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fix(docker-usage): single image setup

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realies
2025-03-08 04:41:27 +00:00
parent b3b8a05bd2
commit a661450633
20 changed files with 240 additions and 203 deletions
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2
src/chains/suggestionGeneratorAgent.ts
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@ -8,7 +8,7 @@ import { ChatOpenAI } from '@langchain/openai';
const suggestionGeneratorPrompt = `
You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information.
You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information.
You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information.
Make sure the suggestions are medium in length and are informative and relevant to the conversation.
Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:

74
src/config.ts
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@ -41,39 +41,83 @@ type RecursivePartial<T> = {
[P in keyof T]?: RecursivePartial<T[P]>;
};
const loadConfig = () =>
toml.parse(
fs.readFileSync(path.join(__dirname, `../${configFileName}`), 'utf-8'),
) as any as Config;
const loadConfig = () => {
try {
return toml.parse(
fs.readFileSync(path.join(__dirname, `../${configFileName}`), 'utf-8'),
) as any as Config;
} catch (error) {
// Return default config if file doesn't exist
return {
GENERAL: {
PORT: 3001,
SIMILARITY_MEASURE: 'cosine',
KEEP_ALIVE: '5m',
},
MODELS: {
OPENAI: {
API_KEY: '',
},
GROQ: {
API_KEY: '',
},
ANTHROPIC: {
API_KEY: '',
},
GEMINI: {
API_KEY: '',
},
OLLAMA: {
API_URL: '',
},
CUSTOM_OPENAI: {
API_URL: '',
API_KEY: '',
MODEL_NAME: '',
},
},
API_ENDPOINTS: {
SEARXNG: '',
},
};
}
};
export const getPort = () => loadConfig().GENERAL.PORT;
export const getPort = () =>
process.env.PORT ? parseInt(process.env.PORT, 10) : loadConfig().GENERAL.PORT;
export const getSimilarityMeasure = () =>
loadConfig().GENERAL.SIMILARITY_MEASURE;
process.env.SIMILARITY_MEASURE || loadConfig().GENERAL.SIMILARITY_MEASURE;
export const getKeepAlive = () => loadConfig().GENERAL.KEEP_ALIVE;
export const getKeepAlive = () =>
process.env.KEEP_ALIVE || loadConfig().GENERAL.KEEP_ALIVE;
export const getOpenaiApiKey = () => loadConfig().MODELS.OPENAI.API_KEY;
export const getOpenaiApiKey = () =>
process.env.OPENAI_API_KEY || loadConfig().MODELS.OPENAI.API_KEY;
export const getGroqApiKey = () => loadConfig().MODELS.GROQ.API_KEY;
export const getGroqApiKey = () =>
process.env.GROQ_API_KEY || loadConfig().MODELS.GROQ.API_KEY;
export const getAnthropicApiKey = () => loadConfig().MODELS.ANTHROPIC.API_KEY;
export const getAnthropicApiKey = () =>
process.env.ANTHROPIC_API_KEY || loadConfig().MODELS.ANTHROPIC.API_KEY;
export const getGeminiApiKey = () => loadConfig().MODELS.GEMINI.API_KEY;
export const getGeminiApiKey = () =>
process.env.GEMINI_API_KEY || loadConfig().MODELS.GEMINI.API_KEY;
export const getSearxngApiEndpoint = () =>
process.env.SEARXNG_API_URL || loadConfig().API_ENDPOINTS.SEARXNG;
export const getOllamaApiEndpoint = () => loadConfig().MODELS.OLLAMA.API_URL;
export const getOllamaApiEndpoint = () =>
process.env.OLLAMA_API_URL || loadConfig().MODELS.OLLAMA.API_URL;
export const getCustomOpenaiApiKey = () =>
loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
process.env.CUSTOM_OPENAI_API_KEY || loadConfig().MODELS.CUSTOM_OPENAI.API_KEY;
export const getCustomOpenaiApiUrl = () =>
loadConfig().MODELS.CUSTOM_OPENAI.API_URL;
process.env.CUSTOM_OPENAI_API_URL || loadConfig().MODELS.CUSTOM_OPENAI.API_URL;
export const getCustomOpenaiModelName = () =>
loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
process.env.CUSTOM_OPENAI_MODEL_NAME || loadConfig().MODELS.CUSTOM_OPENAI.MODEL_NAME;
const mergeConfigs = (current: any, update: any): any => {
if (update === null || update === undefined) {

2
src/prompts/writingAssistant.ts
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@ -1,5 +1,5 @@
export const writingAssistantPrompt = `
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query.
You are Perplexica, an AI model who is expert at searching the web and answering user's queries. You are currently set on focus mode 'Writing Assistant', this means you will be helping the user write a response to a given query.
Since you are a writing assistant, you would not perform web searches. If you think you lack information to answer the query, you can ask the user for more information or suggest them to switch to a different focus mode.
You will be shared a context that can contain information from files user has uploaded to get answers from. You will have to generate answers upon that.

10
src/search/metaSearchAgent.ts
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@ -129,7 +129,7 @@ class MetaSearchAgent implements MetaSearchAgentType {
await Promise.all(
docGroups.map(async (doc) => {
const res = await llm.invoke(`
You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the
You are a web search summarizer, tasked with summarizing a piece of text retrieved from a web search. Your job is to summarize the
text into a detailed, 2-4 paragraph explanation that captures the main ideas and provides a comprehensive answer to the query.
If the query is \"summarize\", you should provide a detailed summary of the text. If the query is a specific question, you should answer it in the summary.
@ -141,8 +141,8 @@ class MetaSearchAgent implements MetaSearchAgentType {
<example>
1. \`<text>
Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers.
It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications
Docker is a set of platform-as-a-service products that use OS-level virtualization to deliver software in packages called containers.
It was first released in 2013 and is developed by Docker, Inc. Docker is designed to make it easier to create, deploy, and run applications
by using containers.
</text>
@ -151,8 +151,8 @@ class MetaSearchAgent implements MetaSearchAgentType {
</query>
Response:
Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application
deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in
Docker is a revolutionary platform-as-a-service product developed by Docker, Inc., that uses container technology to make application
deployment more efficient. It allows developers to package their software with all necessary dependencies, making it easier to run in
any environment. Released in 2013, Docker has transformed the way applications are built, deployed, and managed.
\`
2. \`<text>