---
title: "Research Agent"
sidebarTitle: "Research"
description: "Learn how to create AI agents for conducting comprehensive research and analysis."
icon: "magnifying-glass-chart"
---

```mermaid
flowchart LR
    In[Research Query] --> Search[Web Search]
    Search --> Analyzer[Content Analyzer]
    Analyzer --> Synthesizer[Information Synthesizer]
    Synthesizer --> Out[Research Report]
    
    style In fill:#8B0000,color:#fff
    style Search fill:#2E8B57,color:#fff
    style Analyzer fill:#2E8B57,color:#fff
    style Synthesizer fill:#2E8B57,color:#fff
    style Out fill:#8B0000,color:#fff
```

A workflow demonstrating how the Research Agent can gather, analyze, and synthesize information from various sources.

## Quick Start

<Steps>
    <Step title="Install Package">
        First, install the PraisonAI Agents package:
        ```bash
        pip install praisonaiagents
        ```
    </Step>

    <Step title="Set API Key">
        Set your OpenAI API key as an environment variable:
        ```bash
        export OPENAI_API_KEY=your_api_key_here
        ```
    </Step>

    <Step title="Create Script">
        Create a new file `research_assistant.py`:
        ```python
        from praisonaiagents import Agent, Tools
        from praisonaiagents.tools import duckduckgo

        # Create Research Agent
        research_agent = Agent(
            name="ResearchAssistant",
            role="Research Specialist",
            goal="Conduct comprehensive research and analysis",
            instructions="You are a Research Agent",
            tools=[duckduckgo]
        )

        # Conduct research
        response = research_agent.start(
            "Research about AI developments in 2024"
        )
        
        # Save research findings
        with open('research_report.md', 'w') as f:
            f.write(response)
        ```
    </Step>
</Steps>

## Understanding Research Process

The Research Agent employs a systematic approach to information gathering and analysis:

1. **Web Search**: Uses DuckDuckGo to find relevant sources
2. **Content Analysis**: Evaluates source credibility and relevance
3. **Information Synthesis**: Combines findings into coherent insights
4. **Report Generation**: Creates structured research reports

## Features

<CardGroup cols={2}>
  <Card title="Web Research" icon="globe">
    Comprehensive online information gathering.
  </Card>
  <Card title="Content Analysis" icon="microscope">
    In-depth evaluation of sources.
  </Card>
  <Card title="Information Synthesis" icon="layer-group">
    Integration of multiple sources.
  </Card>
  <Card title="Report Generation" icon="file-lines">
    Structured research documentation.
  </Card>
</CardGroup>

## Example Usage

```python
from praisonaiagents import Agent, Tools
from praisonaiagents.tools import duckduckgo

agent = Agent(instructions="You are a Research Agent", tools=[duckduckgo])
agent.start("Research about AI 2024")
```

## Next Steps

- Learn about [Prompt Chaining](/features/promptchaining) for complex research projects
- Explore [Evaluator Optimizer](/features/evaluator-optimiser) for improving research quality
- Check out the [Data Analyst Agent](/agents/data-analyst) for data-driven research