> ## Documentation Index
> Fetch the complete documentation index at: https://praison.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Wikipedia Search Tool

> Guide for using the Wikipedia Search tool with PraisonAI agents.

The Wikipedia Search tool lets an agent look up and retrieve encyclopedic facts from Wikipedia.

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
graph LR
    subgraph "Wikipedia Search"
        User[User] --> Agent[Agent]
        Agent --> Tool[WikipediaAPIWrapper]
        Tool --> API[Wikipedia API]
        API --> Result[Articles]
    end

    classDef input fill:#8B0000,stroke:#7C90A0,color:#fff
    classDef process fill:#189AB4,stroke:#7C90A0,color:#fff
    classDef output fill:#10B981,stroke:#7C90A0,color:#fff

    class User,Agent input
    class Tool,API process
    class Result output
```

## Overview

The Wikipedia Search tool is a tool that allows you to search and retrieve information from Wikipedia.

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
pip install langchain-community
export OPENAI_API_KEY="${OPENAI_API_KEY:?Set OPENAI_API_KEY in your shell}"
```

```python theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
from praisonaiagents import Agent, AgentTeam
from langchain_community.utilities import WikipediaAPIWrapper

data_agent = Agent(instructions="Gather all of Messi's record in LaLiga", tools=[WikipediaAPIWrapper])
summarise_agent = Agent(instructions="Summarize the data into a well structured format")
agents = AgentTeam(agents=[data_agent, summarise_agent])
agents.start()
```

## How It Works

```mermaid theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
sequenceDiagram
    participant User
    participant Agent
    participant Wikipedia as WikipediaAPIWrapper
    participant API as Wikipedia API

    User->>Agent: "Look up X"
    Agent->>Wikipedia: run(query)
    Wikipedia->>API: HTTPS request
    API-->>Wikipedia: article summary
    Wikipedia-->>Agent: parsed result
    Agent-->>User: final answer
```

## Getting Started

<Steps>
  <Step title="Simple Usage">
    1. Install dependencies (see **Overview** above)
    2. Set required API keys in your environment
    3. Run the agent example in **Overview**
  </Step>

  <Step title="With Configuration">
    Use the same tool with an agent — see the **Overview** example, or pass env vars from the sections above.
  </Step>
</Steps>

## Best Practices

<AccordionGroup>
  <Accordion title="No provider key needed">
    Wikipedia search is free — only `OPENAI_API_KEY` for the agent's LLM is required. `WikipediaAPIWrapper` needs no API key.
  </Accordion>

  <Accordion title="Limit returned characters">
    `WikipediaAPIWrapper` accepts `doc_content_chars_max`. Cap it so long articles do not overflow the agent's context window.
  </Accordion>

  <Accordion title="Disambiguate queries">
    Ambiguous terms return the wrong page. Feed the agent specific titles (e.g. "Lionel Messi") so results match intent.
  </Accordion>
</AccordionGroup>

## Related Tools

<CardGroup cols={2}>
  <Card title="Wikipedia" icon="book" href="/docs/tools/external/wikipedia">
    Wikipedia tool
  </Card>

  <Card title="Tavily" icon="book" href="/docs/tools/external/tavily">
    AI-powered search
  </Card>

  <Card title="ArXiv" icon="book" href="/docs/tools/external/arxiv">
    Academic papers
  </Card>
</CardGroup>