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Merge pull request #1968 from BerriAI/litellm_ui_add_chat_ui
[FEAT] Admin UI - show users playground to test models
This commit is contained in:
Ishaan Jaff
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1:null
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|
||||
+2
-2
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||||
[tool.poetry]
|
||||
name = "litellm"
|
||||
version = "1.23.12"
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||||
version = "1.23.13"
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||||
description = "Library to easily interface with LLM API providers"
|
||||
authors = ["BerriAI"]
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||||
license = "MIT"
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@@ -69,7 +69,7 @@ requires = ["poetry-core", "wheel"]
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||||
build-backend = "poetry.core.masonry.api"
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[tool.commitizen]
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version = "1.23.12"
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version = "1.23.13"
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version_files = [
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"pyproject.toml:^version"
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]
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<!DOCTYPE html><html id="__next_error__"><head><meta charSet="utf-8"/><meta name="viewport" content="width=device-width, initial-scale=1"/><link rel="preload" as="script" fetchPriority="low" href="/ui/_next/static/chunks/webpack-db47c93f042d6d15.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-a85b2c176012d8e5.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-e1b183dda365ec86.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>🚅 LiteLLM</title><meta name="description" content="LiteLLM Proxy Admin UI"/><link rel="icon" href="/ui/favicon.ico" type="image/x-icon" sizes="16x16"/><meta name="next-size-adjust"/><script src="/ui/_next/static/chunks/polyfills-c67a75d1b6f99dc8.js" crossorigin="" noModule=""></script></head><body><script src="/ui/_next/static/chunks/webpack-db47c93f042d6d15.js" crossorigin="" async=""></script><script>(self.__next_f=self.__next_f||[]).push([0]);self.__next_f.push([2,null])</script><script>self.__next_f.push([1,"1:HL[\"/ui/_next/static/media/c9a5bc6a7c948fb0-s.p.woff2\",\"font\",{\"crossOrigin\":\"\",\"type\":\"font/woff2\"}]\n2:HL[\"/ui/_next/static/css/c18941d97fb7245b.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[48016,[\"145\",\"static/chunks/145-9c160ad5539e000f.js\",\"931\",\"static/chunks/app/page-fcb69349f15d154b.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/c18941d97fb7245b.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"lLFQRQnIrRo-GJf5spHEd\",\"assetPrefix\":\"/ui\",\"initialCanonicalUrl\":\"/\",\"initialTree\":[\"\",{\"children\":[\"__PAGE__\",{}]},\"$undefined\",\"$undefined\",true],\"initialSeedData\":[\"\",{\"children\":[\"__PAGE__\",{},[\"$L5\",[\"$\",\"$L6\",null,{\"propsForComponent\":{\"params\":{}},\"Component\":\"$7\",\"isStaticGeneration\":true}],null]]},[null,[\"$\",\"html\",null,{\"lang\":\"en\",\"children\":[\"$\",\"body\",null,{\"className\":\"__className_c23dc8\",\"children\":[\"$\",\"$L8\",null,{\"parallelRouterKey\":\"children\",\"segmentPath\":[\"children\"],\"loading\":\"$undefined\",\"loadingStyles\":\"$undefined\",\"loadingScripts\":\"$undefined\",\"hasLoading\":false,\"error\":\"$undefined\",\"errorStyles\":\"$undefined\",\"errorScripts\":\"$undefined\",\"template\":[\"$\",\"$L9\",null,{}],\"templateStyles\":\"$undefined\",\"templateScripts\":\"$undefined\",\"notFound\":[[\"$\",\"title\",null,{\"children\":\"404: This page could not be found.