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open-webui-embeddings

Official

Wire TEI embeddings into Open WebUI's RAG

Software Engineering#embeddings#rag#translation#rerank#litellm#open-webui#tei
Authorair-gapped
Version1.0.0
Installs0

System Documentation

What problem does it solve?

Open WebUI's retrieval-augmented generation (RAG) stack often requires correct wiring of TEI embeddings and reranking to TEI-compatible endpoints. This skill provides an operator-focused blueprint for connecting HuggingFace TEI embeddings through LiteLLM to TEI/Open WebUI, including exact wire shapes, necessary configuration, and error-handling considerations.

Core Features & Use Cases

  • Wire TEI embeddings via OpenAI-compatible /v1/embeddings path with proper model wiring.
  • Rerank through Cohere↔TEI translation for the /rerank endpoint and the associated data shapes.
  • Use Case: Deploy a robust TEI-backed Open WebUI RAG for enterprise search and knowledge retrieval.

Quick Start

Configure TEI endpoints, LiteLLM, and Open WebUI with the correct embedding and rerank paths to enable end-to-end TEI-backed Open WebUI RAG.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

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Please help me install this Skill:
Name: open-webui-embeddings
Download link: https://github.com/air-gapped/skills/archive/main.zip#open-webui-embeddings

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