RAG Search API
R
RAG Search API
Overview :
RAG Search API, developed by thinkany.ai, is an intelligent search API that utilizes RAG (Retrieval-Augmented Generation) technology. It combines retrieval and generation capabilities to deliver efficient and accurate information retrieval for users. The API supports customizable configurations, including search quantity, re-ranking options, and filtering, to meet diverse user needs.
Target Users :
Targeted at developers and enterprise users, especially teams building or optimizing search functionality. This API can be integrated into existing systems to improve search efficiency and accuracy, saving development time and cost.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 54.4K
Use Cases
Enterprises use RAG Search API to optimize internal document search systems, enhancing employee retrieval efficiency.
Developers leverage the API to build personalized search engines, offering customized search services.
Educational institutions integrate the API to provide students with rapid access to academic resources.
Features
Supports multiple search providers, such as Google.
Provides re-ranking functionality using the flashrank algorithm to optimize search results.
Allows users to customize search quantity and level of detail.
Supports setting a minimum score threshold for result filtering.
Allows users to set the level of detail and quantity of returned results.
Provides an API interface for easy integration and use by developers.
How to Use
1. Create a .env file in the project root directory and set the corresponding environment variables.
2. Install the required dependencies.
3. Start the FastAPI server.
4. Send requests to the API, including query content and search parameters.
5. Parse the search results from the returned JSON data.
6. Further process or display the results as needed.
AIbase
Empowering the Future, Your AI Solution Knowledge Base
© 2025AIbase