mirror of
https://github.com/ItzCrazyKns/Perplexica.git
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Merge pull request #877 from ramkrishna2910/lemonade
Lemonade integration to run local LLMs with NPU and GPU acceleration
This commit is contained in:
23
README.md
23
README.md
@@ -29,6 +29,7 @@
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- [Getting Started with Docker (Recommended)](#getting-started-with-docker-recommended)
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- [Non-Docker Installation](#non-docker-installation)
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- [Ollama Connection Errors](#ollama-connection-errors)
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- [Lemonade Connection Errors](#lemonade-connection-errors)
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- [Using as a Search Engine](#using-as-a-search-engine)
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- [Using Perplexica's API](#using-perplexicas-api)
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- [Expose Perplexica to a network](#expose-perplexica-to-network)
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@@ -89,7 +90,8 @@ There are mainly 2 ways of installing Perplexica - With Docker, Without Docker.
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- `OPENAI`: Your OpenAI API key. **You only need to fill this if you wish to use OpenAI's models**.
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- `CUSTOM_OPENAI`: Your OpenAI-API-compliant local server URL, model name, and API key. You should run your local server with host set to `0.0.0.0`, take note of which port number it is running on, and then use that port number to set `API_URL = http://host.docker.internal:PORT_NUMBER`. You must specify the model name, such as `MODEL_NAME = "unsloth/DeepSeek-R1-0528-Qwen3-8B-GGUF:Q4_K_XL"`. Finally, set `API_KEY` to the appropriate value. If you have not defined an API key, just put anything you want in-between the quotation marks: `API_KEY = "whatever-you-want-but-not-blank"` **You only need to configure these settings if you want to use a local OpenAI-compliant server, such as Llama.cpp's [`llama-server`](https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md)**.
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- `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**.
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- `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.
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- `LEMONADE`: Your Lemonade API URL. Since Lemonade runs directly on your local machine (not in Docker), you should enter it as `http://host.docker.internal:PORT_NUMBER`. If you installed Lemonade on port 8000, use `http://host.docker.internal:8000`. For other ports, adjust accordingly. **You need to fill this if you wish to use Lemonade's models**.
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- `GROQ`: Your Groq API key. **You only need to fill this if you wish to use Groq's hosted models**.`
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- `ANTHROPIC`: Your Anthropic API key. **You only need to fill this if you wish to use Anthropic models**.
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- `Gemini`: Your Gemini API key. **You only need to fill this if you wish to use Google's models**.
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- `DEEPSEEK`: Your Deepseek API key. **Only needed if you want Deepseek models.**
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@@ -150,6 +152,25 @@ If you're encountering an Ollama connection error, it is likely due to the backe
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- Ensure that the port (default is 11434) is not blocked by your firewall.
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#### Lemonade Connection Errors
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If you're encountering a Lemonade connection error, it is likely due to the backend being unable to connect to Lemonade's API. To fix this issue you can:
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1. **Check your Lemonade API URL:** Ensure that the API URL is correctly set in the settings menu.
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2. **Update API URL Based on OS:**
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- **Windows:** Use `http://host.docker.internal:8000`
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- **Mac:** Use `http://host.docker.internal:8000`
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- **Linux:** Use `http://<private_ip_of_host>:8000`
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Adjust the port number if you're using a different one.
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3. **Ensure Lemonade Server is Running:**
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- Make sure your Lemonade server is running and accessible on the configured port (default is 8000).
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- Verify that Lemonade is configured to accept connections from all interfaces (`0.0.0.0`), not just localhost (`127.0.0.1`).
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- Ensure that the port (default is 8000) is not blocked by your firewall.
