mirror of
https://github.com/BerriAI/litellm.git
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Merge pull request #9748 from BerriAI/litellm_ui_allow_testing_image_endpoints
[Feat] UI - Test Key v2 page - allow testing image endpoints + polish the page
This commit is contained in:
commit
e67d16d5bd
7 changed files with 566 additions and 270 deletions
|
@ -20,15 +20,28 @@ import {
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SelectItem,
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TextInput,
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Button,
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Divider,
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} from "@tremor/react";
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import { message, Select } from "antd";
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import { modelAvailableCall } from "./networking";
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import openai from "openai";
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import { ChatCompletionMessageParam } from "openai/resources/chat/completions";
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import { message, Select, Spin, Typography, Tooltip } from "antd";
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import { makeOpenAIChatCompletionRequest } from "./chat_ui/llm_calls/chat_completion";
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import { makeOpenAIImageGenerationRequest } from "./chat_ui/llm_calls/image_generation";
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import { fetchAvailableModels, ModelGroup } from "./chat_ui/llm_calls/fetch_models";
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import { litellmModeMapping, ModelMode, EndpointType, getEndpointType } from "./chat_ui/mode_endpoint_mapping";
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import { Prism as SyntaxHighlighter } from "react-syntax-highlighter";
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import { Typography } from "antd";
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import { coy } from 'react-syntax-highlighter/dist/esm/styles/prism';
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import EndpointSelector from "./chat_ui/EndpointSelector";
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import { determineEndpointType } from "./chat_ui/EndpointUtils";
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import {
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SendOutlined,
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ApiOutlined,
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KeyOutlined,
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ClearOutlined,
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RobotOutlined,
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UserOutlined,
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DeleteOutlined,
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LoadingOutlined
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} from "@ant-design/icons";
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interface ChatUIProps {
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accessToken: string | null;
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@ -38,45 +51,6 @@ interface ChatUIProps {
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disabledPersonalKeyCreation: boolean;
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}
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async function generateModelResponse(
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chatHistory: { role: string; content: string }[],
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updateUI: (chunk: string, model: string) => void,
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selectedModel: string,
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accessToken: string
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) {
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// base url should be the current base_url
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const isLocal = process.env.NODE_ENV === "development";
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if (isLocal !== true) {
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console.log = function () {};
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}
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console.log("isLocal:", isLocal);
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const proxyBaseUrl = isLocal
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? "http://localhost:4000"
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: window.location.origin;
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const client = new openai.OpenAI({
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apiKey: accessToken, // Replace with your OpenAI API key
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baseURL: proxyBaseUrl, // Replace with your OpenAI API base URL
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dangerouslyAllowBrowser: true, // using a temporary litellm proxy key
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});
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try {
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const response = await client.chat.completions.create({
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model: selectedModel,
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stream: true,
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messages: chatHistory as ChatCompletionMessageParam[],
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});
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for await (const chunk of response) {
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console.log(chunk);
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if (chunk.choices[0].delta.content) {
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updateUI(chunk.choices[0].delta.content, chunk.model);
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}
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}
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} catch (error) {
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message.error(`Error occurred while generating model response. Please try again. Error: ${error}`, 20);
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}
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}
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const ChatUI: React.FC<ChatUIProps> = ({
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accessToken,
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token,
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@ -89,63 +63,55 @@ const ChatUI: React.FC<ChatUIProps> = ({
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);
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const [apiKey, setApiKey] = useState("");
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const [inputMessage, setInputMessage] = useState("");
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const [chatHistory, setChatHistory] = useState<{ role: string; content: string; model?: string }[]>([]);