\"}],[\"$\",\"div\",null,{\"style\":{\"fontFamily\":\"system-ui,\\\"Segoe UI\\\",Roboto,Helvetica,Arial,sans-serif,\\\"Apple Color Emoji\\\",\\\"Segoe UI Emoji\\\"\",\"height\":\"100vh\",\"textAlign\":\"center\",\"display\":\"flex\",\"flexDirection\":\"column\",\"alignItems\":\"center\",\"justifyContent\":\"center\"},\"children\":[\"$\",\"div\",null,{\"children\":[[\"$\",\"style\",null,{\"dangerouslySetInnerHTML\":{\"__html\":\"body{color:#000;background:#fff;margin:0}.next-error-h1{border-right:1px solid rgba(0,0,0,.3)}@media (prefers-color-scheme:dark){body{color:#fff;background:#000}.next-error-h1{border-right:1px solid rgba(255,255,255,.3)}}\"}}],[\"$\",\"h1\",null,{\"className\":\"next-error-h1\",\"style\":{\"display\":\"inline-block\",\"margin\":\"0 20px 0 0\",\"padding\":\"0 23px 0 0\",\"fontSize\":24,\"fontWeight\":500,\"verticalAlign\":\"top\",\"lineHeight\":\"49px\"},\"children\":\"404\"}],[\"$\",\"div\",null,{\"style\":{\"display\":\"inline-block\"},\"children\":[\"$\",\"h2\",null,{\"style\":{\"fontSize\":14,\"fontWeight\":400,\"lineHeight\":\"49px\",\"margin\":0},\"children\":\"This page could not be found.\"}]}]]}]}]],\"notFoundStyles\":[],\"styles\":null}]}]}],null]],\"initialHead\":[false,\"$La\"],\"globalErrorComponent\":\"$b\",\"missingSlots\":\"$Wc\"}]]\n"])</script><script>self.__next_f.push([1,"a:[[\"$\",\"meta\",\"0\",{\"name\":\"viewport\",\"content\":\"width=device-width, initial-scale=1\"}],[\"$\",\"meta\",\"1\",{\"charSet\":\"utf-8\"}],[\"$\",\"title\",\"2\",{\"children\":\"🚅 LiteLLM\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"link\",\"4\",{\"rel\":\"icon\",\"href\":\"/ui/favicon.ico\",\"type\":\"image/x-icon\",\"sizes\":\"16x16\"}],[\"$\",\"meta\",\"5\",{\"name\":\"next-size-adjust\"}]]\n5:null\n"])</script><script>self.__next_f.push([1,""])</script></body></html>
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4:I[5613,[],""]
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5:I[31778,[],""]
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||||
6:[["$","meta","0",{"name":"viewport","content":"width=device-width, initial-scale=1"}],["$","meta","1",{"charSet":"utf-8"}],["$","title","2",{"children":"🚅 LiteLLM"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
||||
Generated
+1621
-13
File diff suppressed because it is too large
Load Diff
@@ -19,14 +19,18 @@
|
||||
"jsonwebtoken": "^9.0.2",
|
||||
"jwt-decode": "^4.0.0",
|
||||
"next": "14.1.0",
|
||||
"openai": "^4.28.0",
|
||||
"react": "^18",
|
||||
"react-dom": "^18"
|
||||
"react-dom": "^18",
|
||||
"react-markdown": "^9.0.1",
|
||||
"react-syntax-highlighter": "^15.5.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
"@tailwindcss/forms": "^0.5.7",
|
||||
"@types/node": "^20",
|
||||
"@types/react": "18.2.48",
|
||||
"@types/react-dom": "^18",
|
||||
"@types/react-syntax-highlighter": "^15.5.11",
|
||||
"autoprefixer": "^10.4.17",
|
||||
"eslint": "^8",
|
||||
"eslint-config-next": "14.1.0",
|
||||
|
||||
