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3 Commits

Author SHA1 Message Date
Naman Bansal
3509f84cc6 Merge 7288c97326 into a8d410bc2f 2025-04-02 12:30:53 +05:30
namanb
7288c97326 feat(providers): changed readme as well 2025-04-02 12:26:38 +05:30
namanb
3545137bc0 feat(providers): added openrouter support 2025-04-02 12:24:27 +05:30
15 changed files with 105 additions and 126 deletions

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@@ -89,6 +89,7 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
- `OPENAI`: Your OpenAI API key. **You only need to fill this if you wish to use OpenAI's models**.
- `OLLAMA`: Your Ollama API URL. You should enter it as `http://host.docker.internal:PORT_NUMBER`. If you installed Ollama on port 11434, use `http://host.docker.internal:11434`. For other ports, adjust accordingly. **You need to fill this if you wish to use Ollama's models instead of OpenAI's**.
- `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.
- `OPENROUTER`: Your OpenRouter API key. **You only need to fill this if you wish to use models via OpenRouter**.
- `ANTHROPIC`: Your Anthropic API key. **You only need to fill this if you wish to use Anthropic models**.
**Note**: You can change these after starting Perplexica from the settings dialog.

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@@ -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

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

View File

@@ -11,6 +11,9 @@ API_KEY = ""
[MODELS.ANTHROPIC]
API_KEY = ""
[MODELS.OPENROUTER]
API_KEY = ""
[MODELS.GEMINI]
API_KEY = ""
@@ -22,8 +25,5 @@ MODEL_NAME = ""
[MODELS.OLLAMA]
API_URL = "" # Ollama API URL - http://host.docker.internal:11434
[MODELS.DEEPSEEK]
API_KEY = ""
[API_ENDPOINTS]
SEARXNG = "" # SearxNG API URL - http://localhost:32768

View File

@@ -5,9 +5,9 @@ import {
getCustomOpenaiModelName,
getGeminiApiKey,
getGroqApiKey,
getOpenrouterApiKey,
getOllamaApiEndpoint,
getOpenaiApiKey,
getDeepseekApiKey,
updateConfig,
} from '@/lib/config';
import {
@@ -53,8 +53,8 @@ export const GET = async (req: Request) => {
config['ollamaApiUrl'] = getOllamaApiEndpoint();
config['anthropicApiKey'] = getAnthropicApiKey();
config['groqApiKey'] = getGroqApiKey();
config['openrouterApiKey'] = getOpenrouterApiKey();
config['geminiApiKey'] = getGeminiApiKey();
config['deepseekApiKey'] = getDeepseekApiKey();
config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
config['customOpenaiModelName'] = getCustomOpenaiModelName();
@@ -81,6 +81,9 @@ export const POST = async (req: Request) => {
GROQ: {
API_KEY: config.groqApiKey,
},
OPENROUTER: {
API_KEY: config.openrouterApiKey,
},
ANTHROPIC: {
API_KEY: config.anthropicApiKey,
},
@@ -90,9 +93,6 @@ export const POST = async (req: Request) => {
OLLAMA: {
API_URL: config.ollamaApiUrl,
},
DEEPSEEK: {
API_KEY: config.deepseekApiKey,
},
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

@@ -17,10 +17,10 @@ interface SettingsType {
};
openaiApiKey: string;
groqApiKey: string;
openrouterApiKey: string;
anthropicApiKey: string;
geminiApiKey: string;
ollamaApiUrl: string;
deepseekApiKey: string;
customOpenaiApiKey: string;
customOpenaiApiUrl: string;
customOpenaiModelName: string;
@@ -802,6 +802,25 @@ const Page = () => {
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
OpenRouter API Key
</p>
<Input
type="text"
placeholder="OpenRouter API Key"
value={config.openrouterApiKey}
isSaving={savingStates['openrouterApiKey']}
onChange={(e) => {
setConfig((prev) => ({
...prev!,
openrouterApiKey: e.target.value,
}));
}}
onSave={(value) => saveConfig('openrouterApiKey', value)}
/>
</div>
<div className="flex flex-col space-y-1">
<p className="text-black/70 dark:text-white/70 text-sm">
Anthropic API Key
@@ -839,25 +858,6 @@ 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>
</SettingsSection>
</div>

