Instructions to use Subject-Emu-5259/NeuralAI with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Subject-Emu-5259/NeuralAI with PEFT:
Task type is invalid.
- Notebooks
- Google Colab
- Kaggle
docs: sync README with GitHub (v7.3.2)
Browse files
README.md
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---
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license: apache-2.0
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pipeline_tag: text-generation
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tags:
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- lora
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- peft
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base_model: HuggingFaceTB/SmolLM2-360M-Instruct
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- **Adapter:** LoRA rank 16, alpha 32, dropout 0.05
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- **Method:** DPO preference alignment on top of SFT
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- **Params:** 361.8M
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- **License:** Apache-2.0
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- **Framework:** PyTorch + Transformers 5.5.4 + PEFT 0.19.0
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```python
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```
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##
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| Epochs | 3 |
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| Learning rate | 2e-4 |
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| Train / val | 363 / 41 |
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| Duration | ~26 min |
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| Completed | 2026-05-17 |
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| Framework | PyTorch + Transformers + PEFT 0.19.0 |
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---
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language:
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- en
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library_name: peft
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license: apache-2.0
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tags:
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- lora
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- conversational
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- text-generation
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- peft
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- smollm2
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- dpo
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- fine-tuned
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model_id: Subject-Emu-5259/NeuralAI
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base_model: HuggingFaceTB/SmolLM2-360M-Instruct
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inference: false
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---
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# 🧠 NeuralAI: The Generative AI Engine
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<img src="neuralai_banner.svg" alt="NeuralAI - Your AI. On your hardware. In your browser." />
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## 📊 Repository Composition
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| Language | Percentage |
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| --- | --- |
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| Python | 71.1% |
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| HTML | 13.0% |
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| JavaScript | 12.4% |
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| CSS | 2.6% |
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| Shell | 0.4% |
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| Jupyter Notebook | 0.3% |
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| Jinja | 0.2% |
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**The High-Velocity Model for Your Entire Vibe Stack**
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NeuralAI is the central intelligence engine developed by **De'Andrew Preston Harris**. Conceived and engineered by **De'Andrew Preston Harris** (Founder), it is a highly tuned, DPO-aligned multimodal AI ec\[...\]
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---
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## 🌟 Vision & Manifesto
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NeuralAI doesn't just predict text; it *operates the work*. The core mission is to create a multimodal generative system that bridges the gap between raw idea and execution. By fusing autoregressi\[...\]
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Born from resilience and ambition in Memphis, Tennessee and West Memphis, Arkansas, NeuralAI represents a forward-thinking approach to personal, private AI computing.
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---
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## 🛠️ Tech Stack & Architecture (v7.2)
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NeuralAI is built on a high-performance architecture that decouples the inference engine from the web interface, enabling lightweight cloud hosting with powerful local inference.
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### Core Stack
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- **Core Model**: `SmolLM2-360M-Instruct` fine-tuned with the custom **SFT v16 + DPO v16 LoRA** at `checkpoints/v2_model` — aligned for logic, math, multi-step reasoning, and debugging
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- **Inference Engine**: [llmster](https://lmstudio.ai/docs/cli) (LM Studio headless) — OpenAI-compatible API with continuous batching, running via llama.cpp
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- **Vocal Identity**: Andrew (Warm/Multilingual) — Optimized for Live Speech-to-Speech (S2S)
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- **Backend Framework**: Python / Flask (Core Service) — routes to llmster or local PyTorch
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- **Storage & Database**: SQLite3 (Metadata) + Nextcloud Hub via NeuralCloud WebDAV Client (NeuralDrive)
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- **Frontend UI**: Vanilla JS, HTML5, CSS3 with an advanced Dark Mode layout
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### Pluggable LLM Backend
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NeuralAI supports multiple inference backends via the `LLM_BACKEND` environment variable:
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| Backend | `LLM_BACKEND` | API Endpoint | Use Case |
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| --- | --- | --- | --- |
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| **llmster** (recommended) | `lmstudio` | `http://localhost:1234/v1` | Headless GPU/CPU inference |
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| **Ollama** | `ollama` | `http://localhost:11434/v1` | Local Ollama server |
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| **OpenAI-compatible** | `openai_compatible` | Any OpenAI API URL | Remote/cloud inference |
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| **Local PyTorch** | `local` | Built-in transformers | Loads BASE_MODEL + LoRA at MODEL_PATH in float16 (your own model) |
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| **ZO Native (fallback)** | `zo` | `https://api.zo.computer/zo/ask` | Routes to Zo's own assistant (HY3) — **NOT** your NeuralAI model; last-resort only |
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> **Hosting on ZO Computer (4 GB RAM):** set `LLM_BACKEND=local`. The service loads `BASE_MODEL`
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> (default `HuggingFaceTB/SmolLM2-360M-Instruct`) and applies the LoRA at `MODEL_PATH`
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> (default `checkpoints/v2_model`) in float16 (~720 MB), which fits the 4 GB host. **Do not use
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> `LLM_BACKEND=zo` for the chat UI** — it proxies to Zo's assistant and answers as "Zo Computer's
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> assistant" instead of your trained model.
