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 dual‑stage 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 |
+| **Dual‑Stage Retriever** | Dense recall (bge‑small) + Cross‑encoder rerank (ms‑marco‑MiniLM) |
+| **Emotion Engine** | Detects user emotion on a 1‑10 scale and matches tone |
+| **4‑Tier 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:** ~2.1 GB (4‑bit) | **Hardware:** T4 or better
+
+## 📦 What's Inside
+
+| Component | Model | Purpose |
+|-----------|-------|---------|
+| **Base LLM** | NYXIS1.1B) | Text generation |
+| **Dense Retriever** | bge‑small‑en‑v1.5 | Initial candidate recall |
+| **Cross‑Encoder** | ms‑marco‑MiniLM‑L‑6‑v2 | Precision re‑ranking |
+| **FAISS Index** | 5,426 chunks | Knowledge storage |
+| **Emotion Engine** | Custom keyword‑based | Tone matching |
+
+## 🤖 Emotion Intelligence
+
+NYXIS-PRO detects your emotional state from text and adjusts its personality:
+
+| Level | Emotion | Response Style |
+|:---:|---------|----------------|
+| 1‑3 | Sad / Angry | Gentle, supportive, empathetic |
+| 4‑6 | Neutral | Balanced, warm, helpful |
+| 7‑9 | Happy / Excited | Energetic, playful |
+| 10 | Overjoyed | Celebratory |
+
+## 🛡️ Knowledge Cascade
+
+When you ask a factual question, NYXIS-PRO follows a strict 4‑tier protocol:
+
+1. **AEGIS** — Searches internal verified knowledge base
+2. **External Search** — Falls back to web search (user‑provided 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 keyword‑based, not deep sentiment analysis
+- External search requires user‑provided API function
+- English‑only, 1.5B model size limits complex reasoning
+
+## License
+
+Apache‑2.0
+
+---
+
+*Built with 🛡️ by QuantaSparkLabs*