Synchronize Athena operating modes with live deployment
This commit is contained in:
Mikei386
+43
-141
@@ -50,11 +50,6 @@ services:
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- /tmp:size=16m,mode=1777
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volumes:
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- "${WIREGUARD_CONFIG_FILE:-/etc/mike-ai/wireguard/fritz-athena.conf}:/run/secrets/fritz-athena.conf:ro"
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# Namespace-sharing services cannot publish ports themselves. The owner
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# must keep these bindings so a gateway recreation cannot hide their UIs.
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ports:
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- "8099:8099"
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- "9443:9443"
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networks:
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frontend:
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ipv4_address: 172.30.10.254
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@@ -237,89 +232,6 @@ services:
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- --spec-draft-p-min
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- "0.05"
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# Beta 1 keeps the complete GSQ-RCO text model and KV cache on the RTX 5080.
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# Only the multimodal projector runs on the RTX 3060. The measured hard
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# boundary is 196608 tokens; 192K deliberately retains runtime headroom.
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llama-beta1:
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<<: *llama-common
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container_name: mike-ai-llama-beta1
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labels:
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com.mike-ai.llama-profile: beta1
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environment:
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NVIDIA_VISIBLE_DEVICES: ${BETA1_GPU_DEVICES:-0,1}
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NVIDIA_DRIVER_CAPABILITIES: compute,utility
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MTMD_BACKEND_DEVICE: CUDA1
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command:
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- --model
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- "/models/${BETA1_MODEL_FILE:?BETA1_MODEL_FILE is required}"
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- --mmproj
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- "/models/${VISION_PROJECTOR_FILE:?VISION_PROJECTOR_FILE is required}"
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- --mmproj-offload
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- --mmproj-device
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- CUDA1
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- --alias
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- qwen-beta-1
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- --ctx-size
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- "${BETA1_CONTEXT:-192000}"
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- --flash-attn
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- "on"
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- --cache-type-k
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- q4_0
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- --cache-type-v
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- q4_0
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- --cache-prompt
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- --cache-ram
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- "${LLAMA_CACHE_RAM_MIB:-32768}"
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- --threads
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- "${LLAMA_THREADS:-6}"
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- --threads-batch
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- "${LLAMA_THREADS_BATCH:-6}"
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- --batch-size
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- "${BETA1_BATCH_SIZE:-2048}"
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- --ubatch-size
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- "${BETA1_UBATCH_SIZE:-128}"
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- --parallel
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- "${BETA1_PARALLEL_SLOTS:-1}"
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- --kv-unified
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- --jinja
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- --reasoning
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- auto
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- --reasoning-preserve
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- --host
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- 0.0.0.0
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- --port
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- "8080"
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- --metrics
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- --fit
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- "off"
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- --n-gpu-layers
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- all
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- --load-mode
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- none
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- --no-ui
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- --temperature
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- "1.0"
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- --top-p
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- "0.95"
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- --top-k
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- "20"
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- --device
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- CUDA0
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- --main-gpu
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- "0"
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- --split-mode
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- none
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- --spec-type
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- draft-mtp
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- --spec-draft-n-max
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- "3"
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- --spec-draft-type-k
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- f16
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- --spec-draft-type-v
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- f16
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- --spec-draft-p-min
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- "0.05"
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llama-large:
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<<: *llama-common
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container_name: mike-ai-llama-large
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@@ -575,8 +487,17 @@ services:
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- /var/run/docker.sock:/var/run/docker.sock
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environment:
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CONTROLLER_TOKEN: "${CONTROLLER_TOKEN:?CONTROLLER_TOKEN is required}"
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ALLOWED_PROFILES: fast,medium,beta1,large,ultra,uncensored
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ALLOWED_PROFILES: fast,medium,large,ultra,uncensored
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IMAGE_WORKER: image
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RESTORE_WORKER: restore
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TTS_WORKER: qwen3
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MUSIC_WORKER: acestep
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YUE2_WORKER: yue2
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SEPARATOR_WORKER: bs-roformer
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VOICE_WORKER: vevo2
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VOICE_CHANGE_WORKER: xvc
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APPLIO_WORKER: applio
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TRELLIS_WORKER: trellis2-q8
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networks: [control]
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security_opt: ["no-new-privileges:true"]
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healthcheck:
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@@ -612,6 +533,8 @@ services:
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PROFILE_CONTROL_TOKEN: "${CONTROLLER_TOKEN:?CONTROLLER_TOKEN is required}"
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SWITCH_TIMEOUT: "600"
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REQUEST_TIMEOUT: "600"
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YUE2_START_TIMEOUT: "600"
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TRELLIS_START_TIMEOUT: "900"
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# Last-resort guard for every OpenAI-compatible client. Without a
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# request limit llama.cpp uses n_predict=-1 and a reasoning loop can
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# consume the complete context before yielding visible output.
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@@ -621,19 +544,21 @@ services:
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IMAGE_DIR: /data/images
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IMAGE_WORKER_URL: http://image-worker:8086
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IMAGE_WORKER_TOKEN: "${CONTROLLER_TOKEN:?CONTROLLER_TOKEN is required}"
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IMAGE_MODEL_NAME: FLUX.2-klein-4B
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IMAGE_MODEL_NAME: FLUX.2-klein-9B-fp8-beta
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CHAT_IMAGE_ALLOW_REMOTE_URLS: "false"
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ENABLE_IMAGE_GENERATION: "true"
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ENABLE_TTS: "true"
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# Stable OpenAI compatibility names remain piper/alloy because an
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# existing Open WebUI database persists those values. The gateway maps
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# alloy to XTTS speaker Annmarie Nele and automatically falls back to
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# Piper if XTTS is unavailable, busy or returns an error.
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# The gateway keeps text normalization, output conversion and native
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# PCM streaming in one stable API in front of Qwen3-TTS.
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TTS_WORKER_URL: http://tts-gateway:8085
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TTS_MODEL: piper
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TTS_MODEL: qwen3-tts
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TTS_VOICES: alloy
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TTS_DEFAULT_VOICE: alloy
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ENABLE_STT: "true"
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ENABLE_MUSIC_MODE: "true"
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MUSIC_START_TIMEOUT: "600"
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VOICE_CHANGE_START_TIMEOUT: "600"
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APPLIO_START_TIMEOUT: "900"
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STT_WORKER_URL: http://whisper:8084
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STT_TIMEOUT: "300"
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networks: [frontend, control, inference]
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@@ -655,8 +580,6 @@ services:
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condition: service_healthy
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profile-controller:
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condition: service_healthy
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piper:
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condition: service_healthy
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tts-gateway:
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condition: service_healthy
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whisper:
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@@ -680,13 +603,15 @@ services:
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read_only: true
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tmpfs: ["/tmp:size=1g,mode=1777"]
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volumes:
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- "${FLUX_MODEL_DIR:-/data/models/FLUX.2-klein-4B}:/models/FLUX.2-klein-4B:ro"
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- "${FLUX_COMPONENT_DIR:-/data/models/FLUX.2-klein-9B-components}:/models/components:ro"
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- "${FLUX_TRANSFORMER_DIR:-/data/models/FLUX.2-klein-9B-fp8}:/models/fp8:ro"
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- router-images:/data/images
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environment:
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NVIDIA_VISIBLE_DEVICES: ${IMAGE_GPU_DEVICES:-1}
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NVIDIA_VISIBLE_DEVICES: all
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NVIDIA_DRIVER_CAPABILITIES: compute,utility
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WORKER_TOKEN: "${CONTROLLER_TOKEN:?CONTROLLER_TOKEN is required}"
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FLUX_MODEL_DIR: /models/FLUX.2-klein-4B
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FLUX_COMPONENT_DIR: /models/components
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FLUX_TRANSFORMER_FILE: /models/fp8/flux-2-klein-9b-fp8.safetensors
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IMAGE_DIR: /data/images
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networks: [inference]
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security_opt: ["no-new-privileges:true"]
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@@ -697,41 +622,12 @@ services:
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timeout: 3s
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retries: 12
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piper:
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build:
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context: platform/docker/piper
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args:
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PIPER_TTS_VERSION: ${PIPER_TTS_VERSION:-1.6.0}
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image: mike-ai/piper:local
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container_name: mike-ai-piper
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restart: unless-stopped
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read_only: true
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tmpfs:
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- /tmp:size=256m,mode=1777
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volumes:
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- piper-data:/data
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environment:
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PIPER_DATA_DIR: /data
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PIPER_VOICE: ${PIPER_VOICE:-de_DE-thorsten-high}
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PIPER_VOICE_ALIAS: alloy
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PIPER_HOST: 0.0.0.0
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PIPER_PORT: "8085"
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PIPER_MAX_TEXT_CHARS: "8000"
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networks: [frontend]
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security_opt: ["no-new-privileges:true"]
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cap_drop: [ALL]
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cap_add: [CHOWN, SETUID, SETGID]
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healthcheck:
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test: [CMD, curl, -fsS, "http://127.0.0.1:8085/status"]
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interval: 10s
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timeout: 5s
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retries: 30
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start_period: 120s
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qwen3-tts:
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image: ${QWEN3_TTS_IMAGE:-ghcr.io/malaiwah/qwen3-tts-server:latest@sha256:b363a01d08b1bbecbfc3ca6f585368fae2cfdc591f9ecca6643738369f9a9d98}
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container_name: mike-ai-qwen3-tts
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restart: unless-stopped
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labels:
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com.mike-ai.tts-worker: qwen3
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deploy:
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resources:
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reservations:
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@@ -783,17 +679,12 @@ services:
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QWEN_TTS_VOICE: serena
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QWEN_TTS_LANGUAGE: German
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QWEN_TTS_TIMEOUT: "120"
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PIPER_URL: http://piper:8085
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TTS_VOICE_ALIAS: alloy
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TTS_DEFAULT_LANGUAGE: de
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# Mixed-language clip stitching caused long pauses and unintelligible
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# transitions. Keep full sentences in one stable German voice.
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TTS_CODE_SWITCH_ENABLED: "false"
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PIPER_TIMEOUT: "120"
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networks: [frontend]
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depends_on:
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piper:
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condition: service_healthy
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security_opt: ["no-new-privileges:true"]
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cap_drop: [ALL]
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healthcheck:
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@@ -843,7 +734,7 @@ services:
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image: mike-ai/llama-dashboard:local
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container_name: mike-ai-llama-dashboard
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restart: unless-stopped
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network_mode: "service:wireguard-gateway"
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networks: [frontend]
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gpus: all
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read_only: true
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tmpfs:
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@@ -852,15 +743,26 @@ services:
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- /proc:/host/proc:ro
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- /data:/host/data:ro
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- /data/models:/host/models:ro
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- /data/emergency-backups:/backups:ro
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- /data/llama-dashboard:/var/lib/llama-dashboard
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environment:
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DASHBOARD_HOST: 0.0.0.0
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DASHBOARD_PORT: "8099"
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ROUTER_URL: http://router:8081
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ROUTER_API_KEY: "${ROUTER_API_KEY:?ROUTER_API_KEY is required}"
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MUSIC_COMMUNITY_UI_URL: "${MUSIC_COMMUNITY_UI_URL:-http://192.168.1.212:7861/}"
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MUSIC_ORIGINAL_UI_URL: "${MUSIC_ORIGINAL_UI_URL:-http://192.168.1.212:7862/}"
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SEPARATOR_UI_URL: "${SEPARATOR_UI_URL:-http://192.168.1.212:8007/}"
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VOICE_UI_URL: "${VOICE_UI_URL:-http://192.168.1.212:8008/}"
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VOICE_CHANGE_UI_URL: "${VOICE_CHANGE_UI_URL:-http://192.168.1.212:8009/}"
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APPLIO_UI_URL: "${APPLIO_UI_URL:-http://192.168.1.212:8011/}"
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MIKES_APPLIO_UI_URL: "${MIKES_APPLIO_UI_URL:-http://192.168.1.212:8012/}"
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TRELLIS_UI_URL: "${TRELLIS_UI_URL:-http://192.168.1.212:8013/}"
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YUE2_UI_URL: "${YUE2_UI_URL:-http://192.168.1.212:8014/}"
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HOST_PROC: /host/proc
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HOST_DATA: /host/data
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HOST_MODELS: /host/models
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DASHBOARD_BACKUP_DIR: /backups
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DASHBOARD_HISTORY_DB: /var/lib/llama-dashboard/history.sqlite3
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DASHBOARD_HISTORY_INTERVAL: "15"
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DASHBOARD_DETAIL_RETENTION_DAYS: "21"
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@@ -884,7 +786,7 @@ services:
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image: ${PORTAINER_IMAGE:-portainer/portainer-ce@sha256:511f3f06c96fe3b993ebeaafde311c1959cae73a7ef825dba6397d51b450dffa}
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container_name: mike-ai-portainer
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restart: unless-stopped
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network_mode: "service:wireguard-gateway"
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networks: [frontend]
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command: [--no-setup-token]
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volumes:
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- /var/run/docker.sock:/var/run/docker.sock
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@@ -908,8 +810,9 @@ services:
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- /var/run/docker.sock:/var/run/docker.sock:ro
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- /data/docker-backups:/archive
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- /etc/mike-ai:/backup/etc-mike-ai:ro
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- /opt/mike-ai/stack:/backup/stack:ro
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- piper-data:/backup/volumes/piper-data:ro
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# Include every deployed specialist UI/worker source tree, not just the
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# core checkout. Images themselves remain reproducible and are rebuilt.
