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Control plane for production AI-agent work: plan, govern, and verify agent runs.

Project description

AI Runtime Supervisor / Veille Console

Control plane for production AI-agent work. The Supervisor plans, contextualizes, routes, governs, and verifies each agent run—reducing wasted spend and unreliable outcomes without requiring teams to rebuild their applications.

Current release: 0.2.0 — Phases 1–5 + Local Integration Console. Event schema 0.2.0. All capabilities are opt-in and off by default.

What exists today

  • Versioned data contracts (task, events, plan, policy, validation)
  • Python SDK (Supervisor + RunCollector) for zero-touch event emission
  • LangGraph adapter with automatic callback-based instrumentation
  • OpenAI Agents SDK adapter and OpenAI Responses API adapter (skeleton)
  • Model provider port with 8 provider drivers (LiteLLM, OpenAI, Anthropic, Gemini, OpenRouter, Ollama, LM Studio, OpenAI-compatible)
  • Synthetic cited market-research LangGraph demo workflow with mock tools
  • Representative trace fixtures for success, expensive, and failed-validation runs
  • Observe-only policy engine (duplicate detection, retry budget, cost overrun, validation)
  • Opt-in enforcement (Phase 2): block / retry / pause / stop with full audit trail
  • Budget tracking (BudgetTracker, in-memory default, Redis backend port)
  • Run-explorer CLI and OpenTelemetry export (Console + OTLP)
  • Advisory planning (Phase 3): tier selection, per-step context manifests, capability+tier model routing
  • Adaptive optimization (Phase 4): semantic near-duplicate detection + idempotent result caching (SUPERVISOR_OPTIMIZE, dry-run default)
  • Memory governance (Phase 5): memory store + scoring + governor (memory.retrieved/memory.expired manifest) with audited expiry, no automatic deletion (SUPERVISOR_MEMORY)
  • Local Integration Console (veille CLI + FastAPI + React web UI) — register workflows, connect providers, run live, inspect execution
  • Local development environment (Docker Compose + pytest)

Quickstart

Prerequisites

  • Python 3.12+
  • Docker Desktop (optional, for Postgres/Redis/MinIO scaffold)

Setup (Windows)

.\scripts\dev.ps1
.\.venv\Scripts\Activate.ps1

Run tests

pytest -v

Use the console

# Doctor — environment + safe-config report
veille doctor

# List provider connections
veille connections
veille connections validate openai

# List registered workflows
veille workflows

# Run the mock demo
veille demo mock

# Run the real-world demo
veille demo real-world

# List saved runs
veille runs

# Run an arbitrary registered workflow
veille run cited_market_research --input '{"scenario":"success"}'

# Start the web UI (then open http://127.0.0.1:8000)
veille serve

Run the classic demo workflow

# Successful run
python -m examples.cited_market_research.agent --scenario success

# All scenarios + write trace fixtures
python -m examples.cited_market_research.agent --scenario all --write-fixtures

# Phase 1 run explorer (inspect a captured run)
python -m supervisor.cli explore --run fixtures/traces/expensive_run.json --policy

# Live run with policy observations and OTel export
python -m supervisor.cli explore --live --scenario expensive --policy --otel

No API keys required. Mock models and tools are used by default.

Repository layout

src/supervisor/          Core contracts, SDK, adapters, analytics, policy, telemetry, CLI, console
examples/                Runnable demo workflows
fixtures/traces/         Synthetic trace JSON for tests and baselines
docs/                    Architecture, contracts, roadmap, ADRs
docs/development/        Source master prompt, blueprint, phase plans
ui/                      React+TypeScript+Vite web UI (veille console frontend)
templates/               Baseline measurement templates

Documentation

Document Description
Architecture System components and boundaries
Runtime chain Stage-by-stage runtime flow
Data contracts Schema reference
Roadmap Phase status and deferrals
Integrations Adapter contracts + provider drivers
Operations Local dev, commands, runbooks
Policy engine Policy modes and Phase 1 observe policies
ADR-013 Local Integration Console design

Setup guides

Guide Description
Safe local setup Running with mock providers (default)
Mock demo walkthrough End-to-end mock demo
Real provider setup Setting up real model providers
OpenRouter integration Using OpenRouter as a gateway
OpenAI Agents SDK Running an OpenAI Agents SDK workflow
LiteLLM integration Using LiteLLM for multi-provider access

License

MIT

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