aire-ai 0.3.5

Agent-first AI creation library: one consistent interface from idea to deployed AI system.

aire

Agent-first AI creation library (Apache-2.0, Python 3.11+) — one consistent interface from a local prototype to a deployed system: models, data, RAG, agents, tools, workflows, evaluation, safety, observability, and deployment.

Status: Alpha (0.3.x). APIs can change. Some surfaces (vision, audio, foundation helpers) are intentionally stubby — check return flags / .describe() rather than assuming production-ready multimodal or pretrained weights.

from aire import AI

assistant = (
    AI.project("knowledge_assistant")
    .documents("./docs")
    .model("mock:echo")  # or openai:gpt-4o-mini, ollama:llama3.2, anthropic:claude-sonnet-4-5
    .vector_store("local:default")
    .citations(True)
)

assistant.index()
answer = assistant.ask("What does the documentation say about authentication?")
print(answer.text)
print(answer.citations)

Works offline out of the box (mock:echo + local:hashing) — no API keys, no network. Swap providers with a one-string change.

---

Install

pip install aire-ai
# import name stays `aire`:
#   from aire import AI
#
# or from source
pip install -e ".[dev]"

Note: The PyPI distribution is named aire-ai because the name aire is already taken by an unrelated package. The Python import remains aire.

Optional extras: serve, ml, vision, training, eval, docs, provider-named extras, and all. See pyproject.toml.

Requires Python 3.11+.

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Quick start (offline)

from aire import AI

model = AI.models.use_sync("mock:echo")
result = model.generate_sync("hello, aire")
print(result.text)

# Knowledge assistant / RAG without credentials
assistant = AI.project("demo").documents("./docs").model("mock:echo")
assistant.index()
print(assistant.ask("Summarize the project.").text)

CLI:

aire doctor
aire run "hello, aire"

Runnable samples live under examples/.

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Core ideas

Idea	What it means
Agent-first	Discoverable components (.describe()), tools as contracts, deterministic agent runtime
Provider-independent	provider:name refs (openai:…, anthropic:…, ollama:…, mock:echo) via plugins
Offline-capable	Full local loop with mock:echo / local:hashing
Structured errors	AireError subclasses with stable code, context, retryable
Composable facade	AI.models, AI.rag, AI.agents, AI.workflows, AI.eval, AI.deploy, …

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Honesty about stubs

aire prefers honest stubs over silent fakes:

• Vision / audio — pipelines may return stub=True when no real media provider is configured.
• Foundation / training helpers — config-driven toy stacks and hooks; not pretrained weight downloads by default.
• Some builtins / toolkits — still thin; read .describe() and docs before relying on them in production.

See docs/ (especially honesty / guide pages as they land) and GAPS.md for the rebuild backlog.

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Documentation

Resource	Link
Docs home	docs/
Changelog	CHANGELOG.md
Contributing	CONTRIBUTING.md
Security	SECURITY.md
Code of conduct	CODE_OF_CONDUCT.md
Cite	CITATION.cff

---

Development

make install      # pip install -e ".[dev]"
make lint         # ruff check + format --check
make typecheck    # mypy
make test         # pytest -q
make all          # lint + typecheck + test
pre-commit install

CI runs on Python 3.11–3.13. See Contributing.

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Providers

First-party provider entry points: openai, anthropic, ollama, huggingface, mock, echo. Additional OpenAI-compatible aliases and vector stores are available via integrations — see docs and aire.integrations.

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License

Apache License 2.0 — see LICENSE.