@@ -4,6 +4,7 @@ import { useSearchParams } from "next/navigation";
|
||||
import Navbar from "../components/navbar";
|
||||
import UserDashboard from "../components/user_dashboard";
|
||||
import ModelDashboard from "@/components/model_dashboard";
|
||||
import ChatUI from "@/components/chat_ui";
|
||||
import Sidebar from "../components/leftnav";
|
||||
import Usage from "../components/usage";
|
||||
import { jwtDecode } from "jwt-decode";
|
||||
@@ -88,6 +89,13 @@ const CreateKeyPage = () => {
|
||||
token={token}
|
||||
accessToken={accessToken}
|
||||
/>
|
||||
) : page == "llm-playground" ? (
|
||||
<ChatUI
|
||||
userID={userID}
|
||||
userRole={userRole}
|
||||
token={token}
|
||||
accessToken={accessToken}
|
||||
/>
|
||||
)
|
||||
: (
|
||||
<Usage
|
||||
|
||||
@@ -0,0 +1,301 @@
|
||||
import React, { useState, useEffect } from "react";
|
||||
import ReactMarkdown from "react-markdown";
|
||||
import { Card, Title, Table, TableHead, TableRow, TableCell, TableBody, Grid, Tab,
|
||||
TabGroup,
|
||||
TabList,
|
||||
TabPanel,
|
||||
Metric,
|
||||
Select,
|
||||
SelectItem,
|
||||
TabPanels, } from "@tremor/react";
|
||||
import { modelInfoCall } from "./networking";
|
||||
import openai from "openai";
|
||||
import { Prism as SyntaxHighlighter } from 'react-syntax-highlighter';
|
||||
|
||||
|
||||
interface ChatUIProps {
|
||||
accessToken: string | null;
|
||||
token: string | null;
|
||||
userRole: string | null;
|
||||
userID: string | null;
|
||||
}
|
||||
|
||||
async function generateModelResponse(inputMessage: string, updateUI: (chunk: string) => void, selectedModel: string, accessToken: string) {
|
||||
const client = new openai.OpenAI({
|
||||
apiKey: accessToken, // Replace with your OpenAI API key
|
||||
baseURL: 'http://0.0.0.0:4000', // Replace with your OpenAI API base URL
|
||||
dangerouslyAllowBrowser: true, // using a temporary litellm proxy key
|
||||
});
|
||||
|
||||
const response = await client.chat.completions.create({
|
||||
model: selectedModel,
|
||||
stream: true,
|
||||
messages: [
|
||||
{
|
||||
role: 'user',
|
||||
content: inputMessage,
|
||||
},
|
||||
],
|
||||
});
|
||||
|
||||
for await (const chunk of response) {
|
||||
console.log(chunk);
|
||||
if (chunk.choices[0].delta.content) {
|
||||
updateUI(chunk.choices[0].delta.content);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
const ChatUI: React.FC<ChatUIProps> = ({ accessToken, token, userRole, userID }) => {
|
||||
const [inputMessage, setInputMessage] = useState("");
|
||||
const [chatHistory, setChatHistory] = useState<any[]>([]);
|
||||
const [selectedModel, setSelectedModel] = useState<string | undefined>(undefined);
|
||||
const [modelInfo, setModelInfo] = useState<any | null>(null); // Declare modelInfo at the component level
|
||||
|
||||
useEffect(() => {
|
||||
if (!accessToken || !token || !userRole || !userID) {
|
||||
return;
|
||||
}
|
||||
// Fetch model info and set the default selected model
|
||||
const fetchModelInfo = async () => {
|
||||
const fetchedModelInfo = await modelInfoCall(accessToken, userID, userRole);
|
||||
console.log("model_info:", fetchedModelInfo);
|
||||
|
||||
if (fetchedModelInfo?.data.length > 0) {
|
||||
setModelInfo(fetchedModelInfo);
|
||||
setSelectedModel(fetchedModelInfo.data[0].model_name);
|
||||
}
|
||||
};
|
||||
|
||||
fetchModelInfo();
|
||||
}, [accessToken, userID, userRole]);