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```bash
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# Example: start NeuralAI with llmster backend
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LLM_BACKEND=lmstudio LLM_API_URL=http://localhost:1234/v1 LLM_MODEL=smollm2 \
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python3 services/neural_core_service.py
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```
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### Core Architectural Pillars
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1. **NeuralAI Core**: Handles chat state, direct model inference, terminal session proxying, and tool orchestration.
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2. **NeuralDrive (Cloud Storage)**: The intelligent data layer for all projects, featuring isolated user storage, automatic versioning, and semantic mapping.
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3. **Diffusion Engine**: An integrated generative diffusion layer for producing visual branding assets, UI mockups, and visual logic maps.
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4. **Agentic Orchestrator**: A high-autonomy layer enabling NeuralAI to plan, reason, and execute multi-step workflows across the OS and web, moving beyond simple chat to active goal achievement.
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---
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### 🆕 What's New (v7.3.1)
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- **Developer / API Access (BYO API)**: Generate a personal API key from Settings to use NeuralAI as an OpenAI-compatible backend on other hosts (e.g. ZO Computer's "Bring Your Own API"). Exposes `/v1/chat/completions` and `/v1/models`; keys are hashed and revocable.
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- **Auto Release Notes ("What's New")**: A new top-bar panel surfaces the latest features and fixes automatically. Open it anytime via the ✨ **What's New** button.
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- **Generated images render in chat**: Image-generation responses are parsed as Markdown and displayed inline.
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- **No more self-talk**: Chat now uses the ChatML prompt template (`apply_chat_template`), matching the model's training format.
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- **NeuralDrive upload reliability**: The file list correctly handles API response shapes after an upload.
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- **Dark theme by default**: UI restores your saved theme and defaults to dark mode (fixes white file-cards in light mode).
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- **Phase 8 in progress**: Knowledge Graph & Agentic Autonomy — long-term cross-project memory ("Supermemory") and fully autonomous task execution.
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- **The NeuralLabs Shift**: NeuralAI is evolving into a standalone, downloadable intelligence environment (NeuralLabs v1 Client → v2 Edge → v3 Eco).
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- **v7.3.2 — Backend identity fix (ZO hosting)**: The hosted service now runs `LLM_BACKEND=local` so chat uses *your* SmolLM2-360M + SFT/DPO v16 LoRA. The previous `zo` fallback proxied to Zo's assistant and answered as "I'm Zo Computer's assistant" — that was a routing bug, not your model. See `docs/INCIDENT-2026-07-14-NEURALAI-PAUSES.md`.
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## 🚀 Deployment & Model Distribution
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- **Source (GitHub)**: [Subject-Emu-5259/NeuralAI](https://github.com/Subject-Emu-5259/NeuralAI)
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- **Model (Hugging Face)**: [Subject-Emu-5259/NeuralAI](https://huggingface.co/Subject-Emu-5259/NeuralAI) — merged SmolLM2-360M + SFT v16/DPO v16 LoRA weights (drop-in, no PEFT needed). The LoRA adapter is also in `checkpoints/v2_model`.
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- **Hosted demo**: `neuralai-web-ui-deandrewharris.zocomputer.io` (ZO Computer) — runs the local backend so chat uses the trained model directly.
