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EnergyChain

EnergyChain is the developer infrastructure through which AI applications can understand, interact with, and safely optimize energy systems—from solar installations and batteries to mini-grids, utilities, and electricity networks.

Status: v0.3.0 alpha. Offline-first, Python-first, and read-only by default. Simulated energy data are not live device measurements.

EnergyChain brings composable, vendor-neutral energy data types, connectors, safe callable tools, storage, deterministic energy calculations, a pluggable agent interface, and in-process workflows to Python developers. EnergyChain is a separate project from Energy Data Network (EDN).

Installation

Install the latest release after publication to the official PyPI index:

python -m pip install --upgrade energychain

To pin the expanded SDK after v0.3.0 has been published:

python -m pip install energychain==0.2.0

Until publication, install this branch locally in a development environment:

python -m pip install -e .

Requires Python 3.10 or newer. The core package uses only Python standard-library runtime dependencies.

Model Gateway and Document Intelligence (v0.3)

EnergyChain now offers explicit provider adapters for OpenAI, Anthropic, Gemini, Hugging Face Inference Providers, local Ollama, and HTTPS OpenAI-compatible endpoints. The developer supplies credentials and selects an available model; no inference is hosted. JSON Schema results are validated locally with the models extra.

A tenant-bound Document Intelligence index accepts PDF, DOCX, TXT, Markdown, CSV and XLSX files, retaining source fingerprints, page/sheet/section provenance, and explicit energy quantities. The SQLite search index enforces site permissions and supports optional developer-supplied embeddings.

python -m pip install 'energychain[models]==0.3.0'
python -m pip install 'energychain[documents]==0.3.0'
python -m pip install 'energychain[all]==0.3.0'

See Model Gateway and Document Intelligence for APIs, examples and production security obligations. Offline mock tests do not certify every live vendor model. Parse untrusted files in an isolated, resource-constrained worker; document instructions never grant energy device control permissions.

Quickstart

from energychain import EnergyChain

chain = EnergyChain.demo()
user = chain.principal("developer", allowed_sites={"demo-site"})

assets = chain.tools.invoke("discover_assets", user, "demo-site")
print([a.name for a in assets])

result = chain.tools.invoke(
    "estimate_battery_runtime", user, "demo-site",
    arguments={"battery_id": "demo-battery", "load_w": 900, "reserve_pct": 20},
)
print(result)

Security: principal() is a local-demo convenience, not a production authentication mechanism. Production applications must authenticate principals, assign site-level permissions from a trusted service, and enforce authorization at API boundaries. The included connector simulator never sends live control commands.

Real-world integrations and safety

New opt-in provider integrations include a read-only Home Assistant REST connector (mapped energy sensors, explicit units and bearer authentication) and an Open-Meteo irradiance forecast source. Both require legal use of the provider service and a trustworthy source configuration. No vendor integration has yet been field-validated by EnergyChain.

The framework provides site-scoped fleets, structured episodic memory, a bounded read/analysis-only planning agent, constrained advisory energy scheduling, signed one-time action approvals, and opt-in checkpointed read-only workflows. Physical device dispatch is disabled by default. These extensions are libraries and reference implementations, not a production-operated cloud backend.

Expanded components in 0.2

Component Implementation
Energy models Site, asset, metric, reading, event, tariff, energy plan
Connectors Abstract connector, registry, simulator, CSV import, read-only Home Assistant; opt-in weather forecast
Memory In-process bounded memory, SQLite persistence, episodic records and context retrieval
Energy tools 18 registered tools covering readings, consumption, forecast baselines, anomaly flags, constraints, fleet snapshots, PV and energy balance
Safety Site authorization, declared action boundaries, one-time signed approvals, execution disabled by default
Intelligence Battery-runtime estimate, tariff cost, baseline mean forecast, outlier baseline
Agent Explicit tool selection, optional injected model, bounded read/analysis planning interface
Workflow In-process sequential tools and SQLite checkpointed read/analysis runs
Observability Bounded trace and latency; model-independent forecast metrics and chronological baseline backtest
Developer experience PyPI-ready packaging, examples, tests, CI and trusted-publisher release workflow

Intentionally not included in 0.2

  • Field-tested and authenticated integrations with specific solar/battery vendors (no verified live credentials, calibration or deployment yet)
  • A production-ready control or dispatch runtime, remote device command implementation, or energy safety certification
  • Unbounded/autonomous LLM tool loops, multi-agent coordination, durable multi-instance streaming and production-safe physical action retries
  • Production-grade multi-tenant identity, authorization server, encryption/key management, or high-volume telemetry infrastructure
  • Trained and field-validated forecasting models, high-confidence anomaly accuracy, hardware testing or independently measured energy savings
  • Managed EnergyChain Cloud, hosted APIs, TypeScript SDK, vector-search services or MCP adapter

These are subsequent product-development efforts, not features to advertise as shipped.

Connect existing CSV exports

Provide asset_id,metric,value,timestamp,source columns and register an explicit EnergySite and its EnergyAsset definitions. See CSVConnector.from_csv(path, site=..., assets=...). The latest row is treated as the last recorded value (not necessarily live); caller must check freshness before operational decisions.

Design principles

  1. Developer-first: EnergyChain is software infrastructure for developers, not a national-grid control product.
  2. Standard energy semantics: W, Wh, %, UTC-offset-aware timestamps, data-source and quality fields.
  3. Composable: Connectors, tools, memory and language models can be independently replaced.
  4. Data is not authority: An LLM response cannot issue a physical command. Tools always check policies.
  5. Provenance matters: Simulated, estimated and measured values are explicitly labelled.
  6. Tests and evidence: Do not confuse synthetic demonstrations with field validation.

Local development

python -m pip install -e '.[dev]'
python -m pytest -q
python -m build
python -m twine check dist/*
python examples/quickstart.py

See architecture for contract boundaries and limitations and release guide for verified distribution steps.

Licensing and safety

EnergyChain is MIT licensed; see LICENSE. PyPI wheels and source archives are publicly downloadable even though the development repository remains private. This alpha-quality SDK is not certified for physical energy-equipment control.

Operational deployment boundary

The package supports read-only integrations and advisory application development; it does not ship an authenticated multi-tenant backend, durable broker, high-availability workflow workers or certified device controls. A developer can deploy an application that imports it, but responsibility for tenancy, secrets, privacy, monitoring and operational availability belongs to that application until EnergyChain Cloud exists. See docs/security.md for release gates.

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