OpenAI

OpenAI implementation for @micdrop/server.

This package provides AI agent and speech-to-text implementations using OpenAI's API.

Installation

npm install @micdrop/openai

OpenAI Agent

Usage

import { OpenaiAgent } from '@micdrop/openai'
import { MicdropServer } from '@micdrop/server'

const agent = new OpenaiAgent({
  apiKey: process.env.OPENAI_API_KEY || '',
  model: 'gpt-4o', // Default model
  systemPrompt: 'You are a helpful assistant',

  // Custom OpenAI Responses API settings (optional)
  settings: {
    temperature: 0.7,
    max_output_tokens: 150,
  },
})

// Use with MicdropServer
new MicdropServer(socket, {
  agent,
  // ... other options
})

Options

Option	Type	Default	Description
apiKey	string	Required*	Your OpenAI API key (required if openai not provided)
openai	OpenAI	Optional	OpenAI instance (alternative to apiKey)
model	string	'gpt-4o'	OpenAI model to use
systemPrompt	string	Required	System prompt for the agent
maxRetry	number	3	Maximum number of retries on API failures
maxSteps	number	5	Maximum number of steps (for tool calls)
autoEndCall	boolean | string	false	Auto-detect when user wants to end call
autoSemanticTurn	boolean | string	false	Handle incomplete user sentences
autoIgnoreUserNoise	boolean | string	false	Filter meaningless user sounds
extract	ExtractJsonOptions | ExtractTagOptions	undefined	Extract structured data from responses
onBeforeAnswer	function	undefined	Hook called before answer generation - return true to skip generation
settings	object	{}	Additional OpenAI Responses API parameters

The OpenAI Agent supports adding and removing custom tools to extend its capabilities. For detailed information about tool management, see the Tools documentation.

Advanced Features

The OpenAI Agent supports advanced features for improved conversation handling:

• Auto End Call: Automatically detect when users want to end the conversation
• Semantic Turn Detection: Handle incomplete sentences for natural flow
• User Noise Filtering: Filter out meaningless sounds and filler words
• Extract Value from Answer: Extract structured data from responses
• Tools: Add custom tools to the agent

Langfuse Integration

You can integrate Langfuse for observability by using the openai option with a Langfuse-wrapped OpenAI client:

import { OpenaiAgent } from '@micdrop/openai'
import { Langfuse, observeOpenAI } from 'langfuse'
import OpenAI from 'openai'

// Initialize Langfuse
const langfuse = new Langfuse({
  secretKey: process.env.LANGFUSE_SECRET_KEY,
  publicKey: process.env.LANGFUSE_PUBLIC_KEY,
  baseUrl: process.env.LANGFUSE_BASE_URL, // Optional, defaults to https://cloud.langfuse.com
})

// Get system prompt from Langfuse
const systemPrompt = await langfuse.getPrompt('voice-assistant-system-prompt')

// Create OpenAI client and wrap with Langfuse observability
const openai = observeOpenAI(
  new OpenAI({ apiKey: process.env.OPENAI_API_KEY }),
  {
    sessionId: 'session-123',
    userId: 'user-456',
  }
)

// Create agent with Langfuse-wrapped OpenAI client
const agent = new OpenaiAgent({
  openai,
  model: 'gpt-4o',
  systemPrompt: systemPrompt.prompt,
})

This integration will automatically track all OpenAI API calls, token usage, and conversation flows in your Langfuse dashboard with session and user context.

OpenAI STT (Speech-to-Text)

Real-time speech-to-text implementation using OpenAI's WebSocket-based real-time transcription API.

Usage

import { OpenaiSTT } from '@micdrop/openai'
import { MicdropServer } from '@micdrop/server'

const stt = new OpenaiSTT({
  apiKey: process.env.OPENAI_API_KEY || '',
  model: 'gpt-4o-transcribe', // Default real-time transcription model
  language: 'en', // Optional: specify language for better accuracy
  prompt: 'Transcribe the incoming audio in real time.', // Optional: custom prompt
  transcriptionTimeout: 4000, // Optional: timeout in ms for transcription
})

// Use with MicdropServer
new MicdropServer(socket, {
  stt,
  // ... other options
})

Options

Option	Type	Default	Description
apiKey	string	Required	Your OpenAI API key
model	string	'gpt-4o-transcribe'	Real-time transcription model to use
language	string	'en'	Language code for transcription
prompt	string	'Transcribe the incoming audio in real time.'	Custom prompt to guide transcription behavior
transcriptionTimeout	number	4000	Timeout in milliseconds to wait for transcription result