Welcome to Wikipedia Insights Validator, a project designed to showcase the power of Large Language Models (LLMs) in extracting, interacting with, and validating information from open-source datasets like Wikipedia. This repository is a testament to the harmony between AI and data-driven solutions.
The primary objective of this project is to:
- Query an open-source dataset (Wikipedia Dumps).
- Interact with a Large Language Model (LLM) to answer dataset-related questions.
- Validate and provide constructive feedback on the LLM's responses.
Through this, the project demonstrates the potential of AI in modern problem-solving and knowledge validation.
This project leverages a variety of powerful tools and frameworks:
- Node.js: The backbone for server-side scripting and application logic.
- OpenAI API: For querying and interacting with the GPT-based LLMs.
- sax: For streaming, parsing and processing XML-based Wikipedia Dumps.
- dotenv: For securely managing API keys and environment variables.
- fs: Node.js File System module to handle dataset files.
- Wikipedia Dumps: An open-source treasure trove of structured and unstructured knowledge.
-
Dataset Integration:
- Parses Wikipedia Dumps for structured data.
- Extracts articles based on custom queries.
- Download the simplewiki dataset here
-
AI Interaction:
- Queries OpenAI's LLMs for insights related to the dataset.
- Asks context-based questions about Wikipedia articles.
-
Validation Mechanism:
- Validates LLM responses for accuracy, completeness, and relevance.
- Provides structured feedback to improve interaction quality.
-
Scalability:
- Designed with modular architecture for easy expansion and feature addition.
📁 wikipedia-insights-validator/ ├── 📄 .env # Environment variables (API keys, etc.) ├── 📄 📁 data ├── loadDataset.js # Core script for parsing and querying dataset ├── 📄 package.json # Project dependencies and scripts ├── 📄 README.md # Project documentation ├── 📄 server.js # Optional: Web interface for querying LLMs └── 📄 queryLLM.js # LLM query interaction logic
- Clone the repository:
git clone [email protected]:Alabs02/wikipedia-insights-validator.git cd wikipedia-insights-validator- Install dependencies:
pnpm installOR
npm i -S- Set up your environment:
- Obtain your OpenAI API key.
- Create a ==.env== file and add:
OPENAI_API_KEY=your_api_key_here- Run the script:
pnpm devOR
npm run dev- Educational AI Assistants: Enhance the way students learn by validating LLM-driven insights.
- Knowledge Validation: Automatically fact-check AI-generated content against authoritative datasets.
- AI Research: Benchmark LLM performance on open-source data.
Contributions are welcome! If you’d like to add features, improve existing ones, or fix bugs, feel free to open a PR.
This project is licensed under the MIT License.
If you have any questions or suggestions, feel free to connect: