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https://github.com/Mintplex-Labs/anything-llm.git
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Merge branch 'master' into dark-mode
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commit
351a1447a7
@ -71,23 +71,6 @@ export default function AzureAiOptions({ settings }) {
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</option>
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</select>
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</div>
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<div className="flex flex-col w-60">
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<label className="text-white text-sm font-semibold block mb-3">
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Embedding Deployment Name
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</label>
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<input
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type="text"
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name="AzureOpenAiEmbeddingModelPref"
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className="bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
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placeholder="Azure OpenAI embedding model deployment name"
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defaultValue={settings?.AzureOpenAiEmbeddingModelPref}
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required={true}
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autoComplete="off"
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spellCheck={false}
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/>
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</div>
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<div className="flex-flex-col w-60"></div>
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</div>
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</div>
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);
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@ -8,15 +8,18 @@ import { useTranslation } from "react-i18next";
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import { Link } from "react-router-dom";
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import paths from "@/utils/paths";
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// Some providers can only be associated with a single model.
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// In that case there is no selection to be made so we can just move on.
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const NO_MODEL_SELECTION = [
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"default",
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"huggingface",
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"generic-openai",
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"bedrock",
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];
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const DISABLED_PROVIDERS = ["azure", "native"];
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// Some providers do not support model selection via /models.
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// In that case we allow the user to enter the model name manually and hope they
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// type it correctly.
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const FREE_FORM_LLM_SELECTION = ["bedrock", "azure", "generic-openai"];
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// Some providers do not support model selection via /models
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// and only have a fixed single-model they can use.
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const NO_MODEL_SELECTION = ["default", "huggingface"];
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// Some providers we just fully disable for ease of use.
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const DISABLED_PROVIDERS = ["native"];
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const LLM_DEFAULT = {
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name: "System default",
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value: "default",
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@ -65,8 +68,8 @@ export default function WorkspaceLLMSelection({
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);
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setFilteredLLMs(filtered);
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}, [LLMS, searchQuery, selectedLLM]);
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const selectedLLMObject = LLMS.find((llm) => llm.value === selectedLLM);
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return (
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<div className="border-b border-white/40 pb-8">
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<div className="flex flex-col">
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@ -155,30 +158,66 @@ export default function WorkspaceLLMSelection({
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</button>
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)}
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</div>
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{NO_MODEL_SELECTION.includes(selectedLLM) ? (
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<>
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{selectedLLM !== "default" && (
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<div className="w-full h-10 justify-center items-center flex mt-4">
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<p className="text-sm font-base text-white text-opacity-60 text-center">
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Multi-model support is not supported for this provider yet.
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<br />
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This workspace will use{" "}
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<Link to={paths.settings.llmPreference()} className="underline">
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the model set for the system.
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</Link>
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</p>
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</div>
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)}
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</>
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) : (
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<div className="mt-4 flex flex-col gap-y-1">
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<ChatModelSelection
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provider={selectedLLM}
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workspace={workspace}
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setHasChanges={setHasChanges}
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/>
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</div>
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)}
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<ModelSelector
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selectedLLM={selectedLLM}
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workspace={workspace}
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setHasChanges={setHasChanges}
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/>
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</div>
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);
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}
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// TODO: Add this to agent selector as well as make generic component.
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function ModelSelector({ selectedLLM, workspace, setHasChanges }) {
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if (NO_MODEL_SELECTION.includes(selectedLLM)) {
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if (selectedLLM !== "default") {
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return (
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<div className="w-full h-10 justify-center items-center flex mt-4">
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<p className="text-sm font-base text-white text-opacity-60 text-center">
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Multi-model support is not supported for this provider yet.
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<br />
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This workspace will use{" "}
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<Link to={paths.settings.llmPreference()} className="underline">
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the model set for the system.
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</Link>
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</p>
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</div>
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);
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}
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return null;
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}
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if (FREE_FORM_LLM_SELECTION.includes(selectedLLM)) {
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return (
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<FreeFormLLMInput workspace={workspace} setHasChanges={setHasChanges} />
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);
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}
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return (
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<ChatModelSelection
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provider={selectedLLM}
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workspace={workspace}
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setHasChanges={setHasChanges}
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/>
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);
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}
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function FreeFormLLMInput({ workspace, setHasChanges }) {
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const { t } = useTranslation();
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return (
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<div className="mt-4 flex flex-col gap-y-1">
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<label className="block input-label">{t("chat.model.title")}</label>
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<p className="text-white text-opacity-60 text-xs font-medium py-1.5">
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{t("chat.model.description")}
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</p>
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<input
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type="text"
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name="chatModel"
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defaultValue={workspace?.chatModel || ""}
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onChange={() => setHasChanges(true)}
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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"
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placeholder="Enter model name exactly as referenced in the API (e.g., gpt-3.5-turbo)"
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/>
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</div>
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);
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}
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@ -5,7 +5,7 @@ const {
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} = require("../../helpers/chat/responses");
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class AzureOpenAiLLM {
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constructor(embedder = null, _modelPreference = null) {
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constructor(embedder = null, modelPreference = null) {
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const { OpenAIClient, AzureKeyCredential } = require("@azure/openai");
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if (!process.env.AZURE_OPENAI_ENDPOINT)
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throw new Error("No Azure API endpoint was set.");
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@ -16,7 +16,7 @@ class AzureOpenAiLLM {
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process.env.AZURE_OPENAI_ENDPOINT,
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new AzureKeyCredential(process.env.AZURE_OPENAI_KEY)
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);
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this.model = process.env.OPEN_MODEL_PREF;
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this.model = modelPreference ?? process.env.OPEN_MODEL_PREF;
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this.limits = {
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history: this.promptWindowLimit() * 0.15,
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system: this.promptWindowLimit() * 0.15,
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@ -32,7 +32,7 @@ class AWSBedrockLLM {
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#bedrockClient({ temperature = 0.7 }) {
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const { ChatBedrockConverse } = require("@langchain/aws");
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return new ChatBedrockConverse({
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model: process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE,
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model: this.model,
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region: process.env.AWS_BEDROCK_LLM_REGION,
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credentials: {
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accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID,
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