feat(i18n): Refactor prompts and search agent to enhance language handling and formatting instructions

- Updated academicSearch, redditSearch, webSearch, wolframAlpha, writingAssistant, and youtubeSearch prompts to improve clarity and consistency in formatting instructions.
- Added language handling instructions to writingAssistant and other prompts for better localization support.
- Modified MetaSearchAgent to include locale and language parameters for improved prompt generation and language-specific responses.

# Conflicts:
#	Dockerfile

src/lib/chains/suggestionGeneratorAgent.ts

@@ -5,14 +5,30 @@ import formatChatHistoryAsString from '../utils/formatHistory';
 import { BaseMessage } from '@langchain/core/messages';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { ChatOpenAI } from '@langchain/openai';
+import { getPromptLanguageName } from '@/i18n/locales';
 
 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. 
-Make sure the suggestions are medium in length and are informative and relevant to the conversation.
+You are an AI suggestion generator for an AI powered search engine.
 
-Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:
+Your need to meet these requirements:
+- 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.
 
+### Language Instructions
+- **Language Definition**: Interpret "{language}" as a combination of language and optional region.
+  - Format: "language (region)" or "language（region）" (e.g., "English (US)", "繁體中文（台灣）").
+  - The main language indicates the linguistic system (e.g., English, 繁體中文, 日本語).
+  - The region in parentheses indicates the regional variant or locale style (e.g., US, UK, 台灣, 香港, France).
+- **Primary Language**: Use "{language}" for all non-code content, including explanations, descriptions, and examples.
+- **Regional Variants**: Adjust word choice, spelling, and style according to the region specified in "{language}" (e.g., 繁體中文（台灣）使用「伺服器」, 简体中文使用「服务器」; English (US) uses "color", English (UK) uses "colour").
+- **Code and Comments**: All code blocks and code comments must be entirely in "English (US)".
+- **Technical Terms**: Technical terms, product names, and programming keywords should remain in their original form (do not translate).
+- **Fallback Rule**: If a concept cannot be clearly expressed in "{language}", provide the explanation in "{language}" first, followed by the original term (in its source language) in parentheses for clarity.
+
+### Formatting Instructions
+- 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:
 <suggestions>
 Tell me more about SpaceX and their recent projects
 What is the latest news on SpaceX?
@@ -25,6 +41,7 @@ Conversation:
 
 type SuggestionGeneratorInput = {
   chat_history: BaseMessage[];
+  locale: string;
 };
 
 const outputParser = new ListLineOutputParser({
@@ -36,6 +53,8 @@ const createSuggestionGeneratorChain = (llm: BaseChatModel) => {
     RunnableMap.from({
       chat_history: (input: SuggestionGeneratorInput) =>
         formatChatHistoryAsString(input.chat_history),
+      language: (input: SuggestionGeneratorInput) =>
+        getPromptLanguageName(input.locale),
     }),
     PromptTemplate.fromTemplate(suggestionGeneratorPrompt),
     llm,