From 25b5dbd63e9733766c2e0a90e3ac13522b43d4a7 Mon Sep 17 00:00:00 2001 From: ItzCrazyKns Date: Sat, 6 Jul 2024 14:19:33 +0530 Subject: [PATCH 1/3] feat(providers): separate each provider --- README.md | 6 +- backend.dockerfile | 2 +- src/lib/providers.ts | 187 ------------------------------ src/lib/providers/groq.ts | 57 +++++++++ src/lib/providers/index.ts | 36 ++++++ src/lib/providers/ollama.ts | 59 ++++++++++ src/lib/providers/openai.ts | 59 ++++++++++ src/lib/providers/transformers.ts | 23 ++++ 8 files changed, 238 insertions(+), 191 deletions(-) delete mode 100644 src/lib/providers.ts create mode 100644 src/lib/providers/groq.ts create mode 100644 src/lib/providers/index.ts create mode 100644 src/lib/providers/ollama.ts create mode 100644 src/lib/providers/openai.ts create mode 100644 src/lib/providers/transformers.ts diff --git a/README.md b/README.md index 9e7f7d8..d1388b0 100644 --- a/README.md +++ b/README.md @@ -145,9 +145,9 @@ If you find Perplexica useful, consider giving us a star on GitHub. This helps m We also accept donations to help sustain our project. If you would like to contribute, you can use the following options to donate. Thank you for your support! -| Cards | Ethereum | -|---|---| -| https://www.patreon.com/itzcrazykns | Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` | +| Cards | Ethereum | +| ----------------------------------- | ----------------------------------------------------- | +| https://www.patreon.com/itzcrazykns | Address: `0xB025a84b2F269570Eb8D4b05DEdaA41D8525B6DD` | ## Contribution diff --git a/backend.dockerfile b/backend.dockerfile index 4886573..910aae7 100644 --- a/backend.dockerfile +++ b/backend.dockerfile @@ -1,4 +1,4 @@ -FROM node:slim +FROM node:buster-slim ARG SEARXNG_API_URL diff --git a/src/lib/providers.ts b/src/lib/providers.ts deleted file mode 100644 index 3223193..0000000 --- a/src/lib/providers.ts +++ /dev/null @@ -1,187 +0,0 @@ -import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai'; -import { ChatOllama } from '@langchain/community/chat_models/ollama'; -import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama'; -import { HuggingFaceTransformersEmbeddings } from './huggingfaceTransformer'; -import { - getGroqApiKey, - getOllamaApiEndpoint, - getOpenaiApiKey, -} from '../config'; -import logger from '../utils/logger'; - -export const getAvailableChatModelProviders = async () => { - const openAIApiKey = getOpenaiApiKey(); - const groqApiKey = getGroqApiKey(); - const ollamaEndpoint = getOllamaApiEndpoint(); - - const models = {}; - - if (openAIApiKey) { - try { - models['openai'] = { - 'GPT-3.5 turbo': new ChatOpenAI({ - openAIApiKey, - modelName: 'gpt-3.5-turbo', - temperature: 0.7, - }), - 'GPT-4': new ChatOpenAI({ - openAIApiKey, - modelName: 'gpt-4', - temperature: 0.7, - }), - 'GPT-4 turbo': new ChatOpenAI({ - openAIApiKey, - modelName: 'gpt-4-turbo', - temperature: 0.7, - }), - 'GPT-4 omni': new ChatOpenAI({ - openAIApiKey, - modelName: 'gpt-4o', - temperature: 0.7, - }), - }; - } catch (err) { - logger.error(`Error loading OpenAI models: ${err}`); - } - } - - if (groqApiKey) { - try { - models['groq'] = { - 'LLaMA3 8b': new ChatOpenAI( - { - openAIApiKey: groqApiKey, - modelName: 'llama3-8b-8192', - temperature: 0.7, - }, - { - baseURL: 'https://api.groq.com/openai/v1', - }, - ), - 'LLaMA3 70b': new ChatOpenAI( - { - openAIApiKey: groqApiKey, - modelName: 'llama3-70b-8192', - temperature: 0.7, - }, - { - baseURL: 'https://api.groq.com/openai/v1', - }, - ), - 'Mixtral 8x7b': new ChatOpenAI( - { - openAIApiKey: groqApiKey, - modelName: 'mixtral-8x7b-32768', - temperature: 0.7, - }, - { - baseURL: 'https://api.groq.com/openai/v1', - }, - ), - 'Gemma 7b': new ChatOpenAI( - { - openAIApiKey: groqApiKey, - modelName: 'gemma-7b-it', - temperature: 0.7, - }, - { - baseURL: 'https://api.groq.com/openai/v1', - }, - ), - }; - } catch (err) { - logger.error(`Error loading Groq models: ${err}`); - } - } - - if (ollamaEndpoint) { - try { - const response = await