Compare commits

..

2 Commits

Author SHA1 Message Date
086b8abdf4 Merge 8097610baf into 09661ae11d 2025-04-05 17:57:22 -07:00
8097610baf Adding user session for history 2025-04-05 17:43:04 -07:00
24 changed files with 93 additions and 399 deletions

View File

@ -159,7 +159,6 @@ Perplexica runs on Next.js and handles all API requests. It works right away on
[![Deploy to Sealos](https://raw.githubusercontent.com/labring-actions/templates/main/Deploy-on-Sealos.svg)](https://usw.sealos.io/?openapp=system-template%3FtemplateName%3Dperplexica)
[![Deploy to RepoCloud](https://d16t0pc4846x52.cloudfront.net/deploylobe.svg)](https://repocloud.io/details/?app_id=267)
[![Run on ClawCloud](https://raw.githubusercontent.com/ClawCloud/Run-Template/refs/heads/main/Run-on-ClawCloud.svg)](https://template.run.claw.cloud/?referralCode=U11MRQ8U9RM4&openapp=system-fastdeploy%3FtemplateName%3Dperplexica)
## Upcoming Features

View File

@ -33,7 +33,6 @@ 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
}
```
@ -64,8 +63,6 @@ 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

View File

@ -1,6 +1,6 @@
{
"name": "perplexica-frontend",
"version": "1.10.2",
"version": "1.10.1",
"license": "MIT",
"author": "ItzCrazyKns",
"scripts": {

View File

@ -22,11 +22,5 @@ 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
SEARXNG = "" # SearxNG API URL - http://localhost:32768

View File

@ -29,6 +29,7 @@ type Message = {
messageId: string;
chatId: string;
content: string;
userSessionId: string;
};
type ChatModel = {
@ -138,6 +139,7 @@ const handleHistorySave = async (
where: eq(chats.id, message.chatId),
});
let currentDate = new Date();
if (!chat) {
await db
.insert(chats)
@ -147,6 +149,8 @@ const handleHistorySave = async (
createdAt: new Date().toString(),
focusMode: focusMode,
files: files.map(getFileDetails),
userSessionId: message.userSessionId,
timestamp: currentDate.toISOString(),
})
.execute();
}

View File

@ -1,10 +1,47 @@
import db from '@/lib/db';
import { chats } from '@/lib/db/schema';
import { eq, sql} from 'drizzle-orm';
export const GET = async (req: Request) => {
try {
let chats = await db.query.chats.findMany();
chats = chats.reverse();
return Response.json({ chats: chats }, { status: 200 });
// get header from request
const headers = await req.headers;
let userSessionId = headers.get('user-session-id')?.toString() ?? '';
if (userSessionId == '') {
return Response.json({ chats: {} }, { status: 200 });
}
let chatsRes = await db.query.chats.findMany({
where: eq(chats.userSessionId, userSessionId),
});
chatsRes = chatsRes.reverse();
// Keep only the latest 20 records in the database. Delete older records.
let maxRecordLimit = 20;
if (chatsRes.length > maxRecordLimit) {
const deleteChatsQuery = sql`DELETE FROM chats
WHERE userSessionId = ${userSessionId} AND (
timestamp IS NULL OR
timestamp NOT in (
SELECT timestamp FROM chats
WHERE userSessionId = ${userSessionId}
ORDER BY timestamp DESC
LIMIT ${maxRecordLimit}
)
)
`;
await db.run(deleteChatsQuery);
// Delete messages that no longer link with the chat from the database.
const deleteMessagesQuery = sql`DELETE FROM messages
WHERE chatId NOT IN (
SELECT id FROM chats
)
`;
await db.run(deleteMessagesQuery);
}
return Response.json({ chats: chatsRes }, { status: 200 });
} catch (err) {
console.error('Error in getting chats: ', err);
return Response.json(

View File

@ -7,8 +7,6 @@ import {
getGroqApiKey,
getOllamaApiEndpoint,
getOpenaiApiKey,
getDeepseekApiKey,
getLMStudioApiEndpoint,
updateConfig,
} from '@/lib/config';
import {
@ -52,11 +50,9 @@ 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();
@ -92,12 +88,6 @@ 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,

View File

@ -34,7 +34,6 @@ interface ChatRequestBody {
query: string;
history: Array<[string, string]>;
stream?: boolean;
systemInstructions?: string;
}
export const POST = async (req: Request) => {
@ -126,7 +125,7 @@ export const POST = async (req: Request) => {
embeddings,
body.optimizationMode,
[],
body.systemInstructions || '',
'',
);
if (!body.stream) {

View File

@ -1,5 +1,6 @@