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const [chatHistory, setChatHistory] = useState<{ role: string; content: string; model?: string; isImage?: boolean }[]>([]);
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const [selectedModel, setSelectedModel] = useState<string | undefined>(
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undefined
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);
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const [showCustomModelInput, setShowCustomModelInput] = useState<boolean>(false);
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const [modelInfo, setModelInfo] = useState<any[]>([]);
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const [modelInfo, setModelInfo] = useState<ModelGroup[]>([]);
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const customModelTimeout = useRef<NodeJS.Timeout | null>(null);
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const [endpointType, setEndpointType] = useState<string>(EndpointType.CHAT);
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const [isLoading, setIsLoading] = useState<boolean>(false);
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const abortControllerRef = useRef<AbortController | null>(null);
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const chatEndRef = useRef<HTMLDivElement>(null);
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useEffect(() => {
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let useApiKey = apiKeySource === 'session' ? accessToken : apiKey;
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console.log("useApiKey:", useApiKey);
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if (!useApiKey || !token || !userRole || !userID) {
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console.log("useApiKey or token or userRole or userID is missing = ", useApiKey, token, userRole, userID);
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let userApiKey = apiKeySource === 'session' ? accessToken : apiKey;
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if (!userApiKey || !token || !userRole || !userID) {
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console.log("userApiKey or token or userRole or userID is missing = ", userApiKey, token, userRole, userID);
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return;
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}
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// Fetch model info and set the default selected model
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const fetchModelInfo = async () => {
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const loadModels = async () => {
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try {
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const fetchedAvailableModels = await modelAvailableCall(
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useApiKey ?? '', // Use empty string if useApiKey is null,
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userID,
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userRole
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if (!userApiKey) {
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console.log("userApiKey is missing");
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return;
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}
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const uniqueModels = await fetchAvailableModels(
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userApiKey,
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);
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console.log("model_info:", fetchedAvailableModels);
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console.log("Fetched models:", uniqueModels);
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if (fetchedAvailableModels?.data.length > 0) {
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// Create a Map to store unique models using the model ID as key
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const uniqueModelsMap = new Map();
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fetchedAvailableModels["data"].forEach((item: { id: string }) => {
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uniqueModelsMap.set(item.id, {
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value: item.id,
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label: item.id
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});
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});
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// Convert Map values back to array
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const uniqueModels = Array.from(uniqueModelsMap.values());
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// Sort models alphabetically
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uniqueModels.sort((a, b) => a.label.localeCompare(b.label));
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if (uniqueModels.length > 0) {
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setModelInfo(uniqueModels);
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setSelectedModel(uniqueModels[0].value);
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setSelectedModel(uniqueModels[0].model_group);
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// Auto-set endpoint based on the first model's mode
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if (uniqueModels[0].mode) {
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const initialEndpointType = determineEndpointType(uniqueModels[0].model_group, uniqueModels);
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setEndpointType(initialEndpointType);
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}
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}
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} catch (error) {
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console.error("Error fetching model info:", error);
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}
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};
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fetchModelInfo();
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loadModels();
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}, [accessToken, userID, userRole, apiKeySource, apiKey]);
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@ -162,11 +128,11 @@ const ChatUI: React.FC<ChatUIProps> = ({
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}
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}, [chatHistory]);
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const updateUI = (role: string, chunk: string, model?: string) => {
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const updateTextUI = (role: string, chunk: string, model?: string) => {
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setChatHistory((prevHistory) => {
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const lastMessage = prevHistory[prevHistory.length - 1];
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if (lastMessage && lastMessage.role === role) {
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if (lastMessage && lastMessage.role === role && !lastMessage.isImage) {
