Wikipedia Agent

Wikipedia data retrieval tools for AI agents.

Prerequisites

• Python 3.10 or higher
• PraisonAI Agents package installed
• PraisonAI Tools package installed
• wikipedia package installed

Wikipedia Tools

Use Wikipedia Tools to retrieve and analyze Wikipedia content with AI agents.

1. Install Dependencies

   First, install the required packages:

   pip install praisonaiagents praisonai-tools wikipedia
   
2. Import Components

   Import the necessary components:

   from praisonaiagents import Agent, Task, AgentTeam
   from praisonai_tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language
   
3. Create Agent

   Create a Wikipedia research agent:

   wiki_agent = Agent(
       name="WikiResearcher",
       role="Wikipedia Research Specialist",
       goal="Research and analyze Wikipedia content efficiently.",
       backstory="Expert in information retrieval and content analysis.",
       tools=[wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language],
       reflection=False
   )
   
4. Define Task

   Define the research task:

   research_task = Task(
       description="Research historical events and gather information.",
       expected_output="Comprehensive research summary with citations.",
       agent=wiki_agent,
       name="historical_research"
   )
   
5. Run Agent

   Initialize and run the agent:

   agents = AgentTeam(
       agents=[wiki_agent],
       tasks=[research_task],
       process="sequential"
   )
   agents.start()
   

Understanding Wikipedia Tools

What are Wikipedia Tools?

Wikipedia Tools provide research capabilities for AI agents:

• Article search and retrieval
• Content summary generation
• Full page information access
• Random article discovery
• Multi-language support

Key Components

Wiki Agent

Create specialized research agents:

Agent(tools=[wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language])

Wiki Task

Define research tasks:

Task(description="wiki_query")

Process Types

Sequential or parallel processing:

process="sequential"

Wiki Options

Customize search parameters:

language="en", sentences=3

Available Functions

from praisonai_tools import wiki_search
from praisonai_tools import wiki_summary
from praisonai_tools import wiki_page
from praisonai_tools import wiki_random
from praisonai_tools import wiki_language

Examples

Basic Wikipedia Research Agent

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language

# Create Wikipedia agent
wiki_agent = Agent(
    name="WikiExpert",
    role="Research Specialist",
    goal="Research topics efficiently and accurately.",
    backstory="Expert in information gathering and analysis.",
    tools=[wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language],
    reflection=False
)

# Define research task
research_task = Task(
    description="Research scientific discoveries and breakthroughs.",
    expected_output="Detailed research report with references.",
    agent=wiki_agent,
    name="science_research"
)

# Run agent
agents = AgentTeam(
    agents=[wiki_agent],
    tasks=[research_task],
    process="sequential"
)
agents.start()

Advanced Research with Multiple Agents

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language

# Create research agent
researcher_agent = Agent(
    name="Researcher",
    role="Content Researcher",
    goal="Research topics systematically.",
    tools=[wiki_search, wiki_summary, wiki_page],
    reflection=False
)

# Create analysis agent
analysis_agent = Agent(
    name="Analyzer",
    role="Content Analyst",
    goal="Analyze and summarize research findings.",
    backstory="Expert in content analysis and synthesis.",
    tools=[wiki_summary, wiki_page],
    reflection=False
)

# Define tasks
research_task = Task(
    description="Research technological advancements.",
    agent=researcher_agent,
    name="tech_research"
)

analysis_task = Task(
    description="Analyze and synthesize research findings.",
    agent=analysis_agent,
    name="content_analysis"
)

# Run agents
agents = AgentTeam(
    agents=[researcher_agent, analysis_agent],
    tasks=[research_task, analysis_task],
    process="sequential"
)
agents.start()

Best Practices

Agent Configuration

Configure agents with clear research focus:

from praisonai_tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language

Agent(
    name="WikiResearcher",
    role="Research Specialist",
    goal="Research topics accurately and efficiently",
    tools=[wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language]
)

Task Definition

Define specific research objectives:

Task(
    description="Research historical events and gather sources",
    expected_output="Detailed research summary"
)

Common Patterns

Research Pipeline

from praisonaiagents import Agent, Task, AgentTeam
from praisonai_tools import wiki_search, wiki_summary, wiki_page, wiki_random, wiki_language

# Research agent
researcher = Agent(
    name="Researcher",
    role="Wiki Researcher",
    tools=[wiki_search, wiki_summary, wiki_page]
)

# Analysis agent
analyzer = Agent(
    name="Analyzer",
    role="Content Analyzer",
    tools=[wiki_summary, wiki_page]
)

# Define tasks
research_task = Task(
    description="Research topic",
    agent=researcher
)

analyze_task = Task(
    description="Analyze findings",
    agent=analyzer
)

# Run workflow
agents = AgentTeam(
    agents=[researcher, analyzer],
    tasks=[research_task, analyze_task]
)