chopratejas 9c9bb30ded Add persistent memory system with zero-latency inline extraction ... Features: - with_fast_memory(): Zero-latency inline extraction (Letta-style) - Memory extracted as part of LLM response, no extra API calls - Semantic retrieval with local embeddings (sub-50ms) - with_memory(): Background extraction for non-blocking memory - SQLite + FTS5 storage with vector similarity search - Multi-user isolation by user_id Memory enables temporal compression - extract key facts instead of carrying full conversation history (4000 tokens → 50 tokens). Includes: - Comprehensive test suite (71 new tests) - Documentation (docs/memory.md) - Benchmark examples comparing approaches - E2E test with LLM-as-judge evaluation		2026-01-14 21:32:09 -08:00
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__init__.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00
conftest.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00
test_extractor.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00
test_inline_extractor.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00
test_store.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00
test_wrapper.py	Add persistent memory system with zero-latency inline extraction	2026-01-14 21:32:09 -08:00