Here is an essential update for Cherche. The update retains the previous API and is compatible with previous versions. 🥳
Main additions:
Added compatibility with two new open-source retrievers: Meilisearch and TypeSense.
Compatibility with the Milvus index to use the retriever.Encoder and retriever.DPR models on massive corpora.
Compatibility with the Milvus index to store ranker embeddings in a database rather than in memory.
Progress bar when pre-computing embeddings by Encoder, DPR retrievers and Encoder, DPR rankers.
All pipelines (voting, intersection, concatenation) produce a similarity score. To do so, the pipeline object applies a softmax to normalize the scores, thus allowing us to "compare" the scores of two distinct models.
Integration of collaborative filtering models via adding a Recommend retriever and a Recommend ranker (indexation via Faiss and compatible with Milvus) to consider users' preferences in the search.
Here is an essential update for Cherche. The update retains the previous API and is compatible with previous versions. 🥳
Main additions:
retriever.Encoderandretriever.DPRmodels on massive corpora.