Output Styles

Control how agents display responses — from silent SDK mode to verbose interactive output

Control what your agent prints during a run — silent for APIs, status for CLI, stream for chat UIs.

from praisonaiagents import Agent

agent = Agent(
    name="Assistant",
    instructions="You are helpful.",
    output="status",
)
result = agent.start("What is the capital of France?")

The user runs the agent; output presets control whether responses stay silent, stream, or show status lines.

How It Works

Quick Start

1. Simple Usage

   Pass output as a string preset:

   from praisonaiagents import Agent
   
   agent = Agent(
       name="Assistant",
       instructions="You are a helpful assistant.",
       output="status"
   )
   
   result = agent.start("What is the weather in Tokyo?")
   
2. With Configuration

   Use OutputConfig for fine-grained control:

   from praisonaiagents import Agent, OutputConfig
   
   agent = Agent(
       name="Assistant",
       instructions="You are a helpful assistant.",
       output=OutputConfig(
           verbose=True,
           markdown=True,
           stream=True,
           metrics=True,
       )
   )
   
   result = agent.start("Explain machine learning in simple terms")
   

---

Which Style Should I Use?

Pick a preset based on where the output is consumed.

---

How It Works

Preset	Description	Best For
silent	No output, returns value only (default)	SDK / programmatic use
editor	Step 1: 📄 Creating file → ✓ Done	CLI default, beginners
status	▸ AI → thinking + inline tool calls	Simple CLI output
trace	Status with [HH:MM:SS] timestamps	Progress monitoring
debug	Trace + metrics, no boxes	Developer debugging
verbose	Task + Tools + Response panels	Interactive sessions
stream	Real-time token streaming	Chat interfaces
json	JSONL events on stdout	Scripting / piping

---

Configuration Options

OutputConfig SDK Reference

Full parameter reference for OutputConfig

Precedence ladder — choose the level you need:

# Level 1: String preset
agent = Agent(output="verbose")   # "silent" | "minimal" | "normal" | "verbose" | "debug"

# Level 2: OutputConfig (full control)
agent = Agent(output=OutputConfig(verbose=True, stream=True, output_file="results.md"))

from praisonaiagents import Agent, OutputConfig

agent = Agent(
    instructions="...",
    output=OutputConfig(
        verbose=False,
        markdown=False,
        stream=False,
        metrics=False,
        reasoning_steps=False,
        actions_trace=False,
        json_output=False,
        simple_output=False,
        status_trace=False,
        editor_output=False,
        show_parameters=False,
        output_file=None,
        template=None,
        tool_output_limit=16000,
    )
)

Option	Type	Default	Description
verbose	bool	False	Show Rich panels for tasks and responses
markdown	bool	False	Render markdown formatting
stream	bool	False	Stream tokens in real time
metrics	bool	False	Display token usage and cost after each response
reasoning_steps	bool	False	Show internal reasoning steps
actions_trace	bool	False	Show tool calls and lifecycle events on stderr
json_output	bool	False	Emit JSONL events for piping
simple_output	bool	False	Print response without Rich panels
status_trace	bool	False	Clean inline status updates
editor_output	bool	False	Numbered steps with emoji icons (CLI default)
show_parameters	bool	False	Show LLM parameters (debug preset)
style	Any	None	Custom output styling object
output_file	str	None	File path to automatically save the agent response
template	str	None	Format template for the response
tool_output_limit	int	16000	Maximum characters for tool output

String Preset Aliases

Alias	Maps To
plain, minimal	silent
normal	verbose
text, actions	status

---

Common Patterns

Silent (SDK Default)

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful assistant.",
)

result = agent.start("Summarize this article: ...")
print(result)

Status (CLI / Interactive)

from praisonaiagents import Agent

agent = Agent(
    instructions="You are a helpful assistant.",
    output="status"
)

result = agent.start("What is the capital of France?")

Save Response to File

from praisonaiagents import Agent, OutputConfig

agent = Agent(
    instructions="Write a detailed report",
    output=OutputConfig(
        output_file="report.md",
        markdown=True,
    )
)

agent.start("Write a report on renewable energy trends")

---

Best Practices

Use silent mode for production APIs

Silent mode (the default) has zero output overhead. Use it when the agent’s return value is consumed by code rather than displayed to users.

Use editor mode for beginner-facing CLIs

output="editor" shows human-friendly numbered steps with emoji icons. It is the default when running praisonai "prompt" from the command line.

Use stream mode for chat interfaces

Set output="stream" when building conversational UIs — tokens appear in real time for a responsive feel.

Use output_file to persist long-form responses

Set output=OutputConfig(output_file="result.md") to automatically save the agent’s response. Useful for reports, summaries, and generated documents.

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Related

Async Agents

Run agents asynchronously for better performance

Callbacks

Hook into agent lifecycle events