mirror of
https://github.com/tkenaz/breathe-memory.git
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4e671a0a83
Context optimization and associative memory for LLM applications. Two-phase system: SYNAPSE (pre-generation memory injection) + GraphCompactor (structured context compression). - Interface-based, storage-agnostic, LLM-agnostic - Memory Nexus: PostgreSQL + pgvector reference backend - Zero mandatory dependencies beyond stdlib - 28 tests passing, clean install verified Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
38 lines
950 B
Python
38 lines
950 B
Python
"""
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Memory Nexus — hybrid semantic memory for LLM applications.
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Provides persistent memory storage with semantic search via pgvector.
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Integrates with BREATHE as a VectorSearchClient backend.
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Architecture:
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MemoryStore — abstract storage interface
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PostgresStore — asyncpg + pgvector implementation (optional dep)
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HybridSearch — dense + keyword search
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Quick start::
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from memory_nexus import PostgresMemoryStore
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from breathe import Synapse
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store = PostgresMemoryStore(dsn="postgresql://...")
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await store.initialize()
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synapse = Synapse(vector_client=store)
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"""
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from .models import Memory, MemoryMetadata
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from .store import MemoryStore
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__version__ = "0.1.0"
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__all__ = [
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"Memory",
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"MemoryMetadata",
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"MemoryStore",
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]
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# Optional: PostgreSQL backend (requires asyncpg + pgvector)
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try:
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from .postgres import PostgresMemoryStore
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__all__.append("PostgresMemoryStore")
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except ImportError:
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pass
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