mba/chunking_strategies_evaluation

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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

docs: capture pdf domain language and deferred ingestion backlog

2026-08-02 16:59:42 +03:30

feat(dashboard): add pdf workspace via shared format filter

2026-08-02 16:59:42 +03:30

docs(data): add 21-question evaluation dataset for benchmarking

2026-07-26 13:48:36 +03:30

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

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

.env.example

feat(chunking): add embedding model registry and ollama config

2026-08-10 14:12:36 +03:30

.gitignore

Initial commit

2026-07-21 11:27:49 +03:30

CONTEXT.md

docs: capture pdf domain language and deferred ingestion backlog

2026-08-02 16:59:42 +03:30

LICENSE

Initial commit

2026-07-21 11:27:49 +03:30

pyproject.toml

build(deps): add pymupdf for text pdf extraction

2026-08-02 16:59:42 +03:30

README.md

Initial commit

2026-07-21 11:27:49 +03:30

README.md

chunking_strategies_evaluation

This repo is in order to reach multiple chunking strategies and evaulate them