forked from phoenix/litellm-mirror
Merge pull request #3849 from BerriAI/litellm_model_hub
[Feat] Model Hub
This commit is contained in:
Ishaan Jaff
GitHub
commit
39834aef62
28 changed files with 437 additions and 25 deletions
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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-e85084d25f9ae5e4.js" crossorigin=""/><script src="/ui/_next/static/chunks/fd9d1056-f960ab1e6d32b002.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/69-04708d7d4a17c1ee.js" async="" crossorigin=""></script><script src="/ui/_next/static/chunks/main-app-9b4fb13a7db53edf.js" async="" crossorigin=""></script><title>LiteLLM Dashboard</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-e85084d25f9ae5e4.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/5d93d4a9fa59d72f.css\",\"style\",{\"crossOrigin\":\"\"}]\n0:\"$L3\"\n"])</script><script>self.__next_f.push([1,"4:I[47690,[],\"\"]\n6:I[77831,[],\"\"]\n7:I[39712,[\"936\",\"static/chunks/2f6dbc85-052c4579f80d66ae.js\",\"608\",\"static/chunks/608-d128caa3cfe973c1.js\",\"931\",\"static/chunks/app/page-e266cb0126026d40.js\"],\"\"]\n8:I[5613,[],\"\"]\n9:I[31778,[],\"\"]\nb:I[48955,[],\"\"]\nc:[]\n"])</script><script>self.__next_f.push([1,"3:[[[\"$\",\"link\",\"0\",{\"rel\":\"stylesheet\",\"href\":\"/ui/_next/static/css/5d93d4a9fa59d72f.css\",\"precedence\":\"next\",\"crossOrigin\":\"\"}]],[\"$\",\"$L4\",null,{\"buildId\":\"dYIEEO-62OCgyckEhgBd-\",\"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 Dashboard\"}],[\"$\",\"meta\",\"3\",{\"name\":\"description\",\"content\":\"LiteLLM Proxy Admin UI\"}],[\"$\",\"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 Dashboard"}],["$","meta","3",{"name":"description","content":"LiteLLM Proxy Admin UI"}],["$","link","4",{"rel":"icon","href":"/ui/favicon.ico","type":"image/x-icon","sizes":"16x16"}],["$","meta","5",{"name":"next-size-adjust"}]]
|
||||
1:null
|
||||
|
|
|
|||
|
|
@ -10,6 +10,7 @@ import AdminPanel from "@/components/admins";
|
|||
import Settings from "@/components/settings";
|
||||
import GeneralSettings from "@/components/general_settings";
|
||||
import BudgetPanel from "@/components/budgets/budget_panel";
|
||||
import ModelHub from "@/components/model_hub";
|
||||
import APIRef from "@/components/api_ref";
|
||||
import ChatUI from "@/components/chat_ui";
|
||||
import Sidebar from "../components/leftnav";
|
||||
|
|
@ -193,7 +194,17 @@ const CreateKeyPage = () => {
|
|||
accessToken={accessToken}
|
||||
modelData={modelData}
|
||||
/>
|
||||
) : (
|
||||
) : page == "model-hub" ? (
|
||||
<ModelHub
|
||||
userID={userID}
|
||||
userRole={userRole}
|
||||
token={token}
|
||||
accessToken={accessToken}
|
||||
keys={keys}
|
||||
premiumUser={premiumUser}
|
||||
/>
|
||||
)
|
||||
: (
|
||||
<Usage
|
||||
userID={userID}
|
||||
userRole={userRole}
|
||||
|
|
|
|||
|
|
@ -109,6 +109,9 @@ const Sidebar: React.FC<SidebarProps> = ({
|
|||
<Menu.Item key="12" onClick={() => setPage("api_ref")}>
|
||||
<Text>API Reference</Text>
|
||||
</Menu.Item>
|
||||
<Menu.Item key="14" onClick={() => setPage("model-hub")}>
|
||||
<Text>Model Hub</Text>
|
||||
</Menu.Item>
|
||||
</Menu>
|
||||
</Sider>
|
||||
</Layout>
|
||||
|
|
|
|||
358
ui/litellm-dashboard/src/components/model_hub.tsx
Normal file
358
ui/litellm-dashboard/src/components/model_hub.tsx
Normal file
|
|
@ -0,0 +1,358 @@
|
|||
import React, { useEffect, useState } from 'react';
|
||||
|
||||
import { modelHubCall } from "./networking";
|
||||
|
||||
import { Card, Text, Title, Grid, Button, Badge, Tab,
|
||||
TabGroup,
|
||||
TabList,
|
||||
TabPanel,
|
||||
TabPanels, } from "@tremor/react";
|
||||
|
||||
import { RightOutlined, CopyOutlined } from '@ant-design/icons';
|
||||
|
||||
import { Modal, Tooltip } from 'antd';
|
||||
import { Prism as SyntaxHighlighter } from "react-syntax-highlighter";
|
||||
|
||||
|
||||
|
||||
interface ModelHubProps {
|
||||
userID: string | null;
|
||||
userRole: string | null;
|
||||
token: string | null;
|
||||
accessToken: string | null;
|
||||
keys: any; // Replace with the appropriate type for 'keys' prop
