RateLimitError
together_ai.RateLimitError (HTTP 429)
Stack trace
together_ai.RateLimitError: Error code: 429 - {'error': {'message': 'Rate limit exceeded', 'type': 'requests', 'code': 'rate_limit_exceeded'}} Why it happens
Together AI enforces strict rate limits on API requests to prevent abuse and ensure fair usage. When your application sends more requests than allowed per minute or exceeds concurrency limits, the API responds with a 429 RateLimitError.
Detection
Monitor API response codes and catch together_ai.RateLimitError exceptions to log and alert on rate limit breaches before your app crashes.
Causes & fixes
Sending too many requests in a short time exceeding Together AI's rate limits
Implement exponential backoff and retry logic with delays between requests to stay within rate limits.
Multiple parallel requests exceeding concurrency limits set by Together AI
Limit the number of concurrent API calls by using a request queue or semaphore to throttle concurrency.
Using an incorrect or missing API key causing unauthorized or limited access triggering rate limits
Ensure your API key is correctly set in environment variables and passed in the client initialization.
Code: broken vs fixed
from together_ai import TogetherAIClient
client = TogetherAIClient(api_key='wrong_or_missing_key')
response = client.chat_completions.create(model='together-gpt', messages=[{'role':'user','content':'Hello'}]) # triggers RateLimitError 429import os
from together_ai import TogetherAIClient, RateLimitError
client = TogetherAIClient(api_key=os.environ['TOGETHER_API_KEY'])
try:
response = client.chat.completions.create(model='together-gpt', messages=[{'role':'user','content':'Hello'}])
print(response.choices[0].message.content)
except RateLimitError:
print('Rate limit exceeded, retrying after delay...')
# Implement retry logic hereWorkaround
Catch RateLimitError exceptions and implement a manual delay (e.g., time.sleep(10)) before retrying the request to avoid immediate failures.
Prevention
Design your application to respect Together AI's documented rate limits by throttling request rates and concurrency, and use built-in retry-after headers to schedule retries automatically.