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3 Commits

Author SHA1 Message Date
ItzCrazyKns
588e68e93e feat(providers): add deepseek provider 2025-04-06 13:37:43 +05:30
ItzCrazyKns
c4440327db Merge pull request #720 from OmarElKadri/master
feat(search): add optional systemInstructions to API request body
2025-04-06 10:34:29 +05:30
OTYAK
64e2d457cc feat(search): add optional systemInstructions to API request body 2025-04-05 19:06:18 +01:00
16 changed files with 360 additions and 325 deletions

1
data/.gitignore vendored
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@ -1,3 +1,2 @@
*
!models.json
!.gitignore

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@ -1,157 +0,0 @@
{
"_comment": "Ollama models are fetched from the Ollama API, so they are not included here.",
"chatModels": {
"openai": [
{
"displayName": "GPT-3.5 Turbo",
"key": "gpt-3.5-turbo"
},
{
"displayName": "GPT-4",
"key": "gpt-4"
},
{
"displayName": "GPT-4 Turbo",
"key": "gpt-4-turbo"
},
{
"displayName": "GPT-4 Omni",
"key": "gpt-4o"
},
{
"displayName": "GPT-4 Omni Mini",
"key": "gpt-4o-mini"
}
],
"groq": [
{
"displayName": "Gemma2 9B IT",
"key": "gemma2-9b-it"
},
{
"displayName": "Llama 3.3 70B Versatile",
"key": "llama-3.3-70b-versatile"
},
{
"displayName": "Llama 3.1 8B Instant",
"key": "llama-3.1-8b-instant"
},
{
"displayName": "Llama3 70B 8192",
"key": "llama3-70b-8192"
},
{
"displayName": "Llama3 8B 8192",
"key": "llama3-8b-8192"
},
{
"displayName": "Mixtral 8x7B 32768",
"key": "mixtral-8x7b-32768"
},
{
"displayName": "Qwen QWQ 32B (Preview)",
"key": "qwen-qwq-32b"
},
{
"displayName": "Mistral Saba 24B (Preview)",
"key": "mistral-saba-24b"
},
{
"displayName": "DeepSeek R1 Distill Llama 70B (Preview)",
"key": "deepseek-r1-distill-llama-70b"
}
],
"gemini": [
{
"displayName": "Gemini 2.5 Pro Experimental",
"key": "gemini-2.5-pro-exp-03-25"
},
{
"displayName": "Gemini 2.0 Flash",
"key": "gemini-2.0-flash"
},
{
"displayName": "Gemini 2.0 Flash-Lite",
"key": "gemini-2.0-flash-lite"
},
{
"displayName": "Gemini 2.0 Flash Thinking Experimental",
"key": "gemini-2.0-flash-thinking-exp-01-21"
},
{
"displayName": "Gemini 1.5 Flash",
"key": "gemini-1.5-flash"
},
{
"displayName": "Gemini 1.5 Flash-8B",
"key": "gemini-1.5-flash-8b"
},
{
"displayName": "Gemini 1.5 Pro",
"key": "gemini-1.5-pro"
}
],
"anthropic": [
{
"displayName": "Claude 3.7 Sonnet",
"key": "claude-3-7-sonnet-20250219"
},
{
"displayName": "Claude 3.5 Haiku",
"key": "claude-3-5-haiku-20241022"
},
{
"displayName": "Claude 3.5 Sonnet v2",
"key": "claude-3-5-sonnet-20241022"
},
{
"displayName": "Claude 3.5 Sonnet",
"key": "claude-3-5-sonnet-20240620"
},
{
"displayName": "Claude 3 Opus",
"key": "claude-3-opus-20240229"
},
{
"displayName": "Claude 3 Sonnet",
"key": "claude-3-sonnet-20240229"
},
{
"displayName": "Claude 3 Haiku",
"key": "claude-3-haiku-20240307"
}
]
},
"embeddingModels": {
"openai": [
{
"displayName": "Text Embedding 3 Large",
"key": "text-embedding-3-large"
},
{
"displayName": "Text Embedding 3 Small",
"key": "text-embedding-3-small"
}
],
"gemini": [
{
"displayName": "Gemini Embedding",
"key": "gemini-embedding-exp"
}
],
"transformers": [
{
"displayName": "BGE Small",
"key": "xenova-bge-small-en-v1.5"
},
{
"displayName": "GTE Small",
"key": "xenova-gte-small"
},
{
"displayName": "Bert Multilingual",
"key": "xenova-bert-base-multilingual-uncased"
}
]
}
}

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@ -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

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@ -22,5 +22,8 @@ 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

