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feat/model
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@ -159,6 +159,7 @@ Perplexica runs on Next.js and handles all API requests. It works right away on
|
||||
|
||||
[](https://usw.sealos.io/?openapp=system-template%3FtemplateName%3Dperplexica)
|
||||
[](https://repocloud.io/details/?app_id=267)
|
||||
[](https://template.run.claw.cloud/?referralCode=U11MRQ8U9RM4&openapp=system-fastdeploy%3FtemplateName%3Dperplexica)
|
||||
|
||||
## Upcoming Features
|
||||
|
||||
|
@ -33,6 +33,7 @@ The API accepts a JSON object in the request body, where you define the focus mo
|
||||
["human", "Hi, how are you?"],
|
||||
["assistant", "I am doing well, how can I help you today?"]
|
||||
],
|
||||
"systemInstructions": "Focus on providing technical details about Perplexica's architecture.",
|
||||
"stream": false
|
||||
}
|
||||
```
|
||||
@ -63,6 +64,8 @@ The API accepts a JSON object in the request body, where you define the focus mo
|
||||
|
||||
- **`query`** (string, required): The search query or question.
|
||||
|
||||
- **`systemInstructions`** (string, optional): Custom instructions provided by the user to guide the AI's response. These instructions are treated as user preferences and have lower priority than the system's core instructions. For example, you can specify a particular writing style, format, or focus area.
|
||||
|
||||
- **`history`** (array, optional): An array of message pairs representing the conversation history. Each pair consists of a role (either 'human' or 'assistant') and the message content. This allows the system to use the context of the conversation to refine results. Example:
|
||||
|
||||
```json
|
||||
|
11024
package-lock.json
generated
Normal file
11024
package-lock.json
generated
Normal file
File diff suppressed because it is too large
Load Diff
@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "perplexica-frontend",
|
||||
"version": "1.10.1",
|
||||
"version": "1.10.2",
|
||||
"license": "MIT",
|
||||
"author": "ItzCrazyKns",
|
||||
"scripts": {
|
||||
@ -20,6 +20,7 @@
|
||||
"@langchain/core": "^0.3.42",
|
||||
"@langchain/google-genai": "^0.1.12",
|
||||
"@langchain/openai": "^0.0.25",
|
||||
"@langchain/ollama": "^0.2.0",
|
||||
"@langchain/textsplitters": "^0.1.0",
|
||||
"@tailwindcss/typography": "^0.5.12",
|
||||
"@xenova/transformers": "^2.17.2",
|
||||
|
@ -22,5 +22,11 @@ MODEL_NAME = ""
|
||||
[MODELS.OLLAMA]
|
||||
API_URL = "" # Ollama API URL - http://host.docker.internal:11434
|
||||
|
||||
[MODELS.DEEPSEEK]
|
||||
API_KEY = ""
|
||||
|
||||
[MODELS.LM_STUDIO]
|
||||
API_URL = "" # LM Studio API URL - http://host.docker.internal:1234
|
||||
|
||||
[API_ENDPOINTS]
|
||||
SEARXNG = "" # SearxNG API URL - http://localhost:32768
|
@ -20,6 +20,7 @@ import {
|
||||
getCustomOpenaiApiUrl,
|
||||
getCustomOpenaiModelName,
|
||||
} from '@/lib/config';
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
import { searchHandlers } from '@/lib/search';
|
||||
|
||||
export const runtime = 'nodejs';
|
||||
@ -34,6 +35,7 @@ type Message = {
|
||||
type ChatModel = {
|
||||
provider: string;
|
||||
name: string;
|
||||
ollamaContextWindow?: number;
|
||||
};
|
||||
|
||||
type EmbeddingModel = {
|
||||
@ -232,6 +234,11 @@ export const POST = async (req: Request) => {
|
||||
}) as unknown as BaseChatModel;
|
||||
} else if (chatModelProvider && chatModel) {
|
||||
llm = chatModel.model;
|
||||
|
||||
// Set context window size for Ollama models
|
||||
if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
|
||||
llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
|
||||
}
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
@ -7,6 +7,8 @@ import {
|
||||
getGroqApiKey,
|
||||
getOllamaApiEndpoint,
|
||||
getOpenaiApiKey,
|
||||
getDeepseekApiKey,
|
||||
getLMStudioApiEndpoint,
|
||||
updateConfig,
|
||||
} from '@/lib/config';
|
||||
import {
|
||||
@ -50,9 +52,11 @@ export const GET = async (req: Request) => {
|
||||
|
||||
config['openaiApiKey'] = getOpenaiApiKey();
|
||||
config['ollamaApiUrl'] = getOllamaApiEndpoint();
|
||||
config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
|
||||
config['anthropicApiKey'] = getAnthropicApiKey();
|
||||
config['groqApiKey'] = getGroqApiKey();
|
||||
config['geminiApiKey'] = getGeminiApiKey();
|
||||
config['deepseekApiKey'] = getDeepseekApiKey();
|
||||
config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
|
||||
config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
|
||||
config['customOpenaiModelName'] = getCustomOpenaiModelName();
|
||||
@ -88,6 +92,12 @@ export const POST = async (req: Request) => {
|
||||
OLLAMA: {
|
||||
API_URL: config.ollamaApiUrl,
|
||||
},
|
||||
DEEPSEEK: {
|
||||
API_KEY: config.deepseekApiKey,
|
||||
},
|
||||
LM_STUDIO: {
|
||||
API_URL: config.lmStudioApiUrl,
|
||||
},
|
||||
CUSTOM_OPENAI: {
|
||||
API_URL: config.customOpenaiApiUrl,
|
||||
API_KEY: config.customOpenaiApiKey,
|
||||
|
@ -7,11 +7,13 @@ import {
|
||||
import { getAvailableChatModelProviders } from '@/lib/providers';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
|
||||
interface ChatModel {
|
||||
provider: string;
|
||||
model: string;
|
||||
ollamaContextWindow?: number;
|
||||
}
|
||||
|
||||
interface ImageSearchBody {
|
||||
@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
|
||||
}) as unknown as BaseChatModel;
|
||||
} else if (chatModelProvider && chatModel) {
|
||||
llm = chatModel.model;
|
||||
// Set context window size for Ollama models
|
||||
