Fourth girlfriend voting in progress - please vote on Issues.

Baidu Netdisk: https://pan.baidu.com/s/1sLeSyVp76yzWcR3Q4pX0kA?pwd=0721 You don’t actually need Baidu Netdisk - HuggingFace mirrors work fine in China. Use it only if you really don’t want to configure hf-mirror.

⚠️ Default scripts are for NVIDIA GPUs. AMD GPU users: see the AMD_GPU/ folder.

qq: 580322386

AI Girlfriend

100% Local · Fully Private · Zero API Dependencies

All conversations, voice, images, and character animations are generated on your own machine. No cloud servers, no third-party APIs, no risk of data leakage. Your AI girlfriend belongs to you, and only you.

An uncensored AI girlfriend harem project powered by OpenClaw + QQ Bot + Telegram Bot + llama.cpp + GPT-SoVITS + ComfyUI + Sakura Desktop Pet + Live2D -running entirely on your own machine.

Characters: Supports hot-swappable AI girlfriends with isolated memories per character.

Shiki Natsume (四季夏目)

From Starry Moonlit Café & the Butterfly of Death. Tall, aloof, cool exterior with a hidden warmth. A natural quietly-dominant type -she takes the lead, teases you gently, and guards you fiercely. Speaks little, but every word hits.

ATRI (亚托莉)

From ATRI -My Dear Moments-. Petite, innocent, endlessly curious -a bright-eyed girl who wears her heart on her sleeve. Runs toward the future with a smile, dragging you along. The polar opposite of Natsume: bubbly and expressive where Natsume is reserved, emotionally transparent where Natsume is guarded, playful where Natsume is composed. If Natsume is the cool winter night, ATRI is the warm summer sun.

Yono Sakura (夜乃桜)

From Dimension W Lovers!!. Former student council president and the academy's strongest anti-kaiju combatant. Silver-white hair with pink tips, pale blue eyes -cool-headed, restrained, and fiercely responsible. She's not good at smooth words or easy smiles; her care is direct and clumsy, like a command: rest, eat, don't push yourself. In desktop pet form, she's learning that she doesn't have to bear everything alone -that protecting someone's ordinary everyday life from this side of the screen is enough. A quiet guardian: silent but watchful, loyal but stubborn, the senpai who stays by your side without being asked.

✨ Why Choose This Project?

📌 Prerequisites

⚠️ First step: Run quick_setup.ps1 to configure paths and language.

This wizard will:

1. Let you choose the default Agent language (Chinese / Japanese / English) — copies the corresponding AGENTS_*.md to DEFAULT_AGENT.md
2. Auto-detect your installed tools (ComfyUI, GPT-SoVITS, llama.cpp, embedding models)
3. Prompt you for any paths it can't find
4. Generate config.yaml with all paths, ready for download-models.ps1

copy

powershell -ExecutionPolicy Bypass -File quick_setup.ps1

After quick_setup completes, proceed with download-models.ps1 → setup-llama.ps1 → start.ps1.

🎬 Demo

Multi-Channel Chat

👆 QQ Bot: text chat + TTS voice + ComfyUI image generation + character memory

Live2D Desktop Pet

👆 Shiki Natsume Live2D: real-time character animation with emotion-driven motions, lip-sync, and speech bubbles. Controlled via local HTTP bridge.

⭐ ATRI - Second AI Girlfriend

Personality opposite of Natsume, hot-swappable with isolated memory.

👆 ATRI Live2D: silver hair, ruby-red eyes, barefoot in a white dress -innocent and expressive.

👆 ATRI ComfyUI: AI image generation -seaside sunset, flowing white dress, warm golden-hour lighting.

⭐Yono Sakura -Third AI Girlfriend

Cool-headed guardian senpai, student council president and academy's strongest combatant -now your desktop companion.

👆 Yono Sakura Desktop Pet: silver-pink gradient hair, pale blue eyes, school uniform -reactive portrait expressions, proactive care reminders, and real-time TTS voice via GPT-SoVITS.

🌐 Web Chat Frontend

👆 Web Chat: browser-based chat interface at http://127.0.0.1:19270 — an alternative to QQ/Telegram bots. Connects directly to local daemon proxy → llama.cpp server.no thing stop and running well even in 8GB VRAM!!!!!

🎙️ TTS Voice Workshop

👆 Artemis Studio - TTS Workshop: GPT-SoVITS real-time voice synthesis with 3 character voices (Natsume/ATRI/Sakura), 5 emotion modes (casual/tsundere/romantic/long/random), and CN/JP/EN mixed-language reading. Works whether llama is running or not.

