Prerequisites

  • Python 3.10 or higher
  • PraisonAI Agents package installed
  • wikipedia package installed
  • Basic understanding of Wikipedia APIs

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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 wikipedia
2

Import Components

Import the necessary components:

from praisonaiagents import Agent, Task, PraisonAIAgents
from praisonaiagents.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],
    self_reflect=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 = PraisonAIAgents(
    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

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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

​
Examples

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Basic Wikipedia Research Agent

from praisonaiagents import Agent, Task, PraisonAIAgents
from praisonaiagents.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],
    self_reflect=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 = PraisonAIAgents(
    agents=[wiki_agent],
    tasks=[research_task],
    process="sequential"
)
agents.start()

​
Advanced Research with Multiple Agents

# Create research agent
researcher_agent = Agent(
    name="Researcher",
    role="Content Researcher",
    goal="Research topics systematically.",
    tools=[wiki_search, wiki_summary, wiki_page],
    self_reflect=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],
    self_reflect=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 = PraisonAIAgents(
    agents=[researcher_agent, analysis_agent],
    tasks=[research_task, analysis_task],
    process="sequential"
)
agents.start()

​
Best Practices

​
Common Patterns

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Research Pipeline

# 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 = PraisonAIAgents(
    agents=[researcher, analyzer],
    tasks=[research_task, analyze_task]
)