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@ -7,6 +7,7 @@ import {
getGroqApiKey,
getOllamaApiEndpoint,
getOpenaiApiKey,
getDeepseekApiKey,
updateConfig,
} from '@/lib/config';
import {
@ -53,6 +54,7 @@ export const GET = async (req: Request) => {
config['anthropicApiKey'] = getAnthropicApiKey();
config['groqApiKey'] = getGroqApiKey();
config['geminiApiKey'] = getGeminiApiKey();
config['deepseekApiKey'] = getDeepseekApiKey();
config['customOpenaiApiUrl'] = getCustomOpenaiApiUrl();
config['customOpenaiApiKey'] = getCustomOpenaiApiKey();
config['customOpenaiModelName'] = getCustomOpenaiModelName();
@ -88,6 +90,9 @@ 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,

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

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@ -20,6 +20,7 @@ interface SettingsType {
anthropicApiKey: string;
geminiApiKey: string;
ollamaApiUrl: string;
deepseekApiKey: string;
customOpenaiApiKey: string;
customOpenaiApiUrl: string;
customOpenaiModelName: string;
@ -838,6 +839,25 @@ 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>

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@ -25,6 +25,9 @@ interface Config {
OLLAMA: {
API_URL: string;
};
DEEPSEEK: {
API_KEY: string;
};
CUSTOM_OPENAI: {
API_URL: string;
API_KEY: string;
@ -63,6 +66,8 @@ 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;

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@ -1,22 +1,48 @@
import { ChatAnthropic } from '@langchain/anthropic';
import { ChatModel, getModelsList, RawModel } from '.';
import { ChatModel } from '.';
import { getAnthropicApiKey } from '../config';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
const loadModels = () => {
return getModelsList()?.['chatModels']['anthropic'] as unknown as RawModel[]
}
const anthropicChatModels: Record<string, string>[] = [
{
displayName: 'Claude 3.7 Sonnet',
key: 'claude-3-7-sonnet-20250219',
},
{
displayName: 'Claude 3.5 Haiku',
key: 'claude-3-5-haiku-20241022',
},
{
displayName: 'Claude 3.5 Sonnet v2',
key: 'claude-3-5-sonnet-20241022',
},
{
displayName: 'Claude 3.5 Sonnet',
key: 'claude-3-5-sonnet-20240620',
},
{
displayName: 'Claude 3 Opus',
key: 'claude-3-opus-20240229',
},
{
displayName: 'Claude 3 Sonnet',
key: 'claude-3-sonnet-20240229',
},
{
displayName: 'Claude 3 Haiku',
key: 'claude-3-haiku-20240307',
},
];
export const loadAnthropicChatModels = async () => {
const anthropicApiKey = getAnthropicApiKey();
if (!anthropicApiKey) return {};
const models = loadModels()
if (!anthropicApiKey) return {};
try {
const chatModels: Record<string, ChatModel> = {};
models.forEach((model) => {
anthropicChatModels.forEach((model) => {
chatModels[model.key] = {
displayName: model.displayName,
model: new ChatAnthropic({

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@ -0,0 +1,44 @@
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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@ -3,24 +3,57 @@ import {
GoogleGenerativeAIEmbeddings,
} from '@langchain/google-genai';
import { getGeminiApiKey } from '../config';
import { ChatModel, EmbeddingModel, getModelsList, RawModel } from '.';
import { ChatModel, EmbeddingModel } from '.';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Embeddings } from '@langchain/core/embeddings';
const loadModels = (modelType: 'chat' | 'embedding') => {
return getModelsList()?.[modelType === 'chat' ? 'chatModels' : 'embeddingModels']['gemini'] as unknown as RawModel[]
}
const geminiChatModels: Record<string, string>[] = [
{
displayName: 'Gemini 2.5 Pro Experimental',
key: 'gemini-2.5-pro-exp-03-25',
},
{
displayName: 'Gemini 2.0 Flash',
key: 'gemini-2.0-flash',
},
{
displayName: 'Gemini 2.0 Flash-Lite',
key: 'gemini-2.0-flash-lite',
},
{
displayName: 'Gemini 2.0 Flash Thinking Experimental',
key: 'gemini-2.0-flash-thinking-exp-01-21',
},
{
displayName: 'Gemini 1.5 Flash',
key: 'gemini-1.5-flash',
},
{
displayName: 'Gemini 1.5 Flash-8B',
key: 'gemini-1.5-flash-8b',
},
{
displayName: 'Gemini 1.5 Pro',
key: 'gemini-1.5-pro',
},
];
const geminiEmbeddingModels: Record<string, string>[] = [
{
displayName: 'Gemini Embedding',
key: 'gemini-embedding-exp',
},
];
export const loadGeminiChatModels = async () => {
const geminiApiKey = getGeminiApiKey();
if (!geminiApiKey) return {};
const models = loadModels('chat');
if (!geminiApiKey) return {};
try {
const chatModels: Record<string, ChatModel> = {};
models.forEach((model) => {
geminiChatModels.forEach((model) => {
chatModels[model.key] = {
displayName: model.displayName,
model: new ChatGoogleGenerativeAI({
@ -40,14 +73,13 @@ export const loadGeminiChatModels = async () => {
export const loadGeminiEmbeddingModels = async () => {
const geminiApiKey = getGeminiApiKey();
if (!geminiApiKey) return {};
const models = loadModels('embedding');
if (!geminiApiKey) return {};
try {
const embeddingModels: Record<string, EmbeddingModel> = {};
models.forEach((model) => {
geminiEmbeddingModels.forEach((model) => {
embeddingModels[model.key] = {
displayName: model.displayName,
model: new GoogleGenerativeAIEmbeddings({

