Local AI Expert: Configure Offline Studio on Apple Silicon Mac (Non-Programmer Friendly)

I am looking for a highly capable, technical AI specialist to assist with a complete local, open-source AI software installation, workflow configuration, and user-friendly interface optimization. The goal of this setup is to create a fully offline, high-performance creative ecosystem on my Mac desktop machine to generate music tracks, vocal arrangements, cinematic/animated video assets, and cover art locally without relying on external cloud credits or compromising data privacy. CRITICAL REQUIREMENT: I am a creative writer and designer, not a programmer. The entire environment must be configured with a clean, visual, point-and-click User Interface (UI). The backend must be streamlined so that I can launch, operate, and manage inputs via straightforward visual dashboards without needing to write code or interact with the terminal during my daily workflow. This ease-of-use focus must be achieved through smart UI wrappers and node organization, without sacrificing the raw, professional quality of the output. A live, recorded 1-on-1 remote training walkthrough session (estimated 1.5 to 2 hours) is included in the project scope to ensure an efficient learning curve. Total Project Budget: $500 (Fixed-Price Escrow broken down into 4 mandatory milestones) Key System Specifications: * Hardware: 16-inch Apple MacBook Pro (Apple M-Series Max chip, maximum internal unified memory configuration, 2TB high-speed built-in SSD). * Environment: macOS (Current stable release). * Primary Target Hosts: Native macOS app containers, unified app wrappers, clean web-UI local client dashboards. Project Milestones & Deliverables: Milestone 1: Environment Core & Local Image Pipeline Setup ($100) * Clean installation of background dependencies (Homebrew, Miniconda, Git) optimized for Apple Silicon unified memory. * Installation of a visual frontend dashboard (e.g., Stability Matrix or Draw Things). * Full configuration of local text-to-image checkpoints and LoRA setups. * Success Criteria: Verification via rendering sample test strings across three distinct styles (Gritty Graphic Novel, Photorealistic Live Human, Claymation). Milestone 2: Hybrid ComfyUI Animation Pipeline & Masking ($150) * Clean configuration of a local ComfyUI interface optimized for M-Series Max hardware. * Setup of a dual-track workflow: Pipeline A for Text-to-Video generation; Pipeline B for Image-to-Video structure replication using ControlNet (Lineart/Scribble models) to ingest hand-drawn sketches as exact replica blueprints. * Construction of a progressive temporal latent masking or noise de-masking sequence to achieve a childish "sketch-and-fill" drawing animation effect. * CRITICAL CONSTRAINT: The drawing animation must bloom natively onto the canvas with ABSOLUTELY ZERO visible drawing tools, floating hands, pencils, or artifacts rendered on screen. * Success Criteria: Smooth execution of local folder directory batch ingestion paths and validated video outputs for style test prompts. Milestone 3: Suno-Style Studio, Voice Design, & Stem Separator ($150) * Configuration of a localized open-source audio synthesis engine (e.g., ACE-Step 1.5 XL or equivalent) accessible via an intuitive graphical web interface. * Setup of a zero-shot Voice Design portal enabling the creation of unique, reusable vocal profiles from text descriptions (age, tone, accent, raspiness) without existing recordings. * Integration of a local Audio LoRA training dashboard with exposed parameters (Temperature, Top-K, Top-P) to control musical chaos and ensure dynamic diversity across tracks. * Integration of an automated stem splitting model (e.g., Demucs node wrapper) to cleanly isolate vocals, drums, bass, and instrumentals into separate, uncompressed .WAV files for easy drag-and-drop into professional DAWs (like Apple Logic Pro). * Success Criteria: Generation of a high-quality test audio track splitting provided text lyrics across distinct instrumental and vocal layers. Milestone 4: Live 1-on-1 Walkthrough & Hands-On Validation ($100) * A live, 1-to-2 hour remote sharing session walking the employer through daily usage rules (opening the dashboards, toggling styles, managing local files, running a training batch). * The freelancer must record this session and deliver the video file for future reference. * Success Criteria: The employer must be able to successfully run one custom test prompt independently while the freelancer is online to verify user-friendliness and close out the contract. Required Freelancer Qualifications: * Verified experience configuring open-source machine learning pipelines, Python dependencies, and git environments locally on macOS / Apple Silicon architectures. * Clear expertise in custom node optimization within ComfyUI, memory-management parameters for unified memory configurations, and running audio/vocal generation models natively. * Strong instructional communication skills; must be a patient teacher willing to deliver a clean tutorial to a non-technical creative professional. Important Safety & Delivery Milestones: * Zero Malicious Dependencies: All tools, extensions, and custom nodes must be pulled strictly from verified, official, and trusted open-source repositories to eliminate risk of systemic security flaws or background system access. * Asset Confidentiality: The expert will have zero contact with final copyright lyric databases or private story text. Test generations must be conducted using generic placeholder values. How to Apply: To be considered for this project, please reply with your direct answers to the following three questions. Applications that use generic template cover letters or fail to answer Question 1 exactly as requested will be automatically declined as spam. 1. To confirm you have read our system requirements, please state the exact model size, chip type, and specific built-in storage size of the Mac desktop computer we will be configuring for this project. 2. Briefly describe your experience configuring Python dependencies via Command Line (e.g., Homebrew or Miniconda) specifically on Apple Silicon architectures. 3. Have you built local pipelines for ComfyUI or local music generation frameworks before? If so, which specific local UI frontend do you prefer using on macOS to ensure a clean, seamless Voice Design and training experience for a non-programmer?