mkdir my-project
npm init -y
npm install dotenv

npx baseai@latest pipe

BaseAI is not installed but required to run. Would you like to install it? Yes/No
Name of the pipe? email-generator-agent
Description of the pipe? Generates emails for your dream job in seconds
Status of the pipe? Public/Private
System prompt? You are a helpful AI assistant

npx baseai@latest memory

Name of the memory? email-generator-memory
Description of the memory? Contains my resume
Do you want to create memory from the current project git repository? Yes/No

npx baseai@latest embed -m email-generator-memory

import { PipeI } from '@baseai/core';

const pipePipeWithMemory = (): PipeI => ({
    apiKey: process.env.LANGBASE_API_KEY!, // Replace with your API key https://langbase.com/docs/api-reference/api-keys
    name: 'email-generator-agent',
    description: 'Generates emails for your dream job in seconds',
    status: 'public',
    model: 'openai:gpt-4o-mini',
    stream: true,
    json: false,
    store: true,
    moderate: true,
    top_p: 1,
    max_tokens: 1000,
    temperature: 0.7,
    presence_penalty: 1,
    frequency_penalty: 1,
    stop: [],
    tool_choice: 'auto',
    parallel_tool_calls: false,
    messages: [
        { role: 'system', content: You are a helpful AI assistant. }],
    variables: [],
    memory: [],
    tools: []});
export default pipePipeWithMemory;

Based on the job description and my resume attached, write a compelling cold email tailored to the job, highlighting my most relevant skills, achievements, and experiences. Ensure the tone is professional yet approachable, and include a strong call to action for a follow-up or interview.

import { PipeI } from '@baseai/core';
import emailGeneratorMemoryMemory from '../memory/email-generator-memory';

const pipeEmailGeneratorAgent = (): PipeI => ({
 // Replace with your API key https://langbase.com/docs/api-reference/api-keys
 apiKey: process.env.LANGBASE_API_KEY!,
 name: 'email-generator-agent',
 description: 'Generates emails for your dream job in seconds',
 status: 'private',
 model: 'openai:gpt-4o-mini',
 stream: true,
 json: false,
 store: true,
 moderate: true,
 top_p: 1,
 max_tokens: 1000,
 temperature: 0.7,
 presence_penalty: 1,
 frequency_penalty: 1,
 stop: [],
 tool_choice: 'auto',
 parallel_tool_calls: true,
 messages: [{ role: 'system', content: Based on the job description and my resume attached, write a compelling cold email tailored to the job, highlighting my most relevant skills, achievements, and experiences. Ensure the tone is professional yet approachable, and include a strong call to action for a follow-up or interview. }],
 variables: [],
 memory: [emailGeneratorMemoryMemory()],
 tools: []});

export default pipeEmailGeneratorAgent;

touch index.ts

import 'dotenv/config';
import { Pipe } from '@baseai/core';
import inquirer from 'inquirer';import ora from 'ora';
import chalk from 'chalk';
import pipeEmailGeneratorAgent from './baseai/pipes/email-generator-agent';
const pipe = new Pipe(pipeEmailGeneratorAgent());
async function main() {

   const initialSpinner = ora('Conversation with Memory agent...').start();
   try {
       const { completion: calculatorTool} = await pipe.run({
           messages: [{ role: 'user', content: 'Hello' }],
       });
       initialSpinner.stop();
       console.log(chalk.cyan('Report Generator Agent response...'));
       console.log(calculatorTool);
   } catch (error) {
       initialSpinner.stop();
       console.error(chalk.red('Error processing initial request:'), error);
   }

   while (true) {
       const { userMsg } = await inquirer.prompt([
           {
               type: 'input',
               name: 'userMsg',
               message: chalk.blue('Enter your query (or type "exit" to quit):'),
           },
       ]);


       if (userMsg.toLowerCase() === 'exit') {
           console.log(chalk.green('Goodbye!'));
           break;
       }


       const spinner = ora('Processing your request...').start();


       try {
           const { completion: reportAgentResponse } = await pipe.run({
               messages: [{ role: 'user', content: userMsg }],
           });


           spinner.stop();
           console.log(chalk.cyan('Agent:'));
           console.log(reportAgentResponse);
       } catch (error) {
           spinner.stop();
           console.error(chalk.red('Error processing your request:'), error);
       }
   }}
main();
導入 'dotenv/config';import { Pipe } from '@baseai/core';import inquirer from 'inquirer';import ora from 'ora';從 'chalk' 導入 chalk;import pipeEmailGeneratorAgent from './baseai/pipes/email-generator-agent'; const pipe = new Pipe（pipeEmailGeneratorAgent（））; async function main（） { const initialSpinner = ora（'與內存代理的對話...'）.start（）;   try { const { completion： calculatorTool} = await pipe.run（{ messages： [{ role： 'user'， content： 'Hello' }]， }）;       初始Spinner.stop（）;       console.log（chalk.cyan（'Report Generator Agent 響應...'））;       console.log（calculatorTool）;   } catch （錯誤） { initialSpinner.stop（）;       console.error（chalk.red（'處理初始請求時出錯：'）， error）;   } while （true） { const { userMsg } = await inquirer.prompt（[ { type： 'input'， name： 'userMsg'， message： chalk.blue（'輸入你的查詢（或鍵入 “exit” 退出）：'）， }， ]）;         if （userMsg.toLowerCase（） === 'exit'） { console.log（chalk.green（'Goodbye！'））;           破;       } const spinner = ora（'正在處理你的請求...'）.start（）;         try { const { completion： reportAgentResponse } = await pipe.run（{ messages： [{ role： 'user'， content： userMsg }]， }）;             spinner.stop（）;           console.log（chalk.cyan（'代理：'））;           console.log（reportAgentResponse）;       } catch （錯誤） { spinner.stop（）;           console.error（chalk.red（'處理你的請求時出錯：'）， error）;       } } } main（）;

npx baseai@latest dev

npx tsx index.ts