Lumotia/docs/architecture-map/04-llm-formatting-mcp/llm-cleanup-text.md

---
name: LLM cleanup_text surface
type: architecture-map-page
slice: 04-llm-formatting-mcp
last_verified: 2026/05/09
---

# LLM `cleanup_text` surface

> **Where you are:** [Architecture map](../README.md) → [LLM, Formatting, MCP](README.md) → cleanup_text

**Plain English summary.** `cleanup_text` is the freeform LLM call. Given any system prompt and a transcript, it returns the LLM's cleaned version as plain text. No grammar constraint, no JSON parsing. The formatting crate's `llm_client::cleanup_text` is the only canonical caller and supplies the prompt-injection-hardened system prompt.

## At a glance

- Crate: `magnotia-llm`
- Path: `crates/llm/src/lib.rs:232`
- LOC: 21 lines for this method
- Public surface: `pub fn cleanup_text(&self, system_prompt: &str, transcript: &str) -> Result<String, EngineError>`
- External deps that matter: none beyond what `LlmEngine::generate` already pulls in
- Tauri command that calls this (slice 2, best guess): not called directly by Tauri. The chain is `commands::llm::cleanup_transcript_text_cmd` (`src-tauri/src/commands/llm.rs:363`) → `magnotia_ai_formatting::llm_cleanup_text` (`src-tauri/src/commands/llm.rs:395`) → this method. Also reached from `commands::transcription::*` and `commands::live::*` via the formatting pipeline at `crates/ai-formatting/src/pipeline.rs:84`.

## What's in here

```text
pub fn cleanup_text(&self, system_prompt: &str, transcript: &str) -> Result<String, EngineError>
```

Behaviour:

1. If `transcript.trim().is_empty()`, return `Ok(String::new())` immediately. No model touch.
2. Borrow the loaded model via `loaded_model_arc()`. Returns `EngineError::NotLoaded` if no model is loaded.
3. Render a chat prompt with two messages — `("system", system_prompt)` and `("user", transcript)` — through `render_chat_prompt`, which applies the model's tokenizer-bundled chat template and falls back to ChatML if missing.
4. Call `generate` with:
   - `max_tokens: 1024`
   - `temperature: 0.0`
   - `stop_sequences: ["<|im_end|>", "<|im_end_of_text|>"]`
   - `grammar: None`

Returns the trimmed, post-stop-sequence-truncated output verbatim.

## Data flow

```
(system_prompt: &str, transcript: &str)
  → empty-transcript short-circuit (returns "")
  → loaded_model_arc()  (NotLoaded error if absent)
  → render_chat_prompt([(system, system_prompt), (user, transcript)])
  → generate(prompt, GenerationConfig { max_tokens: 1024, temp: 0.0, stops: [<|im_end|>, <|im_end_of_text|>], grammar: None })
  → trimmed String
```

No JSON parse, no GBNF, no closed set. The contract with the caller is "do whatever the system prompt tells you to do".

## Prompts and grammars

`cleanup_text` itself does not own a prompt — the system prompt is a parameter. The canonical caller is `magnotia_ai_formatting::llm_client::cleanup_text` which composes:

```text
CLEANUP_PROMPT  +  format_dictionary_suffix(dictionary_terms)  +  preset.suffix()
```

See [`formatting-llm-cleanup-bridge.md`](formatting-llm-cleanup-bridge.md) for the full composition logic and prompt-injection-hardening rationale, and [`llm-prompts-and-grammars.md`](llm-prompts-and-grammars.md) for the prompt text in full.

## Watch-outs

- **No grammar means the model can output anything.** This is by design — cleanup is freeform — but it means the prompt is the only line of defence against prompt injection. The `llm_client` bridge handles this; do not call `LlmEngine::cleanup_text` from anywhere else without porting that hardening.
- **`max_tokens: 1024` is a hard ceiling on output length.** A long dictation that compresses well is fine; one that compresses poorly will be cut off mid-sentence. The pipeline does not detect or retry truncated output. If we ever get reports of mid-sentence drops on long transcripts, raise this constant in tandem with the preflight cap.
- **`temperature: 0.0` plus the fixed seed makes output deterministic for a given prompt and loaded model.** Switching tier (e.g. 4B → 9B) will change the output even with the same input.
- **Stop sequences are Qwen-specific.** Both `<|im_end|>` and `<|im_end_of_text|>` are emitted by Qwen3.5 / 3.6 chat templates. A future model from a different family would need its own stop set.
- **Empty transcript returns empty string, not an error.** Callers that want to distinguish "nothing to clean" from "model not loaded" should check `is_loaded()` first.

## See also

- [LLM engine](llm-engine.md)
- [LLM cleanup bridge in formatting crate](formatting-llm-cleanup-bridge.md)
- [Prompts and grammars catalogue](llm-prompts-and-grammars.md)
- [Slice README](README.md)