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return [
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...prevHistory.slice(0, prevHistory.length - 1),
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{ role, content: lastMessage.content + chunk, model },
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@ -177,12 +143,28 @@ const ChatUI: React.FC<ChatUIProps> = ({
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});
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};
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const updateImageUI = (imageUrl: string, model: string) => {
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setChatHistory((prevHistory) => [
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...prevHistory,
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{ role: "assistant", content: imageUrl, model, isImage: true }
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]);
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};
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const handleKeyDown = (event: React.KeyboardEvent<HTMLInputElement>) => {
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if (event.key === 'Enter') {
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handleSendMessage();
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}
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};
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const handleCancelRequest = () => {
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if (abortControllerRef.current) {
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abortControllerRef.current.abort();
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abortControllerRef.current = null;
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setIsLoading(false);
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message.info("Request cancelled");
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}
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};
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const handleSendMessage = async () => {
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if (inputMessage.trim() === "") return;
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|
@ -197,27 +179,52 @@ const ChatUI: React.FC<ChatUIProps> = ({
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return;
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}
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// Create new abort controller for this request
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abortControllerRef.current = new AbortController();
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const signal = abortControllerRef.current.signal;
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// Create message object without model field for API call
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const newUserMessage = { role: "user", content: inputMessage };
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// Create chat history for API call - strip out model field
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const apiChatHistory = [...chatHistory.map(({ role, content }) => ({ role, content })), newUserMessage];
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// Update UI with full message object (including model field for display)
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// Update UI with full message object
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setChatHistory([...chatHistory, newUserMessage]);
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setIsLoading(true);
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try {
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if (selectedModel) {
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await generateModelResponse(
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apiChatHistory,
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(chunk, model) => updateUI("assistant", chunk, model),
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selectedModel,
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effectiveApiKey
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);
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// Use EndpointType enum for comparison
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if (endpointType === EndpointType.CHAT) {
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// Create chat history for API call - strip out model field and isImage field
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const apiChatHistory = [...chatHistory.filter(msg => !msg.isImage).map(({ role, content }) => ({ role, content })), newUserMessage];
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await makeOpenAIChatCompletionRequest(
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apiChatHistory,
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(chunk, model) => updateTextUI("assistant", chunk, model),
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selectedModel,
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effectiveApiKey,
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signal
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);
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} else if (endpointType === EndpointType.IMAGE) {
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// For image generation
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await makeOpenAIImageGenerationRequest(
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inputMessage,
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(imageUrl, model) => updateImageUI(imageUrl, model),
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selectedModel,
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effectiveApiKey,
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signal
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);
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}
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}
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} catch (error) {
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console.error("Error fetching model response", error);
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updateUI("assistant", "Error fetching model response");
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if (signal.aborted) {
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console.log("Request was cancelled");
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} else {
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console.error("Error fetching response", error);
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updateTextUI("assistant", "Error fetching response");
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}
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} finally {
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setIsLoading(false);
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abortControllerRef.current = null;
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}
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setInputMessage("");
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|