if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
|
||||
llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
|
||||
}
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
@ -13,12 +13,14 @@ import {
|
||||
getCustomOpenaiModelName,
|
||||
} from '@/lib/config';
|
||||
import { searchHandlers } from '@/lib/search';
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
|
||||
interface chatModel {
|
||||
provider: string;
|
||||
name: string;
|
||||
customOpenAIKey?: string;
|
||||
customOpenAIBaseURL?: string;
|
||||
ollamaContextWindow?: number;
|
||||
}
|
||||
|
||||
interface embeddingModel {
|
||||
@ -34,6 +36,7 @@ interface ChatRequestBody {
|
||||
query: string;
|
||||
history: Array<[string, string]>;
|
||||
stream?: boolean;
|
||||
systemInstructions?: string;
|
||||
}
|
||||
|
||||
export const POST = async (req: Request) => {
|
||||
@ -96,6 +99,10 @@ export const POST = async (req: Request) => {
|
||||
.model as unknown as BaseChatModel | undefined;
|
||||
}
|
||||
|
||||
if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
|
||||
llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
|
||||
}
|
||||
|
||||
if (
|
||||
embeddingModelProviders[embeddingModelProvider] &&
|
||||
embeddingModelProviders[embeddingModelProvider][embeddingModel]
|
||||
@ -125,7 +132,7 @@ export const POST = async (req: Request) => {
|
||||
embeddings,
|
||||
body.optimizationMode,
|
||||
[],
|
||||
'',
|
||||
body.systemInstructions || '',
|
||||
);
|
||||
|
||||
if (!body.stream) {
|
||||
|
@ -8,10 +8,12 @@ import { getAvailableChatModelProviders } from '@/lib/providers';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
|
||||
interface ChatModel {
|
||||
provider: string;
|
||||
model: string;
|
||||
ollamaContextWindow?: number;
|
||||
}
|
||||
|
||||
interface SuggestionsGenerationBody {
|
||||
@ -57,6 +59,10 @@ export const POST = async (req: Request) => {
|
||||
}) as unknown as BaseChatModel;
|
||||
} else if (chatModelProvider && chatModel) {
|
||||
llm = chatModel.model;
|
||||
// Set context window size for Ollama models
|
||||
if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
|
||||
llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
|
||||
}
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
@ -7,11 +7,13 @@ import {
|
||||
import { getAvailableChatModelProviders } from '@/lib/providers';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { AIMessage, BaseMessage, HumanMessage } from '@langchain/core/messages';
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
|
||||
interface ChatModel {
|
||||
provider: string;
|
||||
model: string;
|
||||
ollamaContextWindow?: number;
|
||||
}
|
||||
|
||||
interface VideoSearchBody {
|
||||
@ -58,6 +60,10 @@ export const POST = async (req: Request) => {
|
||||
}) as unknown as BaseChatModel;
|
||||
} else if (chatModelProvider && chatModel) {
|
||||
llm = chatModel.model;
|
||||
// Set context window size for Ollama models
|
||||
if (llm instanceof ChatOllama && body.chatModel?.provider === 'ollama') {
|
||||
llm.numCtx = body.chatModel.ollamaContextWindow || 2048;
|
||||
}
|
||||
}
|
||||
|
||||
if (!llm) {
|
||||
|
@ -7,6 +7,7 @@ import { Switch } from '@headlessui/react';
|
||||
import ThemeSwitcher from '@/components/theme/Switcher';
|
||||
import { ImagesIcon, VideoIcon } from 'lucide-react';
|
||||
import Link from 'next/link';
|
||||
import { PROVIDER_METADATA } from '@/lib/providers';
|
||||
|
||||
interface SettingsType {
|
||||
chatModelProviders: {
|
||||
@ -20,9 +21,12 @@ interface SettingsType {
|
||||
anthropicApiKey: string;
|
||||
geminiApiKey: string;
|
||||
ollamaApiUrl: string;
|
||||
lmStudioApiUrl: string;
|
||||
deepseekApiKey: string;
|
||||
customOpenaiApiKey: string;
|
||||
customOpenaiApiUrl: string;
|
||||
customOpenaiModelName: string;
|
||||
ollamaContextWindow: number;
|
||||
}
|
||||
|
||||
interface InputProps extends React.InputHTMLAttributes<HTMLInputElement> {
|
||||
@ -145,6 +149,11 @@ const Page = () => {
|
||||
const [automaticVideoSearch, setAutomaticVideoSearch] = useState(false);
|
||||
const [systemInstructions, setSystemInstructions] = useState<string>('');
|
||||
const [savingStates, setSavingStates] = useState<Record<string, boolean>>({});
|
||||
const [contextWindowSize, setContextWindowSize] = useState(2048);
|
||||
const [isCustomContextWindow, setIsCustomContextWindow] = useState(false);
|
||||
const predefinedContextSizes = [
|
||||
1024, 2048, 3072, 4096, 8192, 16384, 32768, 65536, 131072,
|
||||
];
|
||||
|
||||
useEffect(() => {
|
||||
const fetchConfig = async () => {
|
||||
@ -156,6 +165,7 @@ const Page = () => {
|
||||
});
|
||||
|
||||
const data = (await res.json()) as SettingsType;
|
||||
|
||||
setConfig(data);
|
||||
|
||||
const chatModelProvidersKeys = Object.keys(data.chatModelProviders || {});
|
||||
@ -204,6 +214,13 @@ const Page = () => {
|
||||
setAutomaticVideoSearch(
|
||||
localStorage.getItem('autoVideoSearch') === 'true',
|
||||
);
|
||||
const storedContextWindow = parseInt(
|
||||
localStorage.getItem('ollamaContextWindow') ?? '2048',
|
||||
);
|
||||
setContextWindowSize(storedContextWindow);
|
||||
setIsCustomContextWindow(
|
||||
!predefinedContextSizes.includes(storedContextWindow),
|
||||
);
|
||||
|
||||
setSystemInstructions(localStorage.getItem('systemInstructions')!);
|
||||
|
||||
@ -363,6 +380,8 @@ const Page = () => {
|
||||
localStorage.setItem('embeddingModelProvider', value);
|
||||
} else if (key === 'embeddingModel') {
|
||||
localStorage.setItem('embeddingModel', value);
