Eva — agentic shopping assistant
What golden eval suite gates Eva tool-calling releases?
Eva is a production shopping agent Rupam Das built at PostQode: Azure OpenAI Responses API with SSE, 21 RBAC-gated tool groups (about 15 writes), PII scrubbing, citations, and a 2,000+ line golden-eval suite that is a CI merge gate.
Built an SSE-streaming, tool-calling agent on the Azure OpenAI Responses API with 21 RBAC-gated tool groups (~15 write tools), retry/circuit-breaker resilience, PII scrubbing, KB-grounded citations, and a 2,000+ line golden-eval suite in CI.
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The constraint
Shopping agents fail in production when tools are over-privileged, PII leaks into prompts, or quality is vibe-checked after deploy.
Architecture
Azure OpenAI Responses API with SSE streaming. Tool groups sit behind RBAC, including about 15 write tools. Retry and circuit-breaker wrappers bound upstream failure. PII is scrubbed before the model. Knowledge-base answers carry citations. A 2,000+ line golden-eval suite is a merge gate, not a dashboard after the fact.
Sources / stack
- Azure OpenAI Responses API
- SSE
- RBAC tool groups
- Circuit breakers
- PII scrubbing
- KB citations
- Golden evals
Agent control plane
- 01Interface
- SSE stream
- Responses API
- 02Policy
- 21 RBAC tool groups
- PII scrubbing
- 03Grounding
- KB citations
- Retry / circuit breaker
- 04Quality
- Golden evals
- CI merge gate
What we measured
RBAC-gated tool groups
~15 write tools never run without authorization
Golden eval suite
Merge gate on every CI run
Result
Production agent with real users; write tools behind RBAC; evals blocking regressions every CI run.