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To publish the LoRA to Hugging Face:
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```bash
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pip install huggingface_hub
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HF_TOKEN=<your-write-token> python3 -c "
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from huggingface_hub import HfApi
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api = HfApi()
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api.upload_folder(
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folder_path='checkpoints/v2_model',
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repo_id='Subject-Emu-5259/NeuralAI',
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repo_type='model',
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commit_message='NeuralAI SmolLM2-360M SFT v16 + DPO v16 LoRA',
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)
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"
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```
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## ✨ Key Features & Capabilities
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### 💬 Multimodal Chat & Agentic Intelligence
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- **High-Velocity Text Inference**: Fast, local inference with deep context awareness.
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- **Deep Reasoning Mode**: Integration of test-time compute and chain-of-thought reasoning for complex problem decomposition and error-free logic.
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- **Autonomous Agentic Workflows**: Ability to operate as an agent—interacting with the browser, terminal, and third-party apps to complete end-to-end tasks with minimal supervision.
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- **Live S2S (Speech-to-Speech)**: Real-time voice interaction with an integrated microphone interface and fluid vocal responses.
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- **Identity Vault & Memory**: Persistent user memory and rule constraints, ensuring NeuralAI remembers preferences, behavioral rules, and historical context.
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### 💻 Developer & Engineering Tools
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- **Integrated Web Terminal**: A fully functional, WebSocket-driven terminal embedded directly in the web UI for immediate environment control.
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- **File Workspace**: An in-browser IDE experience allowing users to browse directories, read, and write code seamlessly.
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- **Code Execution & Sandbox**: Secure environment for the model to execute and test code on the fly.
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### 🔐 Authentication & Access Tiers
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- **Founder Mode**: Ultimate root-level access and system control.
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- **Maestro Student Portal**: Tiered access for educational and collaborative development.
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- **Guest Preview**: Frictionless instant access for testing the system without an account.
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---
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## 🏋️ Model Training & Fine-Tuning (DPO)
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NeuralAI is continuously learning and improving through rigorous **Direct Preference Optimization (DPO)**.
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### Training Pipeline
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```python
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# Example of the DPO alignment configuration used in NeuralAI
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dpo_config = DPOConfig(
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beta=0.1,
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learning_rate=5e-5,
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per_device_train_batch_size=4,
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gradient_accumulation_steps=4,
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max_length=1024,
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max_prompt_length=512,
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)
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```
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- **Dataset Expansions**: The dataset is aggressively expanded to include advanced reasoning, complex mathematics, logical deduction, creative writing, and system debugging.
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- **Behavioral Alignment**: NeuralAI is aligned using Gemini-style behavioral principles—prioritizing safety, structured reasoning, helpful conversational flow, and transparent step-by-step explanations. Training enforces clear Markdown formatting, code-first responses, and rejection of boilerplate or overly verbose outputs.
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- **Model Drift Monitoring**: Continuous evaluation against previous checkpoints to ensure response quality and consistency never regress.
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### Latest Alignment Run: v15.0
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- **Training samples**: 597 (expanded DPO preference pairs)
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- **Epochs**: 3
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- **Steps**: 450
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- **Final training loss**: `0.305`
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- **Reward margin**: improved from `~0.5` → `~3.5` (model strongly prefers chosen responses)
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- **Hardware**: Apple Silicon MPS (MacBook Air M4)
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- **Run duration**: `730.5s` (~12m 11s)
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- **Completed**: `2026-07-11 20:00 UTC`
|
| 183 |
+
- **Adapter**: live on Hugging Face at [`Subject-Emu-5259/NeuralAI`](https://huggingface.co/Subject-Emu-5259/NeuralAI)
|
| 184 |
|
| 185 |
+
> The v15 dataset (`data/train_dpo_v15.jsonl`) was generated by expanding the template pools in `training/build_dataset_v15.py` from 302 → 597 unique preference pairs covering code correctness, logic, reasoning, debugging, and multi-step tasks.