|
||||
} else if (key === 'ollamaContextWindow') {
|
||||
localStorage.setItem('ollamaContextWindow', value.toString());
|
||||
} else if (key === 'systemInstructions') {
|
||||
localStorage.setItem('systemInstructions', value);
|
||||
}
|
||||
@ -547,6 +566,7 @@ const Page = () => {
|
||||
(provider) => ({
|
||||
value: provider,
|
||||
label:
|
||||
(PROVIDER_METADATA as any)[provider]?.displayName ||
|
||||
provider.charAt(0).toUpperCase() +
|
||||
provider.slice(1),
|
||||
}),
|
||||
@ -595,6 +615,78 @@ const Page = () => {
|
||||
];
|
||||
})()}
|
||||
/>
|
||||
{selectedChatModelProvider === 'ollama' && (
|
||||
<div className="flex flex-col space-y-1">
|
||||
<p className="text-black/70 dark:text-white/70 text-sm">
|
||||
Chat Context Window Size
|
||||
</p>
|
||||
<Select
|
||||
value={
|
||||
isCustomContextWindow
|
||||
? 'custom'
|
||||
: contextWindowSize.toString()
|
||||
}
|
||||
onChange={(e) => {
|
||||
const value = e.target.value;
|
||||
if (value === 'custom') {
|
||||
setIsCustomContextWindow(true);
|
||||
} else {
|
||||
setIsCustomContextWindow(false);
|
||||
const numValue = parseInt(value);
|
||||
setContextWindowSize(numValue);
|
||||
setConfig((prev) => ({
|
||||
...prev!,
|
||||
ollamaContextWindow: numValue,
|
||||
}));
|
||||
saveConfig('ollamaContextWindow', numValue);
|
||||
}
|
||||
}}
|
||||
options={[
|
||||
...predefinedContextSizes.map((size) => ({
|
||||
value: size.toString(),
|
||||
label: `${size.toLocaleString()} tokens`,
|
||||
})),
|
||||
{ value: 'custom', label: 'Custom...' },
|
||||
]}
|
||||
/>
|
||||
{isCustomContextWindow && (
|
||||
<div className="mt-2">
|
||||
<Input
|
||||
type="number"
|
||||
min={512}
|
||||
value={contextWindowSize}
|
||||
placeholder="Custom context window size (minimum 512)"
|
||||
isSaving={savingStates['ollamaContextWindow']}
|
||||
onChange={(e) => {
|
||||
// Allow any value to be typed
|
||||
const value =
|
||||
parseInt(e.target.value) ||
|
||||
contextWindowSize;
|
||||
setContextWindowSize(value);
|
||||
}}
|
||||
onSave={(value) => {
|
||||
// Validate only when saving
|
||||
const numValue = Math.max(
|
||||
512,
|
||||
parseInt(value) || 2048,
|
||||
);
|
||||
setContextWindowSize(numValue);
|
||||
setConfig((prev) => ({
|
||||
...prev!,
|
||||
ollamaContextWindow: numValue,
|
||||
}));
|
||||
saveConfig('ollamaContextWindow', numValue);
|
||||
}}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
<p className="text-xs text-black/60 dark:text-white/60 mt-0.5">
|
||||
{isCustomContextWindow
|
||||
? 'Adjust the context window size for Ollama models (minimum 512 tokens)'
|
||||
: 'Adjust the context window size for Ollama models'}
|
||||
</p>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
@ -689,6 +781,7 @@ const Page = () => {
|
||||
(provider) => ({
|
||||
value: provider,
|
||||
label:
|
||||
(PROVIDER_METADATA as any)[provider]?.displayName ||
|
||||
provider.charAt(0).toUpperCase() +
|
||||
provider.slice(1),
|
||||
}),
|
||||
@ -838,6 +931,44 @@ const Page = () => {
|
||||
onSave={(value) => saveConfig('geminiApiKey', value)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="flex flex-col space-y-1">
|
||||
<p className="text-black/70 dark:text-white/70 text-sm">
|
||||
Deepseek API Key
|
||||
</p>
|
||||
<Input
|
||||
type="text"
|
||||
placeholder="Deepseek API Key"
|
||||
value={config.deepseekApiKey}
|
||||
isSaving={savingStates['deepseekApiKey']}
|
||||
onChange={(e) => {
|
||||
setConfig((prev) => ({
|
||||
...prev!,
|
||||
deepseekApiKey: e.target.value,
|
||||
}));
|
||||
}}
|
||||
onSave={(value) => saveConfig('deepseekApiKey', value)}
|
||||
/>
|
||||
</div>
|
||||
|
||||
<div className="flex flex-col space-y-1">
|
||||
<p className="text-black/70 dark:text-white/70 text-sm">
|
||||
LM Studio API URL
|
||||
</p>
|
||||
<Input
|
||||
type="text"
|
||||
placeholder="LM Studio API URL"
|
||||
value={config.lmStudioApiUrl}
|
||||
isSaving={savingStates['lmStudioApiUrl']}
|
||||
onChange={(e) => {
|
||||
setConfig((prev) => ({
|
||||
...prev!,
|
||||
lmStudioApiUrl: e.target.value,
|
||||
}));
|
||||
}}
|
||||
onSave={(value) => saveConfig('lmStudioApiUrl', value)}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
</SettingsSection>
|
||||
</div>
|
||||
|
@ -16,6 +16,8 @@ const Chat = ({
|
||||
setFileIds,
|
||||
files,
|
||||
setFiles,
|
||||
optimizationMode,
|
||||
setOptimizationMode,
|
||||
}: {
|
||||
messages: Message[];
|
||||
sendMessage: (message: string) => void;
|
||||
@ -26,6 +28,8 @@ const Chat = ({
|
||||
setFileIds: (fileIds: string[]) => void;
|
||||
files: File[];
|
||||
setFiles: (files: File[]) => void;
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
const [dividerWidth, setDividerWidth] = useState(0);
|
||||
const dividerRef = useRef<HTMLDivElement | null>(null);
|
||||
@ -99,6 +103,8 @@ const Chat = ({
|
||||
setFileIds={setFileIds}
|
||||
files={files}
|
||||
setFiles={setFiles}
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
</div>
|
||||
)}
|
||||
|
@ -287,6 +287,16 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
|
||||
const [notFound, setNotFound] = useState(false);
|
||||
|
||||
useEffect(() => {
|
||||
const savedOptimizationMode = localStorage.getItem('optimizationMode');
|
||||
|
||||
if (savedOptimizationMode !== null) {
|
||||
setOptimizationMode(savedOptimizationMode);
|
||||
} else {
|
||||
localStorage.setItem('optimizationMode', optimizationMode);
|
||||
}
|
||||
}, []);
|
||||
|
||||
useEffect(() => {
|
||||
if (
|
||||
chatId &&
|
||||