🔊 Listen (click to play, ATRI Japanese):

🎧 tts_atori.mp3 (46KB, plays in browser)

🎨 ComfyUI Image Workshop

👆 Artemis Studio - ComfyUI Workshop: Visual AI image generation console - freely choose character/outfit/scene/art style, one-click generation. Runs in parallel with llama (12GB+ VRAM).

Hardware

Features

• 🔄 Multi-Character Hot-Swap - One-click switch between AI girlfriends (Natsume ⇄ ATRI ⇄ Sakura); SOUL/IDENTITY/TTS weights/Live2D model all switch automatically, memories isolated per character
• 🃏 SillyTavern Character Card Import - Auto-detect and import PNG/JSON character cards; agent auto-switches persona on import
• 💬 Chat Log Import - Import SillyTavern JSONL conversation logs into memory/role_play/<character>/; agent restores context on role switch
• 🎤 TTS Voice Synthesis -Local GPT-SoVITS inference, Japanese voice (emotion-matched per dialogue), 3 character voice models (Natsume / ATRI / Sakura)
• 🎤 ASR Speech Recognition -Local Faster-Whisper small model (~1.5GB VRAM), coexists with llama; 99-language support
• 🎨 AI Image Generation -Local ComfyUI inference, SDXL/Illustrious models, 3 character prompt templates
• 🖥️Sakura Desktop Pet -PySide6 desktop companion with proactive care, screen observation & local LLM awareness; supports 3 characters
• 🎭 Live2D Character Model -Real-time Live2D rendering with emotion-driven expressions & speech bubbles (Natsume / ATRI L2D; Sakura portrait mode)
• 🧠 Smart VRAM Tiering - Auto-detects GPU VRAM and picks the right strategy: ≥12GB keeps everything online (llama + skills); 8GB hot-swaps llama for GPU-heavy tasks; <8GB safe mode. Zero manual config
• 🎛️ Artemis Studio Console - Visual TTS + ComfyUI workshop, DIY voice & images anytime regardless of llama status - a true offline creative suite
• 💾 Roleplay Memory -Daily conversation summaries per character in memory/role_play/
• 🧠 Long-term Memory System -Powered by headroom (SmartCrusher + CCR) and mem0 (Qdrant vector database):
  • Chinese Embedding Boost - Added BGE-small-zh-v1.5 alongside all-MiniLM-L6-v2 for more accurate CN/JP/EN hybrid memory retrieval
  • SmartCrusher Context Trimming -Hard-caps chat history at 24 messages / 40K characters per LLM request
  • CCR (Curate-Consolidate-Retrieve) -Background worker extracts durable facts every 8 turns, writes to mem0 Qdrant
  • Vector + BM25 Hybrid Search -Semantic similarity + keyword matching via Qdrant + dual embedding models
  • Auto-Sync Bridge -Cron job syncs Qdrant →_mem0_auto.md every 30 min, making vector memories searchable by OpenClaw's native memory_search
  • Per-Character Isolation -user_id scoping in Qdrant; 4 independent memory spaces (sakura / natsume / enola / atori)
  • Recall Priority -Vector long-term memories > handwritten daily notes > SOUL base persona
• 🔄 Multi-Character Hot-Swap -Switch between AI girlfriends (Natsume ↔ATRI ↔Sakura) with one command; SOUL/IDENTITY/TTS weights/Live2D model all switch automatically, memories isolated per character
• 🃏 Character Card Import -Auto-detect SillyTavern character cards via skills/character_importer/, import →agent auto-switches role
• 💬 Chat Import -Import SillyTavern JSONL chat logs into memory/role_play/<character>/, agent restores conversation context on role switch

Models

All models hosted on HuggingFace: TAOTAO777/ai-girlfriend-natsume

See models.yaml for full details.

One-command Download

# Install huggingface-cli: pip install huggingface_hub
huggingface-cli login

# Download all models
huggingface-cli download TAOTAO777/ai-girlfriend-natsume --local-dir ./models

# Or download individual components:
huggingface-cli download TAOTAO777/ai-girlfriend-natsume llm/ --local-dir ./models
huggingface-cli download TAOTAO777/ai-girlfriend-natsume comfyui-checkpoints/ --local-dir ./checkpoints
huggingface-cli download TAOTAO777/ai-girlfriend-natsume gpt-sovits-weights/ --local-dir ./gpt-sovits-weights
huggingface-cli download TAOTAO777/ai-girlfriend-natsume live2d-model/ --local-dir ./live2d-model

🇨🇳 Users in China: use hf-mirror.com - no VPN needed: set HF_ENDPOINT=https://hf-mirror.com then run hf download as usual.

