Open Webui Embeddings | Agent Skills Atlas

About this skill

Wire HuggingFace embedding + reranker models (BGE-M3, BGE-Reranker-v2-m3, etc.) into Open WebUI's RAG pipeline via LiteLLM as a proxy in front of HuggingFace Text Embeddings Inference (TEI). Covers the exact wire shapes Open WebUI sends (URL auto-append on embed but NOT rerank; payload + response shapes for both modes), the LiteLLM ↔ TEI gotchas (encodingformat=null trap, HF-driver tasktype misdetection, openai-driver vs huggingface-driver tradeoffs), TEI configuration cliffs (max-client-batch-size 422 under hybrid search, max-batch-tokens AS the auto-truncate boundary, arch-specific Docker images), and the end-to-end production-grade config. BGE-M3 and BGE-Reranker-v2-m3 are the worked examples; the patterns generalise to any TEI-served encoder.

Quick start

Copy the install prompt. Use the green button above this README.
Send it to your agent. Paste it into your coding agent’s chat and send.
Review the setup. Your agent checks the skill’s instructions, requirements, and installation scope.

Installation guide →

Review, license & listing details

Review the source before using this skill

This is an imported listing. We haven’t certified its safety, license, or compatibility. Skills may include executable scripts.

Automated security scan: Partial

Only SKILL.md was scanned. Supporting files and scripts were not checked. No safety grade has been assigned.

0 potential findings · Scanned 11/4/2026 · Scanner 0.2.1

Content SHA-256: e0505b65b18a9324f4500417f4ab9c315895b721ab2944ceb900452a80cf9964

About scan coverage and limitations

Original listing metadata

Original name

open-webui-embeddings

Original description

Wire HuggingFace embedding + reranker models (BGE-M3, BGE-Reranker-v2-m3, etc.) into Open WebUI's RAG pipeline via LiteLLM as a proxy in front of HuggingFace Text Embeddings Inference (TEI). Covers the exact wire shapes Open WebUI sends (URL auto-append on embed but NOT rerank; payload + response shapes for both modes), the LiteLLM ↔ TEI gotchas (encoding_format=null trap, HF-driver task_type misdetection, openai-driver vs huggingface-driver tradeoffs), TEI configuration cliffs (max-client-batch-size 422 under hybrid search, max-batch-tokens AS the auto-truncate boundary, arch-specific Docker images), and the end-to-end production-grade config. BGE-M3 and BGE-Reranker-v2-m3 are the worked examples; the patterns generalise to any TEI-served encoder.

About this listing

Category: Engineering
Reported license: Not specified
Listing language (estimated): English
Review status: Not individually reviewed
Agent compatibility: Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.