|
||||
|
||||
const updateUI = (role: string, chunk: string) => {
|
||||
setChatHistory((prevHistory) => {
|
||||
const lastMessage = prevHistory[prevHistory.length - 1];
|
||||
|
||||
if (lastMessage && lastMessage.role === role) {
|
||||
return [
|
||||
...prevHistory.slice(0, prevHistory.length - 1),
|
||||
{ role, content: lastMessage.content + chunk },
|
||||
];
|
||||
} else {
|
||||
return [...prevHistory, { role, content: chunk }];
|
||||
}
|
||||
});
|
||||
};
|
||||
|
||||
const handleSendMessage = async () => {
|
||||
if (inputMessage.trim() === "") return;
|
||||
|
||||
if (!accessToken || !token || !userRole || !userID) {
|
||||
return;
|
||||
}
|
||||
|
||||
setChatHistory((prevHistory) => [
|
||||
...prevHistory,
|
||||
{ role: "user", content: inputMessage },
|
||||
]);
|
||||
|
||||
try {
|
||||
if (selectedModel) {
|
||||
await generateModelResponse(inputMessage, (chunk) => updateUI("assistant", chunk), selectedModel, accessToken);
|
||||
}
|
||||
} catch (error) {
|
||||
console.error("Error fetching model response", error);
|
||||
updateUI("assistant", "Error fetching model response");
|
||||
}
|
||||
|
||||
setInputMessage("");
|
||||
};
|
||||
|
||||
return (
|
||||
<div style={{ width: "100%", position: "relative" }}>
|
||||
<Grid className="gap-2 p-10 h-[75vh] w-full">
|
||||
<Card>
|
||||
<TabGroup>
|
||||
<TabList className="mt-4">
|
||||
<Tab>Chat</Tab>
|
||||
<Tab>API Reference</Tab>
|
||||
</TabList>
|
||||
|
||||
<TabPanels>
|
||||
<TabPanel>
|
||||
<div>
|
||||
<label>Select Model:</label>
|
||||
<select
|
||||
value={selectedModel || ""}
|
||||
onChange={(e) => setSelectedModel(e.target.value)}
|
||||
>
|
||||
{/* Populate dropdown options from available models */}
|
||||
{modelInfo?.data.map((element: { model_name: string }) => (
|
||||
<option key={element.model_name} value={element.model_name}>
|
||||
{element.model_name}
|
||||
</option>
|
||||
))}
|
||||
</select>
|
||||
</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>{`${message.role}: ${message.content}`}</TableCell>
|
||||
</TableRow>
|
||||
))}
|
||||
</TableBody>
|
||||
</Table>
|
||||
<div className="mt-3" style={{ position: "absolute", bottom: 5, width: "95%" }}>
|
||||
<div className="flex">
|
||||
<input
|
||||
type="text"
|
||||
value={inputMessage}
|
||||
onChange={(e) => setInputMessage(e.target.value)}
|
||||
className="flex-1 p-2 border rounded-md mr-2"
|
||||
placeholder="Type your message..."
|
||||
/>
|
||||
<button onClick={handleSendMessage} className="p-2 bg-blue-500 text-white rounded-md">
|
||||
Send
|
||||
</button>
|
||||
</div>
|
||||
</div>
|
||||
</TabPanel>
|
||||
<TabPanel>
|
||||
<TabGroup>
|
||||
<TabList>
|
||||
<Tab>OpenAI Python SDK</Tab>
|
||||
<Tab>LlamaIndex</Tab>
|
||||
<Tab>Langchain Py</Tab>
|
||||
</TabList>
|
||||
<TabPanels>
|
||||
<TabPanel>
|
||||
|
||||
<SyntaxHighlighter language="python">
|
||||
{`
|
||||
import openai
|
||||
client = openai.OpenAI(
|
||||
api_key="your_api_key",
|
||||
base_url="http://0.0.0.0:4000" # proxy base url
|
||||
)
|
||||
|
||||
response = client.chat.completions.create(
|
||||
model="gpt-3.5-turbo", # model to use from Models Tab
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "this is a test request, write a short poem"
|
||||
}
|
||||
],
|
||||
extra_body={
|
||||
"metadata": {
|
||||
"generation_name": "ishaan-generation-openai-client",
|
||||
