "https://registry.yarnpkg.com/@tootallnate/once/-/once-2.0.0.tgz#f544a148d3ab35801c1f633a7441fd87c2e484bf"
+ integrity sha512-XCuKFP5PS55gnMVu3dty8KPatLqUoy/ZYzDzAGCQ8JNFCkLXzmI7vNHCR+XpbZaMWQK/vQubr7PkYq8g470J/A==
+
"@types/command-line-args@5.2.0":
version "5.2.0"
resolved "https://registry.yarnpkg.com/@types/command-line-args/-/command-line-args-5.2.0.tgz#adbb77980a1cc376bb208e3f4142e907410430f6"
@@ -1128,6 +1220,15 @@ http-proxy-agent@^4.0.1:
agent-base "6"
debug "4"
+http-proxy-agent@^5.0.0:
+ version "5.0.0"
+ resolved "https://registry.yarnpkg.com/http-proxy-agent/-/http-proxy-agent-5.0.0.tgz#5129800203520d434f142bc78ff3c170800f2b43"
+ integrity sha512-n2hY8YdoRE1i7r6M0w9DIw5GgZN0G25P8zLCRQ8rjXtTU3vsNFBI/vWK/UIeE6g5MUUz6avwAPXmL6Fy9D/90w==
+ dependencies:
+ "@tootallnate/once" "2"
+ agent-base "6"
+ debug "4"
+
https-proxy-agent@^5.0.0:
version "5.0.1"
resolved "https://registry.yarnpkg.com/https-proxy-agent/-/https-proxy-agent-5.0.1.tgz#c59ef224a04fe8b754f3db0063a25ea30d0005d6"
@@ -2301,6 +2402,11 @@ tr46@~0.0.3:
resolved "https://registry.yarnpkg.com/tr46/-/tr46-0.0.3.tgz#8184fd347dac9cdc185992f3a6622e14b9d9ab6a"
integrity sha512-N3WMsuqV66lT30CrXNbEjx4GEwlow3v6rr4mCcv6prnfwhS01rkgyFdjPNBYd9br7LpXV1+Emh01fHnq2Gdgrw==
+tslib@^2.2.0, tslib@^2.4.0:
+ version "2.6.1"
+ resolved "https://registry.yarnpkg.com/tslib/-/tslib-2.6.1.tgz#fd8c9a0ff42590b25703c0acb3de3d3f4ede0410"
+ integrity sha512-t0hLfiEKfMUoqhG+U1oid7Pva4bbDPHYfJNiB7BiIjRkj1pyC++4N3huJfqY6aRH6VTB0rvtzQwjM4K6qpfOig==
+
tslib@^2.5.0:
version "2.6.0"
resolved "https://registry.yarnpkg.com/tslib/-/tslib-2.6.0.tgz#b295854684dbda164e181d259a22cd779dcd7bc3"