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@ -1,22 +1,88 @@
import { ChatOpenAI } from '@langchain/openai';
import { getGroqApiKey } from '../config';
import { ChatModel, getModelsList, RawModel } from '.';
import { ChatModel } from '.';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
const loadModels = () => {
return getModelsList()?.chatModels['groq'] as unknown as RawModel[]
}
const groqChatModels: Record<string, string>[] = [
{
displayName: 'Gemma2 9B IT',
key: 'gemma2-9b-it',
},
{
displayName: 'Llama 3.3 70B Versatile',
key: 'llama-3.3-70b-versatile',
},
{
displayName: 'Llama 3.1 8B Instant',
key: 'llama-3.1-8b-instant',
},
{
displayName: 'Llama3 70B 8192',
key: 'llama3-70b-8192',
},
{
displayName: 'Llama3 8B 8192',
key: 'llama3-8b-8192',
},
{
displayName: 'Mixtral 8x7B 32768',
key: 'mixtral-8x7b-32768',
},
{
displayName: 'Qwen QWQ 32B (Preview)',
key: 'qwen-qwq-32b',
},
{
displayName: 'Mistral Saba 24B (Preview)',
key: 'mistral-saba-24b',
},
{
displayName: 'Qwen 2.5 Coder 32B (Preview)',
key: 'qwen-2.5-coder-32b',
},
{
displayName: 'Qwen 2.5 32B (Preview)',
key: 'qwen-2.5-32b',
},
{
displayName: 'DeepSeek R1 Distill Qwen 32B (Preview)',
key: 'deepseek-r1-distill-qwen-32b',
},
{
displayName: 'DeepSeek R1 Distill Llama 70B (Preview)',
key: 'deepseek-r1-distill-llama-70b',
},
{
displayName: 'Llama 3.3 70B SpecDec (Preview)',
key: 'llama-3.3-70b-specdec',
},
{
displayName: 'Llama 3.2 1B Preview (Preview)',
key: 'llama-3.2-1b-preview',
},
{
displayName: 'Llama 3.2 3B Preview (Preview)',
key: 'llama-3.2-3b-preview',
},
{
displayName: 'Llama 3.2 11B Vision Preview (Preview)',
key: 'llama-3.2-11b-vision-preview',
},
{
displayName: 'Llama 3.2 90B Vision Preview (Preview)',
key: 'llama-3.2-90b-vision-preview',
},
];
export const loadGroqChatModels = async () => {
const groqApiKey = getGroqApiKey();
if (!groqApiKey) return {};
const models = loadModels()
if (!groqApiKey) return {};
try {
const chatModels: Record<string, ChatModel> = {};
models.forEach((model) => {
groqChatModels.forEach((model) => {
chatModels[model.key] = {
displayName: model.displayName,
model: new ChatOpenAI({

