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| #!/usr/bin/env python3 | |
| """Populate Redrob idea submission PPTX from current team content.""" | |
| from __future__ import annotations | |
| import argparse | |
| import shutil | |
| from pathlib import Path | |
| from pptx import Presentation | |
| from pptx.util import Pt | |
| PROJECT_ROOT = Path(__file__).resolve().parent.parent | |
| DEFAULT_TEMPLATE = PROJECT_ROOT / "challenge" / "Idea Submission Template _ Redrob.pptx" | |
| def _set_text(shape, text: str, *, font_pt: int = 14) -> None: | |
| tf = shape.text_frame | |
| tf.clear() | |
| p = tf.paragraphs[0] | |
| p.text = text | |
| p.font.size = Pt(font_pt) | |
| def build_deck(template: Path, output: Path) -> None: | |
| prs = Presentation(str(template)) | |
| # Slide 1 — title fields (text boxes 1–3) | |
| s1 = prs.slides[0].shapes | |
| _set_text(s1[1], "Team Name : Sarva Automata", font_pt=20) | |
| _set_text( | |
| s1[2], | |
| "Problem Statement : Rank 100K candidates for Senior AI Engineer " | |
| "(search/retrieval/ranking); NDCG@10 focus; CPU-only; honeypot-aware.", | |
| font_pt=16, | |
| ) | |
| _set_text(s1[3], "Team Leader Name : Arjun Mangarath", font_pt=18) | |
| slide_bodies = [ | |
| # Slide 2 | |
| "Hybrid recall (BM25 + BGE dense + career RRF) → LightGBM LambdaRank → " | |
| "BGE cross-encoder on top-700 with tuned fusion.\n\n" | |
| "Differentiation: IR + learned ranking + Redrob behavioral signals—not keywords. " | |
| "Explicit trap/honeypot and availability handling.", | |
| # Slide 3 | |
| "JD: 5–8 YOE production ML, search/retrieval/ranking, embeddings, India hubs, " | |
| "product over research, recruiter reachability.\n\n" | |
| "Signals: silver tiers, LTR features, career evidence, GitHub, trap flags, " | |
| "behavioral twins (response, notice, recency). Cross-encoder for semantic fit—no runtime LLM.", | |
| # Slide 4 | |
| "Retrieve ~2K (BM25 + FAISS + career RRF) → LTR + penalties → CE rerank top-700 → " | |
| "fusion + modifiers → top-100 CSV.\n\n" | |
| "Models: BM25, FAISS, LightGBM, BGE-reranker-base, Optuna-tuned fusion/modifiers.\n\n" | |
| "Combine: weighted CE/LTR/RRF × behavioral multiplier − trap/clone/research penalties.", | |
| # Slide 5 | |
| "Reasoning: 5–6 templates from whitelisted fields (YOE, skills, location, availability, " | |
| "production vs research).\n\n" | |
| "No LLM at rank time → no hallucinated justifications.\n\n" | |
| "Traps: hard-exclude honeypots; clone cap top-30; availability down-rank; research penalty.", | |
| # Slide 6 | |
| "Offline: preprocess → features/embeddings/BM25/FAISS → silver labels → train LTR → " | |
| "tune modifiers (~90 min).\n\n" | |
| "Online: rank.py loads artifacts → recall → LTR → CE → fusion/modifiers → " | |
| "team_sarva_automata.csv + audit.", | |
| # Slide 7 | |
| "Offline: preprocess.py, train_ltr.py, tune_modifiers.py\n" | |
| "Online: rank.py + HF Docker sandbox\n" | |
| "Artifacts: parquet features, FAISS, BM25, ltr_model.lgb, fusion_params, modifier_params", | |
| # Slide 8 | |
| "Audit: proxy NDCG@10 = 1.0; NDCG@30 = 0.9922; tier-5 top 10/30/100 = 9/26/70; " | |
| "0 honeypots in top-100; 0 low-availability in top-30.\n\n" | |
| "Constraints: precomputed indexes; rank ~5–8 min CPU, 16GB RAM, no network at inference.", | |
| # Slide 9 | |
| "Python, Polars, LightGBM, sentence-transformers, FAISS, rank-bm25, FastAPI, Optuna. " | |
| "Gemini offline (JD + labels). Cursor for engineering assist.", | |
| # Slide 10 | |
| "GitHub: github.com/ashokbugude/recruiter-candidate\n" | |
| "Sandbox: huggingface.co/spaces/ashokbugude/redrob-ranker " | |
| "(upload JSONL/JSON ≤100 → ranked CSV)\n" | |
| "Portal CSV: team_sarva_automata.csv\n" | |
| "Reproduce: python rank.py --candidates ./challenge/candidates.jsonl " | |
| "--out ./team_sarva_automata.csv", | |
| ] | |
| for slide_idx, body in enumerate(slide_bodies, start=1): | |
| shapes = prs.slides[slide_idx].shapes | |
| content_shape = shapes[-1] | |
| _set_text(content_shape, body, font_pt=13) | |
| output.parent.mkdir(parents=True, exist_ok=True) | |
| prs.save(str(output)) | |
| def main() -> int: | |
| parser = argparse.ArgumentParser(description="Build methodology PPTX for portal upload.") | |
| parser.add_argument("--template", type=Path, default=DEFAULT_TEMPLATE) | |
| parser.add_argument( | |
| "--out", | |
| type=Path, | |
| default=DEFAULT_TEMPLATE, | |
| help="Output .pptx (default: overwrite template in challenge/)", | |
| ) | |
| parser.add_argument( | |
| "--export-pdf", | |
| type=Path, | |
| default=None, | |
| help="Optional PDF path via PowerPoint COM (Windows only)", | |
| ) | |
| args = parser.parse_args() | |
| if args.out.resolve() != args.template.resolve(): | |
| shutil.copy2(args.template, args.out) | |
| build_deck(args.template if args.out == args.template else args.out, args.out) | |
| print(f"Wrote deck: {args.out}") | |
| if args.export_pdf: | |
| try: | |
| import comtypes.client # type: ignore | |
| pdf_path = args.export_pdf.resolve() | |
| pdf_path.parent.mkdir(parents=True, exist_ok=True) | |
| powerpoint = comtypes.client.CreateObject("Powerpoint.Application") | |
| powerpoint.Visible = 1 | |
| deck = powerpoint.Presentations.Open(str(args.out.resolve()), WithWindow=False) | |
| deck.SaveAs(str(pdf_path), 32) | |
| deck.Close() | |
| powerpoint.Quit() | |
| print(f"Wrote PDF: {pdf_path}") | |
| except Exception as exc: | |
| print(f"PDF export skipped ({exc}). Export manually from PowerPoint: Save as PDF") | |
| return 0 | |
| if __name__ == "__main__": | |
| raise SystemExit(main()) | |