pyguardops 0.0.1

Runtime safety proxy for multi-agent AI systems

pyguardops

Runtime safety proxy for multi-agent AI systems. Intercepts agent outputs in real-time — before bad values (or bad decisions) cascade downstream — and auto-corrects or halts the pipeline based on rules you define.

What it does

• DATA_OVERRIDE — detects a breach, corrects the unsafe field, pipeline continues
• SHORT_CIRCUIT — raises GuardOpsRefusalIntercept, halts the pipeline immediately
• Telemetry (optional) — every breach can be logged to Langfuse (live spans) and MLflow (retraining artifacts)

Install

pip install pyguardops==0.0.1

The command-line tool and the Python import both remain guardops:

guardops init

from guardops import guard_runtime

Quickstart

guardops init

This creates two files in your current directory:

• guard_manifest.json — your rules
• custom_guards.py — starter custom check/recovery functions

Edit guard_manifest.json to describe your real rules, then decorate your agent function:

from guardops import guard_runtime

@guard_runtime(node_name="PricingAgent")   # must match a key in guard_manifest.json
async def pricing_agent(payload: dict) -> dict:
    payload["price"] = compute_price(payload)
    return payload   # GuardOps checks the return value before it goes further

@guard_runtime works on both async def and plain def functions — no separate decorator needed for sync code.

Validate your manifest any time:

guardops validate --manifest guard_manifest.json

Manifest basics

Three built-in condition types need no custom Python at all:

{
  "PricingAgent": [
    {
      "metric_key": "price",
      "condition_type": "UNDER_FLOOR",
      "boundary_limit": 5.00,
      "fallback_value": 5.00,
      "strategy": "DATA_OVERRIDE",
      "breach_tag": "PRICE_UNDER_FLOOR"
    }
  ]
}

UNDER_FLOOR, OVER_CEILING, and REGEX_MISMATCH cover most simple checks. For anything more — comparing fields to each other, semantic similarity, LLM-as-judge — use CUSTOM_CHECK, which points at a function in custom_guards.py:

{
  "condition_type": "CUSTOM_CHECK",
  "boundary_limit": "custom_guards.check_my_condition",
  "fallback_value": "custom_guards.recover_my_value",
  "breach_tag": "MY_CUSTOM_BREACH",
  "parameters": { "threshold": 0.85 }
}

Custom functions receive (value, rule_config). rule_config always includes metric_key, condition_type, boundary_limit, fallback_value, strategy, breach_tag, parameters (whatever you defined above — free-form), and payload (the full agent output for this call, so you can read sibling fields alongside value).

Telemetry — fully optional, off by default

GuardOps runs completely standalone with zero telemetry setup. Turning it on requires two things together:

1. Install the extra:

pip install "pyguardops[telemetry]"

2. Set these in your app's environment (via your own .env, loaded by your own app before your first @guard_runtime call — GuardOps does not load .env files itself):

LANGFUSE_PUBLIC_KEY=pk-lf-...
LANGFUSE_SECRET_KEY=sk-lf-...
MLFLOW_TRACKING_URI=http://localhost:5000

Both steps are required. Installing the extra without setting the variables leaves telemetry off. Setting the variables without installing the extra also leaves it off (the import fails gracefully). Neither half alone does anything — and that's intentional, so a bare pip install pyguardops never pulls in mlflow/langfuse for anyone who doesn't want them.

If you already run Langfuse and/or MLflow elsewhere in your stack, point these variables at your existing setup — GuardOps logs into your existing project/experiment, it doesn't spin up a separate instance.

Optional extras

pip install "pyguardops[embeddings]"   # semantic similarity in custom guards (sentence-transformers)
pip install "pyguardops[llm]"          # LLM-as-judge custom guards (openai)
pip install "pyguardops[pydantic]"     # Pydantic BaseModel payload support
pip install "pyguardops[all]"          # everything above

Payloads can be plain dict or Pydantic BaseModel instances — GuardOps detects and round-trips both automatically.

Development

git clone <this-repo>
cd pyguardops
pip install -e ".[dev]"
pytest tests/ -v

License

MIT