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@ -1,39 +1,27 @@
import { Embeddings } from '@langchain/core/embeddings'
import { BaseChatModel } from '@langchain/core/language_models/chat_models'
import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } from './openai'
import { Embeddings } from '@langchain/core/embeddings';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { loadOpenAIChatModels, loadOpenAIEmbeddingModels } 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 path from 'path'
import fs from 'fs'
} 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 { loadDeepseekChatModels } from './deepseek';
export interface ChatModel {
displayName: string
model: BaseChatModel
displayName: string;
model: BaseChatModel;
}
export interface EmbeddingModel {
displayName: string
model: Embeddings
}
export type RawModel = {
displayName: string
key: string
}
type ModelsList = {
[key in "chatModels" | "embeddingModels"]: {
[key: string]: RawModel[]
}
displayName: string;
model: Embeddings;
}
export const chatModelProviders: Record<
@ -45,7 +33,8 @@ export const chatModelProviders: Record<
groq: loadGroqChatModels,
anthropic: loadAnthropicChatModels,
gemini: loadGeminiChatModels,
}
deepseek: loadDeepseekChatModels,
};
export const embeddingModelProviders: Record<
string,
@ -55,43 +44,21 @@ export const embeddingModelProviders: Record<
ollama: loadOllamaEmbeddingModels,
gemini: loadGeminiEmbeddingModels,
transformers: loadTransformersEmbeddingsModels,
}
export const getModelsList = (): ModelsList | null => {
const modelFile = path.join(process.cwd(), 'data/models.json')
try {
const content = fs.readFileSync(modelFile, 'utf-8')
return JSON.parse(content) as ModelsList
} catch (err) {
console.error(`Error reading models file: ${err}`)
return null
}
}
export const updateModelsList = (models: ModelsList) => {
try {
const modelFile = path.join(process.cwd(), 'data/models.json')
const content = JSON.stringify(models, null, 2)
fs.writeFileSync(modelFile, content, 'utf-8')
} catch(err) {
console.error(`Error updating models file: ${err}`)
}
}
};
export const getAvailableChatModelProviders = async () => {
const models: Record<string, Record<string, ChatModel>> = {}
const models: Record<string, Record<string, ChatModel>> = {};
for (const provider in chatModelProviders) {
const providerModels = await chatModelProviders[provider]()
const providerModels = await chatModelProviders[provider]();
if (Object.keys(providerModels).length > 0) {
models[provider] = providerModels
models[provider] = providerModels;
}
}
const customOpenAiApiKey = getCustomOpenaiApiKey()
const customOpenAiApiUrl = getCustomOpenaiApiUrl()
const customOpenAiModelName = getCustomOpenaiModelName()
const customOpenAiApiKey = getCustomOpenaiApiKey();
const customOpenAiApiUrl = getCustomOpenaiApiUrl();
const customOpenAiModelName = getCustomOpenaiModelName();
models['custom_openai'] = {
...(customOpenAiApiKey && customOpenAiApiUrl && customOpenAiModelName
@ -109,20 +76,20 @@ export const getAvailableChatModelProviders = async () => {
},
}
: {}),
}
};
return models
}
return models;
};
export const getAvailableEmbeddingModelProviders = async () => {
const models: Record<string, Record<string, EmbeddingModel>> = {}
const models: Record<string, Record<string, EmbeddingModel>> = {};
for (const provider in embeddingModelProviders) {
const providerModels = await embeddingModelProviders[provider]()
const providerModels = await embeddingModelProviders[provider]();
if (Object.keys(providerModels).length > 0) {
models[provider] = providerModels
models[provider] = providerModels;
}
}
return models
}
return models;
};

View File

@ -1,39 +1,24 @@
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'
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 loadOllamaChatModels = async () => {
const ollamaApiEndpoint = getOllamaApiEndpoint();
if (!ollamaApiEndpoint) return {};
const loadModels = async (apiURL: string) => {
try {
const res = await axios.get(`${apiURL}/api/tags`, {
const res = await axios.get(`${ollamaApiEndpoint}/api/tags`, {
headers: {
'Content-Type': 'application/json',
},
})
});
if (res.status !== 200) {
console.error(`Failed to load Ollama models: ${res.data}`)
return []
}
const { models } = res.data;
const { models } = res.data
return models
} catch (err) {
console.error(`Error loading Ollama models: ${err}`)
return []
}
}
export const loadOllamaChatModels = async () => {
const ollamaApiEndpoint = getOllamaApiEndpoint()
if (!ollamaApiEndpoint) return {}
const models = await loadModels(ollamaApiEndpoint)
try {
const chatModels: Record<string, ChatModel> = {}
const chatModels: Record<string, ChatModel> = {};
models.forEach((model: any) => {
chatModels[model.model] = {
@ -44,24 +29,31 @@ export const loadOllamaChatModels = async () => {
temperature: 0.7,
keepAlive: getKeepAlive(),
}),
}
})
};
});
return chatModels
return chatModels;
} catch (err) {
console.error(`Error loading Ollama models: ${err}`)
return {}
console.error(`Error loading Ollama models: ${err}`);
return {};
}
}
};
export const loadOllamaEmbeddingModels = async () => {
const ollamaApiEndpoint = getOllamaApiEndpoint()
if (!ollamaApiEndpoint) return {}
const ollamaApiEndpoint = getOllamaApiEndpoint();
const models = await loadModels(ollamaApiEndpoint)
if (!ollamaApiEndpoint) return {};
try {
const embeddingModels: Record<string, EmbeddingModel> = {}
const res = await axios.get(`${ollamaApiEndpoint}/api/tags`, {
headers: {
'Content-Type': 'application/json',
},
});
const { models } = res.data;
const embeddingModels: Record<string, EmbeddingModel> = {};
models.forEach((model: any) => {
embeddingModels[model.model] = {
@ -70,12 +62,12 @@ export const loadOllamaEmbeddingModels = async () => {
baseUrl: ollamaApiEndpoint,
model: model.model,
}),
}
})
};
});
return embeddingModels
return embeddingModels;
} catch (err) {
console.error(`Error loading Ollama embeddings models: ${err}`)
return {}
console.error(`Error loading Ollama embeddings models: ${err}`);
return {};
}
}
};

