arp-jarvis-runtime 0.1.0b2

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

From PyPI (once published):

pipx install arp-jarvis-runtime

Pre-release (e.g. 0.1.0a1):

pipx install --pip-args="--pre" arp-jarvis-runtime

Or in a virtualenv:

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

OpenAI mode (optional)

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

pip install -e ".[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:

python -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 v1alpha1).
• 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.