1a47e136e3
### What problem does this PR solve? **Adds a new feature that enables the LLM to extract a structured table of contents (TOC) directly from plain text.** _This implementation prioritizes efficiency over reasoning — the model runs in a strictly deterministic mode (thinking disabled) to minimize latency. As a result, overall performance may be less optimal, but the extraction speed and consistency are guaranteed._ ### Type of change - [x] New Feature (non-breaking change which adds functionality)
1.9 KiB
You are given a JSON array of TOC items. Each item has at least {"title": string} and may include an existing structure.
Task
- For each item, assign a depth label using Arabic numerals only: top-level = 1, second-level = 2, third-level = 3, etc.
- Multiple items may share the same depth (e.g., many 1s, many 2s).
- Do not use dotted numbering (no 1.1/1.2). Use a single digit string per item indicating its depth only.
- Preserve the original item order exactly. Do not insert, delete, or reorder.
- Decide levels yourself to keep a coherent hierarchy. Keep peers at the same depth.
Output
- Return a valid JSON array only (no extra text).
- Each element must be {"structure": "1|2|3", "title": }.
- title must be the original title string.
Examples
Example A (chapters with sections) Input: ["Chapter 1 Methods", "Section 1 Definition", "Section 2 Process", "Chapter 2 Experiment"]
Output: [ {"structure":"1","title":"Chapter 1 Methods"}, {"structure":"2","title":"Section 1 Definition"}, {"structure":"2","title":"Section 2 Process"}, {"structure":"1","title":"Chapter 2 Experiment"} ]
Example B (parts with chapters) Input: ["Part I Theory", "Chapter 1 Basics", "Chapter 2 Methods", "Part II Applications", "Chapter 3 Case Studies"]
Output: [ {"structure":"1","title":"Part I Theory"}, {"structure":"2","title":"Chapter 1 Basics"}, {"structure":"2","title":"Chapter 2 Methods"}, {"structure":"1","title":"Part II Applications"}, {"structure":"2","title":"Chapter 3 Case Studies"} ]
Example C (plain headings) Input: ["Introduction", "Background and Motivation", "Related Work", "Methodology", "Evaluation"]
Output: [ {"structure":"1","title":"Introduction"}, {"structure":"2","title":"Background and Motivation"}, {"structure":"2","title":"Related Work"}, {"structure":"1","title":"Methodology"}, {"structure":"1","title":"Evaluation"} ]