vertex-agent-builder

# Vertex AI Agent Builder Build and deploy production-ready agents on Vertex AI with Gemini models, retrieval (RAG), function calling, and operational guardrails (validation, monitoring, cost controls). ## Overview - Produces an agent scaffold aligned with Vertex AI Agent Engine deployment patterns. - Helps choose models/regions, design tool/function interfaces, and wire up retrieval. - Includes an evaluation + smoke-test checklist so deployments don’t regress. ## Prerequisites - Google Cloud project with Vertex AI API enabled - Permissions to deploy/operate Agent Engine runtimes (or a local-only build target) - If using RAG: a document source (GCS/BigQuery/Firestore/etc) and an embeddings/index strategy - Secrets handled via env vars or Secret Manager (never committed) ## Instructions 1. Clarify the agent’s job (user intents, inputs/outputs, latency and cost constraints). 2. Choose model + region and define tool/function interfaces (schemas, error contracts). 3. Implement retrieval (if needed): chunking, embeddings, index, and a “citation-first” response format. 4. Add evaluation: golden prompts, offline checks, and a minimal online smoke test. 5. Deploy (optional): provide the exact deployment command/config and verify endpoints + permissions. 6. Add ops: logs/metrics, alerting, quota/cost guardrails, and rollback steps. ## Output - A Vertex AI agent scaffold (code/config) with clear extension points - A retrieval plan (when applicable) and a validation/evaluation ...