'use client';
import crypto from 'crypto';
import DeleteChat from '@/components/DeleteChat';
import { cn, formatTimeDifference } from '@/lib/utils';
import { BookOpenText, ClockIcon, Delete, ScanEye } from 'lucide-react';
@ -21,10 +22,17 @@ const Page = () => {
const fetchChats = async () => {
setLoading(true);
let userSessionId = localStorage.getItem('userSessionId');
if (!userSessionId) {
userSessionId = crypto.randomBytes(20).toString('hex');
localStorage.setItem('userSessionId', userSessionId)
}
const res = await fetch(`/api/chats`, {
method: 'GET',
headers: {
'Content-Type': 'application/json',
'user-session-id': userSessionId!,
},
});

View File

@ -7,7 +7,6 @@ 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: {
@ -21,8 +20,6 @@ interface SettingsType {
anthropicApiKey: string;
geminiApiKey: string;
ollamaApiUrl: string;
lmStudioApiUrl: string;
deepseekApiKey: string;
customOpenaiApiKey: string;
customOpenaiApiUrl: string;
customOpenaiModelName: string;
@ -550,9 +547,8 @@ const Page = () => {
(provider) => ({
value: provider,
label:
(PROVIDER_METADATA as any)[provider]?.displayName ||
provider.charAt(0).toUpperCase() +
provider.slice(1),
provider.slice(1),
}),
)}
/>
@ -693,9 +689,8 @@ const Page = () => {
(provider) => ({
value: provider,
label:
(PROVIDER_METADATA as any)[provider]?.displayName ||
provider.charAt(0).toUpperCase() +
provider.slice(1),
provider.slice(1),
}),
)}
/>
@ -843,44 +838,6 @@ 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>

View File

@ -95,6 +95,12 @@ const checkConfig = async (
if (!embeddingModel || !embeddingModelProvider) {
const embeddingModelProviders = providers.embeddingModelProviders;
let userSessionId = localStorage.getItem('userSessionId');
if (!userSessionId) {
userSessionId = crypto.randomBytes(20).toString('hex');
localStorage.setItem('userSessionId', userSessionId!)
}
if (
!embeddingModelProviders ||
Object.keys(embeddingModelProviders).length === 0
@ -342,6 +348,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
let added = false;
messageId = messageId ?? crypto.randomBytes(7).toString('hex');
let userSessionId = localStorage.getItem('userSessionId');
setMessages((prevMessages) => [
...prevMessages,
@ -466,6 +473,7 @@ const ChatWindow = ({ id }: { id?: string }) => {
messageId: messageId,
chatId: chatId!,
content: message,
userSessionId: userSessionId,
},
chatId: chatId!,
files: fileIds,

View File

@ -48,7 +48,6 @@ const MessageBox = ({
const [speechMessage, setSpeechMessage] = useState(message.content);
useEffect(() => {
const citationRegex = /\[([^\]]+)\]/g;
const regex = /\[(\d+)\]/g;
let processedMessage = message.content;
@ -68,36 +67,13 @@ const MessageBox = ({
) {
setParsedMessage(
processedMessage.replace(
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;
},
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>`,
),
);
setSpeechMessage(message.content.replace(regex, ''));
return;
}

View File

@ -1,14 +1,7 @@
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 {
@ -32,12 +25,6 @@ interface Config {
OLLAMA: {
API_URL: string;
};
DEEPSEEK: {
API_KEY: string;
};
LM_STUDIO: {
API_URL: string;
};
CUSTOM_OPENAI: {
API_URL: string;
API_KEY: string;
@ -53,17 +40,10 @@ type RecursivePartial<T> = {
[P in keyof T]?: RecursivePartial<T[P]>;
};
const loadConfig = () => {
// Server-side only
if (typeof window === 'undefined') {
return toml.parse(
fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
) as any as Config;
}
// Client-side fallback - settings will be loaded via API
return {} as Config;
};
const loadConfig = () =>
toml.parse(
fs.readFileSync(path.join(process.cwd(), `${configFileName}`), 'utf-8'),
) as any as Config;
export const getSimilarityMeasure = () =>
loadConfig().GENERAL.SIMILARITY_MEASURE;
@ -83,8 +63,6 @@ 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;
@ -94,9 +72,6 @@ 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;
@ -129,13 +104,10 @@ 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(), `${configFileName}`)),
toml.stringify(mergedConfig),
);
}
const currentConfig = loadConfig();