|
||||
premiumUser: boolean;
|
||||
|
||||
}
|
||||
|
||||
interface ModelInfo {
|
||||
model_group: string;
|
||||
mode: string;
|
||||
supports_function_calling: boolean;
|
||||
supports_vision: boolean;
|
||||
max_input_tokens?: number;
|
||||
max_output_tokens?: number;
|
||||
|
||||
// Add other properties if needed
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
const ModelHub: React.FC<ModelHubProps> = ({
|
||||
|
||||
userID,
|
||||
|
||||
userRole,
|
||||
|
||||
token,
|
||||
|
||||
accessToken,
|
||||
|
||||
keys,
|
||||
|
||||
premiumUser,
|
||||
|
||||
}) => {
|
||||
|
||||
const [modelHubData, setModelHubData] = useState<ModelInfo[] | null>(null);
|
||||
const [isModalVisible, setIsModalVisible] = useState(false);
|
||||
const [selectedModel, setSelectedModel] = useState<null | ModelInfo>(null);
|
||||
|
||||
|
||||
useEffect(() => {
|
||||
|
||||
if (!accessToken || !token || !userRole || !userID) {
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
|
||||
const fetchData = async () => {
|
||||
|
||||
try {
|
||||
|
||||
const _modelHubData = await modelHubCall(accessToken, userID, userRole);
|
||||
|
||||
console.log("ModelHubData:", _modelHubData);
|
||||
|
||||
setModelHubData(_modelHubData.data);
|
||||
|
||||
} catch (error) {
|
||||
|
||||
console.error("There was an error fetching the model data", error);
|
||||
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
fetchData();
|
||||
|
||||
}, [accessToken, token, userRole, userID]);
|
||||
|
||||
|
||||
|
||||
const showModal = (model: ModelInfo) => {
|
||||
|
||||
setSelectedModel(model);
|
||||
|
||||
setIsModalVisible(true);
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
const handleOk = () => {
|
||||
|
||||
setIsModalVisible(false);
|
||||
|
||||
setSelectedModel(null);
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
const handleCancel = () => {
|
||||
|
||||
setIsModalVisible(false);
|
||||
|
||||
setSelectedModel(null);
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
const copyToClipboard = (text: string) => {
|
||||
|
||||
navigator.clipboard.writeText(text);
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
return (
|
||||
|
||||
<div>
|
||||
|
||||
<div className="w-full m-2 mt-2 p-8">
|
||||
|
||||
<div className="relative w-full">
|
||||
|
||||
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
<div className='flex items-center'>
|
||||
|
||||
<Title className='ml-8 text-center '>Model Hub</Title>
|
||||
<Button className='ml-4'>
|
||||
<a href="https://forms.gle/W3U4PZpJGFHWtHyA9" target="_blank">
|
||||
✨ Share
|
||||
</a>
|
||||
|
||||
|
||||
</Button>
|
||||
|
||||
</div>
|
||||
|
||||
|
||||
<div className="grid grid-cols-2 gap-6 sm:grid-cols-3 lg:grid-cols-4">
|
||||
|
||||
|
||||
{modelHubData && modelHubData.map((model: ModelInfo) => (
|
||||
|
||||
<Card
|
||||
|
||||
key={model.model_group}
|
||||
|
||||
className="mt-5 mx-8"
|
||||
|
||||
>
|
||||
|
||||
|
||||
|
||||
<pre className='flex justify-between'>
|
||||
|
||||
|
||||
<Title>{model.model_group}</Title>
|
||||
<Tooltip title={model.model_group}>
|
||||
|
||||
<CopyOutlined onClick={() => copyToClipboard(model.model_group)} style={{ cursor: 'pointer', marginRight: '10px' }} />
|
||||
|
||||
</Tooltip>
|
||||
|
||||
</pre>
|
||||
|
||||
<div className='my-5'>
|
||||
|
||||
<Text>Mode: {model.mode}</Text>
|
||||
<Text>Supports Function Calling: {model?.supports_function_calling == true ? "Yes" : "No"}</Text>
|
||||
<Text>Supports Vision: {model?.supports_vision == true ? "Yes" : "No"}</Text>
|
||||
<Text>Max Input Tokens: {model?.max_input_tokens ? model?.max_input_tokens : "N/A"}</Text>
|
||||
<Text>Max Output Tokens: {model?.max_output_tokens ? model?.max_output_tokens : "N/A"}</Text>
|
||||
|
||||
</div>
|
||||
|
||||
<div style={{ marginTop: 'auto', textAlign: 'right' }}>
|
||||
|
||||
|
||||
|
||||
<a href="#" onClick={() => showModal(model)} style={{ color: '#1890ff', fontSize: 'smaller' }}>
|
||||
|
||||
View more <RightOutlined />
|
||||
|
||||
</a>
|
||||
|
||||
</div>
|
||||
|
||||
</Card>
|
||||
|
||||
))}
