twilio-agent-connect-microsoft 1.0.1

Azure integrations for Twilio Agent Connect (TAC) - connectors for Azure AI agent services

Twilio Agent Connect for Microsoft

Azure integrations for Twilio Agent Connect — connect Microsoft Foundry agents to Twilio's channels, memory, and context.

Documentation ◆ Python SDK ◆ Examples ◆ Deployment

Ships Microsoft Agent Framework and Azure AI Voice Live connectors for Twilio Agent Connect (TAC), plus production Azure deployments for each.

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Features

• AgentFrameworkConnector - Microsoft Agent Framework integration
  • Agent lifecycle management (Voice + SMS + Chat)
  • Supports Foundry Hosted Agents, Foundry Prompt Agents, Azure OpenAI (Responses API, Chat Completions), and other backends
  • Pluggable session persistence via AgentSessionStore protocol
  • Memory context injection and on_message / on_error hooks
• VoiceLiveConnector - Voice Live API integration
  • Text-in / text-streaming-out over WebSocket (STT and TTS handled by Twilio Conversation Relay)
  • Server-side conversation state (no local session management)
  • Native interrupt handling via Voice Live response.cancel (server-side truncation of in-flight responses)
  • Tool execution with async handlers
• Multi-channel support (Voice + SMS + Chat)
• Built-in TAC tools (memory recall, knowledge search, Studio Flow handoff)
• Getting-started deployment guide with Dockerfile and deployment helpers
• AgentSessionStore implementations for in-memory, file, and Cosmos DB

Installation

With Agent Framework

pip install twilio-agent-connect-microsoft[agent-framework,server]

With Voice Live

pip install twilio-agent-connect-microsoft[voice-live,server]

Development

git clone https://github.com/twilio/twilio-agent-connect-microsoft.git
cd twilio-agent-connect-microsoft
uv sync --all-extras

Prerequisites

Before running any examples, you need to create and configure the required Twilio services (Conversation Configuration, phone number, etc.). Follow the TAC Quickstart guide to set these up.

Configuration

TAC Microsoft requires TAC environment variables. See TAC Configuration for details.

Required Environment Variables

# Twilio Agent Connect (required for all examples)
TWILIO_CONVERSATION_CONFIGURATION_ID=conv_configuration_xxxxxxxxxxxxxxxxxx
TWILIO_ACCOUNT_SID=ACxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
TWILIO_AUTH_TOKEN=your_auth_token
TWILIO_API_KEY=SKxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
TWILIO_API_SECRET=your_api_key_secret
TWILIO_PHONE_NUMBER=[phone]

# Server (required for voice)
TWILIO_VOICE_PUBLIC_DOMAIN=your-domain.ngrok.io

# Azure OpenAI — Agent Framework basic example (API key auth)
# Endpoint is the resource base URL only — no /openai/v1 suffix.
AZURE_OPENAI_ENDPOINT=https://your-resource.openai.azure.com/
AZURE_AI_API_KEY=your_azure_openai_api_key
AZURE_AI_DEPLOYMENT_NAME=gpt-4o

# Agent Framework advanced example uses the same AZURE_OPENAI_ENDPOINT as basic,
# but authenticates via `DefaultAzureCredential` (run `az login` first) instead of an API key.

# Voice Live API — voice_live example (hostname only, no https:// prefix)
# AZURE_VOICE_LIVE_ENDPOINT=your-resource.services.ai.azure.com
# AZURE_VOICE_LIVE_API_KEY=your_voice_live_api_key
# AZURE_VOICE_LIVE_MODEL=gpt-realtime

See getting_started/examples/.env.example for the full list including optional features (Cosmos DB, knowledge base, conversation intelligence). Copy it to getting_started/examples/.env and fill in your values — all examples load from that shared file.

Quick Start

Everything imports from tac_microsoft — no need to import from the underlying tac package:

from tac_microsoft import (
    TAC, TACConfig, TACFastAPIServer,
    AgentFrameworkConnector, ConversationSession,
    FileAgentSessionStore,
)
from tac_microsoft.agent_framework_tools import create_memory_tool

Examples

Full examples available in getting_started/examples/:

• agent_framework/basic.py - Minimal Agent Framework setup (~30 lines)
• agent_framework/advanced.py - Full feature set (channel-aware prompts, tools, hooks, session persistence)
• voice_live/basic.py - Voice Live API with tool calling

AgentSessionStore

The AgentSessionStore protocol defines how Agent Framework sessions are persisted between requests, enabling conversation continuity across SMS messages and horizontal scaling for voice.

Three implementations are included:

• InMemoryAgentSessionStore — default, suitable for single-instance deployments
• FileAgentSessionStore — persists sessions as JSON files on disk (single-instance, local dev)
• CosmosDBAgentSessionStore — persists sessions in Azure Cosmos DB for NoSQL (horizontally scaled production). Requires the cosmos extra: pip install twilio-agent-connect-microsoft[cosmos]

Implement the protocol to use any other backing store (Redis, DynamoDB, Postgres, etc.).

Development

Setup

# Clone repository
git clone https://github.com/twilio/twilio-agent-connect-microsoft.git
cd twilio-agent-connect-microsoft

# Install dependencies
uv sync --all-extras

Getting Started

See getting_started/README.md for the full setup and deployment guide.

Dependencies

TAC Microsoft depends on:

• twilio-agent-connect - Core Twilio Agent Connect framework (installed from PyPI)
  • Requires twilio-agent-connect[server] extra for TACFastAPIServer support
• agent-framework (optional) - Microsoft Agent Framework
• websockets (optional) - For Voice Live connector
• azure-cosmos (optional) - For CosmosDB session store

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

MIT License - see LICENSE file for details.