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

# Agent Configuration

> Complete reference for agent configuration parameters

# Agent Configuration

This page provides detailed documentation for all agent configuration parameters, including execution controls, context management, and output formatting options.

## Core Parameters

### Execution Control Parameters

#### `max_iter`

* **Type**: `int`
* **Default**: `15`
* **Description**: Maximum number of iterations an agent will attempt to complete a task
* **Range**: 1-100 (recommended: 10-25)

The `max_iter` parameter controls how many times an agent can iterate through its execution loop when working on a task. This prevents infinite loops and ensures tasks complete within reasonable bounds.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent, ExecutionConfig

agent = Agent(
    name="Researcher",
    execution=ExecutionConfig(max_iter=20),  # Allow up to 20 iterations
)
```

**Best Practices**:

* Set lower values (5-10) for simple tasks
* Use higher values (20-30) for complex research or analysis tasks
* Monitor iteration count to optimize performance

#### `max_retry_limit`

* **Type**: `int`
* **Default**: `2`
* **Description**: Maximum number of times to retry a failed operation
* **Range**: 0-10 (recommended: 2-5)

Controls how many times an agent will retry operations that fail due to transient errors like network issues or API rate limits.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
agent = Agent(
    name="DataAnalyst",
    max_retry_limit=3,  # Retry failed operations up to 3 times
    # other parameters...
)
```

**Use Cases**:

* API calls that may face rate limits
* Network operations that may timeout
* Tool executions that may fail intermittently

### Context Management

#### `context_length`

* **Type**: `int`
* **Default**: `None` (uses model default)
* **Description**: Maximum context window size in tokens
* **Common Values**:
  * GPT-4: 128000
  * GPT-3.5: 16385
  * Claude 3: 200000

Defines the maximum amount of context (in tokens) that can be included in a single LLM request.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import ManagerConfig

agent = Agent(
    name="Analyzer",
    context=ManagerConfig(
        auto_compact=True,  # Automatically manage context window
        compact_threshold=0.8,  # Trigger at 80% usage
    ),
    # other parameters...
)
```

**Important Considerations**:

* Larger context windows allow more information but increase costs
* Some models perform better with focused context
* Always validate against your LLM's maximum context size

### Output Formatting

#### `markdown`

* **Type**: `bool`
* **Default**: `True`
* **Description**: Enable markdown formatting in agent outputs

Controls whether the agent formats its responses using markdown syntax for better readability.

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
agent = Agent(
    name="Reporter",
    instructions="Format your responses using markdown with headers, lists, and code blocks",
    templates={
        "response": """
        ## Analysis Report
        
        {content}
        
        ### Key Findings
        {findings}
        """
    }
)
```

**Features When Enabled**:

* Headers using `#`, `##`, etc.
* Bold text with `**text**`
* Code blocks with ` ``` `
* Lists and tables
* Links and images

## Advanced Execution Controls

### Performance Optimization

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
agent = Agent(
    name="HighPerformanceAgent",
    instructions="Complete tasks efficiently",
    
    # Context optimization
    context=True,  # Enable context management
    
    # Caching configuration
    caching={"enabled": True},
    
    # Rate limiting (via ExecutionConfig)
    execution=ExecutionConfig(max_rpm=60)
)
```

### Error Handling Configuration

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents.config.feature_configs import ExecutionConfig

agent = Agent(
    name="ResilientAgent",
    instructions="Handle tasks with error recovery",
    
    # Code execution via ExecutionConfig
    execution=ExecutionConfig(
        code_execution=True,
        code_mode="safe",  # Safe mode with restrictions
    ),
    
    # LLM configuration
    model="gpt-4o-mini"
)
```

## Configuration Patterns

### Research Agent Configuration

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
research_agent = Agent(
    name="ResearchSpecialist",
    role="Senior Research Analyst",
    goal="Conduct thorough research and provide comprehensive reports",
    backstory="Expert researcher with 10 years of experience",
    
    # Enable reflection for quality
    reflection=True,
    
    # Enable planning for complex tasks
    planning=True,
    
    # LLM with large context
    llm="gpt-4o"  # Supports 128k context
)
```

### Quick Task Agent Configuration

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
quick_agent = Agent(
    name="QuickResponder",
    role="Rapid Task Handler",
    
    # Optimized for speed using execution= config
    execution="fast",  # Uses ExecutionConfig(max_iter=5, max_retry_limit=1)
    
    # Minimal output using output= config
    output="silent"  # Disables verbose, markdown, stream
)
```

## Environment Variable Overrides

Agent parameters can be overridden using environment variables:

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# Override default iteration limit
export PRAISONAI_AGENT_MAX_ITER=20

# Override retry limit
export PRAISONAI_AGENT_MAX_RETRY_LIMIT=5

# Set context length
export PRAISONAI_AGENT_CONTEXT_LENGTH=100000

# Disable markdown
export PRAISONAI_AGENT_MARKDOWN=false
```

## Validation and Constraints

### Parameter Validation Rules

| Parameter         | Validation                                                 | Error Handling                |
| ----------------- | ---------------------------------------------------------- | ----------------------------- |
| `max_iter`        | Must be > 0                                                | Defaults to 15 if invalid     |
| `max_retry_limit` | Must be >= 0                                               | Defaults to 2 if invalid      |
| `context_length`  | Must be greater than 0 and less than or equal to model max | Uses model default if invalid |
| `markdown`        | Must be boolean                                            | Defaults to True if invalid   |

### Interaction Between Parameters

1. **Context Length and Max Iterations**
   * Higher `max_iter` may require larger `context_length`
   * Each iteration adds to context usage

2. **Retry Limit and Execution Time**
   * Higher `max_retry_limit` extends total execution time
   * Consider both when setting timeouts

3. **Markdown and Response Templates**
   * \`\` enables template formatting
   * Templates should use markdown syntax when enabled

## Troubleshooting

### Common Issues

1. **Task taking too long**
   ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   # Solution: Use a faster model or simplify the task
   agent = Agent(
       instructions="Complete tasks concisely",
       llm="gpt-4o-mini"  # Faster model
   )
   ```

2. **Context window exceeded**
   ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   # Solution: Enable context management
   agent = Agent(
       instructions="...",
       context=True  # Enable context management
   )
   ```

3. **Need better quality responses**
   ```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
   # Solution: Enable reflection
   agent = Agent(
       instructions="...",
       reflection=True,
       planning=True
   )
   ```

## See Also

* [Task Configuration](/configuration/task-config) - Configure task execution
* [LLM Configuration](/configuration/llm-config) - LLM-specific settings
* [Best Practices](/configuration/best-practices) - Configuration guidelines