xiaohongshu-ai-feed

To track daily Xiaohongshu AI trends, this tool retrieves posts via a REST API, clusters them by tags, and generates an HTML report with engagement metrics. You simply run the provided Python script to automatically fetch, analyze, and save the daily report locally.

The best way to cluster Xiaohongshu content is by using tag-based clustering on posts retrieved via keyword and time-range queries. This process surfaces the most engaging content by analyzing likes, shares, and comments, outputting a concise summary and a visual HTML report.

Yes, you need an API key stored in the REDFOX_API_KEY environment variable to search Xiaohongshu posts. This key authenticates the REST API requests required to retrieve posts and calculate engagement metrics for the daily trend report.

Yes, you can use keyword and time-range queries to filter Xiaohongshu AI posts. The tool applies these parameters to the REST API to retrieve specific subsets of posts, which are then clustered by tags and evaluated for engagement metrics.

Tag-based clustering for Xiaohongshu content analysis works by grouping retrieved posts into stable, date-level topic overviews based on their content tags. This method organizes high-engagement posts into categorized cards within the generated HTML report.

Limitations of using a REST API for Xiaohongshu trend reporting include dependency on the REDFOX_API_KEY environment variable and the `requests` library. The analysis is constrained by the available engagement metrics and the accuracy of the tag-based clustering algorithm.