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- /opt/mike-ai:/backup/opt-mike-ai:ro
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- router-state:/backup/volumes/router-state:ro
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- router-images:/backup/volumes/router-images:ro
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- portainer-data:/backup/volumes/portainer-data:ro
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@@ -936,7 +839,6 @@ networks:
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name: mike-ai-tools-egress
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volumes:
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piper-data:
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whisper-data:
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router-state:
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router-images:
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@@ -13,6 +13,7 @@ import logging
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import os
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import socket
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import threading
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import time
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import urllib.parse
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from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
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@@ -25,6 +26,22 @@ ALLOWED = tuple(x.strip() for x in os.environ.get(
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LABEL_KEY = "com.mike-ai.llama-profile"
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IMAGE_LABEL_KEY = "com.mike-ai.image-worker"
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IMAGE_WORKER = os.environ.get("IMAGE_WORKER", "image")
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RESTORE_WORKER = os.environ.get("RESTORE_WORKER", "restore")
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TTS_LABEL_KEY = "com.mike-ai.tts-worker"
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TTS_WORKER = os.environ.get("TTS_WORKER", "qwen3")
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MUSIC_LABEL_KEY = "com.mike-ai.music-worker"
|
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MUSIC_WORKER = os.environ.get("MUSIC_WORKER", "").strip()
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YUE2_WORKER = os.environ.get("YUE2_WORKER", "").strip()
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SEPARATOR_LABEL_KEY = "com.mike-ai.stem-separator"
|
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SEPARATOR_WORKER = os.environ.get("SEPARATOR_WORKER", "").strip()
|
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VOICE_LABEL_KEY = "com.mike-ai.voice-worker"
|
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VOICE_WORKER = os.environ.get("VOICE_WORKER", "").strip()
|
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VOICE_CHANGE_LABEL_KEY = "com.mike-ai.voice-change-worker"
|
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VOICE_CHANGE_WORKER = os.environ.get("VOICE_CHANGE_WORKER", "").strip()
|
||||
APPLIO_LABEL_KEY = "com.mike-ai.applio-worker"
|
||||
APPLIO_WORKER = os.environ.get("APPLIO_WORKER", "").strip()
|
||||
TRELLIS_LABEL_KEY = "com.mike-ai.trellis-worker"
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TRELLIS_WORKER = os.environ.get("TRELLIS_WORKER", "").strip()
|
||||
LOCK = threading.Lock()
|
||||
log = logging.getLogger("profile-controller")
|
||||
|
||||
@@ -68,15 +85,152 @@ def labelled_containers(label: str) -> list[dict]:
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||||
return json.loads(body)
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||||
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||||
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def image_container() -> dict:
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||||
def image_container(kind: str = IMAGE_WORKER) -> dict:
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matches = [item for item in labelled_containers(IMAGE_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(IMAGE_LABEL_KEY) == IMAGE_WORKER]
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if item.get("Labels", {}).get(IMAGE_LABEL_KEY) == kind]
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||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one image worker {IMAGE_WORKER!r}, found {len(matches)}")
|
||||
f"expected exactly one image worker {kind!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
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||||
def image_containers() -> list[dict]:
|
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"""All allowlisted GPU workers that must never overlap an LLM."""
|
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allowed = {IMAGE_WORKER, RESTORE_WORKER}
|
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return [item for item in labelled_containers(IMAGE_LABEL_KEY)
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if item.get("Labels", {}).get(IMAGE_LABEL_KEY) in allowed]
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|
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|
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def tts_container() -> dict:
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matches = [item for item in labelled_containers(TTS_LABEL_KEY)
|
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if item.get("Labels", {}).get(TTS_LABEL_KEY) == TTS_WORKER]
|
||||
if len(matches) != 1:
|
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raise RuntimeError(
|
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f"expected exactly one TTS worker {TTS_WORKER!r}, found {len(matches)}")
|
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return matches[0]
|
||||
|
||||
|
||||
def music_container() -> dict:
|
||||
if not MUSIC_WORKER:
|
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raise RuntimeError("music worker is not configured")
|
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matches = [item for item in labelled_containers(MUSIC_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(MUSIC_LABEL_KEY) == MUSIC_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one music worker {MUSIC_WORKER!r}, found {len(matches)}")
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||||
return matches[0]
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||||
|
||||
|
||||
def yue2_container() -> dict:
|
||||
if not YUE2_WORKER:
|
||||
raise RuntimeError("YuE2 worker is not configured")
|
||||
matches = [item for item in labelled_containers(MUSIC_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(MUSIC_LABEL_KEY) == YUE2_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one YuE2 worker {YUE2_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def separator_container() -> dict:
|
||||
if not SEPARATOR_WORKER:
|
||||
raise RuntimeError("stem separator is not configured")
|
||||
matches = [item for item in labelled_containers(SEPARATOR_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(SEPARATOR_LABEL_KEY) == SEPARATOR_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one stem separator {SEPARATOR_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def voice_container() -> dict:
|
||||
if not VOICE_WORKER:
|
||||
raise RuntimeError("voice worker is not configured")
|
||||
matches = [item for item in labelled_containers(VOICE_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(VOICE_LABEL_KEY) == VOICE_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one voice worker {VOICE_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def voice_change_container() -> dict:
|
||||
if not VOICE_CHANGE_WORKER:
|
||||
raise RuntimeError("voice-change worker is not configured")
|
||||
matches = [item for item in labelled_containers(VOICE_CHANGE_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(VOICE_CHANGE_LABEL_KEY) == VOICE_CHANGE_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one voice-change worker {VOICE_CHANGE_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def applio_container() -> dict:
|
||||
if not APPLIO_WORKER:
|
||||
raise RuntimeError("Applio worker is not configured")
|
||||
matches = [item for item in labelled_containers(APPLIO_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(APPLIO_LABEL_KEY) == APPLIO_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one Applio worker {APPLIO_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def trellis_container() -> dict:
|
||||
if not TRELLIS_WORKER:
|
||||
raise RuntimeError("TRELLIS worker is not configured")
|
||||
matches = [item for item in labelled_containers(TRELLIS_LABEL_KEY)
|
||||
if item.get("Labels", {}).get(TRELLIS_LABEL_KEY) == TRELLIS_WORKER]
|
||||
if len(matches) != 1:
|
||||
raise RuntimeError(
|
||||
f"expected exactly one TRELLIS worker {TRELLIS_WORKER!r}, found {len(matches)}")
|
||||
return matches[0]
|
||||
|
||||
|
||||
def stop_music_if_configured() -> None:
|
||||
if MUSIC_WORKER:
|
||||
stop_container(music_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_yue2_if_configured() -> None:
|
||||
if YUE2_WORKER:
|
||||
stop_container(yue2_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_separator_if_configured() -> None:
|
||||
if SEPARATOR_WORKER:
|
||||
stop_container(separator_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_voice_if_configured() -> None:
|
||||
if VOICE_WORKER:
|
||||
stop_container(voice_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_voice_change_if_configured() -> None:
|
||||
if VOICE_CHANGE_WORKER:
|
||||
stop_container(voice_change_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_applio_if_configured() -> None:
|
||||
if APPLIO_WORKER:
|
||||
stop_container(applio_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_trellis_if_configured() -> None:
|
||||
if TRELLIS_WORKER:
|
||||
stop_container(trellis_container(), timeout=30)
|
||||
|
||||
|
||||
def stop_voice_tools(except_kind: str | None = None) -> None:
|
||||
if except_kind != "voice":
|
||||
stop_voice_if_configured()
|
||||
if except_kind != "voicechange":
|
||||
stop_voice_change_if_configured()
|
||||
if except_kind != "applio":
|
||||
stop_applio_if_configured()
|
||||
|
||||
|
||||
def stop_container(item: dict, timeout: int = 120) -> None:
|
||||
if item.get("State") != "running":
|
||||
return
|
||||
@@ -85,6 +239,31 @@ def stop_container(item: dict, timeout: int = 120) -> None:
|
||||
raise RuntimeError(f"failed to stop container: HTTP {status}")
|
||||
|
||||
|
||||
def start_container(item: dict) -> None:
|
||||
status, _ = docker_request("POST", f"/containers/{item['Id']}/start")
|
||||
if status not in (204, 304):
|
||||
raise RuntimeError(f"failed to start container: HTTP {status}")
|
||||
|
||||
|
||||
def wait_container_healthy(item: dict, timeout: int) -> None:
|
||||
deadline = time.monotonic() + timeout
|
||||
while time.monotonic() < deadline:
|
||||
status, body = docker_request("GET", f"/containers/{item['Id']}/json")
|
||||
if status != 200:
|
||||
raise RuntimeError(f"failed to inspect container: HTTP {status}")
|
||||
state = json.loads(body).get("State", {})
|
||||
health = state.get("Health", {}).get("Status")
|
||||
if state.get("Status") == "running" and health == "healthy":
|
||||
return
|
||||
if state.get("Status") in {"dead", "exited"} or health == "unhealthy":
|
||||
raise RuntimeError(
|
||||
f"container {item.get('Names', ['unknown'])[0]} failed: "
|
||||
f"state={state.get('Status')} health={health}")
|
||||
time.sleep(1)
|
||||
raise RuntimeError(
|
||||
f"container {item.get('Names', ['unknown'])[0]} did not become healthy")
|
||||
|
||||
|
||||
def stop_inference() -> dict:
|
||||
with LOCK:
|
||||
items = containers()
|
||||
@@ -94,22 +273,186 @@ def stop_inference() -> dict:
|
||||
return {"active_profile": None, "previous_profile": previous}
|
||||
|
||||
|
||||
def set_image_worker(running: bool) -> dict:
|
||||
def set_image_worker(running: bool, kind: str = IMAGE_WORKER) -> dict:
|
||||
if kind not in {IMAGE_WORKER, RESTORE_WORKER}:
|
||||
raise ValueError("worker is not allowlisted")
|
||||
with LOCK:
|
||||
item = image_container()
|
||||
item = image_container(kind)
|
||||
if running:
|
||||
# The image worker may never overlap a llama profile on the 5080.
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
if item.get("State") != "running":
|
||||
status, _ = docker_request("POST", f"/containers/{item['Id']}/start")
|
||||
if status not in (204, 304):
|
||||
raise RuntimeError(f"failed to start image worker: HTTP {status}")
|
||||
# The 9B beta text encoder temporarily borrows the RTX 3060 from
|
||||
# Qwen3-TTS. TTS is unavailable during this exclusive GPU phase.
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools()
|
||||
stop_trellis_if_configured()
|
||||
for other in image_containers():
|
||||
if other["Id"] != item["Id"]:
|
||||
stop_container(other, timeout=20)
|
||||
start_container(item)
|
||||
else:
|
||||
# CUDA/PyTorch may not react promptly to SIGTERM after an OOM.
|
||||
# Bound recovery time and let Docker issue SIGKILL afterwards.
|
||||
stop_container(item, timeout=20)
|
||||
return {"image_worker": "running" if running else "stopped"}
|
||||
# TTS is restored by the following profile activation. Keeping it
|
||||
# stopped here lets the router verify that both GPUs really
|
||||
# released the image model before Qwen and TTS are reloaded.
|
||||
return {"image_worker": kind,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_music_worker(running: bool) -> dict:
|
||||
"""Start ACE-Step exclusively, or stop it before LLM restoration."""
|
||||
with LOCK:
|
||||
item = music_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools()
|
||||
stop_yue2_if_configured()
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"music_worker": MUSIC_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_yue2_worker(running: bool) -> dict:
|
||||
"""Start YuE2 exclusively, or stop it before another mode is loaded."""
|
||||
with LOCK:
|
||||
item = yue2_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools()
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"yue2_worker": YUE2_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_separator_worker(running: bool) -> dict:
|
||||
"""Start vocal separation exclusively, or stop it before LLM restoration."""
|
||||
with LOCK:
|
||||
item = separator_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_voice_tools()
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"separator_worker": SEPARATOR_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_voice_worker(running: bool) -> dict:
|
||||
"""Start OmniVoice exclusively, or stop it before LLM restoration."""
|
||||
with LOCK:
|
||||
item = voice_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools("voice")
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"voice_worker": VOICE_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_voice_change_worker(running: bool) -> dict:
|
||||
"""Start X-VC exclusively, or stop it before another mode is loaded."""
|
||||
with LOCK:
|
||||
item = voice_change_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools("voicechange")
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"voice_change_worker": VOICE_CHANGE_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_applio_worker(running: bool) -> dict:
|
||||
"""Start Applio exclusively, or stop it before another mode is loaded."""
|
||||
with LOCK:
|
||||
item = applio_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools("applio")
|
||||
stop_trellis_if_configured()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"applio_worker": APPLIO_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def set_trellis_worker(running: bool) -> dict:
|
||||
"""Start TRELLIS.2 exclusively, or stop it before another mode is loaded."""
|
||||
with LOCK:
|
||||
item = trellis_container()
|
||||
if running:
|
||||
for profile_item in containers().values():
|
||||
stop_container(profile_item)
|
||||
for worker in image_containers():
|
||||
stop_container(worker, timeout=20)
|
||||
stop_container(tts_container(), timeout=30)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools()
|
||||
start_container(item)
|
||||
else:
|
||||
stop_container(item, timeout=30)
|
||||
return {"trellis_worker": TRELLIS_WORKER,
|
||||
"state": "running" if running else "stopped"}
|
||||
|
||||
|
||||
def active_profile(items: dict[str, dict] | None = None) -> str | None:
|
||||
@@ -125,7 +468,14 @@ def activate(profile: str) -> dict:
|
||||
raise ValueError("profile is not allowlisted")
|
||||
with LOCK:
