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Installable packages, the resource types built into kdeps, and the versioned assets kdeps runs on, in one catalog. The colored badge on each entry says which kind it is.
8 entries
Rerank a list of documents by relevance to a query using Cohere's reranking API. Returns documents sorted by relevance score. Requires COHERE_API_KEY.
Search for documents semantically similar to a query in the local embedding database. Returns ranked results with similarity scores. Requires: query (natural language search query), collection (name of the document collection). Optional: limit (max results, default 5).
Convert text into vector embeddings using an embedding model. Returns the embedding vectors. Use for indexing documents into the local embedding database or computing semantic similarity. Requires: texts (list of strings to embed). Optional: model, backend.
Rerank a list of documents by relevance to a query using Jina AI's reranking API. Requires JINA_API_KEY.
Load a document file and return its content as text. Supports PDF (langchaingo pdf loader), DOCX/EPUB/RTF/ODT (pandoc), HTML (goquery, lynx), CSV, text, directory, notion, markdown (textutil). Use for reading documents into the conversation for analysis or RAG pipelines. Returns document content with optional splitting into chunks. Requires: source (absolute file path). Optional: type (pdf, csv, html, text - auto-detected from extension), columns (CSV column filter), password (encrypted PDF), chunkSize (split into chunks of N characters), chunkOverlap, chunkSplitter (recursive, token, markdown).
Retrieve semantically relevant text chunks from the configured RAG index. Use for finding code, documentation, or notes related to a query before implementing or answering. Requires KDEPS_RAG_BASE_URL pointing to a compatible RAG service.
Search for text patterns in local files using ripgrep. Returns matching files with a snippet, and (when the query is found) a match_id/line/revision - pass match_id to read_file to jump straight to that hit. Use for finding usages, patterns, or strings across the codebase. Requires: query (search term). path is the directory to search; leave it out to search every folder of the working project (its own and the search folders its card lists). Optional: glob (file pattern), limit (max results, default 3), index (rank results with the folder index); index also accepts fuzzy, maxDistance, indexDBPath and graphBoost.
Rerank a list of documents by relevance to a query using VoyageAI's reranking API. Requires VOYAGEAI_API_KEY.