rag-pipeline

Plugin rag-pipeline from marketplace ai-dev-marketplace in vanman2024/ai-dev-marketplace. Commands read from the repo's manifest — 1 month ago.

Skills (3)

• chunking-strategies

  Document chunking implementations and benchmarking tools for RAG pipelines including fixed-size, semantic, recursive, and sentence-based strategies. Use when implementing document processing, optimizing chunk sizes, comparing chunking approaches, benchmarking retrieval performance, or when user ment

• document-parsers

  Multi-format document parsing tools for PDF, DOCX, HTML, and Markdown with support for LlamaParse, Unstructured.io, PyPDF2, PDFPlumber, and python-docx. Use when parsing documents, extracting text from PDFs, processing Word documents, converting HTML to text, extracting tables from documents, buildi

• google-file-search

  Google File Search API patterns for managed RAG with Gemini. Covers both TypeScript (@google/genai) and Python (google-genai) SDKs. Use when building File Search integrations, implementing RAG with Google AI, or when user mentions Google File Search, Gemini RAG, document indexing, or semantic search

Slash commands (2)

• /rag-pipeline:add

  Add a specific feature to an existing RAG pipeline project. Features include document, search, embeddings, vectordb.

• /rag-pipeline:build

  Build Google File Search powered RAG pipeline - managed retrieval with document processing and chunking

Subagents (3)

• document-processor

  Multi-format document parsing and preparation for Google File Search - handles PDF, DOCX, HTML, Markdown with text extraction and metadata preparation

• google-file-search-py

  Google File Search API specialist for Python - creates stores, uploads documents, implements search and RAG using the official google-genai SDK

• google-file-search-ts

  Google File Search API specialist for TypeScript/JavaScript - creates stores, uploads documents, implements search and RAG using the official @google/genai SDK

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