Talon Example

This example runs a Talon host process with one or more channel adapters in the same container. The host ~/talon-workspace/ directory is mounted at /workspace.

Experimental: Talon is an experimental runtime and is subject to change or removal at any time.

Run

cp .env.example .env
mkdir -p ~/talon-workspace ~/.deepagents
# Fill AGENT_MODEL provider credentials, then uncomment the channel you want to use.
# Build once and run:
docker compose build
docker compose up

WhatsApp

Uncomment the WhatsApp env vars in .env and scan the QR code printed by the bridge. The default exposure mode is self, so only messages sent by the paired WhatsApp account trigger the agent. Use allowlist or open only when you intentionally want other chats to trigger the agent.

Telegram

Uncomment the Telegram env vars in .env and set DEEPAGENTS_TALON_TELEGRAM_BOT_TOKEN. The default exposure mode is self, which requires DEEPAGENTS_TALON_TELEGRAM_OPERATOR_ID to identify your Telegram user ID. Use allowlist or open only when you intentionally want other chats to trigger the agent.

Voice Transcription

Voice transcription is enabled by default in .env.example. The Docker example installs ffmpeg plus the Talon media extra, so inbound voice notes are transcribed locally with NVIDIA Parakeet through Transformers before reaching the agent. The first voice message can be slow because the ASR model is downloaded lazily. Set DEEPAGENTS_TALON_VOICE_TRANSCRIPTION_DEVICE=cuda when running on a GPU-enabled host.

Parakeet and Qwen embedding model downloads persist through the existing home bind mount. For docker run, add -v "$HOME/.deepagents:/root/.deepagents".