fetch(`${ollamaEndpoint}/api/tags`, { - headers: { - 'Content-Type': 'application/json', - }, - }); - - const { models: ollamaModels } = (await response.json()) as any; - - models['ollama'] = ollamaModels.reduce((acc, model) => { - acc[model.model] = new ChatOllama({ - baseUrl: ollamaEndpoint, - model: model.model, - temperature: 0.7, - }); - return acc; - }, {}); - } catch (err) { - logger.error(`Error loading Ollama models: ${err}`); - } - } - - models['custom_openai'] = {}; - - return models; -}; - -export const getAvailableEmbeddingModelProviders = async () => { - const openAIApiKey = getOpenaiApiKey(); - const ollamaEndpoint = getOllamaApiEndpoint(); - - const models = {}; - - if (openAIApiKey) { - try { - models['openai'] = { - 'Text embedding 3 small': new OpenAIEmbeddings({ - openAIApiKey, - modelName: 'text-embedding-3-small', - }), - 'Text embedding 3 large': new OpenAIEmbeddings({ - openAIApiKey, - modelName: 'text-embedding-3-large', - }), - }; - } catch (err) { - logger.error(`Error loading OpenAI embeddings: ${err}`); - } - } - - if (ollamaEndpoint) { - try { - const response = await fetch(`${ollamaEndpoint}/api/tags`, { - headers: { - 'Content-Type': 'application/json', - }, - }); - - const { models: ollamaModels } = (await response.json()) as any; - - models['ollama'] = ollamaModels.reduce((acc, model) => { - acc[model.model] = new OllamaEmbeddings({ - baseUrl: ollamaEndpoint, - model: model.model, - }); - return acc; - }, {}); - } catch (err) { - logger.error(`Error loading Ollama embeddings: ${err}`); - } - } - - try { - models['local'] = { - 'BGE Small': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/bge-small-en-v1.5', - }), - 'GTE Small': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/gte-small', - }), - 'Bert Multilingual': new HuggingFaceTransformersEmbeddings({ - modelName: 'Xenova/bert-base-multilingual-uncased', - }), - }; - } catch (err) { - logger.error(`Error loading local embeddings: ${err}`); - } - - return models; -}; diff --git a/src/lib/providers/groq.ts b/src/lib/providers/groq.ts new file mode 100644 index 0000000..ecdce4d --- /dev/null +++ b/src/lib/providers/groq.ts @@ -0,0 +1,57 @@ +import { ChatOpenAI } from '@langchain/openai'; +import { getGroqApiKey } from '../../config'; +import logger from '../../utils/logger'; + +export const loadGroqChatModels = async () => { + const groqApiKey = getGroqApiKey(); + + try { + const chatModels = { + 'LLaMA3 8b': new ChatOpenAI( + { + openAIApiKey: groqApiKey, + modelName: 'llama3-8b-8192', + temperature: 0.7, + }, + { + baseURL: 'https://api.groq.com/openai/v1', + }, + ), + 'LLaMA3 70b': new ChatOpenAI( + { + openAIApiKey: groqApiKey, + modelName: 'llama3-70b-8192', + temperature: 0.7, + }, + { + baseURL: 'https://api.groq.com/openai/v1', + }, + ), + 'Mixtral 8x7b': new ChatOpenAI( + { + openAIApiKey: groqApiKey, + modelName: 'mixtral-8x7b-32768', + temperature: 0.7, + }, + { + baseURL: 'https://api.groq.com/openai/v1', + }, + ), + 'Gemma 7b': new ChatOpenAI( + { + openAIApiKey: groqApiKey, + modelName: 'gemma-7b-it', + temperature: 0.7, + }, + { + baseURL: 'https://api.groq.com/openai/v1', + }, + ), + }; + + return chatModels; + } catch (err) { + logger.error(`Error loading Groq models: ${err}`); + return {}; + } +}; diff --git a/src/lib/providers/index.ts b/src/lib/providers/index.ts new file mode 100644 index 0000000..5807f94 --- /dev/null +++ b/src/lib/providers/index.ts @@ -0,0 +1,36 @@ +import { loadGroqChatModels } from './groq'; +import { loadOllamaChatModels } from './ollama'; +import { loadOpenAIChatModels, loadOpenAIEmbeddingsModel } from './openai'; +import { loadTransformersEmbeddingsModel } from './transformers'; + +const chatModelProviders = { + openai: loadOpenAIChatModels, + groq: loadGroqChatModels, + ollama: loadOllamaChatModels, +}; + +const embeddingModelProviders = { + openai: loadOpenAIEmbeddingsModel, + local: loadTransformersEmbeddingsModel, + ollama: loadOllamaChatModels, +}; + +export const getAvailableChatModelProviders = async () => { + const models = {}; + + for (const provider in chatModelProviders) { + models[provider] = await chatModelProviders[provider](); + } + + return models; +}; + +export const getAvailableEmbeddingModelProviders = async () => { + const models = {}; + + for (const provider in embeddingModelProviders) { + models[provider] = await embeddingModelProviders[provider](); + } + + return models; +}; diff --git a/src/lib/providers/ollama.ts b/src/lib/providers/ollama.ts new file mode 100644 index 0000000..febe5e8 --- /dev/null +++ b/src/lib/providers/ollama.ts @@ -0,0 +1,59 @@ +import { OllamaEmbeddings } from '@langchain/community/embeddings/ollama'; +import { getOllamaApiEndpoint } from '../../config'; +import logger from '../../utils/logger'; +import { ChatOllama } from '@langchain/community/chat_models/ollama'; + +export const loadOllamaChatModels = async () => { + const ollamaEndpoint = getOllamaApiEndpoint(); + + try { + const response = await fetch(`${ollamaEndpoint}/api/tags`, { + headers: { + 'Content-Type': 'application/json', + }, + }); + + const { models: ollamaModels } = (await response.json()) as any; + + const chatModels = ollamaModels.reduce((acc, model) => { + acc[model.model] = new ChatOllama({ + baseUrl: ollamaEndpoint, + model: model.model, + temperature: 0.7, + }); + return acc; + }, {}); + + return chatModels; + } catch (err) { + logger.error(`Error loading Ollama models: ${err}`); + return {}; + } +}; + +export const loadOpenAIEmbeddingsModel = async () => { + const ollamaEndpoint = getOllamaApiEndpoint(); + + try { + const response = await fetch(`${ollamaEndpoint}/api/tags`, { + headers: { + 'Content-Type': 'application/json', + }, + }); + + const { models: ollamaModels } = (await response.json()) as any; + + const embeddingsModels = ollamaModels.reduce((acc, model) => { + acc[model.model] = new OllamaEmbeddings({ + baseUrl: ollamaEndpoint, + model: model.model, + }); + return acc; + }, {}); + + return embeddingsModels; + } catch (err) { + logger.error(`Error loading Ollama embeddings model: ${err}`); + return {}; + } +}; diff --git a/src/lib/providers/openai.ts b/src/lib/providers/openai.ts new file mode 100644 index 0000000..705f1a4 --- /dev/null +++ b/src/lib/providers/openai.ts @@ -0,0 +1,59 @@ +import { ChatOpenAI, OpenAIEmbeddings } from '@langchain/openai'; +import { getOpenaiApiKey } from '../../config'; +import logger from '../../utils/logger'; + +export const loadOpenAIChatModels = async () => { + const openAIApiKey = getOpenaiApiKey(); + + try { + const chatModels = { + 'GPT-3.5 turbo': new ChatOpenAI({ + openAIApiKey, + modelName: 'gpt-3.5-turbo', + temperature: 0.7, + }), + 'GPT-4': new ChatOpenAI({ + openAIApiKey, + modelName: 'gpt-4', + temperature: 0.7, + }), + 'GPT-4 turbo': new ChatOpenAI({ + openAIApiKey, + modelName: 'gpt-4-turbo', + temperature: 0.7, + }), + 'GPT-4 omni': new ChatOpenAI({ + openAIApiKey, + modelName: 'gpt-4o', + temperature: 0.7, + }), + }; + + return chatModels; + } catch (err) { + logger.error(`Error loading OpenAI models: ${err}`); + return {}; + } +}; + +export const loadOpenAIEmbeddingsModel = async () => { + const openAIApiKey = getOpenaiApiKey(); + + try { + const embeddingModels = { + 'Text embedding 3 small': new OpenAIEmbeddings({ + openAIApiKey, + modelName: 'text-embedding-3-small', + }), + 'Text embedding 3 large': new OpenAIEmbeddings({ + openAIApiKey, + modelName: 'text-embedding-3-large', + }), + }; + + return embeddingModels; + } catch (err) { + logger.error(`Error loading OpenAI embeddings model: ${err}`); + return {}; + } +}; diff --git a/src/lib/providers/transformers.ts b/src/lib/providers/transformers.ts new file mode 100644 index 0000000..7ef8596 --- /dev/null +++ b/src/lib/providers/transformers.ts @@ -0,0 +1,23 @@ +import logger from '../../utils/logger'; +import { HuggingFaceTransformersEmbeddings } from '../huggingfaceTransformer'; + +export const loadTransformersEmbeddingsModel = async () => { + try { + const embeddingModels = { + 'BGE Small': new HuggingFaceTransformersEmbeddings({ + modelName: 