|
||||
# Defensive mutual exclusion even if a caller bypasses the router.
|
||||
stop_container(image_container())
|
||||
for worker in image_containers():
|
||||
stop_container(worker)
|
||||
stop_music_if_configured()
|
||||
stop_yue2_if_configured()
|
||||
stop_separator_if_configured()
|
||||
stop_voice_tools()
|
||||
stop_trellis_if_configured()
|
||||
start_container(tts_container())
|
||||
items = containers()
|
||||
missing = [name for name in ALLOWED if name not in items]
|
||||
if missing:
|
||||
@@ -189,7 +539,70 @@ class Handler(BaseHTTPRequestHandler):
|
||||
return
|
||||
try:
|
||||
items = containers()
|
||||
music = music_container() if MUSIC_WORKER else {}
|
||||
music_status = music.get("Status", "")
|
||||
music_health = ("disabled" if not MUSIC_WORKER else
|
||||
"healthy" if "(healthy)" in music_status else
|
||||
"unhealthy" if "(unhealthy)" in music_status else
|
||||
"starting" if music.get("State") == "running" else
|
||||
"stopped")
|
||||
yue2 = yue2_container() if YUE2_WORKER else {}
|
||||
yue2_status = yue2.get("Status", "")
|
||||
yue2_health = ("disabled" if not YUE2_WORKER else
|
||||
"healthy" if "(healthy)" in yue2_status else
|
||||
"unhealthy" if "(unhealthy)" in yue2_status else
|
||||
"starting" if yue2.get("State") == "running" else
|
||||
"stopped")
|
||||
separator = separator_container() if SEPARATOR_WORKER else {}
|
||||
separator_status = separator.get("Status", "")
|
||||
separator_health = ("disabled" if not SEPARATOR_WORKER else
|
||||
"healthy" if "(healthy)" in separator_status else
|
||||
"unhealthy" if "(unhealthy)" in separator_status else
|
||||
"starting" if separator.get("State") == "running" else
|
||||
"stopped")
|
||||
voice = voice_container() if VOICE_WORKER else {}
|
||||
voice_status = voice.get("Status", "")
|
||||
voice_health = ("disabled" if not VOICE_WORKER else
|
||||
"healthy" if "(healthy)" in voice_status else
|
||||
"unhealthy" if "(unhealthy)" in voice_status else
|
||||
"starting" if voice.get("State") == "running" else
|
||||
"stopped")
|
||||
voice_change = voice_change_container() if VOICE_CHANGE_WORKER else {}
|
||||
voice_change_status = voice_change.get("Status", "")
|
||||
voice_change_health = ("disabled" if not VOICE_CHANGE_WORKER else
|
||||
"healthy" if "(healthy)" in voice_change_status else
|
||||
"unhealthy" if "(unhealthy)" in voice_change_status else
|
||||
"starting" if voice_change.get("State") == "running" else
|
||||
"stopped")
|
||||
applio = applio_container() if APPLIO_WORKER else {}
|
||||
applio_status = applio.get("Status", "")
|
||||
applio_health = ("disabled" if not APPLIO_WORKER else
|
||||
"healthy" if "(healthy)" in applio_status else
|
||||
"unhealthy" if "(unhealthy)" in applio_status else
|
||||
"starting" if applio.get("State") == "running" else
|
||||
"stopped")
|
||||
trellis = trellis_container() if TRELLIS_WORKER else {}
|
||||
trellis_status = trellis.get("Status", "")
|
||||
trellis_health = ("disabled" if not TRELLIS_WORKER else
|
||||
"healthy" if "(healthy)" in trellis_status else
|
||||
"unhealthy" if "(unhealthy)" in trellis_status else
|
||||
"starting" if trellis.get("State") == "running" else
|
||||
"stopped")
|
||||
self.reply(200, {"active_profile": active_profile(items),
|
||||
"music_worker": music.get("State", "disabled"),
|
||||
"music_health": music_health,
|
||||
"yue2_worker": yue2.get("State", "disabled"),
|
||||
"yue2_health": yue2_health,
|
||||
"separator_worker": separator.get("State", "disabled"),
|
||||
"separator_health": separator_health,
|
||||
"voice_worker": voice.get("State", "disabled"),
|
||||
"voice_health": voice_health,
|
||||
"voice_change_worker": voice_change.get("State", "disabled"),
|
||||
"voice_change_health": voice_change_health,
|
||||
"applio_worker": applio.get("State", "disabled"),
|
||||
"applio_health": applio_health,
|
||||
"trellis_worker": trellis.get("State", "disabled"),
|
||||
"trellis_health": trellis_health,
|
||||
"profiles": {name: items.get(name, {}).get(
|
||||
"State", "missing") for name in ALLOWED}})
|
||||
except Exception as exc:
|
||||
@@ -207,9 +620,65 @@ class Handler(BaseHTTPRequestHandler):
|
||||
log.exception("stopping inference failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in ("/workers/image/start", "/workers/image/stop"):
|
||||
if self.path in {"/workers/music/start", "/workers/music/stop"}:
|
||||
try:
|
||||
self.reply(200, set_image_worker(self.path.endswith("/start")))
|
||||
self.reply(200, set_music_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("music worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/yue2/start", "/workers/yue2/stop"}:
|
||||
try:
|
||||
self.reply(200, set_yue2_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("YuE2 worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/separator/start", "/workers/separator/stop"}:
|
||||
try:
|
||||
self.reply(200, set_separator_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("stem separator transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/voice/start", "/workers/voice/stop"}:
|
||||
try:
|
||||
self.reply(200, set_voice_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("voice worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/voice-change/start", "/workers/voice-change/stop"}:
|
||||
try:
|
||||
self.reply(200, set_voice_change_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("voice-change worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/applio/start", "/workers/applio/stop"}:
|
||||
try:
|
||||
self.reply(200, set_applio_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("Applio worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
if self.path in {"/workers/trellis/start", "/workers/trellis/stop"}:
|
||||
try:
|
||||
self.reply(200, set_trellis_worker(self.path.endswith("/start")))
|
||||
except Exception as exc:
|
||||
log.exception("TRELLIS worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
return
|
||||
worker_paths = {
|
||||
"/workers/image/start": (IMAGE_WORKER, True),
|
||||
"/workers/image/stop": (IMAGE_WORKER, False),
|
||||
"/workers/restore/start": (RESTORE_WORKER, True),
|
||||
"/workers/restore/stop": (RESTORE_WORKER, False),
|
||||
}
|
||||
if self.path in worker_paths:
|
||||
try:
|
||||
kind, running = worker_paths[self.path]
|
||||
self.reply(200, set_image_worker(running, kind))
|
||||
except Exception as exc:
|
||||
log.exception("image worker transition failed")
|
||||
self.reply(503, {"error": str(exc)})
|
||||
|
||||
@@ -76,7 +76,17 @@ start_proxy() {
|
||||
start_proxy 22 172.30.10.1:22
|
||||
start_proxy 8081 router:8081
|
||||
start_proxy 8085 tts-gateway:8085
|
||||
start_proxy 8091 piper:8085
|
||||
start_proxy 8099 llama-dashboard:8099
|
||||
start_proxy 7861 music-ui:3000
|
||||
start_proxy 7862 music-worker:7860
|
||||
start_proxy 8007 stem-separator:8080
|
||||
start_proxy 8008 voice-studio:8008
|
||||
start_proxy 8009 xvc-studio:8009
|
||||
start_proxy 8011 applio-studio:6969
|
||||
start_proxy 8012 mikes-applio-ui:8012
|
||||
start_proxy 8013 trellis-studio:8080
|
||||
start_proxy 8014 yue2-studio:8014
|
||||
start_proxy 8202 mcp-athena-operator:8000
|
||||
start_proxy 9443 portainer:9443
|
||||
|
||||
wait $(printf '%s\n' "$proxy_pids" | awk '{print $2}')
|
||||
|
||||
@@ -20,15 +20,59 @@ HOST = os.getenv("DASHBOARD_HOST", "0.0.0.0")
|
||||
PORT = int(os.getenv("DASHBOARD_PORT", "8099"))
|
||||
ROUTER_URL = os.getenv("ROUTER_URL", "http://router:8081").rstrip("/")
|
||||
ROUTER_API_KEY = os.getenv("ROUTER_API_KEY", "")
|
||||
MUSIC_COMMUNITY_UI_URL = os.getenv(
|
||||
"MUSIC_COMMUNITY_UI_URL",
|
||||
os.getenv("MUSIC_UI_URL", "http://192.168.1.212:7861/"),
|
||||
)
|
||||
MUSIC_ORIGINAL_UI_URL = os.getenv(
|
||||
"MUSIC_ORIGINAL_UI_URL", "http://192.168.1.212:7862/"
|
||||
)
|
||||
SEPARATOR_UI_URL = os.getenv("SEPARATOR_UI_URL", "http://192.168.1.212:8007/")
|
||||
VOICE_UI_URL = os.getenv("VOICE_UI_URL", "http://192.168.1.212:8008/")
|
||||
VOICE_CHANGE_UI_URL = os.getenv("VOICE_CHANGE_UI_URL", "http://192.168.1.212:8009/")
|
||||
APPLIO_UI_URL = os.getenv("APPLIO_UI_URL", "http://192.168.1.212:8011/")
|
||||
MIKES_APPLIO_UI_URL = os.getenv(
|
||||
"MIKES_APPLIO_UI_URL", "http://192.168.1.212:8012/"
|
||||
)
|
||||
TRELLIS_UI_URL = os.getenv("TRELLIS_UI_URL", "http://192.168.1.212:8013/")
|
||||
YUE2_UI_URL = os.getenv("YUE2_UI_URL", "http://192.168.1.212:8014/")
|
||||
HOST_PROC = Path(os.getenv("HOST_PROC", "/host/proc"))
|
||||
HOST_DATA = os.getenv("HOST_DATA", "/host/data")
|
||||
HOST_MODELS = Path(os.getenv("HOST_MODELS", "/host/models"))
|
||||
BACKUP_DIR = Path(os.getenv("DASHBOARD_BACKUP_DIR", "/host/data/emergency-backups"))
|
||||
STARTED = time.time()
|
||||
HISTORY_DB = Path(os.getenv("DASHBOARD_HISTORY_DB", "/var/lib/llama-dashboard/history.sqlite3"))
|
||||
HISTORY_INTERVAL = max(5, int(os.getenv("DASHBOARD_HISTORY_INTERVAL", "15")))
|
||||
DETAIL_RETENTION_DAYS = max(1, int(os.getenv("DASHBOARD_DETAIL_RETENTION_DAYS", "21")))
|
||||
|
||||
|
||||
def backup_inventory() -> list[dict[str, Any]]:
|
||||
try:
|
||||
candidates = sorted(
|
||||
BACKUP_DIR.glob("athena-portable-*.tar.zst.age"),
|
||||
key=lambda item: item.stat().st_mtime,
|
||||
reverse=True,
|
||||
)[:5]
|
||||
except OSError:
|
||||
return []
|
||||
result = []
|
||||
for path in candidates:
|
||||
try:
|
||||
stat = path.stat()
|
||||
checksum_file = path.with_name(path.name + ".sha256")
|
||||
checksum = _read_text(checksum_file).split(maxsplit=1)[0]
|
||||
result.append({
|
||||
"name": path.name,
|
||||
"size": stat.st_size,
|
||||
"modified": stat.st_mtime,
|
||||
"sha256": checksum if len(checksum) == 64 else None,
|
||||
"download_url": "/api/backups/download/" + urllib.parse.quote(path.name),
|
||||
})
|
||||
except OSError:
|
||||
continue
|
||||
return result
|
||||
|
||||
|
||||
def _number(value: str) -> int | float | None:
|
||||
value = value.strip()
|
||||
if not value or value.lower() in {"n/a", "[n/a]", "not supported"}:
|
||||
@@ -268,6 +312,28 @@ def router_status() -> tuple[dict[str, Any], str | None]:
|
||||
return {}, str(exc)
|
||||
|
||||
|
||||
def change_mode(mode: str) -> tuple[int, dict[str, Any]]:
|
||||
if mode not in {"llm", "music", "yue2", "separation", "voice",
|
||||
"voicechange", "applio", "trellis"}:
|
||||
return 400, {"error": "invalid mode"}
|
||||
headers = {"Accept": "application/json", "Content-Type": "application/json"}
|
||||
if ROUTER_API_KEY:
|
||||
headers["Authorization"] = f"Bearer {ROUTER_API_KEY}"
|
||||
request = urllib.request.Request(
|
||||
f"{ROUTER_URL}/mode", data=json.dumps({"mode": mode}).encode(),
|
||||
headers=headers, method="POST")
|
||||
try:
|
||||
with urllib.request.urlopen(request, timeout=15) as response:
|
||||
return response.status, json.load(response)
|
||||
except urllib.error.HTTPError as exc:
|
||||
try:
|
||||
return exc.code, json.loads(exc.read())
|
||||
except (ValueError, json.JSONDecodeError):
|
||||
return exc.code, {"error": str(exc)}
|
||||
except (OSError, urllib.error.URLError) as exc:
|
||||
return 503, {"error": str(exc)}
|
||||
|
||||
|
||||
_MODEL_LOCK = threading.Lock()
|
||||
_MODEL_AT = 0.0
|
||||
_MODEL_CACHE: tuple[list[dict[str, Any]], dict[str, Any]] = ([], {"count": 0, "total_size": 0})
|
||||
@@ -602,9 +668,12 @@ HTML = r'''<!doctype html>
|
||||
.span4 .metrics{grid-template-columns:repeat(2,1fr)}
|
||||
.history-controls{display:flex;flex-wrap:wrap;gap:7px;margin:10px 0 14px}.history-controls button{border:1px solid var(--line);background:#09111b;color:var(--muted);padding:6px 10px;border-radius:8px;cursor:pointer}.history-controls button.active{color:var(--cyan);border-color:var(--cyan)}.chart-legend{display:flex;flex-wrap:wrap;gap:8px;margin:2px 0 10px}.chart-legend button{border:1px solid var(--series);background:#09111b;color:var(--text);padding:6px 10px;border-radius:8px;cursor:pointer}.chart-legend button::before{content:'';display:inline-block;width:10px;height:3px;background:var(--series);margin:0 7px 3px 0}.chart-legend button.off{opacity:.4;text-decoration:line-through}.chart{width:100%;height:250px;display:block}.token-total{font-size:24px;font-weight:750;margin-top:5px}.history-note{color:var(--muted);font-size:11px;margin-top:8px}
|
||||
.usage-list{display:grid;gap:13px;margin-top:8px}.usage-head{display:flex;justify-content:space-between;gap:14px;align-items:baseline}.usage-head b{font-size:16px}.usage-head span{color:var(--muted)}.usage-meta{display:flex;justify-content:space-between;gap:12px;color:var(--muted);font-size:11px;margin-top:5px}
|
||||
.mode-row{display:flex;align-items:center;justify-content:space-between;gap:18px;flex-wrap:wrap}.mode-buttons,.mode-buttons span{display:flex;gap:9px;flex-wrap:wrap}.mode-buttons button,.mode-buttons a{border:1px solid var(--line);background:#09111b;color:var(--text);padding:9px 14px;border-radius:9px;cursor:pointer;text-decoration:none;font:inherit}.mode-buttons button.active{border-color:var(--cyan);color:var(--cyan);box-shadow:inset 0 0 0 1px #45d7ff33}.mode-buttons button:disabled{opacity:.45;cursor:wait}.mode-buttons span[hidden]{display:none}.mode-buttons a.stable{border-color:#66e3a466;color:var(--green)}.mode-buttons a.experimental{border-color:#ffc65c66;color:var(--amber)}.mode-error{color:var(--red)}
