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Creates a portable AI workspace on a USB drive or any drive. RAG pipeline with local LLM models (Ollama), vector database (ChromaDB), and preconfigured prompts.
Passed 22 of 22 test cases with the skill, and 7 of 22 without it.
and 17 more in the full report
15 fixed7 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 15 test cases the skill fixed. Same model, same prompt, with and without the skill.
In the AI Portable Setup offline workspace layout, which default embedding model is designated for vectorizing text chunks into ChromaDB?
| Checked | Without skill | With skill |
|---|---|---|
| Identifies nomic-embed-text as the default embedding model | Missed | Passed |
The instructions your model reads when the skill loads.
Erstellt eine portable KI-Arbeitsumgebung mit lokaler RAG-Pipeline. Gedacht fuer USB-Sticks oder externe Laufwerke -- funktioniert offline mit Ollama und lokalen Embedding-Modellen.
# Struktur auf USB-Stick erstellen
python setup_portable.py E:\AI-Portable
# Danach auf dem Zielsystem:
cd E:\AI-Portable
python -m venv venv
venv\Scripts\activate # Windows
pip install chromadb ollama
# Dokumente indexieren
python rag/ingest.py
# Abfragen
python rag/query.py "Meine Frage..."
python rag/query.py --mode icf "Beobachtungen zum Klienten"
AI-Portable/
models/
llm/ Lokale LLM-Modelle (Mistral, Llama, etc.)
embeddings/ Embedding-Modelle (nomic-embed-text, bge-small)
tts/ Optional: Text-to-Speech (Piper, Coqui)
db/
chroma/ ChromaDB Vektordatenbank
sqlite/ Metadaten-DB
documents/
test cases passed, vs 7 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.