Reliability & Retries

Agents operating in production need to handle failures gracefully. The Agent class provides built-in mechanisms for retrying failed operations and controlling error propagation.

Retry Configuration

You can control how many times an agent attempts to execute a task before failing.

retry: The number of additional attempts after the first failure.
mode: How to handle the final failure ("raise" or "return_false").

Basic Retry Logic

from upsonic import Agent, Task

agent = Agent(
    model="anthropic/claude-sonnet-4-5",
    retry=3,         # Will try up to 4 times total (1 initial + 3 retries)
    mode="raise"     # Raise the exception if all retries fail
)

task = Task("Perform a potentially flaky API operation")

try:
    result = agent.do(task)
    print(result)
except Exception as e:
    print(f"Task failed after retries: {e}")

Safe Mode (Return False)

If you prefer the agent to return False instead of crashing your application on failure:

agent = Agent(
    model="anthropic/claude-sonnet-4-5",
    retry=2,
    mode="return_false"  # Return False instead of raising Exception
)

result = agent.do("Some complex task")

if result is False:
    print("Agent failed to complete the task.")
else:
    print(f"Success: {result}")

Best Practices

Network Instability: Set retry >= 2 for agents using web search or external APIs.
Production Systems: Use mode="raise" inside a try/catch block to log specific errors while keeping the application running.

Automatic Model Selection

Reflection

GET STARTED

CONCEPTS

STARTING AN AGENT PROJECT

READY TO USE SNIPPETS

DEPLOYMENT

FURTHER READINGS

Reliability & Retries

Retry Configuration

Basic Retry Logic

Safe Mode (Return False)

Best Practices

​Retry Configuration

​Basic Retry Logic

​Safe Mode (Return False)

​Best Practices

Retry Configuration

Basic Retry Logic

Safe Mode (Return False)

Best Practices