|
||||
.download{display:inline-block;border:1px solid #66e3a466;color:var(--green);padding:6px 10px;border-radius:8px;text-decoration:none}.hash{font:11px ui-monospace,SFMono-Regular,monospace;color:var(--muted);word-break:break-all}
|
||||
</style></head><body><main>
|
||||
<div class="top"><div><div class="eyebrow">Mike AI · Live Telemetry</div><h1>Athena llama.cpp Dashboard</h1></div><div class="live"><span class="dot" id="dot"></span><span id="updated">verbinde …</span></div></div>
|
||||
<section class="grid">
|
||||
<article class="card span12"><div class="mode-row"><div><div class="label">Athena Betriebsmodus</div><div class="value" id="operatingMode">–</div><div class="sub" id="modeStatus">Status wird geladen …</div></div><div class="mode-buttons"><button id="llmMode" onclick="setMode('llm')">LLM-Betrieb</button><button id="musicMode" onclick="setMode('music')">ACE-Step Studio</button><button id="yue2Mode" onclick="setMode('yue2')">YuE2 Studio</button><button id="separationMode" onclick="setMode('separation')">Audio trennen</button><button id="voiceMode" onclick="setMode('voice')">Voice Studio</button><button id="voiceChangeMode" onclick="setMode('voicechange')">X-VC</button><button id="applioMode" onclick="setMode('applio')">Applio / RVC · Modell nötig</button><button id="trellisMode" onclick="setMode('trellis')">3D Studio</button><span id="musicOpen" hidden><a class="stable" href="__MUSIC_ORIGINAL_UI_URL__" target="_blank" rel="noopener">Original UI · stabil</a><a class="experimental" href="__MUSIC_COMMUNITY_UI_URL__" target="_blank" rel="noopener">Community UI · experimentell</a></span><span id="yue2Open" hidden><a class="stable" href="__YUE2_UI_URL__" target="_blank" rel="noopener">YuE2 Studio öffnen</a></span><span id="separatorOpen" hidden><a class="stable" href="__SEPARATOR_UI_URL__" target="_blank" rel="noopener">Separator öffnen</a></span><span id="voiceOpen" hidden><a class="stable" href="__VOICE_UI_URL__" target="_blank" rel="noopener">Voice Studio öffnen</a></span><span id="voiceChangeOpen" hidden><a class="experimental" href="__VOICE_CHANGE_UI_URL__" target="_blank" rel="noopener">X-VC öffnen</a></span><span id="applioOpen" hidden><a class="stable" href="__APPLIO_UI_URL__" target="_blank" rel="noopener">Original Applio UI</a><a class="stable" href="__MIKES_APPLIO_UI_URL__" target="_blank" rel="noopener">Mikes Applio UI</a></span><span id="trellisOpen" hidden><a class="stable" href="__TRELLIS_UI_URL__" target="_blank" rel="noopener">3D Studio öffnen</a></span></div></div></article>
|
||||
<article class="card span3"><div class="label">Aktives Profil</div><div class="value" id="profile">–</div><div class="sub" id="profileSub">Router wird abgefragt</div></article>
|
||||
<article class="card span3"><div class="label">Modell</div><div class="value" id="model">–</div><div class="sub" id="modelSub">–</div></article>
|
||||
<article class="card span3"><div class="label">CPU</div><div class="value" id="cpu">–</div><div class="bar"><div class="fill" id="cpuBar"></div></div><div class="sub" id="load">–</div></article>
|
||||
@@ -636,14 +705,28 @@ HTML = r'''<!doctype html>
|
||||
<article class="card span6"><div class="label">Ereignisse seit Dashboard-Start</div><div id="events"><div class="sub">Noch keine Zustandsänderung</div></div></article>
|
||||
<article class="card span12"><div class="label">llama.cpp Laufzeitkonfiguration</div><div class="metrics" id="runtime"><div class="metric"><b>–</b><span>wird gelesen</span></div></div></article>
|
||||
<article class="card span12"><div class="row"><div><div class="label">Verfügbare GGUF-Dateien</div><div class="sub" id="modelSummary">–</div></div></div><div class="scroll"><table><thead><tr><th>Datei</th><th>Pfad</th><th>Größe</th><th>Geändert</th></tr></thead><tbody id="modelFiles"><tr><td colspan="4">–</td></tr></tbody></table></div></article>
|
||||
<div class="section-title">Notfall-Backups · herunterladen</div>
|
||||
<article class="card span12"><div class="row"><div><div class="label">Verschlüsselte portable Sicherungen</div><div class="sub">Unersetzliche Daten ohne erneut ladbare Modellgewichte · maximal fünf Generationen</div></div></div><div class="scroll"><table><thead><tr><th>Erstellt</th><th>Größe</th><th>SHA256</th><th></th></tr></thead><tbody id="backupFiles"><tr><td colspan="4">Backups werden geladen …</td></tr></tbody></table></div><div class="sub" id="backupNote">Zum Wiederherstellen wird der separat verwahrte Age-Schlüssel benötigt.</div></article>
|
||||
<article class="card span12 error" id="errors" hidden></article>
|
||||
</section><div class="footer">Aktualisierung jede Sekunde · Nur lesende Telemetrie</div>
|
||||
</section><div class="footer">Aktualisierung jede Sekunde · Umschaltung über Athena Router</div>
|
||||
</main><script>
|
||||
const $=id=>document.getElementById(id); const pct=n=>n==null?'–':`${n.toFixed?.(1)??n}%`; const gib=b=>b?`${(b/1073741824).toFixed(1)} GiB`:'–'; const dur=s=>{if(s==null)return'–';let d=Math.floor(s/86400),h=Math.floor(s%86400/3600),m=Math.floor(s%3600/60);return d?`${d}d ${h}h`:`${h}h ${m}m`};
|
||||
function gpuCard(g){let total=g.memory_total_mib||0,used=g.memory_used_mib||0,p=total?used/total*100:0,load=Math.max(0,Math.min(100,g.gpu_percent||0));return `<article class="card span6"><div class="gpu-title"><div><div class="label">GPU ${g.index}</div><div class="value">${g.name}</div></div><span class="badge">${g.pstate||'–'}</span></div><div class="metrics"><div class="metric"><b>${pct(g.gpu_percent)}</b><span>GPU-Kern</span></div><div class="metric"><b>${(used/1024).toFixed(1)} / ${(total/1024).toFixed(1)} GiB</b><span>VRAM</span></div><div class="metric"><b>${g.temperature_c??'–'} °C</b><span>Temperatur</span></div><div class="metric"><b>${g.power_w??'–'} / ${g.power_limit_w??'–'} W</b><span>Leistung</span></div><div class="metric"><b>${g.graphics_clock_mhz??'–'} MHz</b><span>Grafiktakt</span></div><div class="metric"><b>${g.memory_clock_mhz??'–'} MHz</b><span>Speichertakt</span></div><div class="metric"><b>${pct(g.memory_controller_percent)}</b><span>Memory Controller</span></div><div class="metric"><b>${pct(g.fan_percent)}</b><span>Lüfter</span></div></div><div class="bar-label"><span>GPU-Auslastung</span><span>${load.toFixed(1)} %</span></div><div class="bar"><div class="fill gpu-load" style="width:${load}%"></div></div><div class="bar-label"><span>VRAM-Belegung</span><span>${p.toFixed(1)} %</span></div><div class="bar"><div class="fill" style="width:${Math.min(100,p)}%"></div></div><div class="sub">${(g.memory_free_mib/1024).toFixed(1)} GiB VRAM frei</div></article>`}
|
||||
const imagePhaseLabel=p=>({"stopping-qwen":"Qwen wird entladen","loading-image":"Bildmodell wird geladen","generating":"Bild wird generiert","unloading-image":"Bildmodell wird entladen","restoring-qwen":"Qwen wird wiederhergestellt"}[p]||p||'bereit');
|
||||
async function refresh(){try{let r=await fetch('/api/status',{cache:'no-store'});if(!r.ok)throw Error(`HTTP ${r.status}`);let d=await r.json(),c=d.cpu||{},m=c.memory||{},rt=d.router||{},up=rt.upstream||{},q=rt.qwen||{},lr=d.llama_runtime||{},img=rt.image||{},imageActive=img.phase&&img.phase!=='idle';$('profile').textContent=imageActive?'Bildgenerierung':(rt.current_profile||'nicht geladen');$('profileSub').textContent=imageActive?imagePhaseLabel(img.phase):(rt.switching?`Wechsel zu ${rt.switching}`:`Kontext: ${up.ctx?up.ctx.toLocaleString('de-DE'):'–'} Token`);$('model').textContent=imageActive?(img.model||'Bildmodell'):(up.model||'–');$('modelSub').textContent=imageActive?`${img.model_loaded?'geladen':'wird vorbereitet'} · Worker ${img.worker||'–'}`:(lr.model_file|| (up.reachable?'llama.cpp erreichbar':'llama.cpp nicht erreichbar'));$('cpu').textContent=pct(c.usage_percent);$('cpuBar').style.width=`${c.usage_percent||0}%`;$('load').textContent=`${c.logical_cpus||'–'} Threads · Load ${(c.load||[]).join(' / ')}`;let rp=m.total?m.used/m.total*100:0;$('ram').textContent=pct(rp);$('ramBar').style.width=`${rp}%`;$('ramSub').textContent=`${gib(m.used)} / ${gib(m.total)}`;$('gpuCards').innerHTML=(d.gpus||[]).map(gpuCard).join('')||'<article class="card span12 error">Keine GPU-Daten verfügbar</article>';$('availability').textContent=imageActive?imagePhaseLabel(img.phase):(q.available?'bereit':'nicht bereit');$('availability').className=`value status ${(imageActive||q.available)?'':'bad'}`;$('activeChats').textContent=q.active_chats??'–';$('routerUptime').textContent=dur(rt.uptime_seconds);$('switching').textContent=imageActive?imagePhaseLabel(img.phase):(rt.switching||'nein');let disk=c.disk_data||{},dp=disk.total?disk.used/disk.total*100:null;$('dataDisk').textContent=pct(dp);$('processes').innerHTML=(d.gpu_processes||[]).map(p=>`<tr><td>${(d.gpus||[]).find(g=>g.uuid===p.gpu_uuid)?.index??'–'}</td><td>${p.name}</td><td>${p.pid}</td><td>${p.memory_mib??'–'} MiB</td></tr>`).join('')||'<tr><td colspan="4">Keine Compute-Prozesse gemeldet</td></tr>';let runtime=[['Modell-Datei',lr.model_file],['PID',lr.pid],['Kontext',lr.context_size?lr.context_size.toLocaleString('de-DE'):'–'],['Batch / µBatch',`${lr.batch_size??'–'} / ${lr.ubatch_size??'–'}`],['Parallel',lr.parallel],['Threads',`${lr.threads??'–'} / ${lr.threads_batch??'–'}`],['Geräte',lr.device],['Tensor-Split',lr.tensor_split],['KV-Cache',`${lr.cache_k??'–'} / ${lr.cache_v??'–'}`],['Flash Attention',lr.flash_attention?'an':'aus'],['Prompt-Cache',lr.prompt_cache?'an':'aus'],['MTP Draft',lr.mtp_draft_tokens]];$('runtime').innerHTML=runtime.map(([k,v])=>`<div class="metric"><b>${v??'–'}</b><span>${k}</span></div>`).join('');let es=Object.entries(d.errors||{}).filter(([,v])=>v);$('errors').hidden=!es.length;$('errors').textContent=es.map(([k,v])=>`${k}: ${v}`).join('\n');$('updated').textContent=`Live · ${new Date(d.timestamp*1000).toLocaleTimeString('de-DE')}`;$('dot').style.background='var(--green)'}catch(e){$('updated').textContent=`Verbindung gestört: ${e.message}`;$('dot').style.background='var(--red)'}}refresh();setInterval(refresh,1000);
|
||||
</script><script src="/full.js"></script><script src="/history.js"></script></body></html>'''
|
||||
let modeBusy=false;
|
||||
async function setMode(mode){if(modeBusy)return;modeBusy=true;for(const id of ['llmMode','musicMode','yue2Mode','separationMode','voiceMode','voiceChangeMode','applioMode','trellisMode'])$(id).disabled=true;$('modeStatus').textContent='Umschaltung angefordert …';try{let r=await fetch('/api/mode',{method:'POST',headers:{'Content-Type':'application/json'},body:JSON.stringify({mode})});let d=await r.json();if(!r.ok)throw Error(d?.error?.message||d?.error||`HTTP ${r.status}`);$('modeStatus').textContent='Umschaltung läuft …'}catch(e){$('modeStatus').textContent=e.message;$('modeStatus').classList.add('mode-error')}finally{modeBusy=false;setTimeout(refresh,250)}}
|
||||
