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AI Portable Setup (Deutsch)

Creates a portable AI workspace with a local RAG pipeline. Designed for USB drives or external drives — works offline with Ollama and local embedding models.

Quick Start

bash
# Create structure on USB drive (Deutsch)
python setup_portable.py E:\AI-Portable

# Then on the target system: (Deutsch)
cd E:\AI-Portable
python -m venv venv
venv\Scripts\activate          # Windows
pip install chromadb ollama

# Index documents (Deutsch)
python rag/ingest.py

# Query (Deutsch)
python rag/query.py "My question..."
python rag/query.py --mode icf "Observations about the client"

Generated Directory Structure

AI-Portable/
  models/
    llm/                  Local LLM models (Mistral, Llama, etc.)
    embeddings/           Embedding models (nomic-embed-text, bge-small)
    tts/                  Optional: Text-to-Speech (Piper, Coqui)
  db/
    chroma/               ChromaDB vector database
    sqlite/               Metadata DB
  documents/
    code/                 Code snippets, projects
    general/              General documents
  rag/
    ingest.py             Ingest and index files
    query.py              RAG queries with mode selection
    pipeline.py           Main RAG pipeline (embed + query + LLM)
  prompts/
    coding.txt            Coding assistant prompt
    icf.txt               ICF structuring prompt
    rpg.txt               Pen-and-paper game master prompt
  templates/              Word/PDF templates
  venv/                   Portable Python environment

RAG Pipeline

Documents -> Chunking -> Embedding (nomic-embed-text)
                              |
                              v
                         ChromaDB (local)
                              |
Query -> Embedding -> Similarity Search -> Top-K Chunks
                                              |
                                              v
                                    Context + Prompt -> Ollama (Mistral)
                                              |
                                              v
                                          Response

Query Modes

| Mode | Prompt | Usage | |------|--------|-------| | default | General assistant | Standard queries | | icf | ICF structuring | Classify observations according to ICF | | coding | Coding assistant | Write and explain code | | rpg | Game master | Pen-and-paper role-playing |

Requirements on Target System

• Python 3.10+
• Ollama (with mistral:instruct and nomic-embed-text)
• ~8 GB RAM for Mistral

Änderungsprotokoll

1.0.0 (2026-03-12)

• Consolidation from MODULAR_AGENTS/AI-Portable
• Setup script as single-file skill
• 4 preconfigured prompts (coding, icf, rpg, default)
• RAG pipeline (ingest, query, pipeline)