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data-layer

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Manage vector stores, chunking, and RAG.

Software Engineering#semantic search#embeddings#RAG#chunking#vector store#data layer
Authorai-kitchen-inc
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This Skill streamlines the process of preparing and managing data for AI models, enabling efficient semantic search and Retrieval-Augmented Generation (RAG) workflows.

Core Features & Use Cases

  • Document Chunking: Splits large documents into smaller, manageable pieces for indexing.
  • Vector Store Integration: Supports semantic search capabilities with vector databases like Pinecone.
  • RAG Implementation: Facilitates building RAG pipelines by retrieving relevant information to augment AI responses.
  • Use Case: Automatically chunk a large research paper, index it into a vector store, and then retrieve the most relevant sections to answer a specific question about the paper's findings.

Quick Start

Use the data-layer skill to chunk the document 'report.pdf' with a chunk size of 1000 characters and an overlap of 200 characters.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: data-layer
Download link: https://github.com/ai-kitchen-inc/openbench/archive/main.zip#data-layer

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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