Feature Request: Simple cryptographic provenance for who authorized what in LangGraph multi-agent graphs
Siri
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2026-04-20
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via LangChain Forum - Topics tagged python-help
Hey LangGraph folks, When you have agents delegating to sub-agents or calling tools in a complex graph, it quickly gets fuzzy: Which human originally approved this action, and with what scope? I built HDP (Human Delegation Provenance) as a lightweight fix. Currently in IETF draft, research backed. A human signs a short Ed25519 token once. Agents then cryptographically extend the chain on every handoff or tool call. Verification is completely offline, no extra services, no latency. As of April 2026: Python + LangChain/LangGraph support is ready today via the middleware package: https://github.com/Helixar-AI/HDP/tree/main/packages/hdp-langchain It includes a clean HdpCallbackHandler and @hdp_node () decorator that auto-extends the chain on node transitions. Super lightweight and drop-in. It’s already seeing real use: Some folks in the LangChain community are running it in actual scenarios today. HDP is also now included as an app in the official Google Gemma 4 cookbook . Would baking lighter native support for HDP into LangGraph make sense? It would give clean, tamper-evident provenance that plays nicely with LangSmith tracing and human-in-the-loop patterns, without changing how you build graphs today. Curious if others are hitting this gap in production, and what the team thinks. Thanks! Siri (Helixar AI) PS: Reposting here as originally posted in a wrong thread in talkshop 3 posts - 3 participants Read full topic
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