Patter SDK Guide to Building a Restaurant Booking Phone Agent with Dynamic Variables, Guardrails, Latency Dashboards, and Eval Checks
MarkTechPost Sana Hassan
A tutorial demonstrates how to build a voice-agent phone assistant for restaurant bookings using the Patter SDK, covering tool registration, output guardrails, speech simulation, latency tracking, and evaluation checks. The agent handles booking requests by parsing party size, date, and time slot from caller input, manages state across conversation turns, and applies safety guardrails to redact PII, filter profanity, and block off-topic requests. The tutorial shows how to integrate agent logic, tool use, safety checks, and call simulation into a single structured voice-agent pipeline without requiring live telephony credentials.
Why it matters
We explore the Patter SDK by building a voice-agent workflow for a restaurant booking use case. We define dynamic caller variables, register callable tools for availability, bookings, hours, and human transfer, and layer output guardrails over every reply. We simulate speech-to-text and text-to-speech behavior, run scripted call flows, and track modeled latency and cost in a dashboard. We validate the agent with a deterministic eval harness, then map the same logic to a real deployment using Twilio and OpenAI Realtime. The post Patter SDK Guide to Building a Restaurant Booking Phone Agent with Dynamic Variables, Guardrails, Latency Dashboards, and Eval Checks appeared first on MarkTechPost.