const mergedConfig = mergeConfigs(currentConfig, config);
fs.writeFileSync(
path.join(path.join(process.cwd(), `${configFileName}`)),
toml.stringify(mergedConfig),
);
};

View File

@ -25,4 +25,6 @@ export const chats = sqliteTable('chats', {
files: text('files', { mode: 'json' })
.$type<File[]>()
.default(sql`'[]'`),
userSessionId: text('userSessionId'),
timestamp: text('timestamp'),
});

View File

@ -1,11 +1,6 @@
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>[] = [

View File

@ -1,49 +0,0 @@
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 {};
}
};

View File

@ -4,11 +4,6 @@ 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';
@ -45,12 +40,8 @@ const geminiChatModels: Record<string, string>[] = [
const geminiEmbeddingModels: Record<string, string>[] = [
{
displayName: 'Text Embedding 004',
key: 'models/text-embedding-004',
},
{
displayName: 'Embedding 001',
key: 'models/embedding-001',
displayName: 'Gemini Embedding',
key: 'gemini-embedding-exp',
},
];

View File

@ -1,11 +1,6 @@
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>[] = [
@ -77,14 +72,6 @@ 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 () => {

View File

@ -1,60 +1,17 @@
import { Embeddings } from '@langchain/core/embeddings';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import {
loadOpenAIChatModels,
loadOpenAIEmbeddingModels,
PROVIDER_INFO as OpenAIInfo,
PROVIDER_INFO,
} from './openai';
import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai';
import {
getCustomOpenaiApiKey,
getCustomOpenaiApiUrl,
getCustomOpenaiModelName,
} from '../config';
import { ChatOpenAI } from '@langchain/openai';
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',
},
};
import { loadOllamaChatModels, loadOllamaEmbeddingModels } from './ollama';
import { loadGroqChatModels } from './groq';
import { loadAnthropicChatModels } from './anthropic';
import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
import { loadTransformersEmbeddingsModels } from './transformers';
export interface ChatModel {
displayName: string;
@ -75,8 +32,6 @@ export const chatModelProviders: Record<
groq: loadGroqChatModels,
anthropic: loadAnthropicChatModels,
gemini: loadGeminiChatModels,
deepseek: loadDeepseekChatModels,
lmstudio: loadLMStudioChatModels,
};
export const embeddingModelProviders: Record<
@ -87,7 +42,6 @@ export const embeddingModelProviders: Record<
ollama: loadOllamaEmbeddingModels,
gemini: loadGeminiEmbeddingModels,
transformers: loadTransformersEmbeddingsModels,
lmstudio: loadLMStudioEmbeddingsModels,
};
export const getAvailableChatModelProviders = async () => {

View File

@ -1,100 +0,0 @@
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 {};
}
};

View File

@ -1,11 +1,6 @@
import axios from 'axios';
import { getKeepAlive, getOllamaApiEndpoint } from '../config';
import { ChatModel, EmbeddingModel } from '.';
export const PROVIDER_INFO = {
key: 'ollama',
displayName: 'Ollama',
};
import { ChatOllama } from '@langchain/community/chat_models/ollama';
import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama';

View File

@ -1,11 +1,6 @@
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';
@ -30,18 +25,6 @@ const openaiChatModels: Record<string, string>[] = [
displayName: 'GPT-4 omni mini',
key: 'gpt-4o-mini',
},
{
displayName: 'GPT 4.1 nano',
key: 'gpt-4.1-nano',
},
{
displayName: 'GPT 4.1 mini',
key: 'gpt-4.1-mini',
},
{
displayName: 'GPT 4.1',
key: 'gpt-4.1',
},
];
const openaiEmbeddingModels: Record<string, string>[] = [

View File

@ -1,10 +1,5 @@
import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
export const PROVIDER_INFO = {
key: 'transformers',
displayName: 'Hugging Face',
};
export const loadTransformersEmbeddingsModels = async () => {
try {
const embeddingModels = {

View File

@ -64,7 +64,7 @@ export const getDocumentsFromLinks = async ({ links }: { links: string[] }) => {
const splittedText = await splitter.splitText(parsedText);
const title = res.data
.toString('utf8')
.match(/<title.*>(.*?)<\/title>/)?.[1];
.match(/<title>(.*?)<\/title>/)?.[1];
const linkDocs = splittedText.map((text) => {
return new Document({