@ -238,193 +245,240 @@ const ChatUI: React.FC<ChatUIProps> = ({
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);
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}
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const onChange = (value: string) => {
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const onModelChange = (value: string) => {
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console.log(`selected ${value}`);
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setSelectedModel(value);
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// Use the utility function to determine the endpoint type
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if (value !== 'custom') {
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const newEndpointType = determineEndpointType(value, modelInfo);
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setEndpointType(newEndpointType);
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}
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setShowCustomModelInput(value === 'custom');
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};
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return (
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<div style={{ width: "100%", position: "relative" }}>
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<Grid className="gap-2 p-8 h-[80vh] w-full mt-2">
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<Card>
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|
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<TabGroup>
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<TabList>
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<Tab>Chat</Tab>
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</TabList>
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<TabPanels>
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<TabPanel>
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<div className="sm:max-w-2xl">
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<Grid numItems={2}>
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<Col>
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<Text>API Key Source</Text>
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<Select
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disabled={disabledPersonalKeyCreation}
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defaultValue="session"
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style={{ width: "100%" }}
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onChange={(value) => setApiKeySource(value as "session" | "custom")}
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options={[
|
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{ value: 'session', label: 'Current UI Session' },
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{ value: 'custom', label: 'Virtual Key' },
|
||||
]}
|
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/>
|
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{apiKeySource === 'custom' && (
|
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<TextInput
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className="mt-2"
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placeholder="Enter custom API key"
|
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type="password"
|
||||
onValueChange={setApiKey}
|
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value={apiKey}
|
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/>
|
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)}
|
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</Col>
|
||||
<Col className="mx-2">
|
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<Text>Select Model:</Text>
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||||
<Select
|
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placeholder="Select a Model"
|
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onChange={onChange}
|
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options={[
|
||||
...modelInfo,
|
||||
{ value: 'custom', label: 'Enter custom model' }
|
||||
]}
|
||||
style={{ width: "350px" }}
|
||||
showSearch={true}
|
||||
/>
|
||||
{showCustomModelInput && (
|
||||
<TextInput
|
||||
className="mt-2"
|
||||
placeholder="Enter custom model name"
|
||||
onValueChange={(value) => {
|
||||
// Using setTimeout to create a simple debounce effect
|
||||
if (customModelTimeout.current) {
|
||||
clearTimeout(customModelTimeout.current);
|
||||
}
|
||||
|
||||
customModelTimeout.current = setTimeout(() => {
|
||||
setSelectedModel(value);
|
||||
}, 500); // 500ms delay after typing stops
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
</Col>
|
||||
</Grid>
|
||||
const handleEndpointChange = (value: string) => {
|
||||
setEndpointType(value);
|
||||
};
|
||||
|
||||
{/* Clear Chat Button */}
|
||||
<Button
|
||||
onClick={clearChatHistory}
|
||||
className="mt-4"
|
||||
>
|
||||
Clear Chat
|
||||
</Button>
|
||||
</div>
|
||||
<Table
|
||||
className="mt-5"
|
||||
style={{
|
||||
display: "block",
|
||||
maxHeight: "60vh",
|
||||
overflowY: "auto",
|
||||
}}
|
||||
>
|
||||
<TableHead>
|
||||
<TableRow>
|
||||
<TableCell>
|
||||
{/* <Title>Chat</Title> */}
|
||||
</TableCell>
|
||||
</TableRow>
|
||||
</TableHead>
|
||||
<TableBody>
|
||||
{chatHistory.map((message, index) => (
|
||||
<TableRow key={index}>
|
||||
<TableCell>
|
||||
<div style={{
|
||||
display: 'flex',
|
||||
alignItems: 'center',
|
||||
gap: '8px',
|
||||
marginBottom: '4px'
|
||||
}}>
|
||||
<strong>{message.role}</strong>
|
||||
{message.role === "assistant" && message.model && (
|
||||
<span style={{
|
||||
fontSize: '12px',
|
||||
color: '#666',
|
||||
backgroundColor: '#f5f5f5',
|
||||
padding: '2px 6px',
|
||||
borderRadius: '4px',
|
||||
fontWeight: 'normal'
|
||||
}}>
|
||||
{message.model}
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
<div style={{
|
||||
whiteSpace: "pre-wrap",
|
||||
wordBreak: "break-word",
|
||||
maxWidth: "100%"
|
||||
}}>
|
||||
<ReactMarkdown
|
||||
components={{
|
||||
code({node, inline, className, children, ...props}: React.ComponentPropsWithoutRef<'code'> & {
|
||||
inline?: boolean;
|
||||
node?: any;
|
||||
}) {
|
||||
const match = /language-(\w+)/.exec(className || '');
|
||||
return !inline && match ? (
|
||||
<SyntaxHighlighter
|
||||
style={coy as any}
|
||||
language={match[1]}
|
||||
PreTag="div"
|
||||
{...props}
|
||||
>
|
||||
{String(children).replace(/\n$/, '')}
|
||||
</SyntaxHighlighter>
|
||||
) : (
|
||||
<code className={className} {...props}>
|
||||
{children}
|
||||
</code>
|
||||
);
|
||||
}
|
||||
}}
|
||||
>
|
||||
{message.content}
|
||||
</ReactMarkdown>
|
||||
</div>
|
||||
</TableCell>
|
||||
</TableRow>
|
||||
))}
|
||||
<TableRow>
|
||||
<TableCell>
|
||||
<div ref={chatEndRef} style={{ height: "1px" }} />
|
||||
</TableCell>
|
||||
</TableRow>
|
||||
</TableBody>
|
||||
</Table>
|
||||
<div
|
||||
className="mt-3"
|
||||
style={{ position: "absolute", bottom: 5, width: "95%" }}
|
||||
>
|
||||
<div className="flex" style={{ marginTop: "16px" }}>
|
||||
<TextInput
|
||||
type="text"
|
||||
value={inputMessage}
|
||||
onChange={(e) => setInputMessage(e.target.value)}
|
||||
onKeyDown={handleKeyDown}
|
||||
placeholder="Type your message..."