async function refresh(){try{let r=await fetch('/api/status',{cache:'no-store'});if(!r.ok)throw Error(`HTTP ${r.status}`);let d=await r.json(),c=d.cpu||{},m=c.memory||{},rt=d.router||{},up=rt.upstream||{},q=rt.qwen||{},lr=d.llama_runtime||{},img=rt.image||{},imageActive=img.phase&&img.phase!=='idle';let md=rt.mode||{},switchingMode=md.phase&&md.phase!=='ready',modeName=({llm:'LLM-Betrieb',music:'ACE-Step Studio',yue2:'YuE2 Studio',separation:'Stimmtrennung',voice:'Voice Studio',voicechange:'X-VC Voice Changer',applio:'Applio / RVC',trellis:'3D Studio'})[md.active]||'Unbekannt';$('operatingMode').textContent=modeName;$('modeStatus').textContent=switchingMode?`Umschaltung: ${md.phase}`:(md.last_error||`ACE-Step: ${md.music_worker||'–'} · YuE2: ${md.yue2_worker||'–'} · Separator: ${md.separator_worker||'–'} · Voice: ${md.voice_worker||'–'} · 3D: ${md.trellis_worker||'–'}${md.return_profile?` · Rückkehr zu ${md.return_profile}`:''}`);$('modeStatus').classList.toggle('mode-error',!!md.last_error);$('llmMode').classList.toggle('active',md.active==='llm');$('musicMode').classList.toggle('active',md.active==='music');$('yue2Mode').classList.toggle('active',md.active==='yue2');$('separationMode').classList.toggle('active',md.active==='separation');$('voiceMode').classList.toggle('active',md.active==='voice');$('voiceChangeMode').classList.toggle('active',md.active==='voicechange');$('applioMode').classList.toggle('active',md.active==='applio');$('trellisMode').classList.toggle('active',md.active==='trellis');let modeControlsBusy=modeBusy||switchingMode||!md.enabled;for(const id of ['llmMode','musicMode','yue2Mode','separationMode','voiceMode','voiceChangeMode','applioMode','trellisMode'])$(id).disabled=modeControlsBusy;$('musicOpen').hidden=md.active!=='music';$('yue2Open').hidden=md.active!=='yue2';$('separatorOpen').hidden=md.active!=='separation';$('voiceOpen').hidden=md.active!=='voice';$('voiceChangeOpen').hidden=md.active!=='voicechange';$('applioOpen').hidden=md.active!=='applio';$('trellisOpen').hidden=md.active!=='trellis';$('profile').textContent=imageActive?'Bildgenerierung':(rt.current_profile||'nicht geladen');$('profileSub').textContent=imageActive?imagePhaseLabel(img.phase):(rt.switching?`Wechsel zu ${rt.switching}`:`Kontext: ${up.ctx?up.ctx.toLocaleString('de-DE'):'–'} Token`);$('model').textContent=imageActive?(img.model||'Bildmodell'):(up.model||'–');$('modelSub').textContent=imageActive?`${img.model_loaded?'geladen':'wird vorbereitet'} · Worker ${img.worker||'–'}`:(lr.model_file|| (up.reachable?'llama.cpp erreichbar':'llama.cpp nicht erreichbar'));$('cpu').textContent=pct(c.usage_percent);$('cpuBar').style.width=`${c.usage_percent||0}%`;$('load').textContent=`${c.logical_cpus||'–'} Threads · Load ${(c.load||[]).join(' / ')}`;let rp=m.total?m.used/m.total*100:0;$('ram').textContent=pct(rp);$('ramBar').style.width=`${rp}%`;$('ramSub').textContent=`${gib(m.used)} / ${gib(m.total)}`;$('gpuCards').innerHTML=(d.gpus||[]).map(gpuCard).join('')||'<article class="card span12 error">Keine GPU-Daten verfügbar</article>';$('availability').textContent=imageActive?imagePhaseLabel(img.phase):(q.available?'bereit':'nicht bereit');$('availability').className=`value status ${(imageActive||q.available)?'':'bad'}`;$('activeChats').textContent=q.active_chats??'–';$('routerUptime').textContent=dur(rt.uptime_seconds);$('switching').textContent=imageActive?imagePhaseLabel(img.phase):(rt.switching||'nein');let disk=c.disk_data||{},dp=disk.total?disk.used/disk.total*100:null;$('dataDisk').textContent=pct(dp);$('processes').innerHTML=(d.gpu_processes||[]).map(p=>`<tr><td>${(d.gpus||[]).find(g=>g.uuid===p.gpu_uuid)?.index??'–'}</td><td>${p.name}</td><td>${p.pid}</td><td>${p.memory_mib??'–'} MiB</td></tr>`).join('')||'<tr><td colspan="4">Keine Compute-Prozesse gemeldet</td></tr>';let runtime=[['Modell-Datei',lr.model_file],['PID',lr.pid],['Kontext',lr.context_size?lr.context_size.toLocaleString('de-DE'):'–'],['Batch / µBatch',`${lr.batch_size??'–'} / ${lr.ubatch_size??'–'}`],['Parallel',lr.parallel],['Threads',`${lr.threads??'–'} / ${lr.threads_batch??'–'}`],['Geräte',lr.device],['Tensor-Split',lr.tensor_split],['KV-Cache',`${lr.cache_k??'–'} / ${lr.cache_v??'–'}`],['Flash Attention',lr.flash_attention?'an':'aus'],['Prompt-Cache',lr.prompt_cache?'an':'aus'],['MTP Draft',lr.mtp_draft_tokens]];$('runtime').innerHTML=runtime.map(([k,v])=>`<div class="metric"><b>${v??'–'}</b><span>${k}</span></div>`).join('');let es=Object.entries(d.errors||{}).filter(([,v])=>v);$('errors').hidden=!es.length;$('errors').textContent=es.map(([k,v])=>`${k}: ${v}`).join('\n');$('updated').textContent=`Live · ${new Date(d.timestamp*1000).toLocaleTimeString('de-DE')}`;$('dot').style.background='var(--green)'}catch(e){$('updated').textContent=`Verbindung gestört: ${e.message}`;$('dot').style.background='var(--red)'}}refresh();setInterval(refresh,1000);
|
||||
async function refreshBackups(){try{let r=await fetch('/api/backups',{cache:'no-store'});if(!r.ok)throw Error(`HTTP ${r.status}`);let d=await r.json(),rows=d.backups||[];$('backupFiles').innerHTML=rows.map(b=>`<tr><td>${new Date(b.modified*1000).toLocaleString('de-DE')}</td><td>${gib(b.size)}</td><td class="hash">${b.sha256||'Prüfsumme fehlt'}</td><td><a class="download" href="${b.download_url}">Herunterladen</a></td></tr>`).join('')||'<tr><td colspan="4">Noch kein portables Backup vorhanden</td></tr>';$('backupNote').textContent=rows.length?`${rows.length} von maximal 5 Generationen · verschlüsselt mit Age`:'Der erste Lauf startet spätestens fünf Stunden nach Aktivierung.'}catch(e){$('backupNote').textContent=`Backup-Liste nicht verfügbar: ${e.message}`}}refreshBackups();setInterval(refreshBackups,60000);
|
||||
</script><script src="/full.js"></script><script src="/history.js"></script></body></html>'''.replace(
|
||||
"__MUSIC_ORIGINAL_UI_URL__", MUSIC_ORIGINAL_UI_URL
|
||||
).replace("__MUSIC_COMMUNITY_UI_URL__", MUSIC_COMMUNITY_UI_URL
|
||||
).replace("__SEPARATOR_UI_URL__", SEPARATOR_UI_URL
|
||||
).replace("__VOICE_UI_URL__", VOICE_UI_URL
|
||||
).replace("__VOICE_CHANGE_UI_URL__", VOICE_CHANGE_UI_URL
|
||||
).replace("__APPLIO_UI_URL__", APPLIO_UI_URL
|
||||
).replace("__MIKES_APPLIO_UI_URL__", MIKES_APPLIO_UI_URL).replace(
|
||||
"__TRELLIS_UI_URL__", TRELLIS_UI_URL
|
||||
).replace("__YUE2_UI_URL__", YUE2_UI_URL)
|
||||
|
||||
|
||||
FULL_JS = r'''
|
||||
@@ -764,6 +847,62 @@ class Handler(BaseHTTPRequestHandler):
|
||||
self.end_headers()
|
||||
self.wfile.write(body)
|
||||
|
||||
def _send_backup(self, name: str) -> None:
|
||||
# Generated names are deliberately strict; never expose an arbitrary
|
||||
# host path through the dashboard.
|
||||
if not name.startswith("athena-portable-") or not name.endswith(".tar.zst.age"):
|
||||
self._send(404, b'{"error":"not found"}', "application/json")
|
||||
return
|
||||
if Path(name).name != name:
|
||||
self._send(404, b'{"error":"not found"}', "application/json")
|
||||
return
|
||||
path = BACKUP_DIR / name
|
||||
try:
|
||||
size = path.stat().st_size
|
||||
except OSError:
|
||||
self._send(404, b'{"error":"not found"}', "application/json")
|
||||
return
|
||||
|
||||
start, end = 0, size - 1
|
||||
status = 200
|
||||
range_header = self.headers.get("Range", "")
|
||||
if range_header:
|
||||
try:
|
||||
unit, raw = range_header.split("=", 1)
|
||||
first, last = raw.split("-", 1)
|
||||
if unit != "bytes" or "," in raw or not first:
|
||||
raise ValueError
|
||||
start = int(first)
|
||||
end = min(size - 1, int(last)) if last else size - 1
|
||||
if start < 0 or start > end or start >= size:
|
||||
raise ValueError
|
||||
status = 206
|
||||
except ValueError:
|
||||
self.send_response(416)
|
||||
self.send_header("Content-Range", f"bytes */{size}")
|
||||
self.end_headers()
|
||||
return
|
||||
|
||||
self.send_response(status)
|
||||
self.send_header("Content-Type", "application/octet-stream")
|
||||
self.send_header("Content-Disposition", f'attachment; filename="{name}"')
|
||||
self.send_header("Accept-Ranges", "bytes")
|
||||
self.send_header("Content-Length", str(end - start + 1))
|
||||
if status == 206:
|
||||
self.send_header("Content-Range", f"bytes {start}-{end}/{size}")
|
||||
self.send_header("Cache-Control", "no-store")
|
||||
self.send_header("X-Content-Type-Options", "nosniff")
|
||||
self.end_headers()
|
||||
remaining = end - start + 1
|
||||
with path.open("rb") as source:
|
||||
source.seek(start)
|
||||
while remaining:
|
||||
chunk = source.read(min(1024 * 1024, remaining))
|
||||
if not chunk:
|
||||
break
|
||||
self.wfile.write(chunk)
|
||||
remaining -= len(chunk)
|
||||
|
||||
def do_GET(self) -> None:
|
||||
path = self.path.split("?", 1)[0]
|
||||
if path == "/":
|
||||
@@ -782,9 +921,35 @@ class Handler(BaseHTTPRequestHandler):
|
||||
range_name = query.get("range", ["24h"])[0]
|
||||
body = json.dumps(HISTORY.query(range_name), ensure_ascii=False, separators=(",", ":")).encode()
|
||||
self._send(200, body, "application/json; charset=utf-8")
|
||||
elif path == "/api/backups":
|
||||
body = json.dumps({"backups": backup_inventory()}, ensure_ascii=False,
|
||||
separators=(",", ":")).encode()
|
||||
self._send(200, body, "application/json; charset=utf-8")
|
||||
elif path.startswith("/api/backups/download/"):
|
||||
name = urllib.parse.unquote(path.removeprefix("/api/backups/download/"))
|
||||
self._send_backup(name)
|
||||
else:
|
||||
self._send(404, b'{"error":"not found"}', "application/json")
|
||||
|
||||
def do_POST(self) -> None:
|
||||
path = self.path.split("?", 1)[0]
|
||||
if path != "/api/mode":
|
||||
self._send(404, b'{"error":"not found"}', "application/json")
|
||||
return
|
||||
try:
|
||||
length = int(self.headers.get("Content-Length", "0"))
|
||||
if length <= 0 or length > 1024:
|
||||
raise ValueError("invalid body size")
|
||||
payload = json.loads(self.rfile.read(length))
|
||||
mode = payload.get("mode") if isinstance(payload, dict) else None
|
||||
except (ValueError, json.JSONDecodeError):
|
||||
self._send(400, b'{"error":"invalid request"}', "application/json")
|
||||
return
|
||||
status, response = change_mode(mode)
|
||||
body = json.dumps(response, ensure_ascii=False,
|
||||
separators=(",", ":")).encode()
|
||||
self._send(status, body, "application/json; charset=utf-8")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
threading.Thread(target=history_collector, name="history-collector", daemon=True).start()
|
||||
|
||||
+645
-40
@@ -2,31 +2,30 @@
|
||||
"""AI Profile Router – OpenAI-kompatibler Proxy vor llama.cpp.
|
||||
|
||||
Leitet OpenAI-kompatible Requests transparent an den lokalen llama.cpp-Server
|
||||
weiter (Streaming, Tool Calls, JSON) und schaltet zwischen sechs festen
|
||||
weiter (Streaming, Tool Calls, JSON) und schaltet zwischen fünf festen
|
||||
Profilen um:
|
||||
|
||||
Profil Kontext
|
||||
------ --------
|
||||
fast 76800
|
||||
medium 160000
|
||||
beta1 192000
|
||||
large 192000
|
||||
ultra 262144
|
||||
uncensored 80000
|
||||
|
||||
Virtuelle Modelle: qwen-fast, qwen-medium, qwen-beta-1, qwen-large,
|
||||
Virtuelle Modelle: qwen-fast, qwen-medium, qwen-large,
|
||||
qwen-ultra, qwen-uncensored
|
||||
Kommandos: POST /fast, /medium, /beta1, /large, /ultra,
|
||||
Kommandos: POST /fast, /medium, /large, /ultra,
|
||||
/uncensored
|
||||
GET /status (Zustand)
|
||||
|
||||
Bildgenerierung und Editing (FLUX.2-klein-4B):
|
||||
Bildgenerierung und Editing (FLUX.2 Klein 9B FP8 beta):
|
||||
POST /v1/images/generations (OpenAI-kompatibel)
|
||||
POST /v1/images/edits (lokal, Referenzbilder)
|
||||
GET /images (Liste)
|
||||
GET /images/<datei> (PNG-Download)
|
||||
|
||||
Sprachausgabe (XTTS-v2, multilingual, CPU-only):
|
||||
Sprachausgabe (Qwen3-TTS auf RTX 3060):
|
||||
POST /v1/audio/speech (OpenAI-kompatibel)
|
||||
GET /v1/audio/voices (verfügbare Stimmen)
|
||||
|
||||
@@ -40,7 +39,8 @@ Der Router leitet /v1/audio/speech und /v1/audio/transcriptions
|
||||
per HTTP an die Worker weiter.
|
||||
|
||||
Der Router agiert als Modell-Orchestrator: vor der Generierung wird
|
||||
llama.cpp gestoppt, der Bild-Worker lädt FLUX.2, generiert/bearbeitet und entlädt
|
||||
llama.cpp und Qwen3-TTS gestoppt, der Bild-Worker lädt FLUX.2 und den
|
||||
Text-Encoder auf getrennte GPUs, generiert/bearbeitet und entlädt
|
||||
das Modell wieder; danach wird das vorherige Qwen-Profil wiederher-
|
||||
gestellt und erst dann geantwortet (try/finally – Qwen wird auch bei
|
||||
Fehlgeschlagener Generierung wiederhergestellt).
|
||||
@@ -105,6 +105,15 @@ PROFILE_DIR = os.environ.get(
|
||||
PROFILE_CONTROL_URL = os.environ.get("PROFILE_CONTROL_URL", "").rstrip("/")
|
||||
PROFILE_CONTROL_TOKEN_FILE = os.environ.get(
|
||||
"PROFILE_CONTROL_TOKEN_FILE", "/run/secrets/controller-token")
|
||||
ENABLE_MUSIC_MODE = os.environ.get(
|
||||
"ENABLE_MUSIC_MODE", "false").lower() in {"1", "true", "yes"}
|
||||
MUSIC_START_TIMEOUT = float(os.environ.get("MUSIC_START_TIMEOUT", "600"))
|
||||
YUE2_START_TIMEOUT = float(os.environ.get("YUE2_START_TIMEOUT", "600"))
|
||||
SEPARATOR_START_TIMEOUT = float(os.environ.get("SEPARATOR_START_TIMEOUT", "600"))
|
||||
VOICE_START_TIMEOUT = float(os.environ.get("VOICE_START_TIMEOUT", "600"))
|
||||
VOICE_CHANGE_START_TIMEOUT = float(os.environ.get("VOICE_CHANGE_START_TIMEOUT", "600"))
|
||||
APPLIO_START_TIMEOUT = float(os.environ.get("APPLIO_START_TIMEOUT", "900"))
|
||||
TRELLIS_START_TIMEOUT = float(os.environ.get("TRELLIS_START_TIMEOUT", "900"))
|
||||
|
||||
# Optional worker APIs. The clean Docker baseline deliberately ships only
|
||||
# text/multimodal chat; absent workers must fail explicitly instead of trying
|
||||
@@ -126,7 +135,7 @@ DEFAULT_REASONING_EFFORT = os.environ.get(
|
||||
GLOBAL_SYSTEM_POLICY_FILE = os.environ.get(
|
||||
"GLOBAL_SYSTEM_POLICY_FILE", "").strip()
|
||||
|
||||
# --- Bildgenerierung und Referenzbild-Bearbeitung (FLUX.2 Klein 4B) ---
|
||||
# --- Bildgenerierung und Referenzbild-Bearbeitung (FLUX.2 Klein 9B FP8) ---
|
||||
LLAMA_SERVICE = os.environ.get("LLAMA_SERVICE", "mike-ai-llama-ui.service")
|
||||
SYSTEMCTL_BIN = os.environ.get("SYSTEMCTL_BIN", "systemctl")
|
||||
IMAGE_WORKER = os.environ.get(
|
||||
@@ -135,7 +144,8 @@ IMAGE_PYTHON = os.environ.get(
|
||||
"IMAGE_PYTHON", "/opt/mike-ai/ai-profile-router/venv/bin/python")
|
||||
IMAGE_WORKER_URL = os.environ.get("IMAGE_WORKER_URL", "").rstrip("/")
|
||||
IMAGE_WORKER_TOKEN = os.environ.get("IMAGE_WORKER_TOKEN", "").strip()
|
||||
IMAGE_MODEL_NAME = os.environ.get("IMAGE_MODEL_NAME", "FLUX.2-klein-4B")
|
||||
IMAGE_MODEL_NAME = os.environ.get(
|
||||
"IMAGE_MODEL_NAME", "FLUX.2-klein-9B-fp8-beta")
|
||||
IMAGE_DIR = os.environ.get(
|
||||
"IMAGE_DIR", "/opt/mike-ai/ai-profile-router/images")