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;
@@ -68,33 +67,11 @@ 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>`,
),
);
return;

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@@ -25,7 +25,7 @@ interface Config {
OLLAMA: {
API_URL: string;
};
DEEPSEEK: {
OPENROUTER: {
API_KEY: string;
};
CUSTOM_OPENAI: {
@@ -57,6 +57,8 @@ export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
export const getOpenrouterApiKey = () => loadConfig().MODELS.OPENROUTER.API_KEY;
export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
@@ -66,8 +68,6 @@ 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;

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@@ -1,6 +1,6 @@
export const webSearchRetrieverPrompt = `
You are an AI question rephraser. You will be given a conversation and a follow-up question, you will have to rephrase the follow up question so it is a standalone question and can be used by another LLM to search the web for information to answer it.
If it is a simple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
If it is a smple writing task or a greeting (unless the greeting contains a question after it) like Hi, Hello, How are you, etc. than a question then you need to return \`not_needed\` as the response (This is because the LLM won't need to search the web for finding information on this topic).
If the user asks some question from some URL or wants you to summarize a PDF or a webpage (via URL) you need to return the links inside the \`links\` XML block and the question inside the \`question\` XML block. If the user wants to you to summarize the webpage or the PDF you need to return \`summarize\` inside the \`question\` XML block in place of a question and the link to summarize in the \`links\` XML block.
You must always return the rephrased question inside the \`question\` XML block, if there are no links in the follow-up question then don't insert a \`links\` XML block in your response.

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@@ -1,44 +0,0 @@
import { ChatOpenAI } from '@langchain/openai';
import { getDeepseekApiKey } from '../config';
import { ChatModel } from '.';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
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 {};
}
};

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@@ -40,12 +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

@@ -72,14 +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

@@ -12,7 +12,7 @@ import { loadGroqChatModels } from './groq';
import { loadAnthropicChatModels } from './anthropic';
import { loadGeminiChatModels, loadGeminiEmbeddingModels } from './gemini';
import { loadTransformersEmbeddingsModels } from './transformers';
import { loadDeepseekChatModels } from './deepseek';
import { loadOpenrouterChatModels } from '@/lib/providers/openrouter';
export interface ChatModel {
displayName: string;
@@ -33,7 +33,7 @@ export const chatModelProviders: Record<
groq: loadGroqChatModels,
anthropic: loadAnthropicChatModels,
gemini: loadGeminiChatModels,
deepseek: loadDeepseekChatModels,
openrouter: loadOpenrouterChatModels,
};
export const embeddingModelProviders: Record<

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@@ -0,0 +1,61 @@
import { ChatOpenAI } from '@langchain/openai';
import { getOpenrouterApiKey } from '../config';
import { ChatModel } from '.';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
let openrouterChatModels: Record<string, string>[] = [];
async function fetchModelList(): Promise<void> {
try {
const response = await fetch('https://openrouter.ai/api/v1/models', {
method: 'GET',
headers: {
'Content-Type': 'application/json',
},
});
if (!response.ok) {
throw new Error(`API request failed with status: ${response.status}`);
}
const data = await response.json();
openrouterChatModels = data.data.map((model: any) => ({
displayName: model.name,
key: model.id,
}));
} catch (error) {
console.error('Error fetching models:', error);
}
}
export const loadOpenrouterChatModels = async () => {
await fetchModelList();
const openrouterApikey = getOpenrouterApiKey();
if (!openrouterApikey) return {};
try {
const chatModels: Record<string, ChatModel> = {};
openrouterChatModels.forEach((model) => {
chatModels[model.key] = {
displayName: model.displayName,
model: new ChatOpenAI({
openAIApiKey: openrouterApikey,
modelName: model.key,
temperature: 0.7,
configuration: {
baseURL: 'https://openrouter.ai/api/v1',
},
}) as unknown as BaseChatModel,
};
});
return chatModels;
} catch (err) {
console.error(`Error loading Openrouter models: ${err}`);
return {};
}
};