Implementing a full-text search feature typically involves creating an index of all the text content in your notes and images and using a full-text search engine such as Elasticsearch or Solr to perform searches based on keywords or tags. Here are some general steps to follow:

1. Set up a full-text search engine such as Elasticsearch or Solr. These engines provide powerful search capabilities and can handle large amounts of data. They also offer APIs that can be used to integrate search functionality into your website.

2. Index your notes and images. This involves parsing the text content in your notes and images and adding it to the search engine's index. You can use a tool like Apache Tika to extract text from various file formats such as PDFs and images.

3. Define your search queries. You will need to define the queries that users can use to search for notes and images based on keywords or tags. For example, you might allow users to search for notes that contain a specific word or phrase, or images that have been tagged with a certain keyword.

4. Integrate the search functionality into your website. This involves creating a search bar and search results page that allow users to enter their search queries and view the matching notes or images. You can use the search engine's API to perform the search queries and retrieve the matching results.

5. Fine-tune your search results. You may need to adjust your search algorithms to improve the accuracy and relevance of the search results. For example, you might want to boost the relevance of notes or images that match certain keywords or tags.
spam fails_task lang_mismatch pii not_appropriate hate_speech sexual_content quality toxicity humor helpfulness creativity violence