|
||||
/>
|
||||
<Button
|
||||
onClick={handleSendMessage}
|
||||
className="ml-2"
|
||||
>
|
||||
Send
|
||||
</Button>
|
||||
const antIcon = <LoadingOutlined style={{ fontSize: 24 }} spin />;
|
||||
|
||||
return (
|
||||
<div className="w-full h-screen p-4 bg-white">
|
||||
<Card className="w-full rounded-xl shadow-md overflow-hidden">
|
||||
<div className="flex h-[80vh] w-full">
|
||||
{/* Left Sidebar with Controls */}
|
||||
<div className="w-1/4 p-4 border-r border-gray-200 bg-gray-50">
|
||||
<div className="mb-6">
|
||||
<div className="space-y-6">
|
||||
<div>
|
||||
<Text className="font-medium block mb-2 text-gray-700 flex items-center">
|
||||
<KeyOutlined className="mr-2" /> API Key Source
|
||||
</Text>
|
||||
<Select
|
||||
disabled={disabledPersonalKeyCreation}
|
||||
defaultValue="session"
|
||||
style={{ width: "100%" }}
|
||||
onChange={(value) => setApiKeySource(value as "session" | "custom")}
|
||||
options={[
|
||||
{ value: 'session', label: 'Current UI Session' },
|
||||
{ value: 'custom', label: 'Virtual Key' },
|
||||
]}
|
||||
className="rounded-md"
|
||||
/>
|
||||
{apiKeySource === 'custom' && (
|
||||
<TextInput
|
||||
className="mt-2"
|
||||
placeholder="Enter custom API key"
|
||||
type="password"
|
||||
onValueChange={setApiKey}
|
||||
value={apiKey}
|
||||
icon={KeyOutlined}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<Text className="font-medium block mb-2 text-gray-700 flex items-center">
|
||||
<RobotOutlined className="mr-2" /> Select Model
|
||||
</Text>
|
||||
<Select
|
||||
placeholder="Select a Model"
|
||||
onChange={onModelChange}
|
||||
options={[
|
||||
...modelInfo.map((option) => ({
|
||||
value: option.model_group,
|
||||
label: option.model_group
|
||||
})),
|
||||
{ value: 'custom', label: 'Enter custom model' }
|
||||
]}
|
||||
style={{ width: "100%" }}
|
||||
showSearch={true}
|
||||
className="rounded-md"
|
||||
/>
|
||||
{showCustomModelInput && (
|
||||
<TextInput
|
||||
className="mt-2"
|
||||
placeholder="Enter custom model name"
|
||||
onValueChange={(value) => {
|
||||
// Using setTimeout to create a simple debounce effect
|
||||
if (customModelTimeout.current) {
|
||||
clearTimeout(customModelTimeout.current);
|
||||
}
|
||||
|
||||
customModelTimeout.current = setTimeout(() => {
|
||||
setSelectedModel(value);
|
||||
}, 500); // 500ms delay after typing stops
|
||||
}}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
|
||||
<div>
|
||||
<Text className="font-medium block mb-2 text-gray-700 flex items-center">
|
||||
<ApiOutlined className="mr-2" /> Endpoint Type
|
||||
</Text>
|
||||
<EndpointSelector
|
||||
endpointType={endpointType}
|
||||
onEndpointChange={handleEndpointChange}
|
||||
className="mb-4"
|
||||
/>
|
||||
</div>
|
||||
|
||||
<Button
|
||||
onClick={clearChatHistory}
|
||||
className="w-full bg-gray-100 hover:bg-gray-200 text-gray-700 border-gray-300 mt-4"
|
||||
icon={ClearOutlined}
|
||||
>
|
||||
Clear Chat
|
||||
</Button>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
{/* Main Chat Area */}
|
||||
<div className="w-3/4 flex flex-col bg-white">
|
||||
<div className="flex-1 overflow-auto p-4 pb-0">
|
||||
{chatHistory.length === 0 && (
|
||||
<div className="h-full flex flex-col items-center justify-center text-gray-400">
|
||||
<RobotOutlined style={{ fontSize: '48px', marginBottom: '16px' }} />
|
||||
<Text>Start a conversation or generate an image</Text>
|
||||
</div>
|
||||
)}
|
||||
|
||||
{chatHistory.map((message, index) => (
|
||||
<div
|
||||
key={index}
|
||||
className={`mb-4 ${message.role === "user" ? "text-right" : "text-left"}`}
|
||||
>
|
||||
<div className="inline-block max-w-[80%] rounded-lg shadow-sm p-3.5 px-4" style={{
|
||||
backgroundColor: message.role === "user" ? '#f0f8ff' : '#ffffff',
|
||||
border: message.role === "user" ? '1px solid #e6f0fa' : '1px solid #f0f0f0',
|
||||
textAlign: 'left'
|
||||
}}>
|
||||
<div className="flex items-center gap-2 mb-1.5">
|
||||
<div className="flex items-center justify-center w-6 h-6 rounded-full mr-1" style={{
|
||||
backgroundColor: message.role === "user" ? '#e6f0fa' : '#f5f5f5',
|
||||
}}>
|
||||
{message.role === "user" ?