"generation_id": "openai-client-gen-id22",
|
||||
"trace_id": "openai-client-trace-id22",
|
||||
"trace_user_id": "openai-client-user-id2"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
print(response)
|
||||
`}
|
||||
</SyntaxHighlighter>
|
||||
</TabPanel>
|
||||
<TabPanel>
|
||||
|
||||
<SyntaxHighlighter language="python">
|
||||
{`
|
||||
import os, dotenv
|
||||
|
||||
from llama_index.llms import AzureOpenAI
|
||||
from llama_index.embeddings import AzureOpenAIEmbedding
|
||||
from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
|
||||
|
||||
llm = AzureOpenAI(
|
||||
engine="azure-gpt-3.5", # model_name on litellm proxy
|
||||
temperature=0.0,
|
||||
azure_endpoint="http://0.0.0.0:4000", # litellm proxy endpoint
|
||||
api_key="sk-1234", # litellm proxy API Key
|
||||
api_version="2023-07-01-preview",
|
||||
)
|
||||
|
||||
embed_model = AzureOpenAIEmbedding(
|
||||
deployment_name="azure-embedding-model",
|
||||
azure_endpoint="http://0.0.0.0:4000",
|
||||
api_key="sk-1234",
|
||||
api_version="2023-07-01-preview",
|
||||
)
|
||||
|
||||
|
||||
documents = SimpleDirectoryReader("llama_index_data").load_data()
|
||||
service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
|
||||
index = VectorStoreIndex.from_documents(documents, service_context=service_context)
|
||||
|
||||
query_engine = index.as_query_engine()
|
||||
response = query_engine.query("What did the author do growing up?")
|
||||
print(response)
|
||||
|
||||
`}
|
||||
</SyntaxHighlighter>
|
||||
</TabPanel>
|
||||
<TabPanel>
|
||||
|
||||
<SyntaxHighlighter language="python">
|
||||
{`
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
from langchain.prompts.chat import (
|
||||
ChatPromptTemplate,
|
||||
HumanMessagePromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
)
|
||||
from langchain.schema import HumanMessage, SystemMessage
|
||||
|
||||
chat = ChatOpenAI(
|
||||
openai_api_base="http://0.0.0.0:8000",
|
||||
model = "gpt-3.5-turbo",
|
||||
temperature=0.1,
|
||||
extra_body={
|
||||
"metadata": {
|
||||
"generation_name": "ishaan-generation-langchain-client",
|
||||
"generation_id": "langchain-client-gen-id22",
|
||||
"trace_id": "langchain-client-trace-id22",
|
||||
"trace_user_id": "langchain-client-user-id2"
|
||||
}
|
||||
}
|
||||
)
|
||||
|
||||
messages = [
|
||||
SystemMessage(
|
||||
content="You are a helpful assistant that im using to make a test request to."
|
||||
),
|
||||
HumanMessage(
|
||||
content="test from litellm. tell me why it's amazing in 1 sentence"
|
||||
),
|
||||
]
|
||||
response = chat(messages)
|
||||
|
||||
print(response)
|
||||
|
||||
`}
|
||||
</SyntaxHighlighter>
|
||||
</TabPanel>
|
||||
</TabPanels>
|
||||
</TabGroup>
|
||||
|
||||
</TabPanel>
|
||||
</TabPanels>
|
||||
</TabGroup>
|
||||
</Card>
|
||||
</Grid>
|
||||
</div>
|
||||
);
|
||||
};
|
||||
|
||||
|
||||
|
||||
export default ChatUI;
|
||||
@@ -23,7 +23,10 @@ const Sidebar: React.FC<SidebarProps> = ({ setPage }) => {
|
||||
<Menu.Item key="2" onClick={() => setPage("models")}>
|
||||
Models
|
||||
</Menu.Item>
|
||||
<Menu.Item key="3" onClick={() => setPage("usage")}>
|
||||
<Menu.Item key="3" onClick={() => setPage("llm-playground")}>
|
||||
Chat UI
|
||||
</Menu.Item>
|
||||
<Menu.Item key="4" onClick={() => setPage("usage")}>
|
||||
Usage
|
||||
</Menu.Item>
|
||||
</Menu>
|
||||
|
||||
Reference in New Issue
Block a user