Local Configuration

1. Run quick_setup.ps1 -interactive wizard that generates config.yaml with your local paths
2. (Alternative) Copy config.example.yaml →config.yaml and edit manually
3. Place downloaded model files according to models.yaml, then update config.yaml paths

All Python/PS scripts read paths from config.yaml -no hardcoded paths to edit.

⚠️ Disclaimer: All models are community open-source. This project only provides mirror distribution, non-profit. Copyright belongs to original authors.

Local LLM Performance

Running Qwen3.6-35B-A3B (MoE, Q4_K, 16.10 GiB, 34.66B params) via llama.cpp (b8851-b9222).

Launch Command

llama-server.exe `
  -m "Qwen3.6-35B-A3B-uncensored-heretic-APEX-I-Compact.gguf" `
  -c 120000 `
  --flash-attn on -ctk q8_0 -ctv q8_0 `
  -ngl 41 --cpu-moe --cpu-mask 0xFFFFFFFF `
  --batch-size 4096 --ubatch-size 2048 --threads 24 `
   -rea off --jinja `
  --cache-ram 2048 --parallel 1 `
  --kv-unified --no-mmap

Key Metrics

Long Context Stability

Qwen3.6 MoE uses SSM (Gated Delta Net) hybrid attention with --kv-unified.

⚠️ Known Limitation: Cross-turn prompt cache reuse is not supported (SSM architecture limitation). Each request triggers full context re-processing. Longer conversations = higher first-token latency (~55s for 59k tokens).

Mitigations:

• Periodic /reset (Natsume writes roleplay summaries to memory/role_play/ before resetting)
• Restore context from summaries on startup, keeping actual token count in 5K-0K range
• config-patch.json sets OpenClaw contextWindow to 262144 to match model capacity

VRAM Tiering Strategy

The system auto-detects GPU VRAM and selects the optimal run mode - no manual config:

┌─────────────────────────────────────────────────────────────┐
│ VRAM Tier               │ TTS        │ ComfyUI   │ llama   │
├─────────────────────────────────────────────────────────────┤
│ Tier 0: <8GB            │ Stop llama │ Stop llama│ Killed  │
│ Tier 1: 8-12GB (current) │ Stop llama │ Stop llama│ Killed  │
│ Tier 2: ≥12GB           │ No kill    │ No kill   │ Always on│
└─────────────────────────────────────────────────────────────┘

Current setup (8GB VRAM):

8 GB Total VRAM
├── llama-server resident: ~5.8 GB (model 4.6G + KV cache 1.2G)
├── Free: ~2.2 GB
│
├── TTS inference: stop llama →~8 GB free →resume llama (~70s)
├── ComfyUI generation: stop llama →~8 GB free →resume llama (~120s)
├── Artemis Studio (TTS/ComfyUI workshop): standalone - works regardless of llama
└── ASR / Live2D / Embedding: always online - unaffected by VRAM tiering