@ -327,7 +337,11 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
}
|
||||
}, [isMessagesLoaded, isConfigReady]);
|
||||
|
||||
const sendMessage = async (message: string, messageId?: string) => {
|
||||
const sendMessage = async (
|
||||
message: string,
|
||||
messageId?: string,
|
||||
options?: { rewriteIndex?: number },
|
||||
) => {
|
||||
if (loading) return;
|
||||
if (!isConfigReady) {
|
||||
toast.error('Cannot send message before the configuration is ready');
|
||||
@ -340,6 +354,20 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
let sources: Document[] | undefined = undefined;
|
||||
let recievedMessage = '';
|
||||
let added = false;
|
||||
let messageChatHistory = chatHistory;
|
||||
|
||||
if (options?.rewriteIndex !== undefined) {
|
||||
const rewriteIndex = options.rewriteIndex;
|
||||
setMessages((prev) => {
|
||||
return [...prev.slice(0, messages.length > 2 ? rewriteIndex - 1 : 0)];
|
||||
});
|
||||
|
||||
messageChatHistory = chatHistory.slice(
|
||||
0,
|
||||
messages.length > 2 ? rewriteIndex - 1 : 0,
|
||||
);
|
||||
setChatHistory(messageChatHistory);
|
||||
}
|
||||
|
||||
messageId = messageId ?? crypto.randomBytes(7).toString('hex');
|
||||
|
||||
@ -455,6 +483,9 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
}
|
||||
};
|
||||
|
||||
const ollamaContextWindow =
|
||||
localStorage.getItem('ollamaContextWindow') || '2048';
|
||||
|
||||
const res = await fetch('/api/chat', {
|
||||
method: 'POST',
|
||||
headers: {
|
||||
@ -471,10 +502,13 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
files: fileIds,
|
||||
focusMode: focusMode,
|
||||
optimizationMode: optimizationMode,
|
||||
history: chatHistory,
|
||||
history: messageChatHistory,
|
||||
chatModel: {
|
||||
name: chatModelProvider.name,
|
||||
provider: chatModelProvider.provider,
|
||||
...(chatModelProvider.provider === 'ollama' && {
|
||||
ollamaContextWindow: parseInt(ollamaContextWindow),
|
||||
}),
|
||||
},
|
||||
embeddingModel: {
|
||||
name: embeddingModelProvider.name,
|
||||
@ -512,20 +546,13 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
};
|
||||
|
||||
const rewrite = (messageId: string) => {
|
||||
const index = messages.findIndex((msg) => msg.messageId === messageId);
|
||||
|
||||
if (index === -1) return;
|
||||
|
||||
const message = messages[index - 1];
|
||||
|
||||
setMessages((prev) => {
|
||||
return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
|
||||
const messageIndex = messages.findIndex(
|
||||
(msg) => msg.messageId === messageId,
|
||||
);
|
||||
if (messageIndex == -1) return;
|
||||
sendMessage(messages[messageIndex - 1].content, messageId, {
|
||||
rewriteIndex: messageIndex,
|
||||
});
|
||||
setChatHistory((prev) => {
|
||||
return [...prev.slice(0, messages.length > 2 ? index - 1 : 0)];
|
||||
});
|
||||
|
||||
sendMessage(message.content, message.messageId);
|
||||
};
|
||||
|
||||
useEffect(() => {
|
||||
@ -570,6 +597,8 @@ const ChatWindow = ({ id }: { id?: string }) => {
|
||||
setFileIds={setFileIds}
|
||||
files={files}
|
||||
setFiles={setFiles}
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
</>
|
||||
) : (
|
||||
|
@ -48,6 +48,7 @@ const MessageBox = ({
|
||||
const [speechMessage, setSpeechMessage] = useState(message.content);
|
||||
|
||||
useEffect(() => {
|
||||
const citationRegex = /\[([^\]]+)\]/g;
|
||||
const regex = /\[(\d+)\]/g;
|
||||
let processedMessage = message.content;
|
||||
|
||||
@ -67,13 +68,36 @@ const MessageBox = ({
|
||||
) {
|
||||
setParsedMessage(
|
||||
processedMessage.replace(
|
||||
regex,
|
||||
(_, number) =>
|
||||
`<a href="${
|
||||
message.sources?.[number - 1]?.metadata?.url
|
||||
}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${number}</a>`,
|
||||
citationRegex,
|
||||
(_, capturedContent: string) => {
|
||||
const numbers = capturedContent
|
||||
.split(',')
|
||||
.map((numStr) => numStr.trim());
|
||||
|
||||
const linksHtml = numbers
|
||||
.map((numStr) => {
|
||||
const number = parseInt(numStr);
|
||||
|
||||
if (isNaN(number) || number <= 0) {
|
||||
return `[${numStr}]`;
|
||||
}
|
||||
|
||||
const source = message.sources?.[number - 1];
|
||||
const url = source?.metadata?.url;
|
||||
|
||||
if (url) {
|
||||
return `<a href="${url}" target="_blank" className="bg-light-secondary dark:bg-dark-secondary px-1 rounded ml-1 no-underline text-xs text-black/70 dark:text-white/70 relative">${numStr}</a>`;
|
||||
} else {
|
||||
return `[${numStr}]`;
|
||||
}
|
||||
})
|
||||
.join('');
|
||||
|
||||
return linksHtml;
|
||||
},
|
||||
),
|
||||
);
|
||||
setSpeechMessage(message.content.replace(regex, ''));
|
||||
return;
|
||||
}
|
||||
|
||||
|
@ -4,6 +4,7 @@ import { useEffect, useRef, useState } from 'react';
|
||||
import TextareaAutosize from 'react-textarea-autosize';
|
||||
import Attach from './MessageInputActions/Attach';
|
||||
import CopilotToggle from './MessageInputActions/Copilot';
|
||||
import Optimization from './MessageInputActions/Optimization';
|
||||
import { File } from './ChatWindow';
|
||||
import AttachSmall from './MessageInputActions/AttachSmall';
|
||||
|
||||
@ -14,6 +15,8 @@ const MessageInput = ({
|
||||
setFileIds,
|
||||
files,
|
||||
setFiles,
|
||||
optimizationMode,
|
||||
setOptimizationMode,
|
||||
}: {
|
||||
sendMessage: (message: string) => void;
|
||||
loading: boolean;
|
||||
@ -21,6 +24,8 @@ const MessageInput = ({
|
||||
setFileIds: (fileIds: string[]) => void;
|
||||
files: File[];
|
||||
setFiles: (files: File[]) => void;
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
