- ConversationEmbedding ORM model with Vector(384) column (pgvector) - memory_short_key, escalation_status_key, pending_tool_confirm_key in redis_keys.py - orchestrator/memory/short_term.py: RPUSH/LTRIM sliding window (get_recent_messages, append_message) - orchestrator/memory/long_term.py: pgvector HNSW cosine search (retrieve_relevant, store_embedding) - Migration 002: conversation_embeddings table, HNSW index, RLS with FORCE, SELECT/INSERT only - 10 unit tests (fakeredis), 6 integration tests (pgvector) — all passing - Auto-fix [Rule 3]: postgres image updated to pgvector/pgvector:pg16 (extension required)
27 lines
628 B
TOML
27 lines
628 B
TOML
[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[project]
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name = "konstruct-shared"
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version = "0.1.0"
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description = "Shared Pydantic models, SQLAlchemy ORM, and utilities for Konstruct"
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requires-python = ">=3.12"
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dependencies = [
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"fastapi[standard]>=0.115.0",
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"pydantic[email]>=2.12.0",
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"pydantic-settings>=2.8.0",
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"sqlalchemy[asyncio]>=2.0.36",
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"asyncpg>=0.31.0",
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"alembic>=1.14.0",
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"redis>=5.2.0",
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"celery[redis]>=5.4.0",
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"httpx>=0.28.0",
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"slowapi>=0.1.9",
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"bcrypt>=4.0.0",
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"pgvector>=0.3.0",
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]
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[tool.hatch.build.targets.wheel]
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packages = ["shared"]
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