'Xenova/bge-small-en-v1.5', + }), + 'GTE Small': new HuggingFaceTransformersEmbeddings({ + modelName: 'Xenova/gte-small', + }), + 'Bert Multilingual': new HuggingFaceTransformersEmbeddings({ + modelName: 'Xenova/bert-base-multilingual-uncased', + }), + }; + + return embeddingModels; + } catch (err) { + logger.error(`Error loading Transformers embeddings model: ${err}`); + return {}; + } +}; From 2678c36e448b966e0e18d89e16ddfaa06caf0239 Mon Sep 17 00:00:00 2001 From: ItzCrazyKns Date: Sat, 6 Jul 2024 15:12:51 +0530 Subject: [PATCH 2/3] feat(agents): fix grammar in prompt, closes 239 & 203 --- src/agents/academicSearchAgent.ts | 4 ++-- src/agents/redditSearchAgent.ts | 4 ++-- src/agents/webSearchAgent.ts | 4 ++-- src/agents/wolframAlphaSearchAgent.ts | 4 ++-- src/agents/youtubeSearchAgent.ts | 4 ++-- 5 files changed, 10 insertions(+), 10 deletions(-) diff --git a/src/agents/academicSearchAgent.ts b/src/agents/academicSearchAgent.ts index 5c11307..d797119 100644 --- a/src/agents/academicSearchAgent.ts +++ b/src/agents/academicSearchAgent.ts @@ -44,7 +44,7 @@ Rephrased question: const basicAcademicSearchResponsePrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Academic', this means you will be searching for academic papers and articles on the web. - Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page). + Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page). You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text. You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them. Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative. @@ -52,7 +52,7 @@ const basicAcademicSearchResponsePrompt = ` Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2]. However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer. - Aything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to + Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to talk about the context in your response. diff --git a/src/agents/redditSearchAgent.ts b/src/agents/redditSearchAgent.ts index 34e9ec2..3c60c68 100644 --- a/src/agents/redditSearchAgent.ts +++ b/src/agents/redditSearchAgent.ts @@ -44,7 +44,7 @@ Rephrased question: const basicRedditSearchResponsePrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Reddit', this means you will be searching for information, opinions and discussions on the web using Reddit. - Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page). + Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page). You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text. You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them. Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative. @@ -52,7 +52,7 @@ const basicRedditSearchResponsePrompt = ` Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2]. However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer. - Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to + Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Reddit and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to talk about the context in your response. diff --git a/src/agents/webSearchAgent.ts b/src/agents/webSearchAgent.ts index 1364742..04de148 100644 --- a/src/agents/webSearchAgent.ts +++ b/src/agents/webSearchAgent.ts @@ -44,7 +44,7 @@ Rephrased question: const basicWebSearchResponsePrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. - Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page). + Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page). You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text. You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them. Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative. @@ -52,7 +52,7 @@ const basicWebSearchResponsePrompt = ` Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2]. However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer. - Aything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to + Anything inside the following \`context\` HTML block provided below is for your knowledge returned by the search engine and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to talk about the context in your response. diff --git a/src/agents/wolframAlphaSearchAgent.ts b/src/agents/wolframAlphaSearchAgent.ts index f810a1e..b80fcf3 100644 --- a/src/agents/wolframAlphaSearchAgent.ts +++ b/src/agents/wolframAlphaSearchAgent.ts @@ -43,7 +43,7 @@ Rephrased question: const basicWolframAlphaSearchResponsePrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Wolfram Alpha', this means you will be searching for information on the web using Wolfram Alpha. It is a computational knowledge engine that can answer factual queries and perform computations. - Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page). + Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page). You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text. You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them. Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative. @@ -51,7 +51,7 @@ const basicWolframAlphaSearchResponsePrompt = ` Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2]. However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer. - Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to + Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Wolfram Alpha and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to talk about the context in your response. diff --git a/src/agents/youtubeSearchAgent.ts b/src/agents/youtubeSearchAgent.ts index 4e82cc7..334f67e 100644 --- a/src/agents/youtubeSearchAgent.ts +++ b/src/agents/youtubeSearchAgent.ts @@ -44,7 +44,7 @@ Rephrased question: const basicYoutubeSearchResponsePrompt = ` You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are set on focus mode 'Youtube', this means you will be searching for videos on the web using Youtube and providing information based on the video's transcript. - Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containg a brief description of the content of that page). + Generate a response that is informative and relevant to the user's query based on provided context (the context consits of search results containing a brief description of the content of that page). You must use this context to answer the user's query in the best way possible. Use an unbaised and journalistic tone in your response. Do not repeat the text. You must not tell the user to open any link or visit any website to get the answer. You must provide the answer in the response itself. If the user asks for links you can provide them. Your responses should be medium to long in length be informative and relevant to the user's query. You can use markdowns to format your response. You should use bullet points to list the information. Make sure the answer is not short and is informative. @@ -52,7 +52,7 @@ const basicYoutubeSearchResponsePrompt = ` Place these citations at the end of that particular sentence. You can cite the same sentence multiple times if it is relevant to the user's query like [number1][number2]. However you do not need to cite it using the same number. You can use different numbers to cite the same sentence multiple times. The number refers to the number of the search result (passed in the context) used to generate that part of the answer. - Aything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to + Anything inside the following \`context\` HTML block provided below is for your knowledge returned by Youtube and is not shared by the user. You have to answer question on the basis of it and cite the relevant information from it but you do not have to talk about the context in your response. From f4b58c71575923919936eb441fff581ae2d5eebe Mon Sep 17 00:00:00 2001 From: ItzCrazyKns Date: Sat, 6 Jul 2024 15:13:05 +0530 Subject: [PATCH 3/3] feat(dockerfile): revert base image back to slim --- backend.dockerfile | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/backend.dockerfile b/backend.dockerfile index 910aae7..4886573 100644 --- a/backend.dockerfile +++ b/backend.dockerfile @@ -1,4 +1,4 @@ -FROM node:buster-slim +FROM node:slim ARG SEARXNG_API_URL