const [copilotEnabled, setCopilotEnabled] = useState(false);
|
||||
const [message, setMessage] = useState('');
|
||||
@ -40,20 +45,16 @@ const MessageInput = ({
|
||||
useEffect(() => {
|
||||
const handleKeyDown = (e: KeyboardEvent) => {
|
||||
const activeElement = document.activeElement;
|
||||
|
||||
const isInputFocused =
|
||||
activeElement?.tagName === 'INPUT' ||
|
||||
activeElement?.tagName === 'TEXTAREA' ||
|
||||
activeElement?.hasAttribute('contenteditable');
|
||||
|
||||
if (e.key === '/' && !isInputFocused) {
|
||||
e.preventDefault();
|
||||
inputRef.current?.focus();
|
||||
}
|
||||
};
|
||||
|
||||
document.addEventListener('keydown', handleKeyDown);
|
||||
|
||||
return () => {
|
||||
document.removeEventListener('keydown', handleKeyDown);
|
||||
};
|
||||
@ -75,18 +76,35 @@ const MessageInput = ({
|
||||
}
|
||||
}}
|
||||
className={cn(
|
||||
'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center overflow-hidden border border-light-200 dark:border-dark-200',
|
||||
mode === 'multi' ? 'flex-col rounded-lg' : 'flex-row rounded-full',
|
||||
'bg-light-secondary dark:bg-dark-secondary p-4 flex items-center border border-light-200 dark:border-dark-200',
|
||||
mode === 'multi'
|
||||
? 'flex-col rounded-lg'
|
||||
: 'flex-col md:flex-row rounded-lg md:rounded-full',
|
||||
)}
|
||||
>
|
||||
{mode === 'single' && (
|
||||
<div className="flex flex-row items-center justify-between w-full mb-2 md:mb-0 md:w-auto">
|
||||
<div className="flex flex-row items-center space-x-2">
|
||||
<AttachSmall
|
||||
fileIds={fileIds}
|
||||
setFileIds={setFileIds}
|
||||
files={files}
|
||||
setFiles={setFiles}
|
||||
/>
|
||||
<Optimization
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
</div>
|
||||
<div className="md:hidden">
|
||||
<CopilotToggle
|
||||
copilotEnabled={copilotEnabled}
|
||||
setCopilotEnabled={setCopilotEnabled}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
<div className="flex flex-row items-center w-full">
|
||||
<TextareaAutosize
|
||||
ref={inputRef}
|
||||
value={message}
|
||||
@ -99,10 +117,12 @@ const MessageInput = ({
|
||||
/>
|
||||
{mode === 'single' && (
|
||||
<div className="flex flex-row items-center space-x-4">
|
||||
<div className="hidden md:block">
|
||||
<CopilotToggle
|
||||
copilotEnabled={copilotEnabled}
|
||||
setCopilotEnabled={setCopilotEnabled}
|
||||
/>
|
||||
</div>
|
||||
<button
|
||||
disabled={message.trim().length === 0 || loading}
|
||||
className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
|
||||
@ -111,22 +131,40 @@ const MessageInput = ({
|
||||
</button>
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
||||
{mode === 'multi' && (
|
||||
<div className="flex flex-row items-center justify-between w-full pt-2">
|
||||
<div className="flex flex-col md:flex-row items-start md:items-center justify-between w-full pt-2">
|
||||
<div className="flex flex-row items-center justify-between w-full md:w-auto mb-2 md:mb-0">
|
||||
<div className="flex flex-row items-center space-x-2">
|
||||
<AttachSmall
|
||||
fileIds={fileIds}
|
||||
setFileIds={setFileIds}
|
||||
files={files}
|
||||
setFiles={setFiles}
|
||||
/>
|
||||
<div className="flex flex-row items-center space-x-4">
|
||||
<Optimization
|
||||
optimizationMode={optimizationMode}
|
||||
setOptimizationMode={setOptimizationMode}
|
||||
/>
|
||||
</div>
|
||||
<div className="md:hidden">
|
||||
<CopilotToggle
|
||||
copilotEnabled={copilotEnabled}
|
||||
setCopilotEnabled={setCopilotEnabled}
|
||||
/>
|
||||
</div>
|
||||
</div>
|
||||
<div className="flex flex-row items-center space-x-4 self-end">
|
||||
<div className="hidden md:block">
|
||||
<CopilotToggle
|
||||
copilotEnabled={copilotEnabled}
|
||||
setCopilotEnabled={setCopilotEnabled}
|
||||
/>
|
||||
</div>
|
||||
<button
|
||||
disabled={message.trim().length === 0 || loading}
|
||||
className="bg-[#24A0ED] text-white text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
|
||||
className="bg-[#24A0ED] text-white disabled:text-black/50 dark:disabled:text-white/50 hover:bg-opacity-85 transition duration-100 disabled:bg-[#e0e0dc79] dark:disabled:bg-[#ececec21] rounded-full p-2"
|
||||
>
|
||||
<ArrowUp className="bg-background" size={17} />
|
||||
</button>
|
||||
|
@ -1,4 +1,4 @@
|
||||
import { ChevronDown, Sliders, Star, Zap } from 'lucide-react';
|
||||
import { ChevronDown, Minimize2, Sliders, Star, Zap } from 'lucide-react';
|
||||
import { cn } from '@/lib/utils';
|
||||
import {
|
||||
Popover,
|
||||
@ -7,7 +7,6 @@ import {
|
||||
Transition,
|
||||
} from '@headlessui/react';
|
||||
import { Fragment } from 'react';
|
||||
|
||||
const OptimizationModes = [
|
||||
{
|
||||
key: 'speed',
|
||||
@ -41,8 +40,13 @@ const Optimization = ({
|
||||
optimizationMode: string;
|
||||
setOptimizationMode: (mode: string) => void;
|
||||
}) => {
|
||||
const handleOptimizationChange = (mode: string) => {
|
||||
setOptimizationMode(mode);
|
||||
localStorage.setItem('optimizationMode', mode);
|
||||
};
|
||||
|
||||
return (
|
||||
<Popover className="relative w-full max-w-[15rem] md:max-w-md lg:max-w-lg">
|
||||
<Popover className="relative">
|
||||
<PopoverButton
|
||||
type="button"
|
||||
className="p-2 text-black/50 dark:text-white/50 rounded-xl hover:bg-light-secondary dark:hover:bg-dark-secondary active:scale-95 transition duration-200 hover:text-black dark:hover:text-white"
|
||||
@ -70,11 +74,11 @@ const Optimization = ({
|
||||
leaveFrom="opacity-100 translate-y-0"
|
||||
leaveTo="opacity-0 translate-y-1"
|
||||
>
|
||||
