• Create a nodejs server that exposes an endpoint /prompt where user can send their prompt and get back an e2b preview url

import express from "express";

const app = express();

app.post("/prompt", (req, res) => {
    const { prompt } = req.body;

    // create sandbox for user

    // forward enriched prompt to llm

    // Define toolcalls that write to the sandbox.

});

app.listen(3000, () => {
  console.log("Server is running on port 3000");
});

• Define tools in tools/index.ts

import { z } from "zod";

export const createFile = {
    description: 'Create a file at a certain directory',
    parameters: z.object({
      location: z
        .string()
        .describe('Relative path to the file')
    }),
    execute: async ({ location }: { location: string }) => {
      return `File created`;
    },
};

export const updateFile = {
    description: 'Update a file at a certain directory',
    parameters: z.object({
      location: z.string().describe('Relative path to the file'),
      content: z.string().describe('Content of the file'),
    }),
    execute: async ({ location, content }: { location: string, content: string }) => {
      return `File updated`;
    },
};

export const deleteFile = {
    description: 'Delete a file at a certain directory',
    parameters: z.object({
      location: z.string().describe('Relative path to the file'),
    }),
    execute: async ({ location }: { location: string }) => {
      return `File deleted`;
    },
};

export const readFile = {
    description: 'Read a file at a certain directory',
    parameters: z.object({
      location: z.string().describe('Relative path to the file'),
    }),
    execute: async ({ location }: { location: string }) => {
      return `File Contents`;
    },
};

• Write the system prompt, give access to the tools, test the LLM integration.

export const appTsx = `
import { useState } from 'react'
import reactLogo from './assets/react.svg'
import viteLogo from '/vite.svg'
import './App.css'

function App() {
  const [count, setCount] = useState(0)

  return (
    <>
      <div>
        <a href="<https://vite.dev>" target="_blank">
          <img src={viteLogo} className="logo" alt="Vite logo" />
        </a>
        <a href="<https://react.dev>" target="_blank">
          <img src={reactLogo} className="logo react" alt="React logo" />
        </a>
      </div>
      <h1>Vite + React</h1>
      <div className="card">
        <button onClick={() => setCount((count) => count + 1)}>
          count is {count}
        </button>
        <p>
          Edit <code>src/App.tsx</code> and save to test HMR
        </p>
      </div>
      <p className="read-the-docs">
        Click on the Vite and React logos to learn more
      </p>
    </>
  )
}

export default App

`

export const initialFileStructure = `
    - /home/user/index.html
    - /home/user/package.json
    - /home/user/README.md
    - /home/user/src/
    - /home/user/src/App.tsx
    - /home/user/src/App.css
    - /home/user/src/index.css
    - /home/user/src/main.tsx

    App.tsx looks like this:
    ${appTsx}
`;

export const SYSTEM_PROMPT = `
    You are an expert coding agent. Your job is to write code in a sandbox environment.
    You have access to the following tools:
    - createFile
    - updateFile
    - deleteFile
    - readFile
    You will be given a prompt and you will need to write code to implement the prompt.
    Make sure the website is pretty. 
    This is what the initial file structure looks like:
    ${initialFileStructure}

`

• Complete the endpoint

import express from "express";
import { createOpenRouter } from '@openrouter/ai-sdk-provider';
import { streamText } from 'ai';
import { SYSTEM_PROMPT } from "./prompt";
import { createFile, updateFile, deleteFile, readFile } from "./tools";
import { z } from "zod";

const app = express();

app.use(express.json());

app.post("/prompt", (req, res) => {
    const { prompt } = req.body;

    // TODO:  create sandbox for user

    const openrouter = createOpenRouter({
        apiKey: process.env.OPENROUTER_API_KEY,
      });
      const response = streamText({
        model: openrouter("gpt-4o-mini"),
        tools: {
            createFile: createFile,
            updateFile: updateFile,
            deleteFile: deleteFile,
            readFile: readFile
        },
        messages: [
            {
                role: "system",
                content: SYSTEM_PROMPT
            },
            {
                role: "user",
                content: prompt
            }
        ]
      });

      response.pipeTextStreamToResponse(res);
});

app.listen(3000, () => {
  console.log("Server is running on port 3000");
});