| from __future__ import annotations |
|
|
| from typing import TYPE_CHECKING |
|
|
| from codeforge.interrogator.models import InterrogationResult |
|
|
| if TYPE_CHECKING: |
| from codeforge.kb.indexer import SkillsIndex |
|
|
| _TEMPLATES = ( |
| "What is the exact success criterion for '{brief_head}'?", |
| "Have you considered the guidance from {skill_name}: '{section_title}'?", |
| "Which of these assumptions is most load-bearing: success metric, inputs, failure modes?", |
| "What is the single hardest edge case for '{brief_head}'?", |
| "Have you consulted {skill_name2} for the patterns it recommends?", |
| ) |
|
|
|
|
| class Interrogator: |
| """Generates Socratic questions that cite real skill corpus nodes.""" |
|
|
| def __init__(self, index: SkillsIndex | None) -> None: |
| self._index = index |
|
|
| def generate(self, brief: str, *, top_k: int = 5) -> InterrogationResult: |
| brief_head = brief.strip()[:80] or "the task" |
| results = ( |
| self._index.search(brief, top_k=top_k) |
| if self._index is not None |
| else [] |
| ) |
| cited_ids = tuple(r.node_id for r in results[:2]) |
| first = results[0] if results else None |
| second = results[1] if len(results) > 1 else first |
|
|
| skill_name = first.skill_name if first else "the skill library" |
| section_title = ( |
| "/".join(first.section_path) if first else "the relevant section" |
| ) |
| skill_name2 = second.skill_name if second else skill_name |
|
|
| questions = tuple( |
| t.format( |
| brief_head=brief_head, |
| skill_name=skill_name, |
| section_title=section_title, |
| skill_name2=skill_name2, |
| ) |
| for t in _TEMPLATES |
| ) |
| return InterrogationResult(questions=questions, cited_node_ids=cited_ids) |
|
|