<PopoverPanel className="absolute z-10 w-64 md:w-[250px] right-0">
|
||||
<div className="flex flex-col gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-full p-4 max-h-[200px] md:max-h-none overflow-y-auto">
|
||||
<PopoverPanel className="absolute z-10 bottom-[100%] mb-2 left-1/2 transform -translate-x-1/2">
|
||||
<div className="flex flex-col gap-2 bg-light-primary dark:bg-dark-primary border rounded-lg border-light-200 dark:border-dark-200 w-max max-w-[300px] p-4 max-h-[200px] md:max-h-none overflow-y-auto">
|
||||
{OptimizationModes.map((mode, i) => (
|
||||
<PopoverButton
|
||||
onClick={() => setOptimizationMode(mode.key)}
|
||||
onClick={() => handleOptimizationChange(mode.key)}
|
||||
key={i}
|
||||
disabled={mode.key === 'quality'}
|
||||
className={cn(
|
||||
|
@ -35,9 +35,10 @@ const SearchImages = ({
|
||||
|
||||
const chatModelProvider = localStorage.getItem('chatModelProvider');
|
||||
const chatModel = localStorage.getItem('chatModel');
|
||||
|
||||
const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
|
||||
const customOpenAIKey = localStorage.getItem('openAIApiKey');
|
||||
const ollamaContextWindow =
|
||||
localStorage.getItem('ollamaContextWindow') || '2048';
|
||||
|
||||
const res = await fetch(`/api/images`, {
|
||||
method: 'POST',
|
||||
@ -54,6 +55,9 @@ const SearchImages = ({
|
||||
customOpenAIBaseURL: customOpenAIBaseURL,
|
||||
customOpenAIKey: customOpenAIKey,
|
||||
}),
|
||||
...(chatModelProvider === 'ollama' && {
|
||||
ollamaContextWindow: parseInt(ollamaContextWindow),
|
||||
}),
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
@ -50,9 +50,10 @@ const Searchvideos = ({
|
||||
|
||||
const chatModelProvider = localStorage.getItem('chatModelProvider');
|
||||
const chatModel = localStorage.getItem('chatModel');
|
||||
|
||||
const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
|
||||
const customOpenAIKey = localStorage.getItem('openAIApiKey');
|
||||
const ollamaContextWindow =
|
||||
localStorage.getItem('ollamaContextWindow') || '2048';
|
||||
|
||||
const res = await fetch(`/api/videos`, {
|
||||
method: 'POST',
|
||||
@ -69,6 +70,9 @@ const Searchvideos = ({
|
||||
customOpenAIBaseURL: customOpenAIBaseURL,
|
||||
customOpenAIKey: customOpenAIKey,
|
||||
}),
|
||||
...(chatModelProvider === 'ollama' && {
|
||||
ollamaContextWindow: parseInt(ollamaContextWindow),
|
||||
}),
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
@ -6,6 +6,8 @@ export const getSuggestions = async (chatHisory: Message[]) => {
|
||||
|
||||
const customOpenAIKey = localStorage.getItem('openAIApiKey');
|
||||
const customOpenAIBaseURL = localStorage.getItem('openAIBaseURL');
|
||||
const ollamaContextWindow =
|
||||
localStorage.getItem('ollamaContextWindow') || '2048';
|
||||
|
||||
const res = await fetch(`/api/suggestions`, {
|
||||
method: 'POST',
|
||||
@ -21,6 +23,9 @@ export const getSuggestions = async (chatHisory: Message[]) => {
|
||||
customOpenAIKey,
|
||||
customOpenAIBaseURL,
|
||||
}),
|
||||
...(chatModelProvider === 'ollama' && {
|
||||
ollamaContextWindow: parseInt(ollamaContextWindow),
|
||||
}),
|
||||
},
|
||||
}),
|
||||
});
|
||||
|
@ -1,7 +1,14 @@
|
||||
import fs from 'fs';
|
||||
import path from 'path';
|
||||
import toml from '@iarna/toml';
|
||||
|
||||
// Use dynamic imports for Node.js modules to prevent client-side errors
|
||||
let fs: any;
|
||||
let path: any;
|
||||
if (typeof window === 'undefined') {
|
||||
// We're on the server
|
||||
fs = require('fs');
|
||||
path = require('path');
|
||||
}
|
||||
|
||||
const configFileName = 'config.toml';
|
||||
|
||||
interface Config {
|
||||
@ -25,6 +32,12 @@ interface Config {
|
||||
OLLAMA: {
|
||||
API_URL: string;
|
||||
};
|
||||
DEEPSEEK: {
|
||||
API_KEY: string;
|
||||
};
|
||||
LM_STUDIO: {
|
||||
API_URL: string;
|
||||
};
|
||||
CUSTOM_OPENAI: {
|
||||
API_URL: string;
|
||||
API_KEY: string;
|
||||
@ -40,10 +53,17 @@ type RecursivePartial<T> = {
|
||||
[P in keyof T]?: RecursivePartial<T[P]>;
|
||||
};
|
||||
|
||||
const loadConfig = () =>
|
||||
toml.parse(
|
||||
const loadConfig = () => {
|
||||
// Server-side only
|
||||
if (typeof window === 'undefined') {
|
||||
return toml.parse(
|
||||
fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
|
||||
) as any as Config;
|
||||
}
|
||||
|
||||
// Client-side fallback - settings will be loaded via API
|
||||
return {} as Config;
|
||||
};
|
||||
|
||||
export const getSimilarityMeasure = () =>
|
||||
loadConfig().GENERAL.SIMILARITY_MEASURE;
|
||||
@ -63,6 +83,8 @@ export const getSearxngApiEndpoint = () =>
|
||||
|
||||
export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
|
||||
|
||||
export const getDeepseekApiKey = () => loadConfig().MODELS.DEEPSEEK.API_KEY;
|
||||
|
||||
export const getCustomOpenaiApiKey = () =>
|
||||
loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
|
||||
|
||||
@ -72,6 +94,9 @@ export const getCustomOpenaiApiUrl = () =>
|
||||
export const getCustomOpenaiModelName = () =>
|
||||
loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
|
||||
|
||||
export const getLMStudioApiEndpoint = () =>
|
||||
loadConfig().MODELS.LM_STUDIO.API_URL;
|
||||
|
||||
const mergeConfigs = (current: any, update: any): any => {
|
||||
if (update === null || update === undefined) {
|
||||
return current;
|
||||
@ -104,10 +129,13 @@ const mergeConfigs = (current: any, update: any): any => {
|
||||
};
|
||||
|
||||
export const updateConfig = (config: RecursivePartial<Config>) => {
|
||||
// Server-side only
|
||||
if (typeof window === 'undefined') {
