feat: add two-step skills-graph job matching experiment#21
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Introduced a new job matching experiment that utilizes a two-step ranking approach based on skill taxonomy graphs. The implementation includes: - Exact match ranking based on label overlap (exact_match.py). - Graph-based ranking using Dijkstra's algorithm for remaining jobs (graph_dijkstra.py). - A final ranker that combines both methods (final.py). - CLI for running the final ranker for individual users (main.py). - Dashboard generation for visualizing job recommendations (dashboard/run_njila_dashboard.py). - Data paths and requirements for the new system are defined in paths.py and requirements.txt, respectively. - Added a README.md for documentation on usage and structure.
rav3n11
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Jul 15, 2026
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We shouldnt have json like this in the repo. Not only is this live user data (anonymized as it may be), its also a large file that does not belong on VC. Especially not on a public repo. We should remove it.
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we should not commit a 52mb json file to the repo. If its absolurely critical to have large files we should use git lfs but in this case I think we ought to just avoid commiting this altogether.
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quick question @Hamz-Horizon, I see no wiring to make this experiment into an accessible fastapi route. Is this meant to be tested alongside the other experiments or is this just a proof of concept |
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Introduced a new job matching experiment that utilizes a two-step ranking approach based on skill taxonomy graphs. The implementation includes:
Test Results
SHP MATCHING ALGORITHM — FULL TEST SUITE
[1/7] Lint Check .................................. PASS
[2/7] Format Check ................................ PASS
[3/7] Data Validation Check ....................... PASS
[4/7] Data Schema Check ........................... PASS
[5/7] Smoke Check ................................. PASS
[6/7] Job Dict Mapping Check ...................... PASS
[7/7] ML Logic Check .............................. PASS
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ALL CHECKS PASSED (7/7)