| from __future__ import annotations |
|
|
| import re |
|
|
| |
| _CITATION_RE = re.compile(r"#\s*(?:cited|ref|source|from):\s*(\S+)", re.IGNORECASE) |
|
|
|
|
| def citation_shaping_bonus( |
| *, |
| submit_files: dict[str, str], |
| prior_citations: list[dict[str, object]], |
| prior_cluster_hits: list[str], |
| ) -> float: |
| """Retroactive shaping bonus for prior queries whose cited skills appear in submitted code. |
| |
| +0.01 per cited skill name found as an explicit citation comment in the code, |
| max 0.05. Only fires on submit with reward > 0. See SYSTEM_DESIGN §4.8.4. |
| |
| Uses explicit comment matching (``# cited: skill-name``) instead of substring |
| matching to prevent common-word skill names from trivially matching any code. |
| """ |
| if not prior_citations: |
| return 0.0 |
|
|
| cited_skills: set[str] = set() |
| for c in prior_citations: |
| sn = c.get("skill_name") |
| if isinstance(sn, str): |
| cited_skills.add(sn.lower()) |
|
|
| code_text = "\n".join(submit_files.values()) |
| code_citations = {m.group(1).lower() for m in _CITATION_RE.finditer(code_text)} |
|
|
| overlap = len(cited_skills & code_citations) |
| return min(overlap * 0.01, 0.05) |
|
|