|
||||
<UserOutlined style={{ fontSize: '12px', color: '#2563eb' }} /> :
|
||||
<RobotOutlined style={{ fontSize: '12px', color: '#4b5563' }} />
|
||||
}
|
||||
</div>
|
||||
<strong className="text-sm capitalize">{message.role}</strong>
|
||||
{message.role === "assistant" && message.model && (
|
||||
<span className="text-xs px-2 py-0.5 rounded bg-gray-100 text-gray-600 font-normal">
|
||||
{message.model}
|
||||
</span>
|
||||
)}
|
||||
</div>
|
||||
<div className="whitespace-pre-wrap break-words max-w-full message-content">
|
||||
{message.isImage ? (
|
||||
<img
|
||||
src={message.content}
|
||||
alt="Generated image"
|
||||
className="max-w-full rounded-md border border-gray-200 shadow-sm"
|
||||
style={{ maxHeight: '500px' }}
|
||||
/>
|
||||
) : (
|
||||
<ReactMarkdown
|
||||
components={{
|
||||
code({node, inline, className, children, ...props}: React.ComponentPropsWithoutRef<'code'> & {
|
||||
inline?: boolean;
|
||||
node?: any;
|
||||
}) {
|
||||
const match = /language-(\w+)/.exec(className || '');
|
||||
return !inline && match ? (
|
||||
<SyntaxHighlighter
|
||||
style={coy as any}
|
||||
language={match[1]}
|
||||
PreTag="div"
|
||||
className="rounded-md my-2"
|
||||
{...props}
|
||||
>
|
||||
{String(children).replace(/\n$/, '')}
|
||||
</SyntaxHighlighter>
|
||||
) : (
|
||||
<code className={`${className} px-1.5 py-0.5 rounded bg-gray-100 text-sm font-mono`} {...props}>
|
||||
{children}
|
||||
</code>
|
||||
);
|
||||
}
|
||||
}}
|
||||
>
|
||||
{message.content}
|
||||
</ReactMarkdown>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</TabPanel>
|
||||
|
||||
</TabPanels>
|
||||
</TabGroup>
|
||||
</Card>
|
||||
</Grid>
|
||||
</div>
|
||||
))}
|
||||
{isLoading && (
|
||||
<div className="flex justify-center items-center my-4">
|
||||
<Spin indicator={antIcon} />
|
||||
</div>
|
||||
)}
|
||||
<div ref={chatEndRef} style={{ height: "1px" }} />
|
||||
</div>
|
||||
|
||||
<div className="p-4 border-t border-gray-200 bg-white">
|
||||
<div className="flex items-center">
|
||||
<TextInput
|
||||
type="text"
|
||||
value={inputMessage}
|
||||
onChange={(e) => setInputMessage(e.target.value)}
|
||||
onKeyDown={handleKeyDown}
|
||||
placeholder={
|
||||
endpointType === EndpointType.CHAT
|
||||
? "Type your message..."
|
||||
: "Describe the image you want to generate..."
|
||||
}
|
||||
disabled={isLoading}
|
||||
className="flex-1"
|
||||
/>
|
||||
{isLoading ? (
|
||||
<Button
|
||||
onClick={handleCancelRequest}
|
||||
className="ml-2 bg-red-50 hover:bg-red-100 text-red-600 border-red-200"
|
||||
icon={DeleteOutlined}
|
||||
>
|
||||
Cancel
|
||||
</Button>
|
||||
) : (
|
||||
<Button
|
||||
onClick={handleSendMessage}
|
||||
className="ml-2 text-white"
|
||||
icon={endpointType === EndpointType.CHAT ? SendOutlined : RobotOutlined}
|
||||
>
|
||||
{endpointType === EndpointType.CHAT ? "Send" : "Generate"}
|
||||
</Button>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
</Card>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
|
|
@ -0,0 +1,40 @@
|
|||
import React from "react";
|
||||
import { Select } from "antd";
|
||||
import { Text } from "@tremor/react";
|
||||
import { EndpointType } from "./mode_endpoint_mapping";
|
||||
|
||||
interface EndpointSelectorProps {
|
||||
endpointType: string; // Accept string to avoid type conflicts
|
||||
onEndpointChange: (value: string) => void;
|
||||
className?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* A reusable component for selecting API endpoints
|
||||
*/
|
||||
const EndpointSelector: React.FC<EndpointSelectorProps> = ({
|
||||
endpointType,
|
||||
onEndpointChange,
|
||||
className,
|
||||
}) => {
|
||||
// Map endpoint types to their display labels
