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NYXIS-Pro/README.md
ModelHub XC d704951188 初始化项目,由ModelHub XC社区提供模型
Model: QuantaSparkLabs/NYXIS-Pro
Source: Original Platform
2026-06-30 22:08:44 +08:00

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---
license: apache-2.0
language:
- en
tags:
- rag
- retrieval-augmented-generation
- knowledge-base
- emotion-detection
- dual-stage-retrieval
- coding
- math
- science
- history
- nyxis
- quantasparklabs
pipeline_tag: text-generation
base_model:
- QuantaSparkLabs/NYXIS-1.1B
library_name: transformers
datasets:
- QuantaSparkLabs/NYXIS-AEGIS-Knowledge
---
<p align="center">
<img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/preview imgagee.png"
alt="NYXIS Logo"
width="160"
height="160"
style="border-radius: 50%; object-fit: cover;">
</p>
<p align="center">
<img src="https://huggingface.co/QuantaSparkLabs/NYXIS-Pro/resolve/main/logoname.png"
alt="NYXIS Name"
width="700"
style="border-radius: 18px;">
</p>
# NYXIS-PRO 🛡️
<p align="center">
<a href="https://huggingface.co/QuantaSparkLabs/NYXIS-1.1B"><img src="https://img.shields.io/badge/Base-NYXIS--1.1B-purple" alt="Base Model"></a>
<a href="https://huggingface.co/QuantaSparkLabs/NYXIS-AEGIS-KB"><img src="https://img.shields.io/badge/Knowledge-AEGIS-blue" alt="AEGIS KB"></a>
<a href="#"><img src="https://img.shields.io/badge/Retrieval-Dual%20Stage-green" alt="Dual Stage"></a>
<a href="#"><img src="https://img.shields.io/badge/Emotion-1--10%20Scale-orange" alt="Emotion Engine"></a>
<a href="https://www.apache.org/licenses/LICENSE-2.0"><img src="https://img.shields.io/badge/License-Apache%202.0-yellow" alt="License"></a>
</p>
**The all-in-one reasoning engine with the AEGIS knowledge shield.**
NYXIS-PRO combines the NYXIS1.1B base model with a curated 5,000+ chunk knowledge base covering coding, math, science, history, and common knowledge. A dualstage retriever grounds every factual answer in verified data — **zero hallucination.**
## 🧠 What Makes It Different
| Feature | Description |
|---------|-------------|
| **AEGIS Knowledge Base** | 5,426 curated Wikipedia, Trivia QA, and ArXiv chunks |
| **DualStage Retriever** | Dense recall (bgesmall) + Crossencoder rerank (msmarcoMiniLM) |
| **Emotion Engine** | Detects user emotion on a 110 scale and matches tone |
| **4Tier Knowledge Cascade** | AEGIS → External Search → Model Brain → Honest Fallback |
| **Zero Hallucination** | If it doesn't know, it says so — no fabrication |
## 🚀 Quick Start
```python
from huggingface_hub import snapshot_download
import sys
model_dir = snapshot_download("QuantaSparkLabs/NYXIS-Pro")
sys.path.insert(0, model_dir)
from pipeline import NYXISPro
nyxis = NYXISPro(model_dir)
result = nyxis.generate("What is a binary search tree?")
print(result["response"])
```
> **Requirements:** `sentence-transformers`, `faiss-cpu`, `transformers`, `accelerate`, `bitsandbytes`
> **VRAM:** ~2.1GB (4bit) | **Hardware:** T4 or better
## 📦 What's Inside
| Component | Model | Purpose |
|-----------|-------|---------|
| **Base LLM** | NYXIS1.1B) | Text generation |
| **Dense Retriever** | bgesmallenv1.5 | Initial candidate recall |
| **CrossEncoder** | msmarcoMiniLML6v2 | Precision reranking |
| **FAISS Index** | 5,426 chunks | Knowledge storage |
| **Emotion Engine** | Custom keywordbased | Tone matching |
## 🤖 Emotion Intelligence
NYXIS-PRO detects your emotional state from text and adjusts its personality:
| Level | Emotion | Response Style |
|:---:|---------|----------------|
| 13 | Sad / Angry | Gentle, supportive, empathetic |
| 46 | Neutral | Balanced, warm, helpful |
| 79 | Happy / Excited | Energetic, playful |
| 10 | Overjoyed | Celebratory |
## 🛡️ Knowledge Cascade
When you ask a factual question, NYXIS-PRO follows a strict 4tier protocol:
1. **AEGIS** — Searches internal verified knowledge base
2. **External Search** — Falls back to web search (userprovided API)
3. **Model Brain** — Uses training data with honesty guard
4. **Honest Fallback** — Admits "I don't have enough information"
It **never fabricates** an answer.
## Limitations
- Knowledge base covers ~5,400 chunks — not infinite
- Emotion detection is keywordbased, not deep sentiment analysis
- External search requires userprovided API function
- Englishonly, 1.5B model size limits complex reasoning
## License
Apache2.0
---
*Built with 🛡️ by QuantaSparkLabs*