Lesson Content

Handling error conditions.

Common error conditions include authentication failures, invalid request parameters (an invalid voice ID, malformed text input), rate limit exceeded responses, and quota/credit exhaustion. Each requires different handling: authentication and parameter errors require fixing the request, not retrying; rate limits and transient service issues are appropriate to retry with backoff; quota exhaustion requires either waiting for renewal or upgrading the plan, not retrying immediately.

Respecting rate limits.

API rate limits (requests per time period, tied to subscription tier) protect platform infrastructure. A pipeline that exceeds rate limits should back off rather than continuing to send requests – verify current rate limit specifics for the relevant tier at elevenlabs.io/docs.

Retry strategy for transient failures.

For genuinely transient failures (rate limiting, temporary service issues), implement exponential backoff – increasing wait time between successive retries, with a maximum retry count before flagging the failure for human attention rather than retrying indefinitely.

import time

def generate_with_retry(text, voice_id, max_retries=3):
for attempt in range(max_retries):
response = call_tts_api(text, voice_id)
if response.status_code == 200:
return response.content
if response.status_code == 429: # rate limited
time.sleep(2 ** attempt)
continue
raise Exception(f"Non-retryable error: {response.status_code}")
raise Exception("Max retries exceeded")

Monitoring pipeline reliability.

Log success/failure rates, error types, and latency for the pipeline's API calls. A rising failure rate or unusual error pattern is an early signal worth investigating – whether due to a platform-side issue, a pipeline-side request construction problem, or changing input content characteristics.