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53b49845b2
Author | SHA1 | Date | |
---|---|---|---|
|
53b49845b2 |
16
README.md
16
README.md
@ -1,5 +1,21 @@
|
||||
# 🚀 Perplexica - An AI-powered search engine 🔎 <!-- omit in toc -->
|
||||
|
||||
<div align="center" markdown="1">
|
||||
<sup>Special thanks to:</sup>
|
||||
<br>
|
||||
<br>
|
||||
<a href="https://www.warp.dev/perplexica">
|
||||
<img alt="Warp sponsorship" width="400" src="https://github.com/user-attachments/assets/775dd593-9b5f-40f1-bf48-479faff4c27b">
|
||||
</a>
|
||||
|
||||
### [Warp, the AI Devtool that lives in your terminal](https://www.warp.dev/perplexica)
|
||||
|
||||
[Available for MacOS, Linux, & Windows](https://www.warp.dev/perplexica)
|
||||
|
||||
</div>
|
||||
|
||||
<hr/>
|
||||
|
||||
[](https://discord.gg/26aArMy8tT)
|
||||
|
||||

|
||||
|
@ -25,8 +25,5 @@ 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
|
@ -8,7 +8,6 @@ import {
|
||||
getOllamaApiEndpoint,
|
||||
getOpenaiApiKey,
|
||||
getDeepseekApiKey,
|
||||
getLMStudioApiEndpoint,
|
||||
updateConfig,
|
||||
} from '@/lib/config';
|
||||
import {
|
||||
@ -52,7 +51,6 @@ export const GET = async (req: Request) => {
|
||||
|
||||
config['openaiApiKey'] = getOpenaiApiKey();
|
||||
config['ollamaApiUrl'] = getOllamaApiEndpoint();
|
||||
config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
|
||||
config['anthropicApiKey'] = getAnthropicApiKey();
|
||||
config['groqApiKey'] = getGroqApiKey();
|
||||
config['geminiApiKey'] = getGeminiApiKey();
|
||||
@ -95,9 +93,6 @@ export const POST = async (req: Request) => {
|
||||
DEEPSEEK: {
|
||||
API_KEY: config.deepseekApiKey,
|
||||
},
|
||||
LM_STUDIO: {
|
||||
API_URL: config.lmStudioApiUrl,
|
||||
},
|
||||
CUSTOM_OPENAI: {
|
||||
API_URL: config.customOpenaiApiUrl,
|
||||
API_KEY: config.customOpenaiApiKey,
|
||||
|
@ -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: {
|
||||
@ -21,7 +20,6 @@ interface SettingsType {
|
||||
anthropicApiKey: string;
|
||||
geminiApiKey: string;
|
||||
ollamaApiUrl: string;
|
||||
lmStudioApiUrl: string;
|
||||
deepseekApiKey: string;
|
||||
customOpenaiApiKey: string;
|
||||
customOpenaiApiUrl: string;
|
||||
@ -550,9 +548,8 @@ const Page = () => {
|
||||
(provider) => ({
|
||||
value: provider,
|
||||
label:
|
||||
(PROVIDER_METADATA as any)[provider]?.displayName ||
|
||||
provider.charAt(0).toUpperCase() +
|
||||
provider.slice(1),
|
||||
provider.slice(1),
|
||||
}),
|
||||
)}
|
||||
/>
|
||||
@ -693,9 +690,8 @@ const Page = () => {
|
||||
(provider) => ({
|
||||
value: provider,
|
||||
label:
|
||||
(PROVIDER_METADATA as any)[provider]?.displayName ||
|
||||
provider.charAt(0).toUpperCase() +
|
||||
provider.slice(1),
|
||||
provider.slice(1),
|
||||
}),
|
||||
)}
|
||||
/>
|
||||
@ -862,25 +858,6 @@ const Page = () => {
|
||||
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>
|
||||
|
@ -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 {
|
||||
@ -35,9 +28,6 @@ interface Config {
|
||||
DEEPSEEK: {
|
||||
API_KEY: string;
|
||||
};
|
||||
LM_STUDIO: {
|
||||
API_URL: string;
|
||||
};
|
||||
CUSTOM_OPENAI: {
|
||||
API_URL: string;
|
||||
API_KEY: string;
|
||||
@ -53,17 +43,10 @@ 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;
|
||||
@ -94,9 +77,6 @@ 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 +109,10 @@ 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),
|
||||
);
|
||||
};
|
||||
|
@ -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>[] = [
|
||||
|
@ -3,11 +3,6 @@ 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)',
|
||||
|
@ -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';
|
||||
|
||||
|
@ -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>[] = [
|
||||
|
@ -1,60 +1,18 @@
|
||||
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';
|
||||
import { loadDeepseekChatModels } from './deepseek';
|
||||
|
||||
export interface ChatModel {
|
||||
displayName: string;
|
||||
@ -76,7 +34,6 @@ export const chatModelProviders: Record<
|
||||
anthropic: loadAnthropicChatModels,
|
||||
gemini: loadGeminiChatModels,
|
||||
deepseek: loadDeepseekChatModels,
|
||||
lmstudio: loadLMStudioChatModels,
|
||||
};
|
||||
|
||||
export const embeddingModelProviders: Record<
|
||||
@ -87,7 +44,6 @@ export const embeddingModelProviders: Record<
|
||||
ollama: loadOllamaEmbeddingModels,
|
||||
gemini: loadGeminiEmbeddingModels,
|
||||
transformers: loadTransformersEmbeddingsModels,
|
||||
lmstudio: loadLMStudioEmbeddingsModels,
|
||||
};
|
||||
|
||||
export const getAvailableChatModelProviders = async () => {
|
||||
|
@ -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 {};
|
||||
}
|
||||
};
|
@ -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';
|
||||
|
||||
|
@ -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>[] = [
|
||||
|
@ -1,10 +1,5 @@
|
||||
import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
|
||||
|
||||
export const PROVIDER_INFO = {
|
||||
key: 'transformers',
|
||||
displayName: 'Hugging Face',
|
||||
};
|
||||
|
||||
export const loadTransformersEmbeddingsModels = async () => {
|
||||
try {
|
||||
const embeddingModels = {
|
||||
|
@ -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({
|
||||
|
Reference in New Issue
Block a user