|
||||
const endpointOptions = [
|
||||
{ value: EndpointType.CHAT, label: '/chat/completions' },
|
||||
{ value: EndpointType.IMAGE, label: '/images/generations' }
|
||||
];
|
||||
|
||||
return (
|
||||
<div className={className}>
|
||||
<Text>Endpoint Type:</Text>
|
||||
<Select
|
||||
value={endpointType}
|
||||
style={{ width: "100%" }}
|
||||
onChange={onEndpointChange}
|
||||
options={endpointOptions}
|
||||
className="rounded-md"
|
||||
/>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
export default EndpointSelector;
|
|
@ -0,0 +1,27 @@
|
|||
import { ModelGroup } from "./llm_calls/fetch_models";
|
||||
import { ModelMode, EndpointType, getEndpointType } from "./mode_endpoint_mapping";
|
||||
|
||||
/**
|
||||
* Determines the appropriate endpoint type based on the selected model
|
||||
*
|
||||
* @param selectedModel - The model identifier string
|
||||
* @param modelInfo - Array of model information
|
||||
* @returns The appropriate endpoint type
|
||||
*/
|
||||
export const determineEndpointType = (
|
||||
selectedModel: string,
|
||||
modelInfo: ModelGroup[]
|
||||
): EndpointType => {
|
||||
// Find the model information for the selected model
|
||||
const selectedModelInfo = modelInfo.find(
|
||||
(option) => option.model_group === selectedModel
|
||||
);
|
||||
|
||||
// If model info is found and it has a mode, determine the endpoint type
|
||||
if (selectedModelInfo?.mode) {
|
||||
return getEndpointType(selectedModelInfo.mode);
|
||||
}
|
||||
|
||||
// Default to chat endpoint if no match is found
|
||||
return EndpointType.CHAT;
|
||||
};
|
|
@ -0,0 +1,49 @@
|
|||
import openai from "openai";
|
||||
import { ChatCompletionMessageParam } from "openai/resources/chat/completions";
|
||||
import { message } from "antd";
|
||||
|
||||
export async function makeOpenAIChatCompletionRequest(
|
||||
chatHistory: { role: string; content: string }[],
|
||||
updateUI: (chunk: string, model: string) => void,
|
||||
selectedModel: string,
|
||||
accessToken: string,
|
||||
signal?: AbortSignal
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
if (isLocal !== true) {
|
||||
console.log = function () {};
|
||||
}
|
||||
console.log("isLocal:", isLocal);
|
||||
const proxyBaseUrl = isLocal
|
||||
? "http://localhost:4000"
|
||||
: window.location.origin;
|
||||
const client = new openai.OpenAI({
|
||||
apiKey: accessToken, // Replace with your OpenAI API key
|
||||
baseURL: proxyBaseUrl, // Replace with your OpenAI API base URL
|
||||
dangerouslyAllowBrowser: true, // using a temporary litellm proxy key
|
||||
});
|
||||
|
||||
try {
|
||||
const response = await client.chat.completions.create({
|
||||
model: selectedModel,
|
||||
stream: true,
|
||||
messages: chatHistory as ChatCompletionMessageParam[],
|
||||
}, { signal });
|
||||
|
||||
for await (const chunk of response) {
|
||||
console.log(chunk);
|
||||
if (chunk.choices[0].delta.content) {
|
||||
updateUI(chunk.choices[0].delta.content, chunk.model);
|
||||
}
|
||||
}
|
||||
} catch (error) {
|
||||
if (signal?.aborted) {
|
||||
console.log("Chat completion request was cancelled");
|
||||
} else {
|
||||
message.error(`Error occurred while generating model response. Please try again. Error: ${error}`, 20);
|
||||
}
|
||||
throw error; // Re-throw to allow the caller to handle the error
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,35 @@
|
|||
// fetch_models.ts
|
||||
|
||||
import { modelHubCall } from "../../networking";
|
||||
|
||||
export interface ModelGroup {
|
||||
model_group: string;
|
||||
mode?: string;
|
||||
}
|
||||
|
||||
/**
|
||||
* Fetches available models using modelHubCall and formats them for the selection dropdown.
