retrieval-augmented-generation
CommunityEnhance knowledge retrieval with semantic search and graph analysis.
Authorgatovillano
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill solves the challenge of accessing specific user information, in-depth context, and relationship analysis within a knowledge base, providing comprehensive information retrieval through RAG (Retrieval Augmented Generation).
Core Features & Use Cases
- Semantic Search: Allows for searching within the knowledge base using natural language, leveraging pgvector for semantic similarity.
- Knowledge Graph Navigation: Enables exploration of conceptual relationships and in-depth analysis of user's knowledge graph.
- Scoped Analysis: Focuses on specific user content or documents for tailored searches.
- Multi-source Retrieval: Combines results from various knowledge sources for a holistic view.
- Confidence Scoring: Evaluates the relevance of search results.
- Use Case: When a user needs to find specific information from their notes, documents, or the knowledge graph, or when the context of a user's projects needs to be analyzed.
Quick Start
Use the retrieval-augmented-generation skill to find related notes and documents about "machine learning project" in your workspace.
Dependency Matrix
Required Modules
PostgreSQLpgvectorNeo4j
Components
scriptsreferences
💻 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: retrieval-augmented-generation Download link: https://github.com/gatovillano/KognitoAI/archive/main.zip#retrieval-augmented-generation Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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