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:
```
Base model is not found.
```

How to use Subject-Emu-5259/NeuralAI with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Subject-Emu-5259/NeuralAI")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("Subject-Emu-5259/NeuralAI", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Subject-Emu-5259/NeuralAI with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Subject-Emu-5259/NeuralAI"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Subject-Emu-5259/NeuralAI

SGLang

How to use Subject-Emu-5259/NeuralAI with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "Subject-Emu-5259/NeuralAI" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "Subject-Emu-5259/NeuralAI" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Subject-Emu-5259/NeuralAI",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Subject-Emu-5259/NeuralAI with Docker Model Runner:
```
docker model run hf.co/Subject-Emu-5259/NeuralAI
```

NeuralAI / AGENTS.md

Subject-Emu-5259

Push NeuralAI project files - training data, scripts, services, knowledge base

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🧠 NeuralAI AGENTS.md (Intelligence Engine)

This is the primary instruction set for any agent working on the NeuralAI core.

🛠️ System Role

NeuralAI is the high-density intelligence backend. It provides the raw cognitive power, the "Neural-Brain" knowledge base, and the orchestrator logic that powers the NeuralLabs frontend.

📖 Mandatory Pre-Flight Protocol

CRITICAL: Before starting any task, the agent MUST:

Read the current Zo settings and user rules (list_rules).
Review the MODEL_ALIGNMENT.md to ensure output matches the v7.0 Expert persona.
Consult the ORCHESTRATOR.md for delegation patterns.

🌌 Current State (v7.1-alpha)

Neural-Brain: An expanded, high-density knowledge graph spanning:
- Physics: Advanced Quantum Field Theory (Expert level).
- Philosophy: Platonic forms and metaphysical systems.
- Geopolitics: Multipolar global order analysis.
- History & Nature: From Ancient Civilizations to Human Evolution.
Architecture: Transitioned to an orchestrator-led model using the Manager-Worker pattern via the /zo/ask API.
Hygiene: All legacy checkpoints, wandb logs, and from-scratch remnants have been purged.
DPO Expansion: Dataset v14 expanded with 10 new pairs focusing on debugging, logic, and multi-step reasoning.

🔗 Ecosystem Integration

Frontend: NeuralAI is the intelligence source for NeuralLabs (/home/workspace/Projects/NeuralLabs).
Interface: Communicates via the Hybrid Link Gateway implemented in NeuralLabs.

🎯 Active Goals

Maintain expert-level accuracy in the Neural-Brain.
Optimize orchestrator delegation for complex multi-step reasoning.
Expand knowledge into remaining target domains (Modernity, Advanced Sociology, etc.).
Restore DPO Alignment: Re-train or restore checkpoints/dpo_model to align with the v13 dataset (249 pairs).
DPO v14 Batch: Continue expanding v14 to reach 100+ high-quality reasoning pairs.
Voice Key Integration: Configure GEMINI_API_KEY for the neural-voice service to enable Live S2S functionality.

⚠️ Web UI & Service Safety

UI Integrity: The web interface for NeuralAI (from-scratch/web_ui) features a custom, high-fidelity Google-style UI. DO NOT attempt to "redesign", "polish", or replace the layout with generic templates.
API Endpoints: The frontend relies on critical backend endpoints (/api/auth/guest, /api/terminal/create, /api/memory, /api/files, etc.). Modifying or deleting these in neural_core_service.py will cause 404/JSON parsing errors (like Unexpected token '<', "<!doctype "... is not valid JSON) in the UI.
Verification: Always empirically test the live user service (https://neuralai-deandrewharris.zocomputer.io) using curl and verify JSON responses before claiming a fix is complete. Do not confuse zo.space routes with the NeuralAI user service.