Ingest: Streamlining Content Preparation for LLMs
Ingest is a tool I’ve written to make my life easier when preparing content for LLMs. It parses directories of plain text files, such as source code, documentation etc… into a single markdown file suitable for ingestion by AI/LLMs. Ingest can also estimate vRAM requirements for a given model, quantisation and context length: Features Traverse directory structures and generate a tree view Include/exclude files based on glob patterns Estimate vRAM requirements and check model compatibility using another package I’ve created called quantest Parse output directly to LLMs such as Ollama or any OpenAI compatible API for processing Generate and include git diffs and logs Count approximate tokens for LLM compatibility Customisable output templates Copy output to clipboard (when available) Export to file or print to console Optional JSON output Ingest Intro (“Podcast” Episode): ...