|
||||
const currentConfig = loadConfig();
|
||||
const mergedConfig = mergeConfigs(currentConfig, config);
|
||||
fs.writeFileSync(
|
||||
path.join(path.join(process.cwd(), `${configFileName}`)),
|
||||
toml.stringify(mergedConfig),
|
||||
);
|
||||
}
|
||||
};
|
||||
|
@ -1,6 +1,11 @@
|
||||
import { ChatAnthropic } from '@langchain/anthropic';
|
||||
import { ChatModel } from '.';
|
||||
import { getAnthropicApiKey } from '../config';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'anthropic',
|
||||
displayName: 'Anthropic',
|
||||
};
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
|
||||
const anthropicChatModels: Record<string, string>[] = [
|
||||
|
49
src/lib/providers/deepseek.ts
Normal file
49
src/lib/providers/deepseek.ts
Normal file
@ -0,0 +1,49 @@
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { getDeepseekApiKey } from '../config';
|
||||
import { ChatModel } from '.';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'deepseek',
|
||||
displayName: 'Deepseek AI',
|
||||
};
|
||||
|
||||
const deepseekChatModels: Record<string, string>[] = [
|
||||
{
|
||||
displayName: 'Deepseek Chat (Deepseek V3)',
|
||||
key: 'deepseek-chat',
|
||||
},
|
||||
{
|
||||
displayName: 'Deepseek Reasoner (Deepseek R1)',
|
||||
key: 'deepseek-reasoner',
|
||||
},
|
||||
];
|
||||
|
||||
export const loadDeepseekChatModels = async () => {
|
||||
const deepseekApiKey = getDeepseekApiKey();
|
||||
|
||||
if (!deepseekApiKey) return {};
|
||||
|
||||
try {
|
||||
const chatModels: Record<string, ChatModel> = {};
|
||||
|
||||
deepseekChatModels.forEach((model) => {
|
||||
chatModels[model.key] = {
|
||||
displayName: model.displayName,
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey: deepseekApiKey,
|
||||
modelName: model.key,
|
||||
temperature: 0.7,
|
||||
configuration: {
|
||||
baseURL: 'https://api.deepseek.com',
|
||||
},
|
||||
}) as unknown as BaseChatModel,
|
||||
};
|
||||
});
|
||||
|
||||
return chatModels;
|
||||
} catch (err) {
|
||||
console.error(`Error loading Deepseek models: ${err}`);
|
||||
return {};
|
||||
}
|
||||
};
|
@ -4,6 +4,11 @@ import {
|
||||
} from '@langchain/google-genai';
|
||||
import { getGeminiApiKey } from '../config';
|
||||
import { ChatModel, EmbeddingModel } from '.';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'gemini',
|
||||
displayName: 'Google Gemini',
|
||||
};
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { Embeddings } from '@langchain/core/embeddings';
|
||||
|
||||
@ -40,8 +45,12 @@ const geminiChatModels: Record<string, string>[] = [
|
||||
|
||||
const geminiEmbeddingModels: Record<string, string>[] = [
|
||||
{
|
||||
displayName: 'Gemini Embedding',
|
||||
key: 'gemini-embedding-exp',
|
||||
displayName: 'Text Embedding 004',
|
||||
key: 'models/text-embedding-004',
|
||||
},
|
||||
{
|
||||
displayName: 'Embedding 001',
|
||||
key: 'models/embedding-001',
|
||||
},
|
||||
];
|
||||
|
||||
|
@ -1,6 +1,11 @@
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { getGroqApiKey } from '../config';
|
||||
import { ChatModel } from '.';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'groq',
|
||||
displayName: 'Groq',
|
||||
};
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
|
||||
const groqChatModels: Record<string, string>[] = [
|
||||
@ -72,6 +77,14 @@ const groqChatModels: Record<string, string>[] = [
|
||||
displayName: 'Llama 3.2 90B Vision Preview (Preview)',
|
||||
key: 'llama-3.2-90b-vision-preview',
|
||||
},
|
||||
/* {
|
||||
displayName: 'Llama 4 Maverick 17B 128E Instruct (Preview)',
|
||||
key: 'meta-llama/llama-4-maverick-17b-128e-instruct',
|
||||
}, */
|
||||
{
|
||||
displayName: 'Llama 4 Scout 17B 16E Instruct (Preview)',
|
||||
key: 'meta-llama/llama-4-scout-17b-16e-instruct',
|
||||
},
|
||||
];
|
||||
|
||||
export const loadGroqChatModels = async () => {
|
||||
|
@ -1,17 +1,60 @@
|
||||
import { Embeddings } from '@langchain/core/embeddings';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai';
|
||||
import {
|
||||
loadOpenAIChatModels,
|
||||
loadOpenAIEmbeddingModels,
|
||||
PROVIDER_INFO as OpenAIInfo,
|
||||
PROVIDER_INFO,
|
||||
} from './openai';
|
||||
import {
|
||||
getCustomOpenaiApiKey,
|
||||
getCustomOpenaiApiUrl,
|
||||
getCustomOpenaiModelName,
|
||||
} from '../config';
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
|
||||
import { loadGroqChatModels } from './groq';
|
||||
import { loadAnthropicChatModels } from './anthropic';
|
||||
import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
|
||||
import { loadTransformersEmbeddingsModels } from './transformers';
|
||||
import {
|
||||
loadOllamaChatModels,
|
||||
loadOllamaEmbeddingModels,
|
||||
PROVIDER_INFO as OllamaInfo,
|
||||
} from './ollama';
|
||||
import { loadGroqChatModels, PROVIDER_INFO as GroqInfo } from './groq';
|
||||
import {
|
||||
loadAnthropicChatModels,
|
||||
PROVIDER_INFO as AnthropicInfo,
|
||||
} from './anthropic';
|
||||
import {
|
||||
loadGeminiChatModels,
|
||||
loadGeminiEmbeddingModels,
|
||||
PROVIDER_INFO as GeminiInfo,
|
||||
} from './gemini';
|
||||
import {
|
||||
loadTransformersEmbeddingsModels,
|
||||
PROVIDER_INFO as TransformersInfo,
|
||||
} from './transformers';
|
||||
import {
|
||||
loadDeepseekChatModels,
|
||||
PROVIDER_INFO as DeepseekInfo,
|
||||
} from './deepseek';
|
||||
import {
|
||||
loadLMStudioChatModels,
|
||||
loadLMStudioEmbeddingsModels,
|
||||
PROVIDER_INFO as LMStudioInfo,
|
||||
} from './lmstudio';
|
||||
|
||||
export const PROVIDER_METADATA = {
