Persistent Rate Limit Errors Despite Implementing Ephemeral Token Caching

I’m experiencing persistent rate limit errors in my application that uses the OpenAI Realtime API, even after implementing a caching mechanism for the ephemeral token. I’d appreciate guidance on identifying potential issues in my implementation or suggestions for further optimization.

Implementation Details:

Before Caching:
Previously, my application requested a new ephemeral token for each API call to the OpenAI Realtime API. This led to frequent rate limit errors due to excessive token generation requests.

After Implementing Caching:
I’ve implemented a caching mechanism for the ephemeral token with the following key features:

  1. The token is cached for 55 seconds.
  2. A new token is only requested if the cached token is expired or within 5 seconds of expiring.
  3. The cached token is used for all requests within its validity period.
    import { NextResponse } from ‘next/server’

const OPENAI_SESSION_URL = “”
const OPENAI_API_URL = “”
const MODEL_ID = “gpt-4o-mini-realtime-preview”
const VOICE = “ash”
const DEFAULT_INSTRUCTIONS = “You are helpful and have some tools installed. You can control webpage elements through function calls.”

// Token caching mechanism
let cachedToken: string | null = null
let tokenExpiryTime = 0
const TOKEN_VALIDITY_DURATION = 55 * 1000 // 55 seconds in milliseconds
const TOKEN_REFRESH_THRESHOLD = 5 * 1000 // Refresh 5 seconds before expiry

async function getEphemeralToken() {
const now = Date.now()

// Return cached token if it’s still valid
if (cachedToken && now < tokenExpiryTime - TOKEN_REFRESH_THRESHOLD) {
console.log(“Using cached ephemeral token”)
return cachedToken
}

try {
console.log(“Requesting new ephemeral token”)
const response = await fetch(OPENAI_SESSION_URL, {
method: ‘POST’,
headers: {
‘Authorization’: Bearer ${process.env.OPENAI_API_KEY},
‘Content-Type’: ‘application/json’
},
body: JSON.stringify({
model: MODEL_ID,
voice: VOICE
})
})

if (!response.ok) {
  throw new Error(`Failed to obtain ephemeral token: ${response.status}`)
}

const data = await response.json()
const token = data?.client_secret?.value

if (!token) {
  throw new Error('Ephemeral token not found in response')
}

// Cache the new token
cachedToken = token
tokenExpiryTime = now + TOKEN_VALIDITY_DURATION
console.log("New ephemeral token cached successfully")

return token

} catch (error) {
console.error(“Error generating ephemeral token:”, error)
throw error
}
}

export async function POST(request: Request) {
try {
// Get client SDP
const clientSdp = await request.text()
if (!clientSdp) {
return NextResponse.json({ error: ‘No SDP provided’ }, { status: 400 })
}

// Get ephemeral token (cached or new)
const ephemeralToken = await getEphemeralToken()

// Exchange SDP with OpenAI using the realtime endpoint
const sdpResponse = await fetch(
  `${OPENAI_API_URL}?model=${MODEL_ID}&instructions=${encodeURIComponent(DEFAULT_INSTRUCTIONS)}&voice=${VOICE}`,
  {
    method: 'POST',
    headers: {
      'Authorization': `Bearer ${ephemeralToken}`,
      'Content-Type': 'application/sdp'
    },
    body: clientSdp
  }
)

if (!sdpResponse.ok) {
  const errorText = await sdpResponse.text()
  throw new Error(`OpenAI SDP exchange failed: ${sdpResponse.status} ${errorText}`)
}

// Return the SDP response
return new NextResponse(sdpResponse.body, {
  headers: {
    'Content-Type': 'application/sdp'
  }
})

} catch (error) {
console.error(‘RTC connect error:’, error)

// Clear cached token if we get an authentication error
if (error instanceof Error && error.message.includes('401')) {
  cachedToken = null
  tokenExpiryTime = 0
}

return NextResponse.json(
  { error: error instanceof Error ? error.message : 'Internal server error' },
  { status: 500 }
)

}
}

Despite these changes, I’m still encountering rate limit errors. The errors occur less frequently than before, but they still persist, especially during periods of higher usage.

Questions:

  1. Are there any obvious issues in my token caching implementation that could be causing these persistent rate limit errors?
  2. Are there additional measures I should implement to further reduce the risk of rate limit errors?
  3. Could there be other factors beyond token management contributing to these rate limit issues?

Any insights or suggestions would be greatly appreciated. Thank you for your help!

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