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>
57 lines
1.5 KiB
Python
57 lines
1.5 KiB
Python
"""
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BREATHE — context optimization for LLM applications.
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Two-phase system:
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SYNAPSE (inhale) — pre-generation memory injection
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GraphCompactor (exhale) — structured context compression
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Quick start::
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from breathe import Synapse, GraphCompactor, BreatheConfig
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config = BreatheConfig()
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synapse = Synapse(repository=my_repo, config=config)
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await synapse.initialize()
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# Before each LLM call:
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messages = await synapse.inject(messages)
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# When context is getting full:
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compactor = GraphCompactor(llm_client=my_llm)
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result = await compactor.compress(messages)
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messages = result["compressed_messages"]
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"""
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from .config import BreatheConfig, LanguagePack, ENGLISH
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from .interfaces import MemoryRepository, VectorSearchClient, LLMClient, RetrievedNode
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from .anchor_extractor import AnchorExtractor, Anchor, AnchorResult
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from .context_injector import ContextInjector
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from .session_graph import SessionGraph, GraphNode, GraphEdge
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from .graph_compactor import GraphCompactor
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from .synapse import Synapse
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from .metrics import BreatheMetrics
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__version__ = "0.1.0"
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__all__ = [
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# Core
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"Synapse",
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"GraphCompactor",
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"BreatheConfig",
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"LanguagePack",
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# Language packs
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"ENGLISH",
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# Interfaces
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"MemoryRepository",
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"VectorSearchClient",
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"LLMClient",
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"RetrievedNode",
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# Internals (for custom implementations)
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"AnchorExtractor",
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"Anchor",
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"AnchorResult",
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"ContextInjector",
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"SessionGraph",
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"GraphNode",
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"GraphEdge",
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"BreatheMetrics",
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]
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