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## Using as a Search Engine
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If you wish to use Perplexica as an alternative to traditional search engines like Google or Bing, or if you want to add a shortcut for quick access from your browser's search bar, follow these steps:
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@@ -31,5 +31,9 @@ API_KEY = "" # Required to use AI/ML API chat and embedding models
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[MODELS.LM_STUDIO]
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API_URL = "" # LM Studio API URL - http://host.docker.internal:1234
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[MODELS.LEMONADE]
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API_URL = "" # Lemonade API URL - http://host.docker.internal:8000
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API_KEY = "" # Optional API key for Lemonade
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[API_ENDPOINTS]
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SEARXNG = "" # SearxNG API URL - http://localhost:32768
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@@ -10,6 +10,8 @@ import {
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getDeepseekApiKey,
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getAimlApiKey,
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getLMStudioApiEndpoint,
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getLemonadeApiEndpoint,
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getLemonadeApiKey,
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updateConfig,
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getOllamaApiKey,
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} from '@/lib/config';
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@@ -56,6 +58,8 @@ export const GET = async (req: Request) => {
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config['ollamaApiUrl'] = getOllamaApiEndpoint();
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config['ollamaApiKey'] = getOllamaApiKey();
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config['lmStudioApiUrl'] = getLMStudioApiEndpoint();
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config['lemonadeApiUrl'] = getLemonadeApiEndpoint();
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config['lemonadeApiKey'] = getLemonadeApiKey();
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config['anthropicApiKey'] = getAnthropicApiKey();
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config['groqApiKey'] = getGroqApiKey();
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config['geminiApiKey'] = getGeminiApiKey();
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@@ -106,6 +110,10 @@ export const POST = async (req: Request) => {
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LM_STUDIO: {
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API_URL: config.lmStudioApiUrl,
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},
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LEMONADE: {
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API_URL: config.lemonadeApiUrl,
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API_KEY: config.lemonadeApiKey,
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},
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CUSTOM_OPENAI: {
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API_URL: config.customOpenaiApiUrl,
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API_KEY: config.customOpenaiApiKey,
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@@ -23,6 +23,8 @@ interface SettingsType {
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ollamaApiUrl: string;
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ollamaApiKey: string;
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lmStudioApiUrl: string;
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lemonadeApiUrl: string;
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lemonadeApiKey: string;
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deepseekApiKey: string;
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aimlApiKey: string;
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customOpenaiApiKey: string;
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@@ -953,6 +955,48 @@ const Page = () => {
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</div>
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</div>
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</SettingsSection>
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<SettingsSection title="Lemonade">
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<div className="grid grid-cols-1 md:grid-cols-2 gap-4">
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<div className="flex flex-col space-y-1">
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<p className="text-black/70 dark:text-white/70 text-sm">
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Lemonade API URL
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</p>
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<Input
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type="text"
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placeholder="Lemonade API URL"
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value={config.lemonadeApiUrl}
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isSaving={savingStates['lemonadeApiUrl']}
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onChange={(e) => {
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setConfig((prev) => ({
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...prev!,
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lemonadeApiUrl: e.target.value,
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}));
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}}
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onSave={(value) => saveConfig('lemonadeApiUrl', value)}
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/>
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</div>
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<div className="flex flex-col space-y-1">
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<p className="text-black/70 dark:text-white/70 text-sm">
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Lemonade API Key (Optional)
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</p>
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<Input
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type="password"
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placeholder="Lemonade API Key"
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value={config.lemonadeApiKey}
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isSaving={savingStates['lemonadeApiKey']}
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onChange={(e) => {
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setConfig((prev) => ({
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...prev!,
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lemonadeApiKey: e.target.value,
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}));
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}}
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onSave={(value) => saveConfig('lemonadeApiKey', value)}
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/>
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</div>
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</div>
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</SettingsSection>
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</div>
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)
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)}
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@@ -42,6 +42,10 @@ interface Config {
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LM_STUDIO: {
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API_URL: string;
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};
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LEMONADE: {
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API_URL: string;
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API_KEY: string;
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};
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CUSTOM_OPENAI: {
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API_URL: string;
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API_KEY: string;
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@@ -105,6 +109,11 @@ export const getCustomOpenaiModelName = () =>
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export const getLMStudioApiEndpoint = () =>
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loadConfig().MODELS.LM_STUDIO.API_URL;
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export const getLemonadeApiEndpoint = () =>
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loadConfig().MODELS.LEMONADE.API_URL;
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export const getLemonadeApiKey = () => loadConfig().MODELS.LEMONADE.API_KEY;
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const mergeConfigs = (current: any, update: any): any => {
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if (update === null || update === undefined) {
