RAG Search API

RAG Search API is an intelligent search API developed by thinkany.ai. It combines search and generation technologies to provide efficient and accurate information retrieval services. This API supports a variety of custom configurations, including search quantity, sorting method, filtering conditions, etc., which can meet the needs of different users.

The target audience includes developers and enterprise users, especially those teams that need to build or optimize search capabilities. The API can be easily integrated into existing systems, improving search efficiency and accuracy while saving development time and cost.

Example of usage scenario

Enterprise Applications: Enterprises can use RAG Search API to optimize internal document search systems to improve employee retrieval efficiency.

Developer Application: Developers can use this API to build a personalized search engine and provide customized search services.

Educational Institutions: Educational Institutions can integrate this API to provide students with the ability to quickly retrieve academic resources.

Product Features

Supports multiple search providers, such as Google.

Provides rearrangement function and optimizes search results through flashrank algorithm.

Users can customize the search quantity and level of detail.

Supports setting the minimum score threshold for result filtering.

Allows the user to set the degree and quantity of the returned results.

Provides an API interface that is easy to integrate and use.

Usage tutorial

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 through the API, including parameters such as query content and search quantity.

5. Analyze the search results based on the returned JSON data.

6. Further process or display the results as needed.