|
||||
|
||||
</div>
|
||||
|
||||
</div>
|
||||
|
||||
<Modal
|
||||
|
||||
title="Model Usage"
|
||||
width={800}
|
||||
|
||||
visible={isModalVisible}
|
||||
footer={null}
|
||||
|
||||
onOk={handleOk}
|
||||
|
||||
onCancel={handleCancel}
|
||||
|
||||
>
|
||||
|
||||
{selectedModel && (
|
||||
|
||||
<div>
|
||||
|
||||
<p><strong>Model Name:</strong> {selectedModel.model_group}</p>
|
||||
|
||||
<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" # LiteLLM Proxy is OpenAI compatible, Read More: https://docs.litellm.ai/docs/proxy/user_keys
|
||||
)
|
||||
|
||||
response = client.chat.completions.create(
|
||||
model="${selectedModel.model_group}", # model to send to the proxy
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": "this is a test request, write a short poem"
|
||||
}
|
||||
]
|
||||
)
|
||||
|
||||
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="${selectedModel.model_group}", # model_name on litellm proxy
|
||||
temperature=0.0,
|
||||
azure_endpoint="http://0.0.0.0:4000", # litellm proxy endpoint
|
||||
api_key="sk-1234", # litellm proxy API Key
|
||||
api_version="2023-07-01-preview",
|
||||
)
|
||||
|
||||
embed_model = AzureOpenAIEmbedding(
|
||||
deployment_name="azure-embedding-model",
|
||||
azure_endpoint="http://0.0.0.0:4000",
|
||||
api_key="sk-1234",
|
||||
api_version="2023-07-01-preview",
|
||||
)
|
||||
|
||||
|
||||
documents = SimpleDirectoryReader("llama_index_data").load_data()
|
||||
service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
|
||||
index = VectorStoreIndex.from_documents(documents, service_context=service_context)
|
||||
|
||||
query_engine = index.as_query_engine()
|
||||
response = query_engine.query("What did the author do growing up?")
|
||||
print(response)
|
||||
|
||||
`}
|
||||
</SyntaxHighlighter>
|
||||
</TabPanel>
|
||||
<TabPanel>
|
||||
<SyntaxHighlighter language="python">
|
||||
{`
|
||||
from langchain.chat_models import ChatOpenAI
|
||||
from langchain.prompts.chat import (
|
||||
ChatPromptTemplate,
|
||||
HumanMessagePromptTemplate,
|
||||
SystemMessagePromptTemplate,
|
||||
)
|
||||
from langchain.schema import HumanMessage, SystemMessage
|
||||
|
||||
chat = ChatOpenAI(
|
||||
openai_api_base="http://0.0.0.0:4000",
|
||||
model = "${selectedModel.model_group}",
|
||||
temperature=0.1
|
||||
)
|
||||
|
||||
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>
|
||||
|
||||
{/* <p><strong>Additional Params:</strong> {JSON.stringify(selectedModel.litellm_params)}</p> */}
|
||||
|
||||
{/* Add other model details here */}
|
||||
|
||||
</div>
|
||||
|
||||
)}
|
||||
|
||||
</Modal>
|
||||
|
||||
</div>
|
||||
|
||||
);
|
||||
|
||||
};
|
||||
|
||||
|
||||
|
||||
export default ModelHub;
|
||||
|
|
@ -579,6 +579,46 @@ export const modelInfoCall = async (
|
|||
}
|
||||
};
|
||||
|
||||
|
||||
export const modelHubCall = async (
|
||||
accessToken: String,
|
||||
userID: String,
|
||||
userRole: String
|
||||
) => {
|
||||
/**
|
||||
* Get all models on proxy
|
||||
*/
|
||||
try {
|
||||
let url = proxyBaseUrl ? `${proxyBaseUrl}/model_group/info` : `/model_group/info`;
|
||||
|
||||
//message.info("Requesting model data");
|
||||
const response = await fetch(url, {
|
||||
method: "GET",
|
||||
headers: {
|
||||
Authorization: `Bearer ${accessToken}`,
|
||||
"Content-Type": "application/json",
|
||||
},
|
||||
});
|
||||
|
||||
if (!response.ok) {
|
||||
const errorData = await response.text();
|
||||
message.error(errorData, 10);
|
||||
throw new Error("Network response was not ok");
|
||||
}
|
||||
|
||||
const data = await response.json();
|
||||
console.log("modelHubCall:", data);
|
||||
//message.info("Received model data");
|
||||
return data;
|
||||
// Handle success - you might want to update some state or UI based on the created key
|
||||
} catch (error) {
|
||||
console.error("Failed to create key:", error);
|
||||
throw error;
|
||||
}
|
||||
};
|
||||
|
||||
|
||||
|
||||
export const modelMetricsCall = async (
|
||||
accessToken: String,
|
||||
userID: String,
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue