wardhook
Governance and observability for LangGraph agents.
This package contains no code. It installs all four Wardhook packages at a matching version, for when you want the whole toolkit:
pip install wardhook
Which is equivalent to:
pip install wardhook-core wardhook-guardrails wardhook-observability wardhook-evals
| Package | What it does |
|---|---|
| wardhook-core | LangGraph agent runtime, tool calling, RAG with real source citations, one-command FastAPI server |
| wardhook-guardrails | PII redaction, prompt-injection scoring, tool RBAC, compliance audit trail |
| wardhook-observability | Per-node tokens, cost, and latency; static HTML trace viewer |
| wardhook-evals | JSONL test cases, pass/fail runner, baseline regression detection |
Extras
Provider clients and optional backends, passed through to whichever package owns them:
pip install "wardhook[anthropic]" # langchain-anthropic, for a real model
pip install "wardhook[openai]" # langchain-openai
pip install "wardhook[chroma]" # Chroma vector store instead of the built-in one
pip install "wardhook[judge]" # langchain-core, for the llm_judge eval criterion
pip install "wardhook[all]" # all of the above
Should you use this, or the individual packages?
Use the individual packages if you want one capability. Each installs and
works entirely alone — that is the point of the project, and CI proves it by
installing each one in an environment containing no other Wardhook package and
running its suite there. wardhook-guardrails in particular has a single
runtime dependency (PyYAML) and needs no agent framework at all.
Use this package if you want all four and would rather write one line. It
pins each dependency to an exact version, so wardhook==0.1.0 means precisely
the 0.1.0 set. If you need to mix versions, depend on the packages directly.
Links
- Quickstart — all four packages into one working agent
- Architecture overview — how they compose without importing each other
- Main repository
1 maintainer
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