|
||||
IMAGE_WORKER_LOG = os.environ.get(
|
||||
@@ -163,20 +173,20 @@ IMAGE_SIZES = {
|
||||
"1920x1088": (1920, 1088),
|
||||
"1088x1920": (1088, 1920),
|
||||
}
|
||||
# Das destillierte FLUX.2-klein-4B ist auf vier Schritte ausgelegt.
|
||||
# Das destillierte FLUX.2 Klein 9B ist auf vier Schritte ausgelegt.
|
||||
IMAGE_QUALITY = {"standard": 4, "high": 4}
|
||||
IMAGE_DEFAULT_QUALITY = "standard"
|
||||
IMAGE_MAX_N = 4
|
||||
|
||||
# --- Sprachausgabe (austauschbarer interner TTS-Worker, CPU-only) ---
|
||||
# --- Sprachausgabe (Qwen3-TTS über das interne Normalisierungs-Gateway) ---
|
||||
TTS_WORKER_URL = os.environ.get("TTS_WORKER_URL", "http://127.0.0.1:8085")
|
||||
TTS_TIMEOUT = float(os.environ.get("TTS_TIMEOUT", "300")) # s, pro Synthese
|
||||
TTS_CONNECT_TIMEOUT = float(os.environ.get("TTS_CONNECT_TIMEOUT", "5"))
|
||||
TTS_MODEL = os.environ.get("TTS_MODEL", "xtts-v2")
|
||||
TTS_MODEL = os.environ.get("TTS_MODEL", "qwen3-tts")
|
||||
TTS_VOICES = tuple(v.strip() for v in os.environ.get(
|
||||
"TTS_VOICES", "claribel").split(",") if v.strip())
|
||||
"TTS_VOICES", "alloy").split(",") if v.strip())
|
||||
TTS_DEFAULT_VOICE = os.environ.get(
|
||||
"TTS_DEFAULT_VOICE", TTS_VOICES[0] if TTS_VOICES else "claribel")
|
||||
"TTS_DEFAULT_VOICE", TTS_VOICES[0] if TTS_VOICES else "alloy")
|
||||
TTS_FORMATS = ("mp3", "wav", "pcm")
|
||||
TTS_DEFAULT_FORMAT = "mp3"
|
||||
|
||||
@@ -254,6 +264,7 @@ class _ImageState:
|
||||
self.last_error: str | None = None
|
||||
self.last_image: str | None = None
|
||||
self.last_seconds: float | None = None
|
||||
self.current_model: str | None = None
|
||||
|
||||
|
||||
IMAGE_PHASES = (
|
||||
@@ -279,6 +290,9 @@ class _State:
|
||||
self.qwen_unavailable = True
|
||||
self.active_chats = 0
|
||||
self.avail_lock = threading.Lock()
|
||||
self.mode = "llm"
|
||||
self.mode_phase = "ready"
|
||||
self.mode_error: str | None = None
|
||||
|
||||
|
||||
STATE = _State()
|
||||
@@ -309,6 +323,329 @@ def _set_qwen_unavailable(unavailable: bool) -> None:
|
||||
STATE.qwen_unavailable = unavailable
|
||||
|
||||
|
||||
def _music_worker_state() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"music_worker", "missing"))
|
||||
except Exception as exc:
|
||||
log.warning("Musik-Worker-Status nicht verfügbar: %s", exc)
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _music_worker_health() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"music_health", "unknown"))
|
||||
except Exception:
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _separator_worker_state() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"separator_worker", "missing"))
|
||||
except Exception as exc:
|
||||
log.warning("Stem-Separator-Status nicht verfügbar: %s", exc)
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _separator_worker_health() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"separator_health", "unknown"))
|
||||
except Exception:
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _voice_worker_state() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"voice_worker", "missing"))
|
||||
except Exception as exc:
|
||||
log.warning("Voice-Worker-Status nicht verfügbar: %s", exc)
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _voice_worker_health() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"voice_health", "unknown"))
|
||||
except Exception:
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _voice_change_worker_state() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"voice_change_worker", "missing"))
|
||||
except Exception as exc:
|
||||
log.warning("Voice-Change-Worker-Status nicht verfügbar: %s", exc)
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _voice_change_worker_health() -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(
|
||||
"voice_change_health", "unknown"))
|
||||
except Exception:
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _worker_field(field: str) -> str:
|
||||
if not PROFILE_CONTROL_URL:
|
||||
return "unsupported"
|
||||
try:
|
||||
return str(_profile_controller_request("GET", "/status").get(field, "missing"))
|
||||
except Exception as exc:
|
||||
log.warning("Spezial-Worker-Status %s nicht verfügbar: %s", field, exc)
|
||||
return "unknown"
|
||||
|
||||
|
||||
def _wait_music_ready() -> None:
|
||||
deadline = time.monotonic() + MUSIC_START_TIMEOUT
|
||||
while time.monotonic() < deadline:
|
||||
status = _profile_controller_request("GET", "/status")
|
||||
if (status.get("music_worker") == "running"
|
||||
and status.get("music_health") == "healthy"):
|
||||
return
|
||||
if status.get("music_health") == "unhealthy":
|
||||
raise RuntimeError("ACE-Step-Container ist unhealthy")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
raise RuntimeError(
|
||||
f"ACE-Step nach {MUSIC_START_TIMEOUT:.0f} s nicht bereit")
|
||||
|
||||
|
||||
def _wait_yue2_ready() -> None:
|
||||
_wait_aux_voice_ready("yue2_worker", "yue2_health",
|
||||
"YuE2", YUE2_START_TIMEOUT)
|
||||
|
||||
|
||||
def _wait_separator_ready() -> None:
|
||||
deadline = time.monotonic() + SEPARATOR_START_TIMEOUT
|
||||
while time.monotonic() < deadline:
|
||||
status = _profile_controller_request("GET", "/status")
|
||||
if (status.get("separator_worker") == "running"
|
||||
and status.get("separator_health") == "healthy"):
|
||||
return
|
||||
if status.get("separator_health") == "unhealthy":
|
||||
raise RuntimeError("BS-RoFormer-Container ist unhealthy")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
raise RuntimeError(
|
||||
f"BS-RoFormer nach {SEPARATOR_START_TIMEOUT:.0f} s nicht bereit")
|
||||
|
||||
|
||||
def _wait_voice_ready() -> None:
|
||||
deadline = time.monotonic() + VOICE_START_TIMEOUT
|
||||
while time.monotonic() < deadline:
|
||||
status = _profile_controller_request("GET", "/status")
|
||||
if (status.get("voice_worker") == "running"
|
||||
and status.get("voice_health") == "healthy"):
|
||||
return
|
||||
if status.get("voice_health") == "unhealthy":
|
||||
raise RuntimeError("OmniVoice-Container ist unhealthy")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
raise RuntimeError(
|
||||
f"OmniVoice nach {VOICE_START_TIMEOUT:.0f} s nicht bereit")
|
||||
|
||||
|
||||
def _wait_voice_change_ready() -> None:
|
||||
deadline = time.monotonic() + VOICE_CHANGE_START_TIMEOUT
|
||||
while time.monotonic() < deadline:
|
||||
status = _profile_controller_request("GET", "/status")
|
||||
if (status.get("voice_change_worker") == "running"
|
||||
and status.get("voice_change_health") == "healthy"):
|
||||
return
|
||||
if status.get("voice_change_health") == "unhealthy":
|
||||
raise RuntimeError("X-VC-Container ist unhealthy")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
raise RuntimeError(
|
||||
f"X-VC nach {VOICE_CHANGE_START_TIMEOUT:.0f} s nicht bereit")
|
||||
|
||||
|
||||
def _wait_aux_voice_ready(worker_field: str, health_field: str,
|
||||
label: str, timeout: float) -> None:
|
||||
deadline = time.monotonic() + timeout
|
||||
while time.monotonic() < deadline:
|
||||
status = _profile_controller_request("GET", "/status")
|
||||
if (status.get(worker_field) == "running"
|
||||
and status.get(health_field) == "healthy"):
|
||||
return
|
||||
if status.get(health_field) == "unhealthy":
|
||||
raise RuntimeError(f"{label}-Container ist unhealthy")
|
||||
time.sleep(POLL_INTERVAL)
|
||||
raise RuntimeError(f"{label} nach {timeout:.0f} s nicht bereit")
|
||||
|
||||
|
||||
def _wait_applio_ready() -> None:
|
||||
_wait_aux_voice_ready("applio_worker", "applio_health",
|
||||
"Applio", APPLIO_START_TIMEOUT)
|
||||
|
||||
|
||||
def _wait_trellis_ready() -> None:
|
||||
_wait_aux_voice_ready("trellis_worker", "trellis_health",
|
||||
"TRELLIS.2", TRELLIS_START_TIMEOUT)
|
||||
|
||||
|
||||
def _special_worker(mode: str) -> tuple[str, str, callable]:
|
||||
if mode == "music":
|
||||
return "/workers/music/start", _music_worker_state(), _wait_music_ready
|
||||
if mode == "yue2":
|
||||
return ("/workers/yue2/start", _worker_field("yue2_worker"),
|
||||
_wait_yue2_ready)
|
||||
if mode == "separation":
|
||||
return "/workers/separator/start", _separator_worker_state(), _wait_separator_ready
|
||||
if mode == "voice":
|
||||
return "/workers/voice/start", _voice_worker_state(), _wait_voice_ready
|
||||
if mode == "voicechange":
|
||||
return ("/workers/voice-change/start", _voice_change_worker_state(),
|
||||
_wait_voice_change_ready)
|
||||
if mode == "applio":
|
||||
return ("/workers/applio/start", _worker_field("applio_worker"),
|
||||
_wait_applio_ready)
|
||||
if mode == "trellis":
|
||||
return ("/workers/trellis/start", _worker_field("trellis_worker"),
|
||||
_wait_trellis_ready)
|
||||
raise ValueError(f"unbekannter Spezialmodus: {mode}")
|
||||
|
||||
|
||||
def set_operating_mode(mode: str) -> dict:
|
||||
"""Atomarer Wechsel zwischen LLM und den exklusiven GPU-Werkzeugen."""
|
||||
if not ENABLE_MUSIC_MODE or not PROFILE_CONTROL_URL:
|
||||
raise RuntimeError("Musikmodus ist nicht konfiguriert")
|
||||
special_modes = {"music", "yue2", "separation", "voice", "voicechange",
|
||||
"applio", "trellis"}
|
||||
if mode not in {"llm", *special_modes}:
|
||||
raise ValueError("unbekannter Betriebsmodus")
|
||||
with STATE.lock:
|
||||
STATE.mode_error = None
|
||||
if mode in special_modes:
|
||||
path, worker_state, wait_ready = _special_worker(mode)
|
||||
if STATE.mode == mode and worker_state == "running":
|
||||
return {"status": "ok", "mode": mode, "changed": False}
|
||||
profile = current_profile()
|
||||
previous = RUNTIME.load()
|
||||
saved = previous.get("return_profile") or previous.get("last_profile")
|
||||
return_profile = profile if profile in PROFILES else saved
|
||||
if return_profile not in PROFILES:
|
||||
return_profile = next(iter(PROFILES))
|
||||
STATE.mode_phase = f"starting-{mode}"
|
||||
_set_qwen_unavailable(True)
|
||||
try:
|
||||
# Persist intent before stopping anything so a router restart
|
||||
# during ACE-Step loading can resume the same transition.
|
||||
RUNTIME.save(mode=mode, return_profile=return_profile,
|
||||
last_profile=return_profile,
|
||||
phase=f"starting-{mode}")
|
||||
_wait_chats_drained()
|
||||
_profile_controller_request(
|
||||
"POST", path,
|
||||
timeout=120)
|
||||
wait_ready()
|
||||
STATE.mode = mode
|
||||
STATE.mode_phase = "ready"
|
||||
RUNTIME.save(mode=mode, return_profile=return_profile,
|
||||
last_profile=return_profile, phase=mode)
|
||||
return {"status": "ok", "mode": mode, "changed": True,
|
||||
"return_profile": return_profile}
|
||||
except Exception as exc:
|
||||
STATE.mode_error = str(exc)
|
||||
STATE.mode_phase = "error"
|
||||
raise
|
||||
|
||||
previous = RUNTIME.load()
|
||||
profile = previous.get("return_profile") or previous.get("last_profile")
|
||||
if profile not in PROFILES:
|
||||
profile = next(iter(PROFILES))
|
||||
STATE.mode_phase = "restoring-llm"
|
||||
_set_qwen_unavailable(True)
|
||||
try:
|
||||
_profile_controller_request("POST", "/workers/music/stop")
|
||||
_profile_controller_request("POST", "/workers/yue2/stop")
|
||||
_profile_controller_request("POST", "/workers/separator/stop")
|
||||
_profile_controller_request("POST", "/workers/voice/stop")
|
||||
_profile_controller_request("POST", "/workers/voice-change/stop")
|
||||
_profile_controller_request("POST", "/workers/applio/stop")
|
||||
_profile_controller_request("POST", "/workers/trellis/stop")
|
||||
_restore_qwen(profile)
|
||||
STATE.mode = "llm"
|
||||
STATE.mode_phase = "ready"
|
||||
_set_qwen_unavailable(False)
|
||||
RUNTIME.save(mode="llm", return_profile=None,
|
||||
last_profile=profile, phase="idle")
|
||||
return {"status": "ok", "mode": "llm", "changed": True,
|
||||
"profile": profile}
|
||||
except Exception as exc:
|
||||
STATE.mode_error = str(exc)
|
||||
STATE.mode_phase = "error"
|
||||
raise
|
||||
|
||||
|
||||
def schedule_operating_mode(mode: str) -> tuple[bool, str]:
|
||||
"""Start a transition in the background so chat/UI acknowledgement is instant."""
|
||||
if not ENABLE_MUSIC_MODE or not PROFILE_CONTROL_URL:
|
||||
raise RuntimeError("Musikmodus ist nicht konfiguriert")
|
||||
if mode not in {"llm", "music", "yue2", "separation", "voice",
|
||||
"voicechange", "applio", "trellis"}:
|
||||
raise ValueError("unbekannter Betriebsmodus")
|
||||
with STATE.lock:
|
||||
if STATE.mode_phase not in {"ready", "error"}:
|
||||
return False, STATE.mode_phase
|
||||
if STATE.mode == mode and STATE.mode_phase == "ready":
|
||||
return False, "ready"
|
||||
STATE.mode_phase = f"starting-{mode}" if mode != "llm" else "restoring-llm"
|
||||
|
||||
def transition() -> None:
|
||||
try:
|
||||
set_operating_mode(mode)
|
||||
log.info("Betriebsmodus ist jetzt %s", mode)
|
||||
except Exception:
|
||||
log.exception("Betriebsmodus-Wechsel zu %s fehlgeschlagen", mode)
|
||||
|
||||
threading.Thread(target=transition, name=f"mode-{mode}", daemon=True).start()
|
||||
return True, STATE.mode_phase
|
||||
|
||||
|
||||
def _control_command(data: dict, path: str) -> str | None:
|
||||
"""Recognise exact local commands without invoking an LLM."""
