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CHANGELOG.md

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The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
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and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
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## [0.5.0] - 2025-12-23
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### Major Feature: Hybrid Structured-Semantic Search
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MemState moves beyond just storing data to retrieving it intelligently. This release adds a unified search API that combines Vector Similarity with SQL-like strict filtering.
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* **New `store.search()` API:** Finds relevant IDs in the Vector DB and hydrates them with fresh data from the SQL Storage (Source of Truth).
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* Supports `query` (text for embedding).
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* Supports `filters` (metadata filtering).
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* Supports `score_threshold` (cutoff for relevance).
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* **Safety First:** Search results are cross-referenced with the Storage backend. If a vector index finds a "ghost" ID (deleted in SQL), MemState automatically filters it out, preventing hallucinations.
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### Integrations
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* **Qdrant Search:** Implemented search using the modern `query_points` API.
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* **DX Magic:** Added automatic translation of simple dictionary filters (`{"role": "user"}`) into Qdrant's complex `models.Filter` syntax.
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* **ChromaDB Search:** Implemented semantic search with metadata filtering.
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### Breaking Changes (for Custom Hooks)
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* The `MemoryHook` and `AsyncMemoryHook` protocols now require a `search` method.
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* If you have implemented custom hooks, you must add a `search` method (it can return an empty list `[]` if retrieval is not supported).
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### Documentation
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* Added **Hybrid Search** section to Core Concepts.
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## [0.4.0] - 2025-12-18
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### Major: Async Support & Beta Release

pyproject.toml

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[project]
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name = "memstate"
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version = "0.4.0"
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version = "0.5.0"
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description = "Transactional Memory for AI Agents - Keep SQL and Vector DBs in sync with ACID-like guarantees"
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readme = "README.md"
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requires-python = ">=3.10"

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