How to handle Gemini API errors in python
client.chat.completions.create calls to manage RateLimitError, APIConnectionError, and other exceptions gracefully.api_error RateLimitError automatically.Why this happens
Gemini API errors typically occur due to rate limits, network issues, or invalid requests. For example, exceeding the allowed request rate triggers a RateLimitError. Network interruptions cause APIConnectionError. Invalid parameters result in InvalidRequestError. Without error handling, your Python code will crash or fail silently.
Example of broken code that does not handle errors:
import os
from openai import OpenAI
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
response = client.chat.completions.create(
model="gemini-1.5-pro",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Traceback (most recent call last):
File "app.py", line 7, in <module>
response = client.chat.completions.create(...)
openai.error.RateLimitError: You have exceeded your current quota, please check your plan and billing details. The fix
Wrap your API call in a try-except block to catch exceptions like RateLimitError and APIConnectionError. Implement exponential backoff retries to handle transient errors gracefully. This prevents your app from crashing and respects API rate limits.
import os
import time
from openai import OpenAI
from openai import RateLimitError, APIConnectionError
client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
max_retries = 5
retry_delay = 1 # seconds
for attempt in range(max_retries):
try:
response = client.chat.completions.create(
model="gemini-1.5-pro",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)
break # success, exit loop
except RateLimitError:
print(f"Rate limit hit, retrying in {retry_delay} seconds...")
time.sleep(retry_delay)
retry_delay *= 2 # exponential backoff
except APIConnectionError:
print(f"Connection error, retrying in {retry_delay} seconds...")
time.sleep(retry_delay)
retry_delay *= 2
except Exception as e:
print(f"Unexpected error: {e}")
breakHello! How can I assist you today?
Preventing it in production
Use robust retry logic with capped exponential backoff and jitter to avoid thundering herd problems. Validate request parameters before sending to reduce InvalidRequestError. Monitor API usage and implement circuit breakers to pause requests if errors spike. Log errors for diagnostics and alerting.
Consider fallback models or cached responses to maintain user experience during outages.
Key Takeaways
- Always catch and handle API exceptions when calling Gemini with the OpenAI SDK.
- Implement exponential backoff retries to gracefully handle rate limits and transient errors.
- Validate inputs and monitor API usage to prevent common errors in production.