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Enterprise knowledge graph (L2) — optional PyPI package split from AIECS

Project description

aiecs-kg

Enterprise knowledge graph (L2) for AIECS, split from the monorepo as an optional PyPI package.

Status

Alpha 0.9.0a1 — first public PyPI release (Development Status :: 3 - Alpha). Core graph store, reasoning (heuristic + Logic DSL), and builder paths are usable; PostgreSQL / Neo4j dual-store and LLM features require optional extras and caller configuration.

See temporal_kg_memory/KNOWLEDGE_GRAPH_OPTIONAL_PACKAGING.md for the full split checklist.

CI verification scope

GitHub Actions (pip install -e ".[dev]", no external services) validates:

Area CI Requires local / maintainer setup
In-memory graph store Yes
SQLite backend Yes
Reasoning (Logic DSL, orchestrator) Yes
Structured builder import Yes
LLM injection (mock clients) Yes Real LLM keys: manual / nightly
PostgreSQL ([postgres]) No (skip) KG_POSTGRES_URL + .env.test
Neo4j / pg_neo4j / GDS ([graph]) No (skip) KG_NEO4J_URI + system Neo4j 5.26+
AIECS integrations ([aiecs]) No (skip) pip install aiecs-kg[aiecs]

Release gate (tag v*): unit tests + deptry + build + twine check (see scripts/README.md).

Install

# Core (in-memory graph store)
pip install -e .

# With backends
pip install -e ".[postgres,sqlite,reasoning]"

# Neo4j graph compute + PostgreSQL dual-store (Phase NG)
pip install -e ".[graph]"          # neo4j + postgres extras
# or: pip install -e ".[neo4j,postgres]"

# Development
pip install -e ".[dev,sqlite]"

Optional extras

Extra Installs LLM / AIECS
(core) Graph store, reasoning heuristics No LLM — pass llm_client= / embedding_client= yourself
reasoning Lark Logic DSL parser No LLM
builder Structured data import (pandas, etc.) No LLM; GraphBuilder accepts injected embedding_client=
aiecs Declares compatible aiecs version Optional helpers in aiecs_kg.integrations.aiecs only (not core imports)

For LLM usage patterns see LLM integration and LLM_CLIENT_INJECTION_PLAN.md §7.

Deprecated factory methods (GraphBuilder.from_config, LLMEntityExtractor.from_config) remain for compatibility but do not resolve AIECS clients in core — use explicit injection or aiecs_kg.integrations.aiecs.

Storage modes (KG_STORAGE_MODE)

Mode PostgreSQL Neo4j Use case
pg_only (default) authority + vector Zero Neo4j regression; Python graph fallback
pg_neo4j authority + pgvector RAG traverse + GDS projection Recommended production embed path
neo4j_only single store POC / graph-only dev

Design: AIECS_KG_NEO4J_PG_DUAL_STORE_DESIGN.md · ADR: ADR-004

pg_neo4j quick example

export KG_STORAGE_MODE=pg_neo4j
export KG_STORAGE_BACKEND=postgresql
export KG_POSTGRES_URL=postgresql://user:pass@localhost:5432/aiecs_knowledge_graph
export KG_NEO4J_URI=bolt://localhost:7687
export KG_NEO4J_USER=neo4j
export KG_NEO4J_PASSWORD=your-password
export KG_NEO4J_DATABASE=aiecs_graph
from aiecs_kg import create_graph_store, create_graph_algorithm_service

store = create_graph_store()          # CompositeGraphStore when pg_neo4j
await store.initialize()
algo = create_graph_algorithm_service(graph_store=store)
scores = await algo.pagerank(seed_entity_ids=["entity-a"], top_k=10)

See .env.example for all KG_* variables.

Quick start

from aiecs_kg import create_graph_store, Entity

store = create_graph_store()  # KG_STORAGE_BACKEND=inmemory (default)
await store.initialize()

entity = Entity(id="e1", entity_type="Person", properties={"name": "Alice"})
await store.add_entity(entity)

Reasoning (Phase R0–R2)

Prefer ReasoningOrchestrator over ReasoningEngine for NL, Logic DSL, and hybrid pipelines:

import asyncio
from aiecs_kg import create_reasoning_orchestrator, ReasoningOrchestrator
from aiecs_kg.application.reasoning import ReasoningPipelineConfig

async def main():
    orchestrator = create_reasoning_orchestrator()  # or ReasoningOrchestrator(store, ...)
    result = await orchestrator.query(
        "Find all people older than 30",
        mode="hybrid",  # nl | logic_dsl | hybrid
        context={"start_entity_id": "alice"},
    )
    print(result.answer, result.evidence_count)

asyncio.run(main())

Install Logic DSL support: pip install -e ".[reasoning]". Optional rerank extra: pip install -e ".[rerank]".

LLM integration

pip install aiecs-kg does not install or import AIECS. LLM-powered features (entity/relation extraction, NL→DSL, QueryPlan, embeddings) require a caller-provided client via constructor or factory parameters (llm_client=, embedding_client=).

from aiecs_kg import create_reasoning_orchestrator
from aiecs_kg.ports.llm_client import LLMMessage  # use this, not aiecs.llm.LLMMessage

# Heuristic / retrieval-only — no LLM required
orchestrator = create_reasoning_orchestrator()

# With an injected client (AIECS resolve_llm_client, OpenAI SDK wrapper, etc.)
orchestrator = create_reasoning_orchestrator(llm_client=my_client)

All generate_text messages in core code use aiecs_kg.ports.llm_client.LLMMessage. Clients must implement at least generate_text and/or get_embeddings (see LLMClientProtocol). For a minimal OpenAI SDK example without AIECS, see LLM_CLIENT_INJECTION_PLAN.md §7.4.

Optional AIECS convenience helpers (when both packages are installed) live under aiecs_kg.integrations.aiecs — not exported from core __init__.py.

Configuration

All settings use KG_* environment variables. See .env.example.

export KG_STORAGE_BACKEND=inmemory   # inmemory | sqlite | postgresql
export KG_ENABLED=true               # consumed by AIECS core (not this package)

Project layout

src/aiecs_kg/
├── domain/          # Entity, Relation, schema models
├── application/     # search, reasoning, builder, fusion, …
├── storage/         # GraphStore backends (in-memory, SQLite, Postgres)
├── config.py        # KGSettings / get_kg_settings()
└── factory.py       # create_graph_store()

Tests

# 1) 依赖(见 .env.test 注释)
pip install -e ".[dev,rerank]"
python -m spacy download en_core_web_sm
# aiecs:若 PyPI 与 dev 解析冲突,改本地可编辑安装(勿与 [aiecs] extra 同时 pip 解析)
pip install -e /path/to/python-middleware-dev

# 2) 环境
set -a && source .env.test && set +a   # KG_USE_AIECS_STUB=false + XAI_API_KEY 等

pytest tests/unit -q
pytest tests/integration/neo4j_graph/ -q   # 需系统 Neo4j 5.26.x + GDS(ADR-004)

Pre-commit

Same hook set as AI-Execute-Services: license header, black, flake8, mypy, and deptry (no AIECS-specific schema hooks).

Dependencies are declared only in pyproject.toml. CI installs pip install -e ".[dev]" with no ad-hoc packages. See .cursor/rules/dependency-maintenance.mdc.

pip install -e ".[dev]"
pre-commit install
pre-commit run --all-files

License

Apache-2.0 — see License.txt.

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