stacks: add csm (Sesame Conversational Speech Model) to the TTS bench

Sesame CSM-1B via phildougherty/sesame_csm_openai — OpenAI-compat /v1/audio/speech, context-aware conversational speech (voice-agent layer, not a plain reader). Port 8201 on irv-ml1. Gated model: requires CSM_HF_TOKEN (license acceptance) — placeholder in .env.example, real token only in host .env.
2026-05-31 10:59:22 -07:00
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+# Sesame CSM-1B (Conversational Speech Model) served via
+# phildougherty/sesame_csm_openai — an OpenAI-compat wrapper around
+# Sesame's context-aware speech model (Llama backbone + Mimi codec).
+#
+# Why this stack exists alongside the other TTS:
+#   * CSM is a CONVERSATIONAL speech layer, not a plain reader — it
+#     conditions on prior turns (text + audio) to pick prosody, built
+#     for voice-AGENT turn-taking. As pure TTS it works standalone;
+#     its differentiator only pays off in interactive/agent use.
+#   * OpenAI-compat /v1/audio/speech with 6 standard voices
+#     (alloy/echo/fable/onyx/nova/shimmer) + cloned voice IDs.
+#   * ~8 GB VRAM; fits the 3090 (device 0) or A6000 (device 1).
+#
+# NOTE: sesame/csm-1b is a GATED model — you must accept its license at
+# https://huggingface.co/sesame/csm-1b and supply CSM_HF_TOKEN in .env
+# before first boot, or the model download 401s.
+#
+# Image built locally from the upstream wrapper via buildx git-context.
+# All tunables live in .env — edit that, not this file.
+
+services:
+  csm:
+    image: local/csm:${CSM_TAG}
+    build:
+      context: https://github.com/phildougherty/sesame_csm_openai.git#${CSM_SHA}
+      dockerfile: Dockerfile
+    container_name: csm
+    restart: unless-stopped
+    runtime: nvidia
+    ports:
+      - "${CSM_BIND:-0.0.0.0}:${CSM_PORT}:8000"
+    environment:
+      - NVIDIA_VISIBLE_DEVICES=${CSM_GPU_DEVICES:-0}
+      - NVIDIA_DRIVER_CAPABILITIES=compute,utility
+      # Required: gated-model access token (accept the csm-1b license on
+      # HF first). Set the real value in .env, NEVER here.
+      - HF_TOKEN=${CSM_HF_TOKEN}
+      - HF_HUB_ENABLE_HF_TRANSFER=1
+      - HF_HOME=/app/hf_cache
+      # Optional multi-GPU split: auto | balanced | sequential.
+      - CSM_DEVICE_MAP=${CSM_DEVICE_MAP:-}
+    volumes:
+      - ${CSM_VOICES_DIR}:/app/voices
+      - ${CSM_CACHE_DIR}:/app/hf_cache
+    healthcheck:
+      # The wrapper exposes no /health route; GET /v1/audio/voices
+      # returns the voice list only once the model is loaded, so it
+      # doubles as liveness + ready. python urllib (no curl in image),
+      # bound to 127.0.0.1 (uvicorn is IPv4-only).
+      test: ["CMD-SHELL", "python3 -c \"import urllib.request,sys; urllib.request.urlopen('http://127.0.0.1:8000/v1/audio/voices', timeout=5); sys.exit(0)\""]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      # First boot pulls csm-1b + the Llama-3.2-1B tokenizer + Mimi —
+      # gated download, generous deadline.
+      start_period: 600s
+    labels:
+      - homepage.group=AI Systems
+      - homepage.name=Sesame CSM
+      - homepage.icon=mdi-account-voice-outline
+      - homepage.description=Conversational speech model — context-aware voice-agent TTS (irv-ml1)
+      - homepage.href=http://10.100.79.3:${CSM_PORT}