Trieve Primitives

Chunk: A chunk is a piece of data that is uploaded to Trieve. It is the smallest unit of data that can be searched, recommended, or used in RAG. Chunks are typically created by chunking a larger piece of data into smaller pieces. For example, a document can be chunked into paragraphs, sentences, or even words depending on the use case.

• Tag Set: A tag set is a collection of tags that can be associated with a chunk. Tags can be used to categorize or filter chunks based on specific criteria. For example, a chunk representing a job posting could be tagged with the job title, location, company name, etc.

• Metadata: Metadata is a json object that can be associated with a chunk. Metadata can be used to store additional information about a chunk, such as the source of the data, creation date, author, etc. Although filtering by metadata is supported, it is not recommended if latency is a concern.

Groups: Groups are a way to associate related chunks together. Chunks that belong to the same group are considered to be related in some way. For example, chunks representing different sections of a document can be grouped together to indicate that they are part of the same document. You can perform queries within a group or across groups.

Dataset: A dataset is a collection of chunks. Datasets are created in the Trieve dashboard and are used to organize and manage chunks. Datasets can be used to search, recommend, or generate responses using RAG.

Search: Search is the process of finding relevant chunks in a dataset based on a query. Trieve provides a search API that allows you to search for chunks based on text similarity.

Recommendations: Recommendations are a list of chunks that are similar to a given chunk. Trieve provides a recommendation API that allows you to get recommendations for a chunk based on text similarity.

RAG (Retrieval Augmented Generation): RAG is a technique that combines search and generation to generate responses to user queries. Trieve provides a RAG API that allows you to generate responses to user queries based on the content of your dataset.