|
||||
openai: OpenAIInfo,
|
||||
ollama: OllamaInfo,
|
||||
groq: GroqInfo,
|
||||
anthropic: AnthropicInfo,
|
||||
gemini: GeminiInfo,
|
||||
transformers: TransformersInfo,
|
||||
deepseek: DeepseekInfo,
|
||||
lmstudio: LMStudioInfo,
|
||||
custom_openai: {
|
||||
key: 'custom_openai',
|
||||
displayName: 'Custom OpenAI',
|
||||
},
|
||||
};
|
||||
|
||||
export interface ChatModel {
|
||||
displayName: string;
|
||||
@ -32,6 +75,8 @@ export const chatModelProviders: Record<
|
||||
groq: loadGroqChatModels,
|
||||
anthropic: loadAnthropicChatModels,
|
||||
gemini: loadGeminiChatModels,
|
||||
deepseek: loadDeepseekChatModels,
|
||||
lmstudio: loadLMStudioChatModels,
|
||||
};
|
||||
|
||||
export const embeddingModelProviders: Record<
|
||||
@ -42,6 +87,7 @@ export const embeddingModelProviders: Record<
|
||||
ollama: loadOllamaEmbeddingModels,
|
||||
gemini: loadGeminiEmbeddingModels,
|
||||
transformers: loadTransformersEmbeddingsModels,
|
||||
lmstudio: loadLMStudioEmbeddingsModels,
|
||||
};
|
||||
|
||||
export const getAvailableChatModelProviders = async () => {
|
||||
|
100
src/lib/providers/lmstudio.ts
Normal file
100
src/lib/providers/lmstudio.ts
Normal file
@ -0,0 +1,100 @@
|
||||
import { getKeepAlive, getLMStudioApiEndpoint } from '../config';
|
||||
import axios from 'axios';
|
||||
import { ChatModel, EmbeddingModel } from '.';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'lmstudio',
|
||||
displayName: 'LM Studio',
|
||||
};
|
||||
import { ChatOpenAI } from '@langchain/openai';
|
||||
import { OpenAIEmbeddings } from '@langchain/openai';
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { Embeddings } from '@langchain/core/embeddings';
|
||||
|
||||
interface LMStudioModel {
|
||||
id: string;
|
||||
name?: string;
|
||||
}
|
||||
|
||||
const ensureV1Endpoint = (endpoint: string): string =>
|
||||
endpoint.endsWith('/v1') ? endpoint : `${endpoint}/v1`;
|
||||
|
||||
const checkServerAvailability = async (endpoint: string): Promise<boolean> => {
|
||||
try {
|
||||
await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
});
|
||||
return true;
|
||||
} catch {
|
||||
return false;
|
||||
}
|
||||
};
|
||||
|
||||
export const loadLMStudioChatModels = async () => {
|
||||
const endpoint = getLMStudioApiEndpoint();
|
||||
|
||||
if (!endpoint) return {};
|
||||
if (!(await checkServerAvailability(endpoint))) return {};
|
||||
|
||||
try {
|
||||
const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
});
|
||||
|
||||
const chatModels: Record<string, ChatModel> = {};
|
||||
|
||||
response.data.data.forEach((model: LMStudioModel) => {
|
||||
chatModels[model.id] = {
|
||||
displayName: model.name || model.id,
|
||||
model: new ChatOpenAI({
|
||||
openAIApiKey: 'lm-studio',
|
||||
configuration: {
|
||||
baseURL: ensureV1Endpoint(endpoint),
|
||||
},
|
||||
modelName: model.id,
|
||||
temperature: 0.7,
|
||||
streaming: true,
|
||||
maxRetries: 3,
|
||||
}) as unknown as BaseChatModel,
|
||||
};
|
||||
});
|
||||
|
||||
return chatModels;
|
||||
} catch (err) {
|
||||
console.error(`Error loading LM Studio models: ${err}`);
|
||||
return {};
|
||||
}
|
||||
};
|
||||
|
||||
export const loadLMStudioEmbeddingsModels = async () => {
|
||||
const endpoint = getLMStudioApiEndpoint();
|
||||
|
||||
if (!endpoint) return {};
|
||||
if (!(await checkServerAvailability(endpoint))) return {};
|
||||
|
||||
try {
|
||||
const response = await axios.get(`${ensureV1Endpoint(endpoint)}/models`, {
|
||||
headers: { 'Content-Type': 'application/json' },
|
||||
});
|
||||
|
||||
const embeddingsModels: Record<string, EmbeddingModel> = {};
|
||||
|
||||
response.data.data.forEach((model: LMStudioModel) => {
|
||||
embeddingsModels[model.id] = {
|
||||
displayName: model.name || model.id,
|
||||
model: new OpenAIEmbeddings({
|
||||
openAIApiKey: 'lm-studio',
|
||||
configuration: {
|
||||
baseURL: ensureV1Endpoint(endpoint),
|
||||
},
|
||||
modelName: model.id,
|
||||
}) as unknown as Embeddings,
|
||||
};
|
||||
});
|
||||
|
||||
return embeddingsModels;
|
||||
} catch (err) {
|
||||
console.error(`Error loading LM Studio embeddings model: ${err}`);
|
||||
return {};
|
||||
}
|
||||
};
|
@ -1,8 +1,13 @@
|
||||
import axios from 'axios';
|
||||
import { getKeepAlive, getOllamaApiEndpoint } from '../config';
|
||||
import { ChatModel, EmbeddingModel } from '.';
|
||||
import { ChatOllama } from '@langchain/community/chat_models/ollama';
|
||||
import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'ollama',
|
||||
displayName: 'Ollama',
|
||||
};
|
||||
import { ChatOllama } from '@langchain/ollama';
|
||||
import { OllamaEmbeddings } from '@langchain/ollama';
|
||||
|
||||
export const loadOllamaChatModels = async () => {
|
||||
const ollamaApiEndpoint = getOllamaApiEndpoint();
|
||||
|
@ -1,6 +1,11 @@
|
||||
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
|
||||
import { getOpenaiApiKey } from '../config';
|
||||
import { ChatModel, EmbeddingModel } from '.';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'openai',
|
||||
displayName: 'OpenAI',
|
||||
};
|
||||
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
|
||||
import { Embeddings } from '@langchain/core/embeddings';
|
||||
|
||||
|
@ -1,5 +1,10 @@
|
||||
import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'transformers',
|
||||
displayName: 'Hugging Face',
|
||||
};
|
||||
|
||||
export const loadTransformersEmbeddingsModels = async () => {
|
||||
try {
|
||||
const embeddingModels = {
|
||||
|
Reference in New Issue
Block a user