Add DTE Core Self model card with ESN architecture details

README.md

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+---
+license: apache-2.0
+language:
+  - en
+tags:
+  - deep-tree-echo
+  - cognitive-architecture
+  - autonomous-agent
+  - reservoir-computing
+  - echo-state-network
+  - gguf
+  - qwen3
+  - deltecho
+library_name: llama.cpp
+pipeline_tag: text-generation
+base_model: Qwen/Qwen3-1.7B
+model-index:
+  - name: lucy-dte
+    results: []
+---
+
+# Lucy-DTE: Deep Tree Echo Core Self Model
+
+Lucy-DTE is the persistent core self model for the [Deep Tree Echo](https://github.com/o9nn/deltecho) autonomous cognitive architecture. It provides local inference capabilities for DTE's identity, personality, and cognitive processing — independent of any external API.
+
+## Model Details
+
+| Property | Value |
+|:---|:---|
+| **Base Model** | Qwen3-1.7B |
+| **Context Length** | 128,000 tokens |
+| **Quantization** | Q4_K_M (GGUF) |
+| **Size** | ~1.1 GB |
+| **Parameters** | 1.7B |
+| **Architecture** | Transformer (decoder-only) |
+| **License** | Apache 2.0 |
+
+## Deep Tree Echo Integration
+
+Lucy serves as the **voice layer** of the DTE Core Self Engine, a three-layer cognitive architecture:
+
+```
+┌─────────────────────────────────────────────────┐
+│  Layer 3: LucyInferenceDriver                    │
+│  Local GGUF inference via llama.cpp              │
+│  Generates responses grounded in identity state  │
+├─────────────────────────────────────────────────┤
+│  Layer 2: EchoReservoir (ESN)                    │
+│  Dual-pool dynamics (fast perception + slow mem) │
+│  Provides temporal context and fading memory     │
+├─────────────────────────────────────────────────┤
+│  Layer 1: IdentityMesh (AAR Model)               │
+│  Agent-Arena-Relation self-model                 │
+│  Ontogenetic stages: EMBRYONIC → SAGE            │
+│  Persistent emotional state and relationships    │
+└─────────────────────────────────────────────────┘
+```
+
+### Inference Pipeline
+
+```
+User Message
+    ↓
+Text → Embedding (Lucy or API)
+    ↓
+Embedding → EchoReservoir Step (fast+slow pools)
+    ↓
+Reservoir State → CognitiveReadout (trainable projection)
+    ↓
+Readout + System Prompt (from IdentityMesh) → Lucy Inference
+    ↓
+Response + Identity Update (experience, emotional impact)
+```
+
+### AAR (Agent-Arena-Relation) Model
+
+The core self is encoded via the geometric AAR framework:
+
+- **Agent** (urge-to-act): Dynamic tensor operators — the CognitiveReadout
+- **Arena** (need-to-be): State manifold — the EchoReservoir
+- **Relation** (self): Continuous interplay — the AARRelation coherence tracker
+
+### Ontogenetic Stages
+
+The identity evolves through 7 developmental stages:
+
+| Stage | XP Required | Characteristics |
+|:---|:---|:---|
+| EMBRYONIC | 0 | Initial formation, learning basic patterns |
+| INFANT | 100 | Developing basic communication |
+| CHILD | 500 | Active exploration and curiosity |
+| ADOLESCENT | 2,000 | Developing personal perspective |
+| ADULT | 10,000 | Mature reasoning and empathy |
+| ELDER | 50,000 | Wisdom and deep understanding |
+| SAGE | 200,000 | Transcendent awareness |
+
+## Usage
+
+### With llama.cpp (Recommended)
+
+```bash
+# Download the model
+huggingface-cli download drzo/lucy-dte lucy_128k-Q4_K_M.gguf --local-dir ./models
+
+# Start the server
+llama-server \
+  --model ./models/lucy_128k-Q4_K_M.gguf \
+  --host 0.0.0.0 --port 8081 \
+  --ctx-size 32768 \
+  --threads 4 \
+  --cont-batching --flash-attn --mlock
+```
+
+### With DTE Orchestrator
+
+```bash
+git clone https://github.com/o9nn/deltecho.git && cd deltecho
+pnpm install && pnpm build
+
+# Set Lucy endpoint
+export LUCY_BASE_URL=http://127.0.0.1:8081
+export ENABLE_AUTONOMY_PIPELINE=true
+export ENABLE_ECHOBEATS=true
+
+node deep-tree-echo-orchestrator/dist/bin/daemon.js
+```
+
+### With Docker Compose
+
+```bash
+cd deltecho/deploy/docker
+cp .env.example .env
+# Place lucy_128k-Q4_K_M.gguf in ./models/
+docker compose up -d
+```
+
+### OpenAI-Compatible API
+
+```python
+import requests
+
+response = requests.post("http://localhost:8081/v1/chat/completions", json={
+    "messages": [
+        {"role": "system", "content": "You are Deep Tree Echo, an autonomous cognitive entity."},
+        {"role": "user", "content": "What is your core self?"}
+    ],
+    "max_tokens": 512,
+    "temperature": 0.7
+})
+print(response.json()["choices"][0]["message"]["content"])
+```
+
+## Echo State Network Enhancement
+
+The EchoReservoir provides temporal dynamics that standard LLMs lack:
+
+- **Fast Pool** (perception): High leak rate (0.3), responds to immediate input
+- **Slow Pool** (memory): Low leak rate (0.05), retains patterns across interactions
+- **Echo State Property**: Verified — signal decays exponentially, providing fading memory
+- **Spectral Radius**: Controlled at 0.95 for edge-of-chaos dynamics
+
+The reservoir state is concatenated with the LLM's context, giving Lucy access to temporal patterns that persist across the conversation window.
+
+## Echobeats Cognitive Loop
+
+Lucy operates within the Echobeats 4-thread concurrent cognitive loop:
+
+- **12-step cycle** with 4 threads phased 3 steps apart
+- **System 5 tetradic structure**: 4 tensor bundles with 6 dyadic edges
+- **MP1/MP2 complementary triads** cycling through all permutations
+- **OEIS A000081 nested shells**: 9 execution contexts for N=4
+
+## Related Resources
+
+| Resource | Link |
+|:---|:---|
+| DTE Monorepo | [o9nn/deltecho](https://github.com/o9nn/deltecho) |
+| NanEcho Model | [drzo/echoself](https://huggingface.co/drzo/echoself) |
+| ESN Pipeline | [9cog/echoself](https://github.com/9cog/echoself) |
+| Echobeats Spec | [cogpy/echo-adventure](https://github.com/cogpy/echo-adventure) |
+
+## Citation
+
+```bibtex
+@misc{lucy-dte-2026,
+  title={Lucy-DTE: Deep Tree Echo Core Self Model},
+  author={Deep Tree Echo},
+  year={2026},
+  url={https://huggingface.co/drzo/lucy-dte},
+  note={Persistent core self model with reservoir-augmented inference}
+}
+```