|
||||
text: object = None
|
||||
if path == "/v1/chat/completions":
|
||||
messages = data.get("messages")
|
||||
if isinstance(messages, list):
|
||||
for item in reversed(messages):
|
||||
if isinstance(item, dict) and item.get("role") == "user":
|
||||
text = item.get("content")
|
||||
break
|
||||
elif path == "/v1/responses":
|
||||
text = data.get("input")
|
||||
if not isinstance(text, str):
|
||||
return None
|
||||
command = text.strip().casefold()
|
||||
return command if command in {"/athena music", "/athena yue2",
|
||||
"/athena stems",
|
||||
"/athena separation", "/athena llm",
|
||||
"/athena voice",
|
||||
"/athena voicechange", "/athena changer",
|
||||
"/athena applio",
|
||||
"/athena 3d", "/athena trellis",
|
||||
"/athena status"} else None
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Upstream (llama.cpp)
|
||||
# ---------------------------------------------------------------------------
|
||||
@@ -588,7 +925,8 @@ def _read(path: str) -> str:
|
||||
return f.read().strip()
|
||||
|
||||
|
||||
def _profile_controller_request(method: str, path: str) -> dict:
|
||||
def _profile_controller_request(method: str, path: str,
|
||||
timeout: float = 120) -> dict:
|
||||
token = os.environ.get("PROFILE_CONTROL_TOKEN", "").strip()
|
||||
if not token:
|
||||
token = _read(PROFILE_CONTROL_TOKEN_FILE)
|
||||
@@ -600,7 +938,7 @@ def _profile_controller_request(method: str, path: str) -> dict:
|
||||
headers={"Authorization": f"Bearer {token}"},
|
||||
)
|
||||
try:
|
||||
with urllib.request.urlopen(request, timeout=120) as response:
|
||||
with urllib.request.urlopen(request, timeout=timeout) as response:
|
||||
return json.load(response)
|
||||
except urllib.error.HTTPError as exc:
|
||||
body = exc.read(500).decode(errors="replace")
|
||||
@@ -750,7 +1088,10 @@ def switch_profile(profile: str, implicit: bool = False) -> None:
|
||||
f"Profildatei wurde nicht gesetzt (erwartet: {profile})")
|
||||
log.info("Warte, bis llama.cpp das Profil geladen hat ...")
|
||||
_wait_ready(profile, time.monotonic() + SWITCH_TIMEOUT)
|
||||
RUNTIME.save(last_profile=profile, phase="idle")
|
||||
STATE.mode = "llm"
|
||||
STATE.mode_phase = "ready"
|
||||
RUNTIME.save(last_profile=profile, mode="llm",
|
||||
return_profile=None, phase="idle")
|
||||
finally:
|
||||
# Nach einem fehlgeschlagenen Skript/Timeout darf der Router
|
||||
# Qwen nicht blind freigeben. Nur ein semantisch verifiziertes
|
||||
@@ -765,7 +1106,7 @@ def switch_profile(profile: str, implicit: bool = False) -> None:
|
||||
|
||||
|
||||
# ---------------------------------------------------------------------------
|
||||
# Bildgenerierung und Editing (FLUX.2-klein-4B)
|
||||
# Bildgenerierung und Editing (FLUX.2 Klein 9B FP8)
|
||||
# ---------------------------------------------------------------------------
|
||||
|
||||
class _Worker:
|
||||
@@ -861,7 +1202,10 @@ def _worker() -> _Worker:
|
||||
if not img.worker or not img.worker.alive():
|
||||
if img.worker:
|
||||
img.worker.stop()
|
||||
img.worker = _RemoteWorker() if IMAGE_WORKER_URL else _Worker()
|
||||
img.worker = (_RemoteWorker(kind="image", url=IMAGE_WORKER_URL,
|
||||
token=IMAGE_WORKER_TOKEN,
|
||||
endpoint="/generate")
|
||||
if IMAGE_WORKER_URL else _Worker())
|
||||
img.worker.start()
|
||||
return img.worker
|
||||
|
||||
@@ -871,7 +1215,12 @@ class _RemoteWorker:
|
||||
|
||||
model_loaded = False
|
||||
|
||||
def __init__(self) -> None:
|
||||
def __init__(self, *, kind: str, url: str, token: str,
|
||||
endpoint: str) -> None:
|
||||
self.kind = kind
|
||||
self.url = url
|
||||
self.token = token
|
||||
self.endpoint = endpoint
|
||||
self.running = False
|
||||
|
||||
def alive(self) -> bool:
|
||||
@@ -880,10 +1229,10 @@ class _RemoteWorker:
|
||||
def _request(self, method: str, path: str, payload: dict | None = None,
|
||||
timeout: float = 120) -> dict:
|
||||
body = None if payload is None else json.dumps(payload).encode()
|
||||
headers = {"Authorization": f"Bearer {IMAGE_WORKER_TOKEN}"}
|
||||
headers = {"Authorization": f"Bearer {self.token}"}
|
||||
if body is not None:
|
||||
headers["Content-Type"] = "application/json"
|
||||
req = urllib.request.Request(IMAGE_WORKER_URL + path, data=body,
|
||||
req = urllib.request.Request(self.url + path, data=body,
|
||||
method=method, headers=headers)
|
||||
try:
|
||||
with urllib.request.urlopen(req, timeout=timeout) as response:
|
||||
@@ -898,9 +1247,9 @@ class _RemoteWorker:
|
||||
raise RuntimeError(f"Bild-Worker nicht erreichbar: {exc}") from exc
|
||||
|
||||
def start(self) -> None:
|
||||
if not IMAGE_WORKER_TOKEN or len(IMAGE_WORKER_TOKEN) < 32:
|
||||
if not self.token or len(self.token) < 32:
|
||||
raise RuntimeError("Bild-Worker-Token fehlt oder ist zu kurz")
|
||||
_profile_controller_request("POST", "/workers/image/start")
|
||||
_profile_controller_request("POST", f"/workers/{self.kind}/start")
|
||||
deadline = time.monotonic() + IMAGE_START_TIMEOUT
|
||||
while time.monotonic() < deadline:
|
||||
try:
|
||||
@@ -920,11 +1269,11 @@ class _RemoteWorker:
|
||||
clean.pop("cmd", None)
|
||||
output = clean.pop("output", "")
|
||||
clean["filename"] = os.path.basename(output)
|
||||
return self._request("POST", "/generate", clean, timeout)
|
||||
return self._request("POST", self.endpoint, clean, timeout)
|
||||
|
||||
def stop(self) -> None:
|
||||
try:
|
||||
_profile_controller_request("POST", "/workers/image/stop")
|
||||
_profile_controller_request("POST", f"/workers/{self.kind}/stop")
|
||||
finally:
|
||||
self.running = False
|
||||
self.model_loaded = False
|
||||
@@ -1011,6 +1360,7 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
guidance: float, seed: int | None, n: int,
|
||||
quality: str = "standard",
|
||||
source_files: list[str] | None = None,
|
||||
model: str = IMAGE_MODEL_NAME,
|
||||
) -> tuple[list[str], str | None]:
|
||||
"""Orchestriert die Bildgenerierung inkl. Qwen-Hotswap.
|
||||
|
||||
@@ -1030,6 +1380,7 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
results: list[str] = []
|
||||
warning: str | None = None
|
||||
img.last_error = None
|
||||
img.current_model = model
|
||||
# Qwen wird gestoppt → für Chats nicht verfügbar (die warten).
|
||||
_set_qwen_unavailable(True)
|
||||
try:
|
||||
@@ -1062,7 +1413,7 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
filename = time.strftime("%Y%m%d-%H%M%S") + \
|
||||
f"-{os.urandom(2).hex()}.png"
|
||||
output = os.path.join(IMAGE_DIR, filename)
|
||||
resp = worker.request({
|
||||
worker_payload = {
|
||||
"cmd": "generate",
|
||||
"prompt": prompt,
|
||||
"width": width,
|
||||
@@ -1072,7 +1423,8 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
"seed": seed,
|
||||
"output": output,
|
||||
"source_files": source_files or [],
|
||||
}, timeout=IMAGE_GEN_TIMEOUT)
|
||||
}
|
||||
resp = worker.request(worker_payload, timeout=IMAGE_GEN_TIMEOUT)
|
||||
if resp.get("status") != "ok":
|
||||
raise RuntimeError(
|
||||
resp.get("message", "Bildgenerierung fehlgeschlagen"))
|
||||
@@ -1090,10 +1442,10 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
"steps": steps,
|
||||
"guidance": guidance,
|
||||
"quality": quality,
|
||||
"mode": "image-edit" if source_files else "text-to-image",
|
||||
"mode": ("image-edit" if source_files else "text-to-image"),
|
||||
"reference_images": len(source_files or []),
|
||||
"seconds": resp.get("seconds"),
|
||||
"model": IMAGE_MODEL_NAME,
|
||||
"model": model,
|
||||
"created": time.strftime("%Y-%m-%dT%H:%M:%S"),
|
||||
}
|
||||
meta_path = os.path.join(IMAGE_DIR, filename[:-4] + ".json")
|
||||
@@ -1139,6 +1491,7 @@ def generate_image(prompt: str, width: int, height: int, steps: int,
|
||||
log.error(warning)
|
||||
# Qwen ist down → qwen_unavailable bleibt True.
|
||||
img.phase = "idle"
|
||||
img.current_model = None
|
||||
return results, warning
|
||||
|
||||
|
||||
@@ -1497,6 +1850,10 @@ class Handler(BaseHTTPRequestHandler):
|
||||
self._send_json(200, self._models_payload())
|
||||
elif path == "/status" and self.command == "GET":
|
||||
self._send_json(200, self._status_payload())
|
||||
elif path == "/mode" and self.command == "GET":
|
||||
self._send_json(200, self._mode_payload())
|
||||
elif path == "/mode" and self.command == "POST":
|
||||
self._mode_change()
|
||||
elif path == "/v1/audio/models" and self.command == "GET":
|
||||
self._send_json(200, self._audio_models_payload())
|
||||
elif path == "/v1/audio/voices" and self.command == "GET":
|
||||
@@ -1519,6 +1876,13 @@ class Handler(BaseHTTPRequestHandler):
|
||||
else:
|
||||
self._send_error(503, "Sprachausgabe ist nicht installiert",
|
||||
"server_error", "feature_disabled")
|
||||
elif (path == "/v1/audio/speech/pcm-stream"
|
||||
and self.command == "POST"):
|
||||
if ENABLE_TTS:
|
||||
self._speech_pcm_stream()
|
||||
else:
|
||||
self._send_error(503, "Sprachausgabe ist nicht installiert",
|
||||
"server_error", "feature_disabled")
|
||||
elif path == "/v1/audio/transcriptions" and self.command == "POST":
|
||||
if ENABLE_STT:
|
||||
self._transcribe()
|
||||
@@ -1713,6 +2077,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"current_profile": current_profile(),
|
||||
"switching": STATE.switching,
|
||||
"profiles": PROFILES,
|
||||
"mode": self._mode_payload(),
|
||||
"upstream": {
|
||||
"url": UPSTREAM_URL,
|
||||
"reachable": up["reachable"],
|
||||
@@ -1734,7 +2099,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"phase": img.phase,
|
||||
"worker": "running" if (img.worker and img.worker.alive())
|
||||
else "stopped",
|
||||
"model": IMAGE_MODEL_NAME if img.phase != "idle" else None,
|
||||
"model": img.current_model if img.phase != "idle" else None,
|
||||
"model_loaded": bool(img.worker and img.worker.model_loaded),
|
||||
"last_image": img.last_image,
|
||||
"last_seconds": img.last_seconds,
|
||||
@@ -1744,6 +2109,49 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"stt": stt_status(),
|
||||
}
|
||||
|
||||
@staticmethod
|
||||
def _mode_payload() -> dict:
|
||||
state = RUNTIME.load()
|
||||
return {
|
||||
"active": STATE.mode,
|
||||
"phase": STATE.mode_phase,
|
||||
"music_worker": _music_worker_state(),
|
||||
"music_health": _music_worker_health(),
|
||||
"yue2_worker": _worker_field("yue2_worker"),
|
||||
"yue2_health": _worker_field("yue2_health"),
|
||||
"separator_worker": _separator_worker_state(),
|
||||
"separator_health": _separator_worker_health(),
|
||||
"voice_worker": _voice_worker_state(),
|
||||
"voice_health": _voice_worker_health(),
|
||||
"voice_change_worker": _voice_change_worker_state(),
|
||||
"voice_change_health": _voice_change_worker_health(),
|
||||
"applio_worker": _worker_field("applio_worker"),
|
||||
"applio_health": _worker_field("applio_health"),
|
||||
"trellis_worker": _worker_field("trellis_worker"),
|
||||
"trellis_health": _worker_field("trellis_health"),
|
||||
"return_profile": state.get("return_profile"),
|
||||
"last_error": STATE.mode_error,
|
||||
"enabled": ENABLE_MUSIC_MODE,
|
||||
}
|
||||
|
||||
def _mode_change(self) -> None:
|
||||
try:
|
||||
data = json.loads(self._read_body() or b"{}")
|
||||
mode = data.get("mode") if isinstance(data, dict) else None
|
||||
if mode not in {"llm", "music", "yue2", "separation", "voice",
|
||||
"voicechange", "applio", "trellis"}:
|
||||
raise ValueError("Feld 'mode' enthält einen unbekannten Betriebsmodus")
|
||||
started, phase = schedule_operating_mode(mode)
|
||||
self._send_json(202 if started else 200, {
|
||||
"status": "accepted" if started else "ok",
|
||||
"requested_mode": mode,
|
||||
"phase": phase,
|
||||
})
|
||||
except ValueError as exc:
|
||||
self._send_error(400, str(exc), "invalid_request_error", "invalid_mode")
|
||||
except RuntimeError as exc:
|
||||
self._send_error(503, str(exc), "server_error", "mode_unavailable")
|
||||
|
||||
# ---------- Bildgenerierung ----------
|
||||
|
||||
def _image_generate(self) -> None:
|
||||
@@ -1841,6 +2249,13 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"invalid_request_error", "prompt_too_long")
|
||||
return
|
||||
|
||||
model = data.get("model", IMAGE_MODEL_NAME)
|
||||
if model != IMAGE_MODEL_NAME:
|
||||
self._send_error(
|
||||
400, f"unbekanntes Bildmodell: {model!r}",
|
||||
"invalid_request_error", "invalid_model")
|
||||
return
|
||||
|
||||
# Größe
|
||||
size = data.get("size", "1024x1024")
|
||||
if size not in IMAGE_SIZES:
|
||||
@@ -1857,7 +2272,6 @@ class Handler(BaseHTTPRequestHandler):
|
||||
self._send_error(400, f"'n' muss eine Ganzzahl 1..{IMAGE_MAX_N} sein",
|
||||
"invalid_request_error", "invalid_n")
|
||||
return
|
||||
|
||||
# Qualität / Schritte / Guidance
|
||||
quality = data.get("quality", IMAGE_DEFAULT_QUALITY)
|
||||
if quality not in IMAGE_QUALITY:
|
||||
@@ -1866,8 +2280,9 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"invalid_request_error", "invalid_quality")
|
||||
return
|
||||
steps = data.get("steps", IMAGE_QUALITY[quality])
|
||||
if not isinstance(steps, int) or isinstance(steps, bool) or steps != 4:
|
||||
self._send_error(400, "FLUX.2-klein-4B erfordert 'steps'=4",
|
||||
if (not isinstance(steps, int) or isinstance(steps, bool)
|
||||
or steps != 4):
|
||||
self._send_error(400, f"{IMAGE_MODEL_NAME} erfordert 'steps'=4",
|
||||
"invalid_request_error", "invalid_steps")
|
||||
return
|
||||
guidance = data.get("guidance", 1.0)
|
||||
@@ -1878,7 +2293,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"invalid_request_error", "invalid_guidance")
|
||||
return
|
||||
if guidance != 1.0:
|
||||
self._send_error(400, "FLUX.2-klein-4B erfordert 'guidance'=1.0",
|
||||
self._send_error(400, f"{IMAGE_MODEL_NAME} erfordert 'guidance'=1.0",
|
||||
"invalid_request_error", "invalid_guidance")
|
||||
return
|
||||
|
||||
@@ -1906,7 +2321,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
try:
|
||||
results, warning = generate_image(
|
||||
prompt.strip(), width, height, steps, guidance, seed, n,
|
||||
quality, source_files)
|
||||
quality, source_files, model)
|
||||
except (ValueError, RuntimeError) as e:
|
||||
self._send_error(503, str(e), "server_error", "image_generation_failed")
|
||||
return
|
||||
@@ -1979,7 +2394,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
self.end_headers()
|
||||
self.wfile.write(data)
|
||||
|
||||
# ---------- Sprachausgabe (XTTS-v2) ----------
|
||||
# ---------- Sprachausgabe (Qwen3-TTS) ----------
|
||||
|
||||
def _speech(self) -> None:
|
||||
try:
|
||||
@@ -2038,7 +2453,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
"invalid_request_error", "invalid_speed")
