@cellular-ai/engine

API for building agentic coding editors/platforms

Features

AI-powered code generation with streaming support
Tool execution with automatic function calling
Memory management for context-aware conversations
Express.js integration for easy web server setup
TypeScript support with full type definitions

Installation

npm install @cellular-ai/engine

Quick Start

Basic Usage

import { engine, stream } from '@cellular-ai/engine';

// Create an engine instance
const engineInstance = engine('./my-project', true, 'session-123', 'your-api-key');

// Stream AI responses
for await (const token of engineInstance.stream('Write a function to sort an array')) {
  process.stdout.write(token);
}

Express.js Integration

import express from 'express';
import { stream } from '@cellular-ai/engine';

const app = express();
const engineInstance = engine('./my-project', true, 'session-123', 'your-api-key');

app.post('/generate', async (req, res) => {
  const { prompt, context } = req.body;
  
  res.setHeader('Content-Type', 'text/plain');
  res.setHeader('Transfer-Encoding', 'chunked');
  
  await stream(res, engineInstance, prompt, context);
  return res;
});

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

API Reference

`engine(dir, fullContext?, sessionId?, apikey?, debug?)`

Creates a new engine instance.

Parameters:

dir (string): Project directory path
fullContext (boolean, optional): Whether to include full context. Default: false
sessionId (string, optional): Session identifier. Auto-generated if not provided
apikey (string, optional): Gemini API key. Can also be set via GEMINI_API_KEY environment variable
debug (boolean, optional): Enable debug logging. Default: false

Returns: EngineService instance

`stream(response, engine, prompt, context?)`

Streams AI responses to an Express.js response object.

Parameters:

response (Response): Express.js response object
engine (EngineService): Engine instance
prompt (string): User prompt
context (string, optional): Additional context

EngineService Methods

`stream(message, context?)`

Streams AI responses as an async generator.

for await (const token of engineInstance.stream('Your prompt here')) {
  console.log(token);
}

`getTools()`

Returns available tools as function declarations.

const tools = await engineInstance.getTools();
console.log('Available tools:', tools.map(t => t.name));

`executeTool(toolName, params)`

Executes a specific tool with parameters.

const result = await engineInstance.executeTool('read-file', { path: './example.js' });
console.log(result);

`getMemoryContent()`

Returns the current memory content.

const memory = engineInstance.getMemoryContent();
console.log('Memory content:', memory);

Configuration

Environment Variables

GEMINI_API_KEY: Your Gemini API key (required)

Examples

Code Generation

import { engine } from '@cellular-ai/engine';

const engineInstance = engine('./my-project', true, 'code-gen-session');

for await (const token of engineInstance.stream(
  'Create a React component that displays a user profile'
)) {
  process.stdout.write(token);
}

Tool Execution

import { engine } from '@cellular-ai/engine';

const engineInstance = engine('./my-project');

// Get available tools
const tools = await engineInstance.getTools();
console.log('Available tools:', tools.map(t => t.name));

// Execute a specific tool
const fileContent = await engineInstance.executeTool('read-file', {
  path: './src/index.js'
});
console.log('File content:', fileContent);

License

All code in this project is maintained under the Apache-2.0 License