How to Orchestrate Multi-Call Conversations with an LLM and Twilio Conversation Memory

Twilio’s tutorial demonstrates how to build a C# .NET 9 ASP.NET Core voice agent that preserves context across separate phone calls by combining Twilio Conversation Memory, Conversation Relay, and OpenAI’s GPT-4o-mini model. Developers create a Twilio Memory Store, configure credentials and phone settings through environment variables, and implement services that create caller profiles based on phone numbers, retrieve prior summaries and observations, and save an AI-generated summary after each call. A WebSocket relay receives transcribed caller speech from Twilio, supplies the current and recalled conversation context to OpenAI, and streams the model’s responses back to the caller while handling interruptions by removing incomplete assistant responses from the active history. The example uses an auto repair assistant, but notes that the same pattern can support applications such as technical support or travel services; after exposing the local webhook with ngrok and assigning it to a Twilio number, users can test memory by placing two calls from the same number and confirming that the agent recalls details from the earlier conversation.

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