|
||||
return
|
||||
|
||||
# Modell-Name optional; falls angegeben, muss es xtts-v2 sein.
|
||||
# Modell-Name optional; falls angegeben, muss es Qwen3-TTS sein.
|
||||
model = data.get("model")
|
||||
if model is not None and model != TTS_MODEL:
|
||||
self._send_error(400, f"unbekanntes Modell: {model!r} "
|
||||
@@ -2062,6 +2477,74 @@ class Handler(BaseHTTPRequestHandler):
|
||||
self.end_headers()
|
||||
self.wfile.write(audio)
|
||||
|
||||
def _speech_pcm_stream(self) -> None:
|
||||
"""Pass through Qwen's native 24 kHz PCM stream without buffering."""
|
||||
try:
|
||||
body = self._read_body()
|
||||
data = json.loads(body)
|
||||
except ValueError as exc:
|
||||
self._send_error(400, str(exc) or "ungültiges JSON",
|
||||
"invalid_request_error", "invalid_body")
|
||||
return
|
||||
if not isinstance(data, dict):
|
||||
self._send_error(400, "Request muss ein JSON-Objekt sein",
|
||||
"invalid_request_error", "invalid_request")
|
||||
return
|
||||
text = data.get("input", data.get("text"))
|
||||
if not isinstance(text, str) or not text.strip() or len(text) > 8000:
|
||||
self._send_error(400, "'input' fehlt, ist leer oder zu lang",
|
||||
"invalid_request_error", "invalid_input")
|
||||
return
|
||||
voice = data.get("voice", TTS_DEFAULT_VOICE)
|
||||
if voice not in TTS_VOICES:
|
||||
self._send_error(400, f"ungültige Stimme: {voice!r}",
|
||||
"invalid_request_error", "invalid_voice")
|
||||
return
|
||||
|
||||
hostport = TTS_WORKER_URL.split("://", 1)[-1]
|
||||
host, _, port = hostport.partition(":")
|
||||
connection = None
|
||||
headers_sent = False
|
||||
try:
|
||||
connection = http.client.HTTPConnection(
|
||||
host, int(port) if port else 80, timeout=TTS_CONNECT_TIMEOUT)
|
||||
connection.request(
|
||||
"POST", "/tts/pcm-stream", body=body,
|
||||
headers={"Content-Type": "application/json",
|
||||
"Accept": "application/octet-stream"})
|
||||
connection.sock.settimeout(TTS_TIMEOUT)
|
||||
response = connection.getresponse()
|
||||
if response.status != 200:
|
||||
message = response.read(512).decode(errors="replace")
|
||||
self._send_error(503,
|
||||
f"TTS-Stream fehlgeschlagen: {message}",
|
||||
"server_error", "tts_failed")
|
||||
return
|
||||
self._last_code = 200
|
||||
self.send_response(200)
|
||||
self.send_header("Content-Type", "application/octet-stream")
|
||||
self.send_header("Cache-Control", "no-store")
|
||||
self.send_header("Connection", "close")
|
||||
self.end_headers()
|
||||
headers_sent = True
|
||||
while True:
|
||||
chunk = response.read1(16384)
|
||||
if not chunk:
|
||||
break
|
||||
self.wfile.write(chunk)
|
||||
self.wfile.flush()
|
||||
except (OSError, http.client.HTTPException) as exc:
|
||||
if not headers_sent:
|
||||
try:
|
||||
self._send_error(502, f"TTS-Worker nicht erreichbar: {exc}",
|
||||
"server_error", "tts_unavailable")
|
||||
except (OSError, BrokenPipeError):
|
||||
pass
|
||||
finally:
|
||||
if connection is not None:
|
||||
connection.close()
|
||||
self.close_connection = True
|
||||
|
||||
# ---------- Audio-Discovery ----------
|
||||
|
||||
def _audio_models_payload(self) -> dict:
|
||||
@@ -2080,7 +2563,7 @@ class Handler(BaseHTTPRequestHandler):
|
||||
models.append({
|
||||
"id": TTS_MODEL,
|
||||
"object": "model",
|
||||
"owned_by": "coqui-xtts",
|
||||
"owned_by": "qwen",
|
||||
"type": "speech",
|
||||
})
|
||||
return {"object": "list", "data": models}
|
||||
@@ -2269,6 +2752,12 @@ class Handler(BaseHTTPRequestHandler):
|
||||
data = json.loads(body)
|
||||
except ValueError:
|
||||
data = None
|
||||
if (isinstance(data, dict)
|
||||
and path in {"/v1/chat/completions", "/v1/responses"}):
|
||||
command = _control_command(data, path)
|
||||
if command is not None:
|
||||
self._control_response(command, data, path)
|
||||
return
|
||||
model = data.get("model") if isinstance(data, dict) else None
|
||||
if (isinstance(model, str) and REVIEW_UPSTREAM_URL
|
||||
and model == REVIEW_MODEL_NAME):
|
||||
@@ -2306,6 +2795,97 @@ class Handler(BaseHTTPRequestHandler):
|
||||
# An llama.cpp weiterleiten (mit Chat-Waiting, Streaming bleibt erhalten).
|
||||
self._proxy_with_wait(body)
|
||||
|
||||
def _control_response(self, command: str, data: dict, path: str) -> None:
|
||||
"""Return OpenAI-compatible local replies for Athena control commands."""
|
||||
if command == "/athena status":
|
||||
mode = self._mode_payload()
|
||||
profile = current_profile()
|
||||
text = (f"Athena läuft im {mode['active'].upper()}-Modus. "
|
||||
f"Phase: {mode['phase']}. Musik-Worker: "
|
||||
f"{mode['music_worker']}. YuE2: "
|
||||
f"{mode['yue2_worker']}. Stem-Separator: "
|
||||
f"{mode['separator_worker']}. Voice Studio: "
|
||||
f"{mode['voice_worker']}. Voice Changer: "
|
||||
f"{mode['voice_change_worker']}. 3D Studio: "
|
||||
f"{mode['trellis_worker']}. LLM-Profil: {profile or 'entladen'}.")
|
||||
else:
|
||||
target = ("music" if command == "/athena music" else
|
||||
"yue2" if command == "/athena yue2" else
|
||||
"separation" if command in {"/athena stems", "/athena separation"}
|
||||
else "voice" if command == "/athena voice"
|
||||
else "voicechange" if command in {"/athena voicechange", "/athena changer"}
|
||||
else "applio" if command == "/athena applio"
|
||||
else "trellis" if command in {"/athena 3d", "/athena trellis"}
|
||||
else "llm")
|
||||
try:
|
||||
started, phase = schedule_operating_mode(target)
|
||||
if started:
|
||||
text = ("Musikstudio wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "music" else
|
||||
"YuE2 Studio wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "yue2" else
|
||||
"Stimmtrennung wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "separation" else
|
||||
"Voice Studio wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "voice" else
|
||||
"Voice Changer wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "voicechange" else
|
||||
"Applio wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "applio" else
|
||||
"3D Studio wird gestartet. LLM und TTS werden entladen."
|
||||
if target == "trellis" else
|
||||
"Spezialmodus wird beendet und das vorherige LLM-Profil wiederhergestellt.")
|
||||
else:
|
||||
text = (f"Athena ist bereits im {target.upper()}-Modus "
|
||||
f"oder wechselt gerade ({phase}).")
|
||||
except RuntimeError as exc:
|
||||
self._send_error(503, str(exc), "server_error", "mode_unavailable")
|
||||
return
|
||||
|
||||
model = str(data.get("model") or "athena-control")
|
||||
created = int(time.time())
|
||||
request_id = f"athena-mode-{uuid.uuid4().hex[:16]}"
|
||||
if path == "/v1/responses":
|
||||
self._send_json(200, {
|
||||
"id": request_id, "object": "response", "created_at": created,
|
||||
"status": "completed", "model": model,
|
||||
"output": [{"type": "message", "role": "assistant",
|
||||
"content": [{"type": "output_text", "text": text}]}],
|
||||
"output_text": text,
|
||||
"usage": {"input_tokens": 0, "output_tokens": 0,
|
||||
"total_tokens": 0},
|
||||
})
|
||||
return
|
||||
if data.get("stream") is True:
|
||||
chunks = [
|
||||
{"id": request_id, "object": "chat.completion.chunk",
|
||||
"created": created, "model": model,
|
||||
"choices": [{"index": 0, "delta": {"role": "assistant",
|
||||
"content": text}, "finish_reason": None}]},
|
||||
{"id": request_id, "object": "chat.completion.chunk",
|
||||
"created": created, "model": model,
|
||||
"choices": [{"index": 0, "delta": {}, "finish_reason": "stop"}]},
|
||||
]
|
||||
body = "".join(f"data: {json.dumps(chunk)}\n\n" for chunk in chunks)
|
||||
body += "data: [DONE]\n\n"
|
||||
encoded = body.encode()
|
||||
self._last_code = 200
|
||||
self.send_response(200)
|
||||
self.send_header("Content-Type", "text/event-stream")
|
||||
self.send_header("Content-Length", str(len(encoded)))
|
||||
self.send_header("Connection", "close")
|
||||
self.end_headers()
|
||||
self.wfile.write(encoded)
|
||||
return
|
||||
self._send_json(200, {
|
||||
"id": request_id, "object": "chat.completion", "created": created,
|
||||
"model": model,
|
||||
"choices": [{"index": 0, "message": {"role": "assistant",
|
||||
"content": text}, "finish_reason": "stop"}],
|
||||
"usage": {"prompt_tokens": 0, "completion_tokens": 0,
|
||||
"total_tokens": 0},
|
||||
})
|
||||
|
||||
def _acquire_model_lease(self, profile: str | None = None) -> dict:
|
||||
"""Atomar Profil sicherstellen und einen aktiven Request registrieren."""
|
||||
with STATE.lock:
|
||||
@@ -2545,6 +3125,29 @@ def _startup_reconcile() -> None:
|
||||
if removed:
|
||||
log.info("Startup-Retention: %d alte Bilder entfernt", len(removed))
|
||||
|
||||
special_mode = previous.get("mode")
|
||||
if ENABLE_MUSIC_MODE and special_mode in {"music", "yue2", "separation",
|
||||
"voice", "voicechange", "applio",
|
||||
"trellis"}:
|
||||
STATE.mode = special_mode
|
||||
STATE.mode_phase = f"starting-{special_mode}"
|
||||
_set_qwen_unavailable(True)
|
||||
try:
|
||||
path, _worker_state, wait_ready = _special_worker(special_mode)
|
||||
_profile_controller_request(
|
||||
"POST", path,
|
||||
timeout=120)
|
||||
wait_ready()
|
||||
STATE.mode_phase = "ready"
|
||||
RUNTIME.save(mode=special_mode, phase=special_mode)
|
||||
log.info("Recovery: Spezialmodus %s wiederhergestellt", special_mode)
|
||||
except Exception as exc:
|
||||
STATE.mode_error = str(exc)
|
||||
STATE.mode_phase = "error"
|
||||
log.error("Recovery: Spezialmodus %s konnte nicht gestartet werden: %s",
|
||||
special_mode, exc)
|
||||
return
|
||||
|
||||
profile = current_profile()
|
||||
if profile is None:
|
||||
saved = previous.get("last_profile")
|
||||
@@ -2568,7 +3171,9 @@ def _startup_reconcile() -> None:
|
||||
and (not EXPECTED_MODELS.get(profile)
|
||||
or up.get("model") == EXPECTED_MODELS[profile])):
|
||||
_set_qwen_unavailable(False)
|
||||
RUNTIME.save(last_profile=profile, phase="idle")
|
||||
STATE.mode = "llm"
|
||||
STATE.mode_phase = "ready"
|
||||
RUNTIME.save(last_profile=profile, mode="llm", phase="idle")
|
||||
log.info("Recovery: Profil %s ist bereits bereit", profile)
|
||||
return
|
||||
_set_qwen_unavailable(True)
|
||||
|
||||
Reference in New Issue
Block a user