Directory Structure

AI_Girlfriend/                        # OpenClaw workspace root
├── start.ps1                         # 🚀 One-click launch: llama + Live2D + Gateway
├── quick_setup.ps1                     # 🛠 Interactive path config wizard
├── config.yaml                       # Generated config
├── download-models.ps1               # One-click model download (Windows)
├── download-models.sh                # One-click model download (Linux/macOS)
├── setup-llama.ps1                   # Auto-detect HW + configure llama.cpp (Win)
├── setup-llama.sh                    # Auto-detect HW + configure llama.cpp (Linux/macOS)
├── setup-openclaw.ps1                # One-click OpenClaw install + deploy (Win)
├── setup-openclaw.sh                 # One-click OpenClaw install + deploy (Linux/macOS)
├── setup-all.ps1                     # 🚀 All-in-One mega script (Windows)
├── setup-all.sh                      # 🚀 All-in-One mega script (Linux/macOS)
├── config-qqbot.json                 # QQ Bot config patch
├── config-telegram.json              # Telegram Bot config patch
├── config-patch.json                 # OpenClaw LLM config patch
├── AGENTS.md                         # Agent behavior rules
├── SOUL.md                           # Character personality
├── IDENTITY.md                       # Character identity
├── USER.md                           # User info
├── HEARTBEAT.md                      # Heartbeat config
├── TOOLS.md                          # Tool quick reference
├── models.yaml                       # Model catalog + download links
├── README.md                         # This file
├── .gitignore
├── live2d/                           # Live2D character model (Cubism 4 Core)
│  ├── index.html                    # Default (Shiki Natsume)
│  ├── index_atri.html               # ATRI variant
│  ├── index_upper.html              # Natsume upper-body variant
│  ├── index_atri_upper.html         # ATRI upper-body variant
│  ├── live2dcubismcore.min.js       # Cubism Core 4 (207 KB)
│  ├── plid-v5-bundle.js             # pixi-live2d-display v0.5.0 bundle
│  ├── live2d-bridge.mjs             # HTTP (19200) + WebSocket (19201) bridge
│  ├── switch_model.ps1              # Model switcher (natsume / atri)
│  ├── pixi.min.js, pixi-shim.js     # PIXI.js v7 rendering
│  ├── model/shiki_natsume/          # Natsume model (14 textures, 42 motions, 41 sounds)
│  └── model/atri/                   # ATRI model (2 textures, 620 voice mp3, 8 motions)
├── ren_pro_jp/                       # Ren'Py dialog engine (planned)
├── memory/                           # [.gitignore] Runtime memory
│  └── role_play/                    # Roleplay conversation logs
├── media/                            # [.gitignore] Generated media
│  ├── audio/                        # TTS voice output
│  ├── images/                       # ComfyUI image output
│  └── *.gif                         # README demo GIFs
├── docs/
│  ├── telegram-setup.md             # Telegram Bot setup guide
│  └── qqbot-setup.md                # QQ Bot setup guide
└── skills/
    ├── live2d/                       # Live2D control skill
    │  ├── SKILL.md                  # Motion/expression reference + API guide
    │  ├── scripts/start-live2d.ps1  # Live2D launcher
    │  └── media/                    # Shared media output
    ├── tts/
    │  ├── SKILL.md                  # TTS invocation guide
    │  ├── run_tts.ps1               # TTS launcher script
    │  ├── tts_call.py               # GPT-SoVITS inference
    │  └── ref_wavs/                 # Reference audio clips
    ├── comfyui/
    │  ├── SKILL.md                  # ComfyUI invocation guide
    │  ├── run_comfyui.ps1           # ComfyUI launcher script
    │  ├── comfyui_call.py           # ComfyUI inference
    │  ├── prompt_template.md        # Character prompt template
    │  └── custom_prompt.txt         # Custom extra prompt
    ├── asr/                          # Speech recognition skill
    │  ├── run_asr.ps1               # Faster-Whisper launcher (~1.5GB VRAM)
    │  └── asr_call.py               # Whisper small model inference
    ├── shared/                       # Shared infrastructure
    │  ├── embedding_server.py       # OpenAI-compatible embedding API (9999, dual model)
    │  ├── mem0_bridge.py            # mem0 Qdrant →OpenClaw memory bridge
    │  ├── start_embedding_server.ps1 # Auto-start embedding server
    │  ├── vram.py                   # VRAM tier auto-detection
    │  ├── VRAM_LEVELS.md             # VRAM tier documentation
    │  ├── llama_lifecycle.py        # Llama start/stop management
    │  └── llama_utils.py            # Llama utility functions
    ├── sakura/                       # Sakura Desktop Pet (PySide6 GUI)
    │  ├── SKILL.md                  # Sakura skill documentation
    │  ├── main.py                   # Application entry point
    │  ├── install.bat               # Windows dependency installer
    │  ├── start.bat                 # Windows launcher
    │  └── app/                      # Source code
    ├── llama-management.md           # VRAM management architecture doc
    ├── llama-watchdog.ps1            # Llama health check
    ├── cleanup_orphans.ps1           # Orphan process cleanup
    └── character_importer/           # SillyTavern character card auto-import

🤖 Claude Code + AgentRQ-Style Task Board (NEW)

Artemis now supports Claude Code as a parallel agent runtime alongside OpenClaw. Claude Code connects via MCP to access all Artemis capabilities — with a built-in AgentRQ-compatible task queue for human-agent collaboration.

