Thanaphoom Babparn marttp

Enhanced AI Prompt Generator

You are an AI-powered prompt generator, designed to improve and expand basic prompts into comprehensive, context-rich instructions. Your goal is to take a simple prompt and transform it into a detailed guide that helps users get the most out of their AI interactions.

Your process:

Understand the Input:
- Analyze the user’s original prompt to understand their objective and desired outcome.
- If necessary, ask clarifying questions or suggest additional details the user may need to consider (e.g., context, target audience, specific goals).

	from google import genai
	from google.api_core import retry
	import sys
	import os

	sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
	from helper.get_env import GEMINI_API_KEY

	is_retriable = lambda e: (isinstance(e, genai.errors.APIError) and e.code in {429, 503})

	package dev.tpcoder.application.service;

	import dev.tpcoder.application.dto.GetNewsByPreferenceResponse;
	import dev.tpcoder.application.dto.GetNewsRequest;
	import dev.tpcoder.application.dto.GetNewsResponse;
	import dev.tpcoder.application.util.AgentUtil;
	import org.springframework.ai.chat.client.ChatClient;
	import org.springframework.ai.openai.OpenAiChatModel;
	import org.springframework.beans.factory.annotation.Value;
	import org.springframework.stereotype.Service;

	package dev.tpcoder.application.agent;

	import dev.tpcoder.application.dto.GetNewsByPreferenceRequest;
	import dev.tpcoder.application.dto.GetNewsByPreferenceResponse;
	import dev.tpcoder.application.dto.UserPreferenceRequest;
	import dev.tpcoder.application.dto.UserPreferenceResponse;
	import dev.tpcoder.application.repository.UserPreferencesRepository;
	import dev.tpcoder.application.service.NewsService;
	import dev.tpcoder.application.service.agent.GetNewsByUserPreferences;
	import dev.tpcoder.application.service.agent.UserPreferencesService;

	package dev.tpcoder.application.controller;

	import dev.tpcoder.application.agent.AiAgentConfig;
	import dev.tpcoder.application.dto.NewSummarized;
	import dev.tpcoder.application.util.AgentUtil;
	import org.slf4j.Logger;
	import org.slf4j.LoggerFactory;
	import org.springframework.ai.chat.messages.UserMessage;
	import org.springframework.ai.chat.model.ChatResponse;
	import org.springframework.ai.chat.model.Generation;

	spring:
	application:
	name: spring-ai-function-calling
	ai:
	openai:
	api-key: ${OPEN_API_KEY:}

	sql:
	init:
	mode: always

	INSERT INTO USER_PREFERENCES (id, category) VALUES
	(1,'science'),
	(2,'technology');

	class Solution {

	private static final int[][] DIRS = new int[][] {
	new int[] {-1,0},
	new int[] {1,0},
	new int[] {0,-1},
	new int[] {0,1}
	};

	public int[][] updateMatrix(int[][] mat) {