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Quick Start

1

Install Dependencies

First, install the required packages:
pip install praisonaiagents gradio
2

Create Script

Create a new file app.py:
import gradio as gr
from praisonaiagents import Agent, Tools
from praisonaiagents.tools import duckduckgo

def research(query):
    agent = Agent(instructions="You are a Research Agent", tools=[duckduckgo])
    result = agent.start(query)
    # Format the result with enhanced markdown
    formatted_result = f"""
{result}
----
*Generated by PraisonAI Research Assistant*
    """
    return formatted_result

# Create a simple Gradio interface
demo = gr.Interface(
    fn=research,
    inputs=gr.Textbox(
        label="Research Query",
        placeholder="Enter your research topic...",
        lines=2
    ),
    outputs=gr.Markdown(
        show_copy_button=True,
        height=500,
        container=True
    ),
    title="AI Research Assistant",
    description="Enter your research query below to get started!",
)

if __name__ == "__main__":
    demo.launch()
3

Run Application

Run your Gradio app:
python app.py

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Features

Simple Interface

Create beautiful UIs with minimal code.

Markdown Support

Rich text output with built-in markdown rendering.

Copy Button

One-click copying of results.

Responsive Design

Mobile-friendly interface out of the box.

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Understanding the Code

The example demonstrates a simple research assistant with these key components:
  1. Function Definition:
    • research() function that processes user input
    • Agent initialization and execution
    • Result formatting with markdown
  2. Interface Setup:
    • Input textbox configuration
    • Markdown output with copy button
    • Title and description settings
  3. Launch Configuration:
    • Main entry point check
    • Server launch with default settings

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Customization

You can enhance the UI with additional Gradio components: 
# Add multiple input types
demo = gr.Interface(
    fn=process_inputs,
    inputs=[
        gr.Textbox(label="Query"),
        gr.File(label="Upload Document"),
        gr.Dropdown(choices=["Option 1", "Option 2"])
    ],
    outputs=[
        gr.Markdown(label="Results"),
        gr.Plot(label="Visualization")
    ]
)

# Add themes and styling
demo = gr.Interface(
    ...
    theme="default",
    css=".gradio-container {background-color: #f0f0f0}"
)

# Add authentication
demo.launch(auth=("username", "password"))

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Next Steps