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:
- The token is cached for 55 seconds.
- A new token is only requested if the cached token is expired or within 5 seconds of expiring.
- 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:
- Are there any obvious issues in my token caching implementation that could be causing these persistent rate limit errors?
- Are there additional measures I should implement to further reduce the risk of rate limit errors?
- 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!