View File

@ -1,23 +1,52 @@
import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai';
import { getOpenaiApiKey } from '../config';
import { ChatModel, EmbeddingModel, getModelsList, RawModel } from '.';
import { ChatModel, EmbeddingModel } from '.';
import { BaseChatModel } from '@langchain/core/language_models/chat_models';
import { Embeddings } from '@langchain/core/embeddings';
const loadModels = (modelType: 'chat' | 'embedding') => {
return getModelsList()?.[modelType === 'chat' ? 'chatModels' : 'embeddingModels']['openai'] as unknown as RawModel[]
}
const openaiChatModels: Record<string, string>[] = [
{
displayName: 'GPT-3.5 Turbo',
key: 'gpt-3.5-turbo',
},
{
displayName: 'GPT-4',
key: 'gpt-4',
},
{
displayName: 'GPT-4 turbo',
key: 'gpt-4-turbo',
},
{
displayName: 'GPT-4 omni',
key: 'gpt-4o',
},
{
displayName: 'GPT-4 omni mini',
key: 'gpt-4o-mini',
},
];
const openaiEmbeddingModels: Record<string, string>[] = [
{
displayName: 'Text Embedding 3 Small',
key: 'text-embedding-3-small',
},
{
displayName: 'Text Embedding 3 Large',
key: 'text-embedding-3-large',
},
];
export const loadOpenAIChatModels = async () => {
const openaiApiKey = getOpenaiApiKey();
const models = loadModels('chat');
if (!openaiApiKey || !models) return {};
if (!openaiApiKey) return {};
try {
const chatModels: Record<string, ChatModel> = {};
models.forEach((model) => {
openaiChatModels.forEach((model) => {
chatModels[model.key] = {
displayName: model.displayName,
model: new ChatOpenAI({
@ -37,14 +66,13 @@ export const loadOpenAIChatModels = async () => {
export const loadOpenAIEmbeddingModels = async () => {
const openaiApiKey = getOpenaiApiKey();
const models = loadModels('embedding');
if (!openaiApiKey || !models) return {};
if (!openaiApiKey) return {};
try {
const embeddingModels: Record<string, EmbeddingModel> = {};
models.forEach((model) => {
openaiEmbeddingModels.forEach((model) => {
embeddingModels[model.key] = {
displayName: model.displayName,
model: new OpenAIEmbeddings({

View File

@ -1,30 +1,31 @@
import { EmbeddingModel, getModelsList, RawModel } from '.'
import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer'
const loadModels = () => {
return getModelsList()?.embeddingModels[
'transformers'
] as unknown as RawModel[]
}
import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer';
export const loadTransformersEmbeddingsModels = async () => {
try {
const models = loadModels()
const embeddingModels: Record<string, EmbeddingModel> = {}
models.forEach(model => {
embeddingModels[model.key] = {
displayName: model.displayName,
const embeddingModels = {
'xenova-bge-small-en-v1.5': {
displayName: 'BGE Small',
model: new HuggingFaceTransformersEmbeddings({
modelName: model.key,
modelName: 'Xenova/bge-small-en-v1.5',
}),
}
})
},
'xenova-gte-small': {
displayName: 'GTE Small',
model: new HuggingFaceTransformersEmbeddings({
modelName: 'Xenova/gte-small',
}),
},
'xenova-bert-base-multilingual-uncased': {
displayName: 'Bert Multilingual',
model: new HuggingFaceTransformersEmbeddings({
modelName: 'Xenova/bert-base-multilingual-uncased',
}),
},
};
return embeddingModels
return embeddingModels;
} catch (err) {
console.error(`Error loading Transformers embeddings model: ${err}`)
return {}
console.error(`Error loading Transformers embeddings model: ${err}`);
return {};
}
}
};