`mp-ai-module-controller` is a Rust CLI scaffold for local llama.cpp-driven action dispatch. It starts a local `llama-server`, generates an action dictionary for small-model training and runtime lookup, queries the server through its OpenAI-compatible chat endpoint, and dispatches exact-match Rust scripts.
## Commands
- Build: `cargo build`
- Test: `cargo test`
- Generate dictionary: `cargo run -- dictionary generate`
- Start llama.cpp: `cargo run -- serve`
- Query local model: `cargo run -- query "log hello from codex"`
- Direct proof-of-concept dispatch: `cargo run -- run logger --payload '{"message":"hello from codex"}'`
Use `.env` for local values and keep it out of git. Update `.env.example`, `README.md`, `manifest.llm.json`, and `llm.txt` when environment variables or commands change.
## Dictionary Rules
-`src/registry.rs` is the source of truth for action definitions.
-`dictionary/actions.jsonl` is generated canonical training data.
-`dictionary/actions.index.json` is the generated runtime lookup file.
- Regenerate dictionary files with `cargo run -- dictionary generate` after changing registered actions.
- Do not manually edit generated dictionary files.
## Dispatch Rules
- Dispatch only exact `action_id` values present in `dictionary/actions.index.json`.
- Aliases and intent examples are training hints only; they are not executable ids.
- Unknown, malformed, ambiguous, missing, or empty action ids must be rejected without running scripts.
- Script processes are detached. The controller spawns them and does not monitor completion.
- Keep script payload validation strict and local to the script module.