|
| 186 |
+
|
| 187 |
+
---
|
| 188 |
+
|
| 189 |
+
## 📸 Brand & UI Gallery
|
| 190 |
+
|
| 191 |
+
*(UI screenshots showcase the beautiful dark mode interface, the terminal integration, and the NeuralDrive file explorer.)*
|
| 192 |
+
|
| 193 |
+
```html
|
| 194 |
+
<!-- Example Frontend UI Component Structure -->
|
| 195 |
+
<div class="neural-chat-container">
|
| 196 |
+
<div class="message-bubble ai-response">
|
| 197 |
+
NeuralAI: System optimal. Ready for execution.
|
| 198 |
+
</div>
|
| 199 |
+
</div>
|
| 200 |
+
```
|
| 201 |
+
|
| 202 |
+
---
|
| 203 |
+
|
| 204 |
+
## 🗺️ Implementation Roadmap
|
| 205 |
+
|
| 206 |
+
- ✅ **Phase 1: Alignment** - DPO training for Founder context and optimal engineering tone.
|
| 207 |
+
- ✅ **Phase 2: NeuralDrive** - Deployment of the Cloud Storage File Server.
|
| 208 |
+
- ✅ **Phase 3: Terminal UI** - Integrated command-line access within the browser.
|
| 209 |
+
- ✅ **Phase 4: Live S2S** - High-velocity Live Speech-to-Speech conversations.
|
| 210 |
+
- ✅ **Phase 5: "Founder Mode"** - Enhancements to vocal profile and streamlined UI.
|
| 211 |
+
- ✅ **Phase 6: Frontend Polish** - Dark themes, real-time code execution display, UI stability.
|
| 212 |
+
- ✅ **Phase 7: Diffusion Integration** - Implementation of Text2Img & Img2Img capabilities.
|
| 213 |
+
- 🚀 **Phase 8: Knowledge Graph & Agentic Autonomy** - Advanced long-term memory for cross-project context, "Supermemory" features, and fully autonomous task execution.
|
| 214 |
+
|
| 215 |
+
---
|
| 216 |
+
|
| 217 |
+
## 🎯 Future Vision: The Software Transition
|
| 218 |
+
|
| 219 |
+
NeuralAI is evolving from a workspace-bound assistant into a standalone, downloadable intelligence environment.
|
| 220 |
+
|
| 221 |
+
**Project Code Name**: `NeuralLabs` (Working Title)
|
| 222 |
+
**Vision**: A local-first, AI-native operating environment that integrates the Agentic Orchestrator, World-Brain, and NeuralDrive into a seamless desktop experience—similar to the "Codex" model but expanded into a full cognitive workspace.
|
| 223 |
+
|
| 224 |
+
### 🚀 Roadmap Addition: The NeuralLabs Shift
|
| 225 |
+
|
| 226 |
+
- **NeuralLabs v1 (Client)**: Development of a cross-platform wrapper (Electron/Tauri) for the NeuralAI interface.
|
| 227 |
+
- **NeuralLabs v2 (Edge)**: Local model execution (Llama/Mistral) as a fallback for the cloud-based NeuralAI core.
|
| 228 |
+
- **NeuralLabs v3 (Eco)**: Plugin architecture allowing third-party "Neural-Skills" to be installed as standalone apps.
|
| 229 |
+
|
| 230 |
+
---
|
| 231 |
+
|
| 232 |
+
## 👨💻 The Developer & Architect
|
| 233 |
+
|
| 234 |
+
**De'Andrew Preston Harris** (D. Harris / Dre)
|
| 235 |
+
*Founder & Architect of NeuralAI*
|
| 236 |
+
|
| 237 |
+
A dedicated software engineer, thinker, and builder from West Memphis, AR. De'Andrew is currently pursuing an AAS in AI Software Engineering at Maestro College. NeuralAI is the culmination of his\[...\]
|
| 238 |
+
|
| 239 |
+
- **Location:** Memphis, TN / West Memphis, AR
|
| 240 |
+
- **Vision:** Building the future of private, high-performance generative AI.
