Felipe Cardoso 96e6400bd8 feat(context): enhance performance, caching, and settings management ...

- Replace hard-coded limits with configurable settings (e.g., cache memory size, truncation strategy, relevance settings).
- Optimize parallel execution in token counting, scoring, and reranking for source diversity.
- Improve caching logic:
  - Add per-context locks for safe parallel scoring.
  - Reuse precomputed fingerprints for cache efficiency.
- Make truncation, scoring, and ranker behaviors fully configurable via settings.
- Add support for middle truncation, context hash-based hashing, and dynamic token limiting.
- Refactor methods for scalability and better error handling.

Tests: Updated all affected components with additional test cases.

2026-01-04 12:37:58 +01:00

..

__init__.py

feat(context): implement context scoring and ranking (Phase 3)

2026-01-04 02:24:06 +01:00

base.py

chore(context): apply linter fixes and sort imports (#86)

2026-01-04 02:46:56 +01:00

composite.py

feat(context): enhance performance, caching, and settings management

2026-01-04 12:37:58 +01:00

priority.py

chore(context): apply linter fixes and sort imports (#86)

2026-01-04 02:46:56 +01:00

recency.py

chore(context): apply linter fixes and sort imports (#86)

2026-01-04 02:46:56 +01:00

relevance.py

feat(context): enhance performance, caching, and settings management

2026-01-04 12:37:58 +01:00