wikiqa 0.1.1

A powerful Wikipedia QA system with LLM integration

🎯 WikiQA

A powerful Wikipedia Question Answering system with LLM integration. WikiQA allows you to extract information from Wikipedia articles using natural language questions and various extraction methods.

✨ Features

• 🤖 Direct question answering about Wikipedia content
• 🔍 Entity extraction from articles
• 📝 Article summarization with customizable length and focus
• ⏳ Timeline extraction from articles
• 🔌 Support for multiple LLM providers (OpenAI, Anthropic, Together)

🚀 Installation

pip install wikiqa

🎮 Quick Start

from wikiqa import WikiQA

# Initialize with your preferred LLM provider
qa = WikiQA(
    llm_provider="together",  # or "openai" or "anthropic"
    api_key="your_api_key",
    model="your_model_name"  # optional, defaults to provider's best model
)

# Ask a question about a Wikipedia article
answer, page_url, revision_id = qa.ask(
    "What is the capital of France?",
    article="France"
)
print(f"Answer: {answer}")
print(f"Source: {page_url}")

# Extract specific information
birth_date, page_url, revision_id = qa.extract_entity(
    "Albert Einstein",
    "date of birth"
)
print(f"Birth date: {birth_date}")

# Get a summary
summary, page_url, revision_id = qa.summarize(
    article="Python (programming language)",
    length="paragraph"
)
print(f"Summary: {summary}")

# Extract a timeline
timeline, page_url, revision_id = qa.extract_timeline("World War II")
print(f"Timeline: {timeline.events}")

🤝 Supported LLM Providers

• 🎨 OpenAI (GPT models)
• 🧠 Anthropic (Claude models)
• 🌟 Together (various open-source models)

📋 Requirements

• 🐍 Python 3.8 or higher
• 🌐 Internet connection for Wikipedia access
• 🔑 API key for your chosen LLM provider

📄 License

MIT License

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

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