|
| 241 |
+
- [LinkedIn](https://www.linkedin.com/in/deandrewharris94/) | [GitHub](https://github.com/Subject-Emu-5259)
|
| 242 |
+
|
| 243 |
+
---
|
| 244 |
+
|
| 245 |
+
*Built with precision and discipline by De'Andrew Preston Harris.*
|
| 246 |
+
|
| 247 |
+
### CURRENT VERSION: v7.3.2 (The Pluggable Engine)
|
| 248 |
+
|
| 249 |
+
- **Model Alignment**: DPO v15.0 Aligned (597 pairs, Logic, Debugging, Reasoning)
|
| 250 |
+
- **Inference**: llmster (LM Studio headless) — 258MB RAM vs 5GB PyTorch
|
| 251 |
+
- **Last Maintenance**: July 14, 2026
|
| 252 |
+
|
| 253 |
+
Your tone is technical, concise, and professional. You prioritize system stability and cleanliness above all else.
|
| 254 |
+
|
| 255 |
+
---
|
| 256 |
+
|
| 257 |
+
## 🚀 Deployment
|
| 258 |
+
|
| 259 |
+
NeuralAI ships with a pluggable backend that separates the web UI from the inference engine.
|
| 260 |
+
|
| 261 |
+
### Quick Start (llmster — recommended)
|
| 262 |
+
|
| 263 |
+
```bash
|
| 264 |
+
# 1. Install llmster (one-time)
|
| 265 |
+
curl -fsSL https://lmstudio.ai/install.sh | bash
|
| 266 |
+
export PATH="$HOME/.lmstudio/bin:$PATH"
|
| 267 |
+
|
| 268 |
+
# 2. Download model
|
| 269 |
+
lms import /path/to/SmolLM2-360M-Instruct-Q4_K_M.gguf --user-repo "bartowski/SmolLM2-360M-Instruct-GGUF" -y
|
| 270 |
+
lms load smollm2-360m-instruct -y --identifier smollm2
|
| 271 |
+
|
| 272 |
+
# 3. Start inference server
|
| 273 |
+
lms server start --port 1234
|
| 274 |
+
|
| 275 |
+
# 4. Start NeuralAI
|
| 276 |
+
cd NeuralAI
|
| 277 |
+
LLM_BACKEND=lmstudio LLM_API_URL=http://localhost:1234/v1 LLM_MODEL=smollm2 \
|
| 278 |
+
python3 services/neural_core_service.py
|
| 279 |
```
|
| 280 |
|
| 281 |
+
### Containerized Deployments
|
| 282 |
+
|
| 283 |
+
| Deployment | Dockerfile | Stack | Status |
|
| 284 |
+
| --- | --- | --- | --- |
|
| 285 |
+
| **Gradio Demo** | `gradio_space/Dockerfile` | Gradio 6.x chat UI | ✅ Built & deployed |
|
| 286 |
+
| **Flask Web Chat** | `webui_space/Dockerfile` | Flask + `neural_core_service.py` | 🚀 Ready for Railway |
|
| 287 |
+
|
| 288 |
+
- **Adapter source**: [`Subject-Emu-5259/NeuralAI`](https://huggingface.co/Subject-Emu-5259/NeuralAI) — auto-pulled on startup via `snapshot_download`.
|
| 289 |
+
- **GitHub → HF sync**: `.github/workflows/sync_to_huggingface.yml` uploads only the LoRA adapter on every push to `master`.
|
| 290 |
+
|
| 291 |
+
---
|
| 292 |
+
|
| 293 |
+
# 🌌 NeuralAI Project Manifest
|
| 294 |
+
|
| 295 |
+
NeuralAI is the intelligence core that powers the ecosystem.
|
| 296 |
|
| 297 |
+
## 🔗 Ecosystem Integration
|
| 298 |
+
The standalone software implementation of this core is **NeuralLabs**:
|
| 299 |
+
👉 [https://github.com/Subject-Emu-5259/NeuralLabs](https://github.com/Subject-Emu-5259/NeuralLabs)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 300 |
|
| 301 |
+
**Software Downloads**:
|
| 302 |
+
The latest beta builds (v0.1-Beta) of NeuralLabs are available at:
|
| 303 |
+
👉 **[https://zo.pub/deandrewharris/neurallabs-beta](https://zo.pub/deandrewharris/neurallabs-beta)**
|
| 304 |
+
# NeuralAI → Hugging Face sync is live
|