untamedai-runtime 0.3.1

LangGraph-based runtime for emotionally adaptive AI companions.

Untamed Companion Runtime

LangGraph-based runtime primitives for emotionally adaptive AI companions.

This package exposes reusable graph builders, SSE event adapters, provider interfaces, store interfaces, prompt overrides, FastAPI routes, deterministic tests, and a local demo showcase. It is product-agnostic by design: application copy, private prompts, production deployment config, billing, and secrets stay outside this repository.

Release Status

This package is an alpha runtime. Public APIs, event payload details, and provider/store extension points may evolve before 1.0.0, but published patch/minor releases should remain backward compatible. Pin exact versions for application use and follow the release policy before upgrading.

The FastAPI router is intentionally unauthenticated by default. Production applications must pass auth_hook to create_chat_router(...) and enforce their own ownership, session, API key, or tenant policy.

Install

From source:

git clone https://github.com/wkddns40/untamedai-runtime.git
cd untamedai-runtime
pip install -e ".[fastapi,dev]"

From PyPI:

pip install untamedai-runtime

Optional extras:

pip install "untamedai-runtime[fastapi]"
pip install "untamedai-runtime[openai]"
pip install "untamedai-runtime[supabase]"
pip install "untamedai-runtime[postgres]"

Verify:

python -m pytest

Quickstart

from untamed_companion.graph import GraphRuntime, build_chat_graph
from untamed_companion.providers import FakeLLMProvider

runtime = GraphRuntime(llm_provider=FakeLLMProvider())
graph = build_chat_graph(runtime=runtime)

result = await graph.ainvoke(
    {
        "companion_id": "demo",
        "last_user_message": "your name is Luna",
        "user_lang": "en",
        "companion": {"name": "???"},
    }
)

print(result["emit"])

FastAPI

from fastapi import FastAPI

from untamed_companion.fastapi import ChatRouterSettings, create_chat_router
from untamed_companion.graph import GraphRuntime
from untamed_companion.store import InMemoryCompanionStore

app = FastAPI()
runtime = GraphRuntime(companion_store=InMemoryCompanionStore())
app.include_router(
    create_chat_router(
        runtime=runtime,
        prefix="/api",
        settings=ChatRouterSettings(history_limit_default=20, history_limit_max=50),
    )
)

Routes:

• GET /api/chat/{companion_id}/history
• GET /api/chat/{companion_id}/greeting
• POST /api/chat/{companion_id}/stream

Auth is app-owned. Pass auth_hook to create_chat_router(...) to enforce ownership, sessions, API keys, or any other policy.

Demo Showcase

pip install -e ".[fastapi,dev]"
python examples/demo_showcase/backend/app.py

Open:

http://127.0.0.1:8000/demo

The showcase uses the public FastAPI router, in-memory store, fake providers, SSE event inspector, Korean/English language toggle, reset endpoint, and daily emotion dry-run.

Prompt Override

from untamed_companion.graph import GraphRuntime
from untamed_companion.prompts import StaticPromptProvider

runtime = GraphRuntime(
    prompt_provider=StaticPromptProvider(chat_prompt="Your app-owned prompt.")
)

Event Contract

SSE frames are emitted as JSON in data: lines:

data: {"type": "stream", "content": "Hello"}

Stable event types:

Type	Purpose
stream	Assistant text chunk or complete deterministic message.
end	Stream completion marker. May include final content and intent.
greeting	First greeting response.
name_reveal	Companion name accepted.
user_name_set	User display name accepted.
naming_prompt	Runtime asks user to name the companion.
coffee_request	Coffee-turn shortcut event.
error	Stream failure frame.

Golden fixtures live under tests/golden/fixtures. They compare public event order and payloads with whitespace-tolerant diffs, using only fake providers and in-memory state.

Documentation

• Architecture
• Event Contract
• Integrations
• Migration Guide
• Persistence
• Public Release Audit
• Release Policy
• Roadmap

Intended Scope

• LangGraph chat, greeting, and daily emotion graph builders
• naming ceremony state machine
• SSE event adapter
• store/provider interfaces
• neutral prompt provider with app-owned override support
• in-memory demo and tests
• optional FastAPI, OpenAI, Supabase, and Postgres integrations

Out of Scope

• product frontend
• private prompts and brand copy
• production deployment config
• billing/webhooks
• service role keys or project-specific environment values

License

MIT.