arp-jarvis-runtime 0.1.0

Jarvis Agent Runtime for executing ARP-style flows with planning support.

JARVIS Runtime

This repo contains the Jarvis Agent Runtime: a Python runtime for executing Agent Runtime Protocol-style agent flows using the 3-role loop:

Planner → Tool Executor (arg-gen + invoke) → Chat

It is designed to run against an ARP Tool Registry service and share contracts via the ARP Standard Python SDK (arp-standard-py / arp_sdk).

Quickstart

See:

• docs/quickstart.md
• docs/trace.md

Install

# CLI installs (recommended)
pipx install arp-jarvis-runtime

# or, in a virtualenv
python3 -m pip install arp-jarvis-runtime

Run against a real Tool Registry service

Terminal A (Tool Registry):

arp-jarvis-tool-registry

Terminal B (Runtime):

arp-jarvis-runtime demo --tool-registry-url http://127.0.0.1:8000

Or configure via env var (preferred when launched by a daemon):

export ARP_TOOL_REGISTRY_URL=http://127.0.0.1:8000
arp-jarvis-runtime demo

Back-compat env var: JARVIS_TOOL_REGISTRY_URL.

Run as a Runtime HTTP server (v1)

arp-jarvis-runtime serve --host 127.0.0.1 --port 8081 --tool-registry-url http://127.0.0.1:8000

If --port is omitted and 8081 is already in use, the runtime binds to a free port and prints it (or use --port 0 to always pick a free port). Use --auto-port to fall back when an explicit --port is in use.

Runtime API endpoints (selected):

• GET /v1/health
• GET /v1/version
• POST /v1/runs
• GET /v1/runs/{run_id}
• GET /v1/runs/{run_id}/result

OpenAI mode (optional)

This runtime uses the OpenAI Python SDK for Responses parsing + structured outputs. To enable it:

python3 -m pip install "arp-jarvis-runtime[openai]"
export OPENAI_API_KEY=...
arp-jarvis-runtime demo --mode openai --tool-registry-url http://127.0.0.1:8000

Optional model overrides:

• JARVIS_MODEL_PLANNER
• JARVIS_MODEL_TOOL_ARGS
• JARVIS_MODEL_CHAT
• JARVIS_MODEL_DEFAULT

Validation

Unit tests:

python3 -m unittest discover -v

Or (if you have pytest installed):

pytest -q

Typecheck (pyright):

pyright -p pyrightconfig.json

Design docs

• docs/intro.md
• docs/design/overview.md

Repo boundaries

• This repo: flow execution, LLM role orchestration, runtime packaging.
• Tool_Registry (separate repo): tool discovery + schemas + invocation routing (+ MCP aggregation).
• ARP_Standard (separate repo): spec + schemas + SDKs (published as arp-standard-py).

MVP capabilities + known gaps

Capabilities:

• Stub-mode 3-role loop (Planner → Tool → Chat) with trace JSONL.
• Tool Registry integration via HTTP (ARP Standard v1).
• Trace replay: rerun Chat from recorded tool results.

Known gaps:

• No production hardening (auth, multi-tenancy, concurrency controls, streaming, persistence).
• Prompt packs and planning heuristics are MVP-grade; no memory/scheduler/control plane yet.