llayer applies the Unix philosophy to large language model orchestration by building framework-free agents with bash, curl, and jq. The architecture decomposes the agent lifecycle into three fundamentals: an append-only JSONL history file for state and memory, a jq stream reducer for context window management, and a standard bash while loop for control flow. This stateless text pipeline enables time-travel debugging via simple file slicing, zero abstraction tooling through native bash functions, and seamless POSIX tool integration for filtering or benchmarking. The system functions as a REPL-style loop that ingests user input, constructs context, evaluates it against a local model like Ollama, handles tool dispatches, and outputs results. All interactions are recorded immutably in a structured JSONL event schema, prioritizing transparency, composability, and minimalist design.
- Append-only JSONL history for auditing and replayability
- Modular command chaining for stateless and stateful interactions
- Docker Compose integration for local Ollama inference
- Transparent POSIX tool pipeline for data filtering and token benchmarking
- Minimalist schema with explicit event types and sources
- Append-only JSONL history for auditing and replayability
- Modular command chaining for stateless and stateful interactions
- Docker Compose integration for local Ollama inference
- Transparent POSIX tool pipeline for data filtering and token benchmarking
- Minimalist schema with explicit event types and sources
yq is a command-line tool that processes YAML, XML, and TOML files by converting them to JSON and using jq for further processing. It supports various options for preserving YAML tags and styles, and can be used as a module for in-place edits.
The article discusses the use of jq, xq, and yq tools for processing JSON, XML, and YAML data from the command line. It includes examples of how to use these tools to extract and manipulate data, as well as converting GPX files to CSV format.
A new plugin for LLM, llm-jq, generates and executes jq programs based on human-language descriptions, allowing users to manipulate JSON data without needing to write jq syntax.