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return current;
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loadLMStudioEmbeddingsModels,
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PROVIDER_INFO as LMStudioInfo,
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} from './lmstudio';
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import {
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loadLemonadeChatModels,
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loadLemonadeEmbeddingModels,
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PROVIDER_INFO as LemonadeInfo,
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} from './lemonade';
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export const PROVIDER_METADATA = {
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openai: OpenAIInfo,
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@@ -56,6 +61,7 @@ export const PROVIDER_METADATA = {
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deepseek: DeepseekInfo,
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aimlapi: AimlApiInfo,
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lmstudio: LMStudioInfo,
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lemonade: LemonadeInfo,
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custom_openai: {
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key: 'custom_openai',
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displayName: 'Custom OpenAI',
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@@ -84,6 +90,7 @@ export const chatModelProviders: Record<
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deepseek: loadDeepseekChatModels,
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aimlapi: loadAimlApiChatModels,
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lmstudio: loadLMStudioChatModels,
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lemonade: loadLemonadeChatModels,
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};
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export const embeddingModelProviders: Record<
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@@ -96,6 +103,7 @@ export const embeddingModelProviders: Record<
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transformers: loadTransformersEmbeddingsModels,
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aimlapi: loadAimlApiEmbeddingModels,
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lmstudio: loadLMStudioEmbeddingsModels,
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lemonade: loadLemonadeEmbeddingModels,
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};
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export const getAvailableChatModelProviders = async () => {
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94
src/lib/providers/lemonade.ts
Normal file
94
src/lib/providers/lemonade.ts
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@@ -0,0 +1,94 @@
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import axios from 'axios';
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import { getLemonadeApiEndpoint, getLemonadeApiKey } from '../config';
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import { ChatModel, EmbeddingModel } from '.';
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export const PROVIDER_INFO = {
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key: 'lemonade',
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displayName: 'Lemonade',
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};
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import { ChatOpenAI } from '@langchain/openai';
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import { OpenAIEmbeddings } from '@langchain/openai';
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export const loadLemonadeChatModels = async () => {
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const lemonadeApiEndpoint = getLemonadeApiEndpoint();
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const lemonadeApiKey = getLemonadeApiKey();
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if (!lemonadeApiEndpoint) return {};
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try {
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const res = await axios.get(`${lemonadeApiEndpoint}/api/v1/models`, {
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headers: {
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'Content-Type': 'application/json',
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...(lemonadeApiKey
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? { Authorization: `Bearer ${lemonadeApiKey}` }
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: {}),
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},
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});
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const { data: models } = res.data;
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const chatModels: Record<string, ChatModel> = {};
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models.forEach((model: any) => {
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chatModels[model.id] = {
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displayName: model.id,
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model: new ChatOpenAI({
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apiKey: lemonadeApiKey || 'lemonade-key',
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modelName: model.id,
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temperature: 0.7,
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configuration: {
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baseURL: `${lemonadeApiEndpoint}/api/v1`,
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},
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}),
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};
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});
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return chatModels;
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} catch (err) {
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console.error(`Error loading Lemonade models: ${err}`);
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return {};
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}
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};
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export const loadLemonadeEmbeddingModels = async () => {
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const lemonadeApiEndpoint = getLemonadeApiEndpoint();
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const lemonadeApiKey = getLemonadeApiKey();
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if (!lemonadeApiEndpoint) return {};
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try {
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const res = await axios.get(`${lemonadeApiEndpoint}/api/v1/models`, {
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headers: {
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'Content-Type': 'application/json',
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...(lemonadeApiKey
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? { Authorization: `Bearer ${lemonadeApiKey}` }
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: {}),
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},
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});
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const { data: models } = res.data;
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const embeddingModels: Record<string, EmbeddingModel> = {};
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// Filter models that support embeddings (if Lemonade provides this info)
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// For now, we'll assume all models can be used for embeddings
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models.forEach((model: any) => {
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embeddingModels[model.id] = {
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displayName: model.id,
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model: new OpenAIEmbeddings({
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apiKey: lemonadeApiKey || 'lemonade-key',
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modelName: model.id,
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configuration: {
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baseURL: `${lemonadeApiEndpoint}/api/v1`,
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},
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}),
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};
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});
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return embeddingModels;
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} catch (err) {
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console.error(`Error loading Lemonade embedding models: ${err}`);
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return {};
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}
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};
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