e-p-armstrong/augmentoolkit

Health v2 · maintenance only

Adoption not part of the score

1864 stars · 247 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Augmentoolkit is a Python application that generates domain-expert fine-tuning datasets from uploaded documents and trains custom LLMs on them, optionally fully offline using local inference. It also produces RAG-ready datasets and can spin up an inference server.

Use cases

• create a custom LLM trained on my own documents
• generate fine-tuning datasets from text files
• make an AI expert in a specific domain or research field
• build a RAG dataset automatically from my documents
• fine-tune an LLM offline without an API key
• create a lore expert chatbot for a fictional universe

When to choose

• you want full control over an LLM's knowledge by fine-tuning it on your own sources
• you need synthetic instruction datasets generated locally without external APIs
• you want both a fine-tuned model and a RAG dataset from the same documents

When to avoid

• you only need prompt-based RAG without fine-tuning
• you lack a capable GPU and don't want to rent training compute
• you need a quick no-code chatbot rather than a training pipeline

Facets

application · maturity active

llm-training rag data-generation llm-inference etl large-language-models machine-learning artificial-intelligence windows python self-hosted finetuning synthetic-data domain-expert-llm dataset-generation local-inference offline retrieval-augmented-generation data-engineering linux macos gpu

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