|
||||
*/
|
||||
export const fetchAvailableModels = async (
|
||||
accessToken: string
|
||||
): Promise<ModelGroup[]> => {
|
||||
try {
|
||||
const fetchedModels = await modelHubCall(accessToken);
|
||||
console.log("model_info:", fetchedModels);
|
||||
|
||||
if (fetchedModels?.data.length > 0) {
|
||||
const models: ModelGroup[] = fetchedModels.data.map((item: any) => ({
|
||||
model_group: item.model_group, // Display the model_group to the user
|
||||
mode: item?.mode, // Save the mode for auto-selection of endpoint type
|
||||
}));
|
||||
|
||||
// Sort models alphabetically by label
|
||||
models.sort((a, b) => a.model_group.localeCompare(b.model_group));
|
||||
return models;
|
||||
}
|
||||
return [];
|
||||
} catch (error) {
|
||||
console.error("Error fetching model info:", error);
|
||||
throw error;
|
||||
}
|
||||
};
|
|
@ -0,0 +1,57 @@
|
|||
import openai from "openai";
|
||||
import { message } from "antd";
|
||||
|
||||
export async function makeOpenAIImageGenerationRequest(
|
||||
prompt: string,
|
||||
updateUI: (imageUrl: string, model: string) => void,
|
||||
selectedModel: string,
|
||||
accessToken: string,
|
||||
signal?: AbortSignal
|
||||
) {
|
||||
// base url should be the current base_url
|
||||
const isLocal = process.env.NODE_ENV === "development";
|
||||
if (isLocal !== true) {
|
||||
console.log = function () {};
|
||||
}
|
||||
console.log("isLocal:", isLocal);
|
||||
const proxyBaseUrl = isLocal
|
||||
? "http://localhost:4000"
|
||||
: window.location.origin;
|
||||
const client = new openai.OpenAI({
|
||||
apiKey: accessToken,
|
||||
baseURL: proxyBaseUrl,
|
||||
dangerouslyAllowBrowser: true,
|
||||
});
|
||||
|
||||
try {
|
||||
const response = await client.images.generate({
|
||||
model: selectedModel,
|
||||
prompt: prompt,
|
||||
}, { signal });
|
||||
|
||||
console.log(response.data);
|
||||
|
||||
if (response.data && response.data[0]) {
|
||||
// Handle either URL or base64 data from response
|
||||
if (response.data[0].url) {
|
||||
// Use the URL directly
|
||||
updateUI(response.data[0].url, selectedModel);
|
||||
} else if (response.data[0].b64_json) {
|
||||
// Convert base64 to data URL format
|
||||
const base64Data = response.data[0].b64_json;
|
||||
updateUI(`data:image/png;base64,${base64Data}`, selectedModel);
|
||||
} else {
|
||||
throw new Error("No image data found in response");
|
||||
}
|
||||
} else {
|
||||
throw new Error("Invalid response format");
|
||||
}
|
||||
} catch (error) {
|
||||
if (signal?.aborted) {
|
||||
console.log("Image generation request was cancelled");
|
||||
} else {
|
||||
message.error(`Error occurred while generating image. Please try again. Error: ${error}`, 20);
|
||||
}
|
||||
throw error; // Re-throw to allow the caller to handle the error
|
||||
}
|
||||
}
|
|
@ -0,0 +1,34 @@
|
|||
// litellmMapping.ts
|
||||
|
||||
// Define an enum for the modes as returned in model_info
|
||||
export enum ModelMode {
|
||||
IMAGE_GENERATION = "image_generation",
|
||||
CHAT = "chat",
|
||||
// add additional modes as needed
|
||||
}
|
||||
|
||||
// Define an enum for the endpoint types your UI calls
|
||||
export enum EndpointType {
|
||||
IMAGE = "image",
|
||||
CHAT = "chat",
|
||||
// add additional endpoint types if required
|
||||
}
|
||||
|
||||
// Create a mapping between the model mode and the corresponding endpoint type
|
||||
export const litellmModeMapping: Record<ModelMode, EndpointType> = {
|
||||
[ModelMode.IMAGE_GENERATION]: EndpointType.IMAGE,
|
||||
[ModelMode.CHAT]: EndpointType.CHAT,
|
||||
};
|
||||
|
||||
export const getEndpointType = (mode: string): EndpointType => {
|
||||
// Check if the string mode exists as a key in ModelMode enum
|
||||
console.log("getEndpointType:", mode);
|
||||
if (Object.values(ModelMode).includes(mode as ModelMode)) {
|
||||
const endpointType = litellmModeMapping[mode as ModelMode];
|
||||
console.log("endpointType:", endpointType);
|
||||
return endpointType;
|
||||
}
|
||||
|
||||
// else default to chat
|
||||
return EndpointType.CHAT;
|
||||
};
|
Loading…
Add table
Add a link
Reference in a new issue