| """Semantic router: three answer tiers plus the four skills. |
| |
| Queries are compared against the centroid of a few reference examples per |
| route. Routing is deliberately asymmetric: sending a real question to a route |
| without the profile produces a confident answer about the candidate with no |
| evidence behind it, while sending a greeting to the full profile merely wastes |
| tokens. So anything short of a clear, confident match falls back to FULL. |
| |
| The skill routes use the same rule: a request must clearly ask for a skill to |
| get one, otherwise it is answered as ordinary chat. The route names equal the |
| skill keys in skills.py. |
| """ |
|
|
| import logging |
|
|
| import numpy as np |
|
|
| logger = logging.getLogger(__name__) |
|
|
| TRIVIAL = "trivial" |
| SPECIFIC = "specific" |
| FULL = "full" |
| |
| REVIEW = "review" |
| ATS = "ats" |
| COVER_LETTER = "cover_letter" |
| EMAIL = "email" |
|
|
| SKILL_ROUTES = (REVIEW, ATS, COVER_LETTER, EMAIL) |
|
|
| REFERENCE_QUERIES = { |
| TRIVIAL: [ |
| "hello", |
| "hi there", |
| "hey", |
| "how are you?", |
| "thanks!", |
| "thank you", |
| "good morning", |
| "good evening", |
| "who are you?", |
| "what can you do?", |
| "bye", |
| ], |
| SPECIFIC: [ |
| "do I know Rust?", |
| "what is my Python experience?", |
| "have I used Kubernetes?", |
| "which projects used FAISS?", |
| "tell me about my volunteer work", |
| "what certifications do I have?", |
| "where did I use Docker?", |
| "what did I do at my last job?", |
| "which languages do I know?", |
| ], |
| FULL: [ |
| "am I a fit for this role?", |
| "what are my weakest areas?", |
| "how should I position myself?", |
| "summarise my background", |
| "what should I emphasise in the interview?", |
| "what gaps do I have for this job?", |
| "what do I bring to the table?", |
| "how do I compare to this job description?", |
| "what will they push back on?", |
| ], |
| REVIEW: [ |
| "review my resume", |
| "critique my resume for this job", |
| "how can I improve my resume?", |
| "give me feedback on my resume", |
| "tear down my resume against this job description", |
| "which resume bullets are weak?", |
| "rewrite my weakest resume bullets", |
| ], |
| ATS: [ |
| "what is my ATS score?", |
| "run an ATS check", |
| "which keywords am I missing for this job?", |
| "will my resume pass the applicant tracking system?", |
| "compare my resume keywords to the job description", |
| "how well do my keywords match this posting?", |
| ], |
| COVER_LETTER: [ |
| "write me a cover letter", |
| "draft a cover letter for this role", |
| "I need a cover letter for this job", |
| "can you write my cover letter?", |
| "cover letter for this position", |
| ], |
| EMAIL: [ |
| "write an application email", |
| "draft an email to the recruiter for this job", |
| "write a short email applying for this role", |
| "help me email the hiring manager", |
| "give me subject lines and an email to apply", |
| ], |
| } |
|
|
| |
| |
| MIN_SCORE = 0.35 |
| MIN_MARGIN = 0.10 |
|
|
|
|
| class SemanticRouter: |
| def __init__(self, embed_fn, references=None, min_score=MIN_SCORE, min_margin=MIN_MARGIN): |
| self.min_score = min_score |
| self.min_margin = min_margin |
| references = references or REFERENCE_QUERIES |
|
|
| self.routes = list(references) |
| centroids = np.stack([embed_fn(references[route]).mean(axis=0) for route in self.routes]) |
| norms = np.linalg.norm(centroids, axis=1, keepdims=True) |
| self.centroids = centroids / np.where(norms == 0, 1, norms) |
| self.embed_fn = embed_fn |
|
|
| def scores(self, query) -> dict: |
| vector = self.embed_fn([query])[0] |
| norm = np.linalg.norm(vector) |
| if norm: |
| vector = vector / norm |
| return dict(zip(self.routes, (self.centroids @ vector).tolist())) |
|
|
| def route(self, query) -> str: |
| |
| if not isinstance(query, str) or not query.strip(): |
| logger.info("Route %s | unroutable query, not scored", FULL) |
| return FULL |
|
|
| scores = self.scores(query) |
| ranked = sorted(scores.items(), key=lambda item: item[1], reverse=True) |
| (winner, top), (runner_up_route, runner_up) = ranked[0], ranked[1] |
| margin = top - runner_up |
|
|
| |
| if winner == FULL: |
| chosen, why = FULL, "top match" |
| elif top < self.min_score: |
| chosen, why = FULL, f"{winner} below min_score {self.min_score}" |
| elif margin < self.min_margin: |
| chosen, why = FULL, f"{winner} over {runner_up_route} below min_margin {self.min_margin}" |
| else: |
| chosen, why = winner, "top match" |
|
|
| logger.info( |
| "Route %s | %s | margin %.3f | %s | query: %.60r", |
| chosen, |
| why, |
| margin, |
| " ".join(f"{route}={score:.3f}" for route, score in ranked), |
| query, |
| ) |
| return chosen |
|
|