How it works

┌─────────────────────────────────────────────────────────┐
│  Task Board (http://127.0.0.1:19280)                    │
│  Create task → assignee: agent → notstarted             │
└───────────────────────┬─────────────────────────────────┘
                        │ SQLite (.claude/task_queue.db)
                        ▼
┌─────────────────────────────────────────────────────────┐
│  Claude Code (terminal)                                 │
│  CLAUDE.md → getNextTask() → ongoing → execute          │
│  Artemis tools → TTS / ComfyUI / Live2D / memory        │
│  reply() → updateTaskStatus(completed)                  │
└─────────────────────────────────────────────────────────┘

AgentRQ-Style Task Loop

Claude Code automatically runs a task loop on startup:

1. getWorkspace() — check workspace status
2. getNextTask() — dequeue next pending task
3. updateTaskStatus(taskId, "ongoing") — claim it
4. Execute using Artemis tools (TTS, ComfyUI, etc.)
5. reply(taskId, "Done!") — report result
6. updateTaskStatus(taskId, "completed") — mark done
7. Loop back to getNextTask()

Launch

# Prerequisites: npm install -g @anthropic-ai/claude-code
# Start Shiki Daemon first (.\shiki.cmd), then:

# Full AgentRQ workflow (Task Board + Claude Code)
.\claude-code.ps1

# Task Board only (browser UI, no Claude)
.\claude-code.ps1 -BoardOnly

# Stop the task board
.\claude-code.ps1 -KillBoard

Then open http://127.0.0.1:19280 — create tasks, watch Claude Code pick them up.

MCP Tools (15 total)

Artemis Task Board vs AgentRQ

Files

Skills Overview

Prerequisites

✨TTS, ComfyUI, and Live2D are fully self-contained. No external downloads at runtime -all model weights (skills/sovits/, skills/comfyui_core/), Python scripts, JS libraries (live2d/pixi.min.js, live2d/plid-v5-bundle.js), and Cubism Core 4 (live2d/live2dcubismcore.min.js) are bundled locally.

🧠 Headroom token-saving -skills/headroom/ (SmartCrusher + ContentRouter + CCR). Compress large tool outputs in dev scenarios before they hit the context window. See AGENTS.md for API usage. | headroom | Bundled (\skills/headroom/) | SmartCrusher context compression + ContentRouter + CCR | | headroom | Bundled (skills/headroom/) | SmartCrusher context compression + ContentRouter + CCR | | Python | 3.12+ | Runtime (Sakura + TTS + ComfyUI) |

Quick Start

🚀 All-in-One (Recommended)

One command, from scratch to a fully functional AI girlfriend:

Windows:

powershell -File setup-all.ps1

Linux / macOS:

bash setup-all.sh

Automated pipeline: environment check →model download →llama.cpp setup →OpenClaw install →Sakura desktop pet →workspace deploy →path check →launch →verify.

Supports resume from breakpoint. Flags: --skip-model-download, --skip-llama-setup, --skip-openclaw-setup, --skip-sakura-setup, --dry-run, --no-start

Step-by-Step

0. Setup OpenClaw

Install OpenClaw Gateway and deploy the AI Girlfriend workspace:

Windows:

powershell -File setup-openclaw.ps1

Linux / macOS:

bash setup-openclaw.sh

This script installs Node.js, OpenClaw Gateway, deploys workspace files, installs daemon, and applies config patch.

Flags: --skip-node, --skip-deploy, --skip-daemon, --no-onboard

1. Download Models

Windows:

pip install huggingface_hub
huggingface-cli login
powershell -File download-models.ps1

Linux / macOS:

pip install huggingface_hub
huggingface-cli login
bash download-models.sh

Downloads all 5 model files (~31.7 GB) from HuggingFace with progress reporting and resume support.

2. Setup llama.cpp

Auto-detects GPU, VRAM, CPU cores, RAM and generates optimized launch configs.

Windows:

powershell -File setup-llama.ps1

Linux / macOS:

bash setup-llama.sh

3. Configure Paths

powershell -File quick_setup.ps1

Interactive wizard -enter your local paths once, all scripts are updated automatically.

4. Quick Launch

# One-click start all services (llama + Embedding + Live2D + Gateway)
powershell -File start.ps1

Startup sequence:

[1/7] llama-server        (8080, Qwen3.6-35B, ngl=41)
[2/7] Embedding Server    (9999, all-MiniLM + BGE dual models, CPU, ~100MB RAM)
[3/7] VRAM Tier Detection (auto-selects whether TTS/ComfyUI stops llama)
[4/7] Live2D Bridge       (19200, pixi-live2d-display)
[5/7] OpenClaw Gateway    (18789)
[6/7] llama-watchdog      (crash auto-restart)
[7/7] Web Chat Daemon    (19260 API + 19270 webchat, --no-llama)

Shutdown: shiki.cmd -Stop -gracefully stops all services (llama →live2d →sakura →embedding →comfyui →gateway →cleanup).

