mba/chunking_strategies_evaluation

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Mahdi Bazrafshan 5fd19c12d9 feat(chunking): add embedding model registry and ollama config

Why:
- Operators need Cloud and Local Embedding Models with stable ids, dimensions, and defaults.

Changes:
- Add Embedding Model Registry; Ollama client; env defaults for model, Ollama host, and Neighbor Expansion knobs.

Impact:
- New installs default to text-embedding-3-large; OLLAMA_BASE_URL required for Local provider.

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

2026-08-10 14:12:36 +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(chunking): add embedding model registry and ollama config

2026-08-10 14:12:36 +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