> ## Documentation Index
> Fetch the complete documentation index at: https://docs.upsonic.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Reflection

> Enable self-critique and improvement for agent responses

Reflection allows the agent to critique and improve its own responses before returning them. This "Self-Correction" pattern improves output quality by checking for errors, clarity, and completeness.

## Enabling Reflection

To enable reflection, set `reflection=True` during agent initialization.

```python theme={null}
from upsonic import Agent, Task

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

task = Task("Write a python function to Fibonacci sequence with detailed docstrings.")

# The agent will:
# 1. Generate an initial response
# 2. Critique the response (finding bugs or missing docs)
# 3. Regenerate an improved response
result = agent.print_do(task)
print(result)
```

## Configuring Reflection

You can customize the reflection process using `ReflectionConfig`.

```python theme={null}
from upsonic import Agent, Task
from upsonic.reflection import ReflectionConfig

# Custom reflection configuration
config = ReflectionConfig(
    max_iterations=2,           # Maximum improvement attempts
    acceptance_threshold=0.9    # Minimum score to accept response
)

agent = Agent(
    model="anthropic/claude-sonnet-4-5",
    reflection=True,
    reflection_config=config,
    debug=True  # useful to see the reflection steps
)

task = Task("Optimize this database query...")
result = agent.do(task)
print(result)
```

## When to Use Reflection?

* **Coding Tasks**: To catch bugs and improve code quality.
* **Complex Reasoning**: To verify logic and assumptions.
* **Creative Writing**: To refine style and tone.

<Note>
  Reflection increases the time and token usage for each task as it involves additional model calls for critique and revision.
</Note>