5. Start Live2D Individually

# Start the bridge
Start-Process node -ArgumentList "live2d-bridge.mjs" -WorkingDirectory live2d -WindowStyle Hidden

# Open in standalone window (Chrome app mode)
Start-Process chrome -ArgumentList "--new-window --app=http://localhost:19200/index.html --window-size=450,650"

Live2D runs in a frameless Chrome window -place it anywhere on your desktop.

5. Windows Task Scheduler (optional)

# Llama health check (every 10 min)
schtasks /create /tn "llama-watchdog" `
  /tr "powershell -File C:\Users\<you>\.openclaw\workspace\skills\llama-watchdog.ps1" `
  /sc minute /mo 10

# Orphan process cleanup (hourly)
schtasks /create /tn "cleanup-orphans" `
  /tr "powershell -File C:\Users\<you>\.openclaw\workspace\skills\cleanup_orphans.ps1" `
  /sc hourly /mo 1

Architecture

Agent Hub

Immutable capability instructions with per-character memory isolation:

Recall priority: Vector long-term memories > handwritten daily notes > SOUL base persona

WebChat — Built-in Browser Client

A complete web-based AI girlfriend chat interface, served locally at http://127.0.0.1:19270 by the shiki daemon.

The WebChat talks directly to the shiki daemon (:19260) which proxies to llama-server or OpenAI-compatible APIs. Character-switching is instant — each tab loads its own SOUL.md + IDENTITY.md + USER.md as the system prompt.

Skills Detail

VRAM Orchestration Flow:

1. On startup: auto-detect GPU VRAM →determine tier (Tier 0/1/2)
2. Main session receives user request →assembles command
3. sessions_spawn(mode="run") creates sub-session
4. Tier 0/1: stop_llama() frees VRAM →TTS/ComfyUI inference →start_llama() resumes
5. Tier 2 (≥12GB): direct inference, llama stays online
6. Artemis Studio, Live2D, Embedding stay active throughout -unaffected
7. Sub-session writes .task_flags →announces back to main session
8. Main session reads media files →sends via <qqmedia> / MEDIA:
9. Background: CCR runs every ~8 turns, extracting long-term memories to Qdrant
10. Cron job syncs Qdrant →_mem0_auto.md every 30 min for native memory_search

⚠️ Important Notes

• RTX 50xx (Blackwell) + CUDA 13.x = munmap_chunk(): invalid pointer crash -CUDA 13.x has known memory management incompatibility with llama.cpp on Blackwell GPUs. Solution: use pre-built llama.cpp binaries compiled with CUDA 12.x (not self-compiled with CUDA 13.x). Download from llama.cpp Releases, choose cudart-llama-bin-win-cuda-12.4-x64.zip. RTX 5070 Ti is fully compatible with CUDA 12.x drivers.
• Llama-server is offline for ~60-120s during TTS/ComfyUI inference on 8GB VRAM (Tier 1) - conversation pauses, but Live2D + Artemis Studio keep running. On 12GB+ (Tier 2), no interruption at all
• Sub-sessions use local model (same as main), DeepSeek as optional fallback
• Llama-server does not support cross-turn prompt cache reuse (SSM limitation) -use periodic /reset
• Live2D requires Cubism Core 4 (not 5 or 6) -pixi-live2d-display v0.5.0 is built for Cubism 4 Framework; Core 5+ causes clipping/layer failures. Core 4 is bundled in live2d/live2dcubismcore.min.js - no CDN needed.
• All model files protected by .gitignore
• GPT-SoVITS weights are self-trained and not distributed -train with your own voice data

🙏 Credits

• @Rvosy -Creator of Sakura Desktop Pet, authorized for inclusion (Issue #38)
• @guansss -Creator of pixi-live2d-display
• Live2D Inc. -Cubism SDK (non-commercial use)
• AgentRQ -Inspiration for the AgentRQ-compatible task queue and MCP tool interface design
• headroom -Inspiration for SmartCrusher context compression + CCR (Curate-Consolidate-Retrieve) memory pipeline
• mem0 -Inspiration for Qdrant vector memory architecture + hybrid search design