Mahdi Bazrafshan f562b91f83 feat(benchmarking): add model-scoped query and neighbor expansion ...

Why:
- Queries and Experiments must hit the Corpus Embedding Model's collections and optionally widen fixed_size context.

Changes:
- Resolve corpus model per request; apply Neighbor Expansion with Expansion Tree; persist and report expansion provenance.

Co-authored-by: Cursor <cursoragent@cursor.com>

2026-08-10 14:13:07 +03:30

..

__init__.py

feat(benchmarking): add query pipeline with logging and tracing

2026-07-26 12:06:04 +03:30

benchmark_service.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30

evaluation.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30

models.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30

query_service.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30

report.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30

routes.py

feat(benchmarking): add model-scoped query and neighbor expansion

2026-08-10 14:13:07 +03:30