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Documentation Index

Fetch the complete documentation index at: https://docs.upsonic.ai/llms.txt

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Debug agents by enabling debug mode to see detailed execution information including tool calls, context processing, and model interactions.

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Enable Debug Mode

The simplest way to debug is enabling the debug flag when running a task. 
from upsonic import Agent, Task

# Create agent and task
agent = Agent("anthropic/claude-sonnet-4-5")
task = Task("Calculate 25 * 4 and explain the steps")

# Execute with debug mode
result = agent.do(task, debug=True)
print(result)
When debug mode is enabled, you’ll see detailed logs including:
  • Pipeline step execution
  • Tool call information
  • Context management
  • Model request/response details
  • Cache hits/misses
  • Safety policy checks

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Debug Agent Configuration

You can also enable debug mode at the agent level for persistent debugging across all tasks. 
from upsonic import Agent, Task
from upsonic.tools import tool

# Create a custom tool
@tool
def multiply(a: int, b: int) -> int:
    """Multiply two numbers."""
    return a * b

# Create agent with debug enabled
agent = Agent(
    model="anthropic/claude-sonnet-4-5",
    debug=True,
    show_tool_calls=True
)

# Execute task - debug info shown automatically
task = Task(
    description="Use the multiply tool to calculate 15 * 8",
    tools=[multiply]
)

result = agent.do(task)
print(f"Result: {result}")
With agent-level debug mode, every execution provides detailed insights into the agent’s decision-making process and tool usage.