AskAITools Community Edition provides a foundational, open-source search engine framework for the AI product domain. It enables developers to build specialized vertical search engines or internal document search systems by integrating their own data. The project aims to offer a fast, accurate, and intelligent search experience.

How It Works

The engine utilizes a hybrid search architecture, combining PostgreSQL's full-text search with Pgvector for semantic (vector) search. It leverages OpenAI's text-embedding-3 model for generating embeddings and employs weighted fusion techniques to balance relevance and popularity. This approach offers a robust and scalable solution for diverse search needs.

Quick Start & Requirements

• Install dependencies: yarn install
• Run development environment: yarn dev
• Deployment: Follow Vercel official documentation.
• Prerequisites: Supabase account, OpenAI API key, Node.js (for Next.js).
• Setup involves data structuring, Supabase table creation, environment variable configuration, and potential modification of search parameters in specified files.

Highlighted Details

• Hybrid search combining keyword and semantic (vector) search.
• Built with Next.js, Supabase (PostgreSQL, Pgvector), and Tailwind CSS.
• Utilizes OpenAI text-embedding-3 for vector generation.
• Weighted fusion techniques for relevance and popularity balancing.

Maintenance & Community

The project is maintained by askaitools. Further community engagement channels are not explicitly detailed in the README.

Licensing & Compatibility

The Community Edition is open-source. Projects derived from it must prominently acknowledge AskAITools and avoid using the AskAITools brand name. Redesign of front-end pages is recommended for projects closely resembling the commercial edition to prevent potential plagiarism issues with search engines.

Limitations & Caveats

Derived projects must retain the "Powered by AskAITools" component. Using this open-source project as a foundation for products closely resembling the commercial edition requires significant front-end redesign to avoid search engine plagiarism flags.