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cv usk
@cv_usk
AI / Software Research Notes AI Agent, LLMOps, MLOps, Software Architecture ๆŠ•็จฟใฏๅ€‹ไบบใฎๆ„่ฆ‹ใงใ™ใ€‚
Joined May 2026
258 Following    228 Followers
๐Ÿค "LLMs for ambiguity, deterministic agents for hard policy"โ€”a contract-compliance ADK sample that takes role separation seriously. Title: Contract Compliance Pipeline (GoogleCloudPlatform/generative-ai) URL: An auditable demo that uses Google ADK's A2A protocol to coordinate a Python (intake) agent and a Go (validation) agent. Three highlights worth your attention. ๐Ÿง  Separating LLM from deterministic work Instead of routing everything through an LLM, ambiguous extraction goes to the LLM/parser side while hard policy enforcement runs in a deterministic Go engine. Rules like "value โ‰ค $500k" or "term โ‰ค 5 years" get checked in a repeatable, identical-every-time way. ๐Ÿ”Œ Cross-language A2A handoff ADK's RemoteA2aAgent discovers the Go service via its Agent Card (/.well-known/agent.json) and sends a JSON-RPC 2.0 SendMessage. A Python agent (FastAPI:8000) and a Go agent (net/http:8888) collaborate using only a standard protocol. ๐Ÿ“œ Auditable policy and artifacts Policies (value cap, term limit, minimum insurance, required exit clause, no unlimited liability, etc.) are passed as custom_policies and swappable per audit. Results are visualized with an execution trace, and the system even auto-generates compliance certificates and parameter sheets. It reads like a template you could lift straight